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Scientific Research – Types, Purpose and Guide

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Scientific Research

Definition:

Scientific research is the systematic and empirical investigation of phenomena, theories, or hypotheses, using various methods and techniques in order to acquire new knowledge or to validate existing knowledge.

It involves the collection, analysis, interpretation, and presentation of data, as well as the formulation and testing of hypotheses. Scientific research can be conducted in various fields, such as natural sciences, social sciences, and engineering, and may involve experiments, observations, surveys, or other forms of data collection. The goal of scientific research is to advance knowledge, improve understanding, and contribute to the development of solutions to practical problems.

Types of Scientific Research

There are different types of scientific research, which can be classified based on their purpose, method, and application. In this response, we will discuss the four main types of scientific research.

Descriptive Research

Descriptive research aims to describe or document a particular phenomenon or situation, without altering it in any way. This type of research is usually done through observation, surveys, or case studies. Descriptive research is useful in generating ideas, understanding complex phenomena, and providing a foundation for future research. However, it does not provide explanations or causal relationships between variables.

Exploratory Research

Exploratory research aims to explore a new area of inquiry or develop initial ideas for future research. This type of research is usually conducted through observation, interviews, or focus groups. Exploratory research is useful in generating hypotheses, identifying research questions, and determining the feasibility of a larger study. However, it does not provide conclusive evidence or establish cause-and-effect relationships.

Experimental Research

Experimental research aims to test cause-and-effect relationships between variables by manipulating one variable and observing the effects on another variable. This type of research involves the use of an experimental group, which receives a treatment, and a control group, which does not receive the treatment. Experimental research is useful in establishing causal relationships, replicating results, and controlling extraneous variables. However, it may not be feasible or ethical to manipulate certain variables in some contexts.

Correlational Research

Correlational research aims to examine the relationship between two or more variables without manipulating them. This type of research involves the use of statistical techniques to determine the strength and direction of the relationship between variables. Correlational research is useful in identifying patterns, predicting outcomes, and testing theories. However, it does not establish causation or control for confounding variables.

Scientific Research Methods

Scientific research methods are used in scientific research to investigate phenomena, acquire knowledge, and answer questions using empirical evidence. Here are some commonly used scientific research methods:

Observational Studies

This method involves observing and recording phenomena as they occur in their natural setting. It can be done through direct observation or by using tools such as cameras, microscopes, or sensors.

Experimental Studies

This method involves manipulating one or more variables to determine the effect on the outcome. This type of study is often used to establish cause-and-effect relationships.

Survey Research

This method involves collecting data from a large number of people by asking them a set of standardized questions. Surveys can be conducted in person, over the phone, or online.

Case Studies

This method involves in-depth analysis of a single individual, group, or organization. Case studies are often used to gain insights into complex or unusual phenomena.

Meta-analysis

This method involves combining data from multiple studies to arrive at a more reliable conclusion. This technique can be used to identify patterns and trends across a large number of studies.

Qualitative Research

This method involves collecting and analyzing non-numerical data, such as interviews, focus groups, or observations. This type of research is often used to explore complex phenomena and to gain an understanding of people’s experiences and perspectives.

Quantitative Research

This method involves collecting and analyzing numerical data using statistical techniques. This type of research is often used to test hypotheses and to establish cause-and-effect relationships.

Longitudinal Studies

This method involves following a group of individuals over a period of time to observe changes and to identify patterns and trends. This type of study can be used to investigate the long-term effects of a particular intervention or exposure.

Data Analysis Methods

There are many different data analysis methods used in scientific research, and the choice of method depends on the type of data being collected and the research question. Here are some commonly used data analysis methods:

• Descriptive statistics: This involves using summary statistics such as mean, median, mode, standard deviation, and range to describe the basic features of the data.
• Inferential statistics: This involves using statistical tests to make inferences about a population based on a sample of data. Examples of inferential statistics include t-tests, ANOVA, and regression analysis.
• Qualitative analysis: This involves analyzing non-numerical data such as interviews, focus groups, and observations. Qualitative analysis may involve identifying themes, patterns, or categories in the data.
• Content analysis: This involves analyzing the content of written or visual materials such as articles, speeches, or images. Content analysis may involve identifying themes, patterns, or categories in the content.
• Data mining: This involves using automated methods to analyze large datasets to identify patterns, trends, or relationships in the data.
• Machine learning: This involves using algorithms to analyze data and make predictions or classifications based on the patterns identified in the data.

Application of Scientific Research

Scientific research has numerous applications in many fields, including:

• Medicine and healthcare: Scientific research is used to develop new drugs, medical treatments, and vaccines. It is also used to understand the causes and risk factors of diseases, as well as to develop new diagnostic tools and medical devices.
• Agriculture : Scientific research is used to develop new crop varieties, to improve crop yields, and to develop more sustainable farming practices.
• Technology and engineering : Scientific research is used to develop new technologies and engineering solutions, such as renewable energy systems, new materials, and advanced manufacturing techniques.
• Environmental science : Scientific research is used to understand the impacts of human activity on the environment and to develop solutions for mitigating those impacts. It is also used to monitor and manage natural resources, such as water and air quality.
• Education : Scientific research is used to develop new teaching methods and educational materials, as well as to understand how people learn and develop.
• Business and economics: Scientific research is used to understand consumer behavior, to develop new products and services, and to analyze economic trends and policies.
• Social sciences : Scientific research is used to understand human behavior, attitudes, and social dynamics. It is also used to develop interventions to improve social welfare and to inform public policy.

How to Conduct Scientific Research

Conducting scientific research involves several steps, including:

• Identify a research question: Start by identifying a question or problem that you want to investigate. This question should be clear, specific, and relevant to your field of study.
• Conduct a literature review: Before starting your research, conduct a thorough review of existing research in your field. This will help you identify gaps in knowledge and develop hypotheses or research questions.
• Develop a research plan: Once you have a research question, develop a plan for how you will collect and analyze data to answer that question. This plan should include a detailed methodology, a timeline, and a budget.
• Collect data: Depending on your research question and methodology, you may collect data through surveys, experiments, observations, or other methods.
• Analyze data: Once you have collected your data, analyze it using appropriate statistical or qualitative methods. This will help you draw conclusions about your research question.
• Interpret results: Based on your analysis, interpret your results and draw conclusions about your research question. Discuss any limitations or implications of your findings.
• Communicate results: Finally, communicate your findings to others in your field through presentations, publications, or other means.

Purpose of Scientific Research

The purpose of scientific research is to systematically investigate phenomena, acquire new knowledge, and advance our understanding of the world around us. Scientific research has several key goals, including:

• Exploring the unknown: Scientific research is often driven by curiosity and the desire to explore uncharted territory. Scientists investigate phenomena that are not well understood, in order to discover new insights and develop new theories.
• Testing hypotheses: Scientific research involves developing hypotheses or research questions, and then testing them through observation and experimentation. This allows scientists to evaluate the validity of their ideas and refine their understanding of the phenomena they are studying.
• Solving problems: Scientific research is often motivated by the desire to solve practical problems or address real-world challenges. For example, researchers may investigate the causes of a disease in order to develop new treatments, or explore ways to make renewable energy more affordable and accessible.
• Advancing knowledge: Scientific research is a collective effort to advance our understanding of the world around us. By building on existing knowledge and developing new insights, scientists contribute to a growing body of knowledge that can be used to inform decision-making, solve problems, and improve our lives.

Examples of Scientific Research

Here are some examples of scientific research that are currently ongoing or have recently been completed:

• Clinical trials for new treatments: Scientific research in the medical field often involves clinical trials to test new treatments for diseases and conditions. For example, clinical trials may be conducted to evaluate the safety and efficacy of new drugs or medical devices.
• Genomics research: Scientists are conducting research to better understand the human genome and its role in health and disease. This includes research on genetic mutations that can cause diseases such as cancer, as well as the development of personalized medicine based on an individual’s genetic makeup.
• Climate change: Scientific research is being conducted to understand the causes and impacts of climate change, as well as to develop solutions for mitigating its effects. This includes research on renewable energy technologies, carbon capture and storage, and sustainable land use practices.
• Neuroscience : Scientists are conducting research to understand the workings of the brain and the nervous system, with the goal of developing new treatments for neurological disorders such as Alzheimer’s disease and Parkinson’s disease.
• Artificial intelligence: Researchers are working to develop new algorithms and technologies to improve the capabilities of artificial intelligence systems. This includes research on machine learning, computer vision, and natural language processing.
• Space exploration: Scientific research is being conducted to explore the cosmos and learn more about the origins of the universe. This includes research on exoplanets, black holes, and the search for extraterrestrial life.

When to use Scientific Research

Some specific situations where scientific research may be particularly useful include:

• Solving problems: Scientific research can be used to investigate practical problems or address real-world challenges. For example, scientists may investigate the causes of a disease in order to develop new treatments, or explore ways to make renewable energy more affordable and accessible.
• Decision-making: Scientific research can provide evidence-based information to inform decision-making. For example, policymakers may use scientific research to evaluate the effectiveness of different policy options or to make decisions about public health and safety.
• Innovation : Scientific research can be used to develop new technologies, products, and processes. For example, research on materials science can lead to the development of new materials with unique properties that can be used in a range of applications.
• Knowledge creation : Scientific research is an important way of generating new knowledge and advancing our understanding of the world around us. This can lead to new theories, insights, and discoveries that can benefit society.

Advantages of Scientific Research

There are many advantages of scientific research, including:

• Improved understanding : Scientific research allows us to gain a deeper understanding of the world around us, from the smallest subatomic particles to the largest celestial bodies.
• Evidence-based decision making: Scientific research provides evidence-based information that can inform decision-making in many fields, from public policy to medicine.
• Technological advancements: Scientific research drives technological advancements in fields such as medicine, engineering, and materials science. These advancements can improve quality of life, increase efficiency, and reduce costs.
• New discoveries: Scientific research can lead to new discoveries and breakthroughs that can advance our knowledge in many fields. These discoveries can lead to new theories, technologies, and products.
• Economic benefits : Scientific research can stimulate economic growth by creating new industries and jobs, and by generating new technologies and products.
• Improved health outcomes: Scientific research can lead to the development of new medical treatments and technologies that can improve health outcomes and quality of life for people around the world.
• Increased innovation: Scientific research encourages innovation by promoting collaboration, creativity, and curiosity. This can lead to new and unexpected discoveries that can benefit society.

Limitations of Scientific Research

Scientific research has some limitations that researchers should be aware of. These limitations can include:

• Research design limitations : The design of a research study can impact the reliability and validity of the results. Poorly designed studies can lead to inaccurate or inconclusive results. Researchers must carefully consider the study design to ensure that it is appropriate for the research question and the population being studied.
• Sample size limitations: The size of the sample being studied can impact the generalizability of the results. Small sample sizes may not be representative of the larger population, and may lead to incorrect conclusions.
• Time and resource limitations: Scientific research can be costly and time-consuming. Researchers may not have the resources necessary to conduct a large-scale study, or may not have sufficient time to complete a study with appropriate controls and analysis.
• Ethical limitations : Certain types of research may raise ethical concerns, such as studies involving human or animal subjects. Ethical concerns may limit the scope of the research that can be conducted, or require additional protocols and procedures to ensure the safety and well-being of participants.
• Limitations of technology: Technology may limit the types of research that can be conducted, or the accuracy of the data collected. For example, certain types of research may require advanced technology that is not yet available, or may be limited by the accuracy of current measurement tools.
• Limitations of existing knowledge: Existing knowledge may limit the types of research that can be conducted. For example, if there is limited knowledge in a particular field, it may be difficult to design a study that can provide meaningful results.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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• v.37(16); 2022 Apr 25

A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

• EXAMPLE 1. Descriptive research question (quantitative research)
• - Presents research variables to be assessed (distinct phenotypes and subphenotypes)
• “BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
• RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
• EXAMPLE 2. Relationship research question (quantitative research)
• - Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
• “Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
• Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
• EXAMPLE 3. Comparative research question (quantitative research)
• - Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
• “BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
• RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
• STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
• EXAMPLE 4. Exploratory research question (qualitative research)
• - Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
• “Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
• EXAMPLE 5. Relationship research question (quantitative research)
• - Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
• “Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

• EXAMPLE 1. Working hypothesis (quantitative research)
• - A hypothesis that is initially accepted for further research to produce a feasible theory
• “As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
• “In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
• EXAMPLE 2. Exploratory hypothesis (qualitative research)
• - Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
• “We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
• “Conclusion
• Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
• EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
• “We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
• Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
• EXAMPLE 4. Statistical hypothesis (quantitative research)
• - An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
• “Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
• “Statistical Analysis
• ( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

• EXAMPLE 1. Background, hypotheses, and aims are provided
• “Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
• “ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
• “This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
• EXAMPLE 2. Background, hypotheses, and aims are provided
• “We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
• “ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
• EXAMPLE 3. Background, aim, and hypothesis are provided
• “In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
• “This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
• “ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Methodology: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ.

Scientific Method

Illustration by J.R. Bee. ThoughtCo. 

• Cell Biology
• Weather & Climate
• B.A., Biology, Emory University
• A.S., Nursing, Chattahoochee Technical College

The scientific method is a series of steps followed by scientific investigators to answer specific questions about the natural world. It involves making observations, formulating a hypothesis , and conducting scientific experiments . Scientific inquiry starts with an observation followed by the formulation of a question about what has been observed. The steps of the scientific method are as follows:

Observation

The first step of the scientific method involves making an observation about something that interests you. This is very important if you are doing a science project because you want your project to be focused on something that will hold your attention. Your observation can be on anything from plant movement to animal behavior, as long as it is something you really want to know more about.​ This is where you come up with the idea for your science project.

Once you've made your observation, you must formulate a question about what you have observed. Your question should tell what it is that you are trying to discover or accomplish in your experiment. When stating your question you should be as specific as possible.​ For example, if you are doing a project on plants , you may want to know how plants interact with microbes. Your question may be: Do plant spices inhibit bacterial growth ?

The hypothesis is a key component of the scientific process. A hypothesis is an idea that is suggested as an explanation for a natural event, a particular experience, or a specific condition that can be tested through definable experimentation. It states the purpose of your experiment, the variables used, and the predicted outcome of your experiment. It is important to note that a hypothesis must be testable. That means that you should be able to test your hypothesis through experimentation .​ Your hypothesis must either be supported or falsified by your experiment. An example of a good hypothesis is: If there is a relation between listening to music and heart rate, then listening to music will cause a person's resting heart rate to either increase or decrease.

Once you've developed a hypothesis, you must design and conduct an experiment that will test it. You should develop a procedure that states very clearly how you plan to conduct your experiment. It is important that you include and identify a controlled variable or dependent variable in your procedure. Controls allow us to test a single variable in an experiment because they are unchanged. We can then make observations and comparisons between our controls and our independent variables (things that change in the experiment) to develop an accurate conclusion.​

The results are where you report what happened in the experiment. That includes detailing all observations and data made during your experiment. Most people find it easier to visualize the data by charting or graphing the information.​

The final step of the scientific method is developing a conclusion. This is where all of the results from the experiment are analyzed and a determination is reached about the hypothesis. Did the experiment support or reject your hypothesis? If your hypothesis was supported, great. If not, repeat the experiment or think of ways to improve your procedure.

• Null Hypothesis Examples
• Examples of Independent and Dependent Variables
• The 10 Most Important Lab Safety Rules
• Difference Between Independent and Dependent Variables
• Six Steps of the Scientific Method
• Scientific Method Flow Chart
• What Is an Experiment? Definition and Design
• Scientific Method Lesson Plan
• How To Design a Science Fair Experiment
• Science Projects for Every Subject
• How to Do a Science Fair Project
• What Are the Elements of a Good Hypothesis?
• How to Write a Lab Report
• What Is a Hypothesis? (Science)
• Understanding Simple vs Controlled Experiments
• Biology Science Fair Project Ideas

Science and the scientific method: Definitions and examples

Here's a look at the foundation of doing science — the scientific method.

The scientific method

Hypothesis, theory and law, a brief history of science, additional resources, bibliography.

Science is a systematic and logical approach to discovering how things in the universe work. It is also the body of knowledge accumulated through the discoveries about all the things in the universe. 

The word "science" is derived from the Latin word "scientia," which means knowledge based on demonstrable and reproducible data, according to the Merriam-Webster dictionary . True to this definition, science aims for measurable results through testing and analysis, a process known as the scientific method. Science is based on fact, not opinion or preferences. The process of science is designed to challenge ideas through research. One important aspect of the scientific process is that it focuses only on the natural world, according to the University of California, Berkeley . Anything that is considered supernatural, or beyond physical reality, does not fit into the definition of science.

When conducting research, scientists use the scientific method to collect measurable, empirical evidence in an experiment related to a hypothesis (often in the form of an if/then statement) that is designed to support or contradict a scientific theory .

"As a field biologist, my favorite part of the scientific method is being in the field collecting the data," Jaime Tanner, a professor of biology at Marlboro College, told Live Science. "But what really makes that fun is knowing that you are trying to answer an interesting question. So the first step in identifying questions and generating possible answers (hypotheses) is also very important and is a creative process. Then once you collect the data you analyze it to see if your hypothesis is supported or not."

The steps of the scientific method go something like this, according to Highline College :

• Make an observation or observations.
• Form a hypothesis — a tentative description of what's been observed, and make predictions based on that hypothesis.
• Test the hypothesis and predictions in an experiment that can be reproduced.
• Analyze the data and draw conclusions; accept or reject the hypothesis or modify the hypothesis if necessary.
• Reproduce the experiment until there are no discrepancies between observations and theory. "Replication of methods and results is my favorite step in the scientific method," Moshe Pritsker, a former post-doctoral researcher at Harvard Medical School and CEO of JoVE, told Live Science. "The reproducibility of published experiments is the foundation of science. No reproducibility — no science."

Some key underpinnings to the scientific method:

• The hypothesis must be testable and falsifiable, according to North Carolina State University . Falsifiable means that there must be a possible negative answer to the hypothesis.
• Research must involve deductive reasoning and inductive reasoning . Deductive reasoning is the process of using true premises to reach a logical true conclusion while inductive reasoning uses observations to infer an explanation for those observations.
• An experiment should include a dependent variable (which does not change) and an independent variable (which does change), according to the University of California, Santa Barbara .
• An experiment should include an experimental group and a control group. The control group is what the experimental group is compared against, according to Britannica .

The process of generating and testing a hypothesis forms the backbone of the scientific method. When an idea has been confirmed over many experiments, it can be called a scientific theory. While a theory provides an explanation for a phenomenon, a scientific law provides a description of a phenomenon, according to The University of Waikato . One example would be the law of conservation of energy, which is the first law of thermodynamics that says that energy can neither be created nor destroyed. 

A law describes an observed phenomenon, but it doesn't explain why the phenomenon exists or what causes it. "In science, laws are a starting place," said Peter Coppinger, an associate professor of biology and biomedical engineering at the Rose-Hulman Institute of Technology. "From there, scientists can then ask the questions, 'Why and how?'"

Laws are generally considered to be without exception, though some laws have been modified over time after further testing found discrepancies. For instance, Newton's laws of motion describe everything we've observed in the macroscopic world, but they break down at the subatomic level.

This does not mean theories are not meaningful. For a hypothesis to become a theory, scientists must conduct rigorous testing, typically across multiple disciplines by separate groups of scientists. Saying something is "just a theory" confuses the scientific definition of "theory" with the layperson's definition. To most people a theory is a hunch. In science, a theory is the framework for observations and facts, Tanner told Live Science.

The earliest evidence of science can be found as far back as records exist. Early tablets contain numerals and information about the solar system , which were derived by using careful observation, prediction and testing of those predictions. Science became decidedly more "scientific" over time, however.

1200s: Robert Grosseteste developed the framework for the proper methods of modern scientific experimentation, according to the Stanford Encyclopedia of Philosophy. His works included the principle that an inquiry must be based on measurable evidence that is confirmed through testing.

1400s: Leonardo da Vinci began his notebooks in pursuit of evidence that the human body is microcosmic. The artist, scientist and mathematician also gathered information about optics and hydrodynamics.

1500s: Nicolaus Copernicus advanced the understanding of the solar system with his discovery of heliocentrism. This is a model in which Earth and the other planets revolve around the sun, which is the center of the solar system.

1600s: Johannes Kepler built upon those observations with his laws of planetary motion. Galileo Galilei improved on a new invention, the telescope, and used it to study the sun and planets. The 1600s also saw advancements in the study of physics as Isaac Newton developed his laws of motion.

1700s: Benjamin Franklin discovered that lightning is electrical. He also contributed to the study of oceanography and meteorology. The understanding of chemistry also evolved during this century as Antoine Lavoisier, dubbed the father of modern chemistry , developed the law of conservation of mass.

1800s: Milestones included Alessandro Volta's discoveries regarding electrochemical series, which led to the invention of the battery. John Dalton also introduced atomic theory, which stated that all matter is composed of atoms that combine to form molecules. The basis of modern study of genetics advanced as Gregor Mendel unveiled his laws of inheritance. Later in the century, Wilhelm Conrad Röntgen discovered X-rays , while George Ohm's law provided the basis for understanding how to harness electrical charges.

1900s: The discoveries of Albert Einstein , who is best known for his theory of relativity, dominated the beginning of the 20th century. Einstein's theory of relativity is actually two separate theories. His special theory of relativity, which he outlined in a 1905 paper, " The Electrodynamics of Moving Bodies ," concluded that time must change according to the speed of a moving object relative to the frame of reference of an observer. His second theory of general relativity, which he published as " The Foundation of the General Theory of Relativity ," advanced the idea that matter causes space to curve.

In 1952, Jonas Salk developed the polio vaccine , which reduced the incidence of polio in the United States by nearly 90%, according to Britannica . The following year, James D. Watson and Francis Crick discovered the structure of DNA , which is a double helix formed by base pairs attached to a sugar-phosphate backbone, according to the National Human Genome Research Institute .

2000s: The 21st century saw the first draft of the human genome completed, leading to a greater understanding of DNA. This advanced the study of genetics, its role in human biology and its use as a predictor of diseases and other disorders, according to the National Human Genome Research Institute .

• This video from City University of New York delves into the basics of what defines science.
• Learn about what makes science science in this book excerpt from Washington State University .
• This resource from the University of Michigan — Flint explains how to design your own scientific study.

Merriam-Webster Dictionary, Scientia. 2022. https://www.merriam-webster.com/dictionary/scientia

University of California, Berkeley, "Understanding Science: An Overview." 2022. ​​ https://undsci.berkeley.edu/article/0_0_0/intro_01  

Highline College, "Scientific method." July 12, 2015. https://people.highline.edu/iglozman/classes/astronotes/scimeth.htm  

North Carolina State University, "Science Scripts." https://projects.ncsu.edu/project/bio183de/Black/science/science_scripts.html  

University of California, Santa Barbara. "What is an Independent variable?" October 31,2017. http://scienceline.ucsb.edu/getkey.php?key=6045  

Encyclopedia Britannica, "Control group." May 14, 2020. https://www.britannica.com/science/control-group  

The University of Waikato, "Scientific Hypothesis, Theories and Laws." https://sci.waikato.ac.nz/evolution/Theories.shtml  

Stanford Encyclopedia of Philosophy, Robert Grosseteste. May 3, 2019. https://plato.stanford.edu/entries/grosseteste/  

Encyclopedia Britannica, "Jonas Salk." October 21, 2021. https://www.britannica.com/ biography /Jonas-Salk

National Human Genome Research Institute, "​Phosphate Backbone." https://www.genome.gov/genetics-glossary/Phosphate-Backbone  

National Human Genome Research Institute, "What is the Human Genome Project?" https://www.genome.gov/human-genome-project/What  

‌ Live Science contributor Ashley Hamer updated this article on Jan. 16, 2022.

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1.2 Scientific Research in Psychology

Learning objectives.

• Describe a general model of scientific research in psychology and give specific examples that fit the model.
• Explain who conducts scientific research in psychology and why they do it.
• Distinguish between basic research and applied research.

A Model of Scientific Research in Psychology

Figure 1.2 “A Simple Model of Scientific Research in Psychology” presents a more specific model of scientific research in psychology. The researcher (who more often than not is really a small group of researchers) formulates a research question, conducts a study designed to answer the question, analyzes the resulting data, draws conclusions about the answer to the question, and publishes the results so that they become part of the research literature. Because the research literature is one of the primary sources of new research questions, this process can be thought of as a cycle. New research leads to new questions, which lead to new research, and so on. Figure 1.2 “A Simple Model of Scientific Research in Psychology” also indicates that research questions can originate outside of this cycle either with informal observations or with practical problems that need to be solved. But even in these cases, the researcher would start by checking the research literature to see if the question had already been answered and to refine it based on what previous research had already found.

Figure 1.2 A Simple Model of Scientific Research in Psychology

The research by Mehl and his colleagues is described nicely by this model. Their question—whether women are more talkative than men—was suggested to them both by people’s stereotypes and by published claims about the relative talkativeness of women and men. When they checked the research literature, however, they found that this question had not been adequately addressed in scientific studies. They conducted a careful empirical study, analyzed the results (finding very little difference between women and men), and published their work so that it became part of the research literature. The publication of their article is not the end of the story, however, because their work suggests many new questions (about the reliability of the result, about potential cultural differences, etc.) that will likely be taken up by them and by other researchers inspired by their work.

Scientific research has confirmed that cell phone use impairs a variety of driving behaviors.

Indiana Stan – CC BY-NC 2.0.

As another example, consider that as cell phones became more widespread during the 1990s, people began to wonder whether, and to what extent, cell phone use had a negative effect on driving. Many psychologists decided to tackle this question scientifically (Collet, Guillot, & Petit, 2010). It was clear from previously published research that engaging in a simple verbal task impairs performance on a perceptual or motor task carried out at the same time, but no one had studied the effect specifically of cell phone use on driving. Under carefully controlled conditions, these researchers compared people’s driving performance while using a cell phone with their performance while not using a cell phone, both in the lab and on the road. They found that people’s ability to detect road hazards, reaction time, and control of the vehicle were all impaired by cell phone use. Each new study was published and became part of the growing research literature on this topic.

Who Conducts Scientific Research in Psychology?

Scientific research in psychology is generally conducted by people with doctoral degrees (usually the doctor of philosophy [PhD] ) and master’s degrees in psychology and related fields, often supported by research assistants with bachelor’s degrees or other relevant training. Some of them work for government agencies (e.g., the National Institute of Mental Health), for nonprofit organizations (e.g., the American Cancer Society), or in the private sector (e.g., in product development). However, the majority of them are college and university faculty, who often collaborate with their graduate and undergraduate students. Although some researchers are trained and licensed as clinicians—especially those who conduct research in clinical psychology—the majority are not. Instead, they have expertise in one or more of the many other subfields of psychology: behavioral neuroscience, cognitive psychology, developmental psychology, personality psychology, social psychology, and so on. Doctoral-level researchers might be employed to conduct research full-time or, like many college and university faculty members, to conduct research in addition to teaching classes and serving their institution and community in other ways.

Of course, people also conduct research in psychology because they enjoy the intellectual and technical challenges involved and the satisfaction of contributing to scientific knowledge of human behavior. You might find that you enjoy the process too. If so, your college or university might offer opportunities to get involved in ongoing research as either a research assistant or a participant. Of course, you might find that you do not enjoy the process of conducting scientific research in psychology. But at least you will have a better understanding of where scientific knowledge in psychology comes from, an appreciation of its strengths and limitations, and an awareness of how it can be applied to solve practical problems in psychology and everyday life.

Scientific Psychology Blogs

A fun and easy way to follow current scientific research in psychology is to read any of the many excellent blogs devoted to summarizing and commenting on new findings. Among them are the following:

• Child-Psych, http://www.child-psych.org
• PsyBlog, http://www.spring.org.uk
• Research Digest, http://bps-research-digest.blogspot.com
• Social Psychology Eye, http://socialpsychologyeye.wordpress.com
• We’re Only Human, http://www.psychologicalscience.org/onlyhuman

You can also browse to http://www.researchblogging.org , select psychology as your topic, and read entries from a wide variety of blogs.

The Broader Purposes of Scientific Research in Psychology

People have always been curious about the natural world, including themselves and their behavior. (In fact, this is probably why you are studying psychology in the first place.) Science grew out of this natural curiosity and has become the best way to achieve detailed and accurate knowledge. Keep in mind that most of the phenomena and theories that fill psychology textbooks are the products of scientific research. In a typical introductory psychology textbook, for example, one can learn about specific cortical areas for language and perception, principles of classical and operant conditioning, biases in reasoning and judgment, and people’s surprising tendency to obey authority. And scientific research continues because what we know right now only scratches the surface of what we can know.

Scientific research is often classified as being either basic or applied. Basic research in psychology is conducted primarily for the sake of achieving a more detailed and accurate understanding of human behavior, without necessarily trying to address any particular practical problem. The research of Mehl and his colleagues falls into this category. Applied research is conducted primarily to address some practical problem. Research on the effects of cell phone use on driving, for example, was prompted by safety concerns and has led to the enactment of laws to limit this practice. Although the distinction between basic and applied research is convenient, it is not always clear-cut. For example, basic research on sex differences in talkativeness could eventually have an effect on how marriage therapy is practiced, and applied research on the effect of cell phone use on driving could produce new insights into basic processes of perception, attention, and action.

Key Takeaways

• Research in psychology can be described by a simple cyclical model. A research question based on the research literature leads to an empirical study, the results of which are published and become part of the research literature.
• Scientific research in psychology is conducted mainly by people with doctoral degrees in psychology and related fields, most of whom are college and university faculty members. They do so for professional and for personal reasons, as well as to contribute to scientific knowledge about human behavior.
• Basic research is conducted to learn about human behavior for its own sake, and applied research is conducted to solve some practical problem. Both are valuable, and the distinction between the two is not always clear-cut.
• Practice: Find a description of an empirical study in a professional journal or in one of the scientific psychology blogs. Then write a brief description of the research in terms of the cyclical model presented here. One or two sentences for each part of the cycle should suffice.
• Practice: Based on your own experience or on things you have already learned about psychology, list three basic research questions and three applied research questions of interest to you.

Collet, C., Guillot, A., & Petit, C. (2010). Phoning while driving I: A review of epidemiological, psychological, behavioural and physiological studies. Ergonomics, 53 , 589–601.

Research Methods in Psychology Copyright © 2016 by University of Minnesota is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

Education During Coronavirus

A Smithsonian magazine special report

Science | June 15, 2020

Seventy-Five Scientific Research Projects You Can Contribute to Online

From astrophysicists to entomologists, many researchers need the help of citizen scientists to sift through immense data collections

Rachael Lallensack

Former Assistant Editor, Science and Innovation

If you find yourself tired of streaming services, reading the news or video-chatting with friends, maybe you should consider becoming a citizen scientist. Though it’s true that many field research projects are paused , hundreds of scientists need your help sifting through wildlife camera footage and images of galaxies far, far away, or reading through diaries and field notes from the past.

Plenty of these tools are free and easy enough for children to use. You can look around for projects yourself on Smithsonian Institution’s citizen science volunteer page , National Geographic ’s list of projects and CitizenScience.gov ’s catalog of options. Zooniverse is a platform for online-exclusive projects , and Scistarter allows you to restrict your search with parameters, including projects you can do “on a walk,” “at night” or “on a lunch break.”

To save you some time, Smithsonian magazine has compiled a collection of dozens of projects you can take part in from home.

American Wildlife

If being home has given you more time to look at wildlife in your own backyard, whether you live in the city or the country, consider expanding your view, by helping scientists identify creatures photographed by camera traps. Improved battery life, motion sensors, high-resolution and small lenses have made camera traps indispensable tools for conservation.These cameras capture thousands of images that provide researchers with more data about ecosystems than ever before.

Smithsonian Conservation Biology Institute’s eMammal platform , for example, asks users to identify animals for conservation projects around the country. Currently, eMammal is being used by the Woodland Park Zoo ’s Seattle Urban Carnivore Project, which studies how coyotes, foxes, raccoons, bobcats and other animals coexist with people, and the Washington Wolverine Project, an effort to monitor wolverines in the face of climate change. Identify urban wildlife for the Chicago Wildlife Watch , or contribute to wilderness projects documenting North American biodiversity with The Wilds' Wildlife Watch in Ohio , Cedar Creek: Eyes on the Wild in Minnesota , Michigan ZoomIN , Western Montana Wildlife and Snapshot Wisconsin .

"Spend your time at home virtually exploring the Minnesota backwoods,” writes the lead researcher of the Cedar Creek: Eyes on the Wild project. “Help us understand deer dynamics, possum populations, bear behavior, and keep your eyes peeled for elusive wolves!"

If being cooped up at home has you daydreaming about traveling, Snapshot Safari has six active animal identification projects. Try eyeing lions, leopards, cheetahs, wild dogs, elephants, giraffes, baobab trees and over 400 bird species from camera trap photos taken in South African nature reserves, including De Hoop Nature Reserve and Madikwe Game Reserve .

With South Sudan DiversityCam , researchers are using camera traps to study biodiversity in the dense tropical forests of southwestern South Sudan. Part of the Serenegeti Lion Project, Snapshot Serengeti needs the help of citizen scientists to classify millions of camera trap images of species traveling with the wildebeest migration.

Classify all kinds of monkeys with Chimp&See . Count, identify and track giraffes in northern Kenya . Watering holes host all kinds of wildlife, but that makes the locales hotspots for parasite transmission; Parasite Safari needs volunteers to help figure out which animals come in contact with each other and during what time of year.

Mount Taranaki in New Zealand is a volcanic peak rich in native vegetation, but native wildlife, like the North Island brown kiwi, whio/blue duck and seabirds, are now rare—driven out by introduced predators like wild goats, weasels, stoats, possums and rats. Estimate predator species compared to native wildlife with Taranaki Mounga by spotting species on camera trap images.

The Zoological Society of London’s (ZSL) Instant Wild app has a dozen projects showcasing live images and videos of wildlife around the world. Look for bears, wolves and lynx in Croatia ; wildcats in Costa Rica’s Osa Peninsula ; otters in Hampshire, England ; and both black and white rhinos in the Lewa-Borana landscape in Kenya.

Under the Sea

Researchers use a variety of technologies to learn about marine life and inform conservation efforts. Take, for example, Beluga Bits , a research project focused on determining the sex, age and pod size of beluga whales visiting the Churchill River in northern Manitoba, Canada. With a bit of training, volunteers can learn how to differentiate between a calf, a subadult (grey) or an adult (white)—and even identify individuals using scars or unique pigmentation—in underwater videos and images. Beluga Bits uses a “ beluga boat ,” which travels around the Churchill River estuary with a camera underneath it, to capture the footage and collect GPS data about the whales’ locations.

Many of these online projects are visual, but Manatee Chat needs citizen scientists who can train their ear to decipher manatee vocalizations. Researchers are hoping to learn what calls the marine mammals make and when—with enough practice you might even be able to recognize the distinct calls of individual animals.

Several groups are using drone footage to monitor seal populations. Seals spend most of their time in the water, but come ashore to breed. One group, Seal Watch , is analyzing time-lapse photography and drone images of seals in the British territory of South Georgia in the South Atlantic. A team in Antarctica captured images of Weddell seals every ten minutes while the seals were on land in spring to have their pups. The Weddell Seal Count project aims to find out what threats—like fishing and climate change—the seals face by monitoring changes in their population size. Likewise, the Año Nuevo Island - Animal Count asks volunteers to count elephant seals, sea lions, cormorants and more species on a remote research island off the coast of California.

With Floating Forests , you’ll sift through 40 years of satellite images of the ocean surface identifying kelp forests, which are foundational for marine ecosystems, providing shelter for shrimp, fish and sea urchins. A project based in southwest England, Seagrass Explorer , is investigating the decline of seagrass beds. Researchers are using baited cameras to spot commercial fish in these habitats as well as looking out for algae to study the health of these threatened ecosystems. Search for large sponges, starfish and cold-water corals on the deep seafloor in Sweden’s first marine park with the Koster seafloor observatory project.

The Smithsonian Environmental Research Center needs your help spotting invasive species with Invader ID . Train your eye to spot groups of organisms, known as fouling communities, that live under docks and ship hulls, in an effort to clean up marine ecosystems.

If art history is more your speed, two Dutch art museums need volunteers to start “ fishing in the past ” by analyzing a collection of paintings dating from 1500 to 1700. Each painting features at least one fish, and an interdisciplinary research team of biologists and art historians wants you to identify the species of fish to make a clearer picture of the “role of ichthyology in the past.”

Interesting Insects

Notes from Nature is a digitization effort to make the vast resources in museums’ archives of plants and insects more accessible. Similarly, page through the University of California Berkeley’s butterfly collection on CalBug to help researchers classify these beautiful critters. The University of Michigan Museum of Zoology has already digitized about 300,000 records, but their collection exceeds 4 million bugs. You can hop in now and transcribe their grasshopper archives from the last century . Parasitic arthropods, like mosquitos and ticks, are known disease vectors; to better locate these critters, the Terrestrial Parasite Tracker project is working with 22 collections and institutions to digitize over 1.2 million specimens—and they’re 95 percent done . If you can tolerate mosquito buzzing for a prolonged period of time, the HumBug project needs volunteers to train its algorithm and develop real-time mosquito detection using acoustic monitoring devices. It’s for the greater good!

For the Birders

Birdwatching is one of the most common forms of citizen science . Seeing birds in the wilderness is certainly awe-inspiring, but you can birdwatch from your backyard or while walking down the sidewalk in big cities, too. With Cornell University’s eBird app , you can contribute to bird science at any time, anywhere. (Just be sure to remain a safe distance from wildlife—and other humans, while we social distance ). If you have safe access to outdoor space—a backyard, perhaps—Cornell also has a NestWatch program for people to report observations of bird nests. Smithsonian’s Migratory Bird Center has a similar Neighborhood Nest Watch program as well.

Birdwatching is easy enough to do from any window, if you’re sheltering at home, but in case you lack a clear view, consider these online-only projects. Nest Quest currently has a robin database that needs volunteer transcribers to digitize their nest record cards.

You can also pitch in on a variety of efforts to categorize wildlife camera images of burrowing owls , pelicans , penguins (new data coming soon!), and sea birds . Watch nest cam footage of the northern bald ibis or greylag geese on NestCams to help researchers learn about breeding behavior.

Or record the coloration of gorgeous feathers across bird species for researchers at London’s Natural History Museum with Project Plumage .

Pretty Plants

If you’re out on a walk wondering what kind of plants are around you, consider downloading Leafsnap , an electronic field guide app developed by Columbia University, the University of Maryland and the Smithsonian Institution. The app has several functions. First, it can be used to identify plants with its visual recognition software. Secondly, scientists can learn about the “ the ebb and flow of flora ” from geotagged images taken by app users.

What is older than the dinosaurs, survived three mass extinctions and still has a living relative today? Ginko trees! Researchers at Smithsonian’s National Museum of Natural History are studying ginko trees and fossils to understand millions of years of plant evolution and climate change with the Fossil Atmospheres project . Using Zooniverse, volunteers will be trained to identify and count stomata, which are holes on a leaf’s surface where carbon dioxide passes through. By counting these holes, or quantifying the stomatal index, scientists can learn how the plants adapted to changing levels of carbon dioxide. These results will inform a field experiment conducted on living trees in which a scientist is adjusting the level of carbon dioxide for different groups.

Help digitize and categorize millions of botanical specimens from natural history museums, research institutions and herbaria across the country with the Notes from Nature Project . Did you know North America is home to a variety of beautiful orchid species? Lend botanists a handby typing handwritten labels on pressed specimens or recording their geographic and historic origins for the New York Botanical Garden’s archives. Likewise, the Southeastern U.S. Biodiversity project needs assistance labeling pressed poppies, sedums, valerians, violets and more. Groups in California , Arkansas , Florida , Texas and Oklahoma all invite citizen scientists to partake in similar tasks.

Historic Women in Astronomy

Become a transcriber for Project PHaEDRA and help researchers at the Harvard-Smithsonian Center for Astrophysics preserve the work of Harvard’s women “computers” who revolutionized astronomy in the 20th century. These women contributed more than 130 years of work documenting the night sky, cataloging stars, interpreting stellar spectra, counting galaxies, and measuring distances in space, according to the project description .

More than 2,500 notebooks need transcription on Project PhaEDRA - Star Notes . You could start with Annie Jump Cannon , for example. In 1901, Cannon designed a stellar classification system that astronomers still use today. Cecilia Payne discovered that stars are made primarily of hydrogen and helium and can be categorized by temperature. Two notebooks from Henrietta Swan Leavitt are currently in need of transcription. Leavitt, who was deaf, discovered the link between period and luminosity in Cepheid variables, or pulsating stars, which “led directly to the discovery that the Universe is expanding,” according to her bio on Star Notes .

Volunteers are also needed to transcribe some of these women computers’ notebooks that contain references to photographic glass plates . These plates were used to study space from the 1880s to the 1990s. For example, in 1890, Williamina Flemming discovered the Horsehead Nebula on one of these plates . With Star Notes, you can help bridge the gap between “modern scientific literature and 100 years of astronomical observations,” according to the project description . Star Notes also features the work of Cannon, Leavitt and Dorrit Hoffleit , who authored the fifth edition of the Bright Star Catalog, which features 9,110 of the brightest stars in the sky.

Microscopic Musings

Electron microscopes have super-high resolution and magnification powers—and now, many can process images automatically, allowing teams to collect an immense amount of data. Francis Crick Institute’s Etch A Cell - Powerhouse Hunt project trains volunteers to spot and trace each cell’s mitochondria, a process called manual segmentation. Manual segmentation is a major bottleneck to completing biological research because using computer systems to complete the work is still fraught with errors and, without enough volunteers, doing this work takes a really long time.

For the Monkey Health Explorer project, researchers studying the social behavior of rhesus monkeys on the tiny island Cayo Santiago off the southeastern coast of Puerto Rico need volunteers to analyze the monkeys’ blood samples. Doing so will help the team understand which monkeys are sick and which are healthy, and how the animals’ health influences behavioral changes.

Using the Zooniverse’s app on a phone or tablet, you can become a “ Science Scribbler ” and assist researchers studying how Huntington disease may change a cell’s organelles. The team at the United Kingdom's national synchrotron , which is essentially a giant microscope that harnesses the power of electrons, has taken highly detailed X-ray images of the cells of Huntington’s patients and needs help identifying organelles, in an effort to see how the disease changes their structure.

Oxford University’s Comprehensive Resistance Prediction for Tuberculosis: an International Consortium—or CRyPTIC Project , for short, is seeking the aid of citizen scientists to study over 20,000 TB infection samples from around the world. CRyPTIC’s citizen science platform is called Bash the Bug . On the platform, volunteers will be trained to evaluate the effectiveness of antibiotics on a given sample. Each evaluation will be checked by a scientist for accuracy and then used to train a computer program, which may one day make this process much faster and less labor intensive.

Out of This World

If you’re interested in contributing to astronomy research from the comfort and safety of your sidewalk or backyard, check out Globe at Night . The project monitors light pollution by asking users to try spotting constellations in the night sky at designated times of the year . (For example, Northern Hemisphere dwellers should look for the Bootes and Hercules constellations from June 13 through June 22 and record the visibility in Globe at Night’s app or desktop report page .)

For the amateur astrophysicists out there, the opportunities to contribute to science are vast. NASA's Wide-field Infrared Survey Explorer (WISE) mission is asking for volunteers to search for new objects at the edges of our solar system with the Backyard Worlds: Planet 9 project .

Galaxy Zoo on Zooniverse and its mobile app has operated online citizen science projects for the past decade. According to the project description, there are roughly one hundred billion galaxies in the observable universe. Surprisingly, identifying different types of galaxies by their shape is rather easy. “If you're quick, you may even be the first person to see the galaxies you're asked to classify,” the team writes.

With Radio Galaxy Zoo: LOFAR , volunteers can help identify supermassive blackholes and star-forming galaxies. Galaxy Zoo: Clump Scout asks users to look for young, “clumpy” looking galaxies, which help astronomers understand galaxy evolution.

If current events on Earth have you looking to Mars, perhaps you’d be interested in checking out Planet Four and Planet Four: Terrains —both of which task users with searching and categorizing landscape formations on Mars’ southern hemisphere. You’ll scroll through images of the Martian surface looking for terrain types informally called “spiders,” “baby spiders,” “channel networks” and “swiss cheese.”

Gravitational waves are telltale ripples in spacetime, but they are notoriously difficult to measure. With Gravity Spy , citizen scientists sift through data from Laser Interferometer Gravitational­-Wave Observatory, or LIGO , detectors. When lasers beamed down 2.5-mile-long “arms” at these facilities in Livingston, Louisiana and Hanford, Washington are interrupted, a gravitational wave is detected. But the detectors are sensitive to “glitches” that, in models, look similar to the astrophysical signals scientists are looking for. Gravity Spy teaches citizen scientists how to identify fakes so researchers can get a better view of the real deal. This work will, in turn, train computer algorithms to do the same.

Similarly, the project Supernova Hunters needs volunteers to clear out the “bogus detections of supernovae,” allowing researchers to track the progression of actual supernovae. In Hubble Space Telescope images, you can search for asteroid tails with Hubble Asteroid Hunter . And with Planet Hunters TESS , which teaches users to identify planetary formations, you just “might be the first person to discover a planet around a nearby star in the Milky Way,” according to the project description.

Help astronomers refine prediction models for solar storms, which kick up dust that impacts spacecraft orbiting the sun, with Solar Stormwatch II. Thanks to the first iteration of the project, astronomers were able to publish seven papers with their findings.

With Mapping Historic Skies , identify constellations on gorgeous celestial maps of the sky covering a span of 600 years from the Adler Planetarium collection in Chicago. Similarly, help fill in the gaps of historic astronomy with Astronomy Rewind , a project that aims to “make a holistic map of images of the sky.”

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Rachael Lallensack | READ MORE

Rachael Lallensack is the former assistant web editor for science and innovation at Smithsonian .

Scientific research cooperation: Why collaborate in science? Benefits and examples

The need for a stronger scientific collaboration

It was one of the longest-standing enigmas in art history. For centuries, no one had been able to say for sure that a Madonna and Child painting, often attributed to Raphael, had been directly created by the great Renaissance master himself.

During that time, the painting had changed hands many times. It became the property of popes, was looted by Napoleon during the Italian campaign and in the 1930s ended up in a private collection in Prague, disappearing from public view.

The painting lay almost forgotten until 2020, when a robotic scanner using a particle detector developed at CERN , the European Organization for Nuclear Research, confirmed the brushstrokes on the canvas were indeed Raphael’s.

The authentication of Raphael’s painting through particle detection is just one of the many scientific discoveries that have moved from CERN’s laboratories in Switzerland to daily life, along with the World Wide Web and medical scanners.

Since its foundation in 1954 under the auspices of UNESCO, the complex – one of the largest scientific facilities on earth – has been home to scientists, engineers and students from CERN’s 21 Member States and visiting scholars from other countries.

More than six decades later, CERN has become one the most striking examples of successful scientific cooperation in the world. Its birth was one of the first large initiatives in science and science diplomacy at UNESCO, as well as a diplomatic answer to seek the peaceful benefits of atomic energy after the destruction caused by WW2. Today, CERN has become a model for cooperation in terms of research, embodying the ‘one-earth’ approach that the world needs to tackle the global challenges we are facing.

Places like CERN contribute to the kind of knowledge that not only enriches humanity but provides the wellspring of ideas that become the technologies of the future.

The path of science diplomacy

World War II had not long ended when the idea of scientific laboratories began to emerge under the auspices of UNESCO. It was felt that such endeavours would bring warring nations together, rebuild cooperation and reach scientific excellence.

US Nobel laureate for physics Isidor Rabi’s proposal resulted in the constitution of CERN four years later.

As the world emerged from the ravages of the war, the idea of science diplomacy began to gain traction. In August 1955, the United Nations’ International Conference on the Peaceful Uses of Atomic Energy, known as "Atoms for Peace", was held in Geneva, attended by a delegation from the USSR that included a number of scientists. It was the first time that a large delegation of Soviet scientists working in particle physics took part in a scientific conference in the West. The symposium offered the opportunity for many to make personal contacts. Several Soviet physicists who attended went on to fill important roles in their countries and their work began to be translated into English and published in the West.

Using CERN as a blueprint, global cooperation among scientists became one of UNESCO’s key missions and paved the way to support other institutions that combine scientific excellence with science diplomacy. Science diplomacy helps establish links and strengthen relations between societies, especially where there may not be another official approach.  Science is then used to strengthen or build links between countries that have tense or even non-existent relationships.

UNESCO should be the catalyst for the science in the world. I do not mean that UNESCO should run the research centres, but that it should make the initial plans, get them started and see that they are kept going.

Scientific community: linking East and West

Even though the Cold War continued to intensify, scientific cooperation projects were able to demonstrate the capacity of scientific cooperation to forge links between countries and colleagues beyond political or religious considerations.

Ten years after the birth of CERN, UNESCO supported the creation of another venture that would provide a rare line of communication between scientists from the East and the West.

In 1960, a 34-year-old physicist from Pakistan, future Nobel laureate Abdus Salam, suggested the founding of an international theoretical physics institute to help advance scientific expertise.

Salam was convinced that "scientific thought and its creation are the common and shared heritage of mankind". However, at that time, researchers in developing countries, as well as those in smaller countries of the developed world, were often unable to improve their knowledge and sharpen their skills.

His proposal became a reality in 1964 when the International Centre for Theoretical Physics (ICTP) was set up in Trieste, Italy, through an agreement between UNESCO, the Italian Government and the International Atomic Energy Agency.

Over the decades, ICTP has provided scientists from developing countries with the continuing education and skills necessary to further their careers. Many alumni teach at major universities in their countries, lead key research centres and have been recognized for their contributions to science.

Another example of international cooperation in science: a global vision for the Earth’s soil

Amid the successive waves of decolonisation in Africa and Asia, the 1960s became the United Nations Development Decade. At the time, soil erosion – along with the threat it posed to the global food supply – was a main concern for conservationists, just like global warming is today for 21st-century citizens.

The world needed a global map to obtain a comprehensive appraisal of its soil resources.  However, no international soil classification existed at the time. Many countries, in fact, had multiple competing regional classifications or were developing their own national systems. Only international collaboration could produce reliable knowledge with worldwide legitimacy and deal with the terminology jungle that until then had undermined international scientific communication.

The Soil Map of the World , backed by UNESCO and the UN’s Food and Agriculture Organization (FAO) , began in 1961 – just a few months before President Kennedy proclaimed the 1960s were the Decade of Development at a meeting of the UN General Assembly.

The Herculean project, completed over a span of twenty years and now available in digital form, is the result of a worldwide collaboration between many soil scientists from different countries who worked together to develop a new international classification system. Until recently, it was the only global overview of the planet’s soil resources and a concrete example of the power of scientific collaboration to bring the world together.

Benefits of scientific collaboration: Humanity and the Biosphere

By the late 1960s and early 1970s, global environmental problems had taken centre stage. The post-war economic boom had brought an endless appetite for non-renewable resources, higher levels of pollution and the potential loss of environmental habitats.

In 1971, some 4,000 scientists from around the world warned the UN Secretary-General in the "Menton Message" that there were already far too many people on Earth in proportion to the available resources.

How could human beings continue to develop while preserving the biodiversity that surrounds them? To help answer this question, UNESCO launched the Man and the Biosphere Programme (MAB) in 1971.

One year before the landmark Stockholm conference that spearheaded the concept of sustainable development, UNESCO’s Man and Biosphere programme proposed the creation of some areas committed to the conservation of nature through sustainable socio-economic development, where local cultures and traditions are respected. This was clearly a revolutionary approach to nature conservation, stating that the preservation of nature did not mean the creation of pristine isolated parks and reserves, but the development and promotion of sustainable ways to manage resources and live in harmony with nature. These places were called Biosphere Reserves. Since the birth of the programme, the reserves have promoted the peaceful and balanced coexistence between people and nature, the development of society and the respect for natural and geological heritage. Each reserve supports projects in many different areas, such as sustainable tourism, organic production and, most importantly, scientific investigation.

Through MAB, UNESCO provides a unique platform for cooperation on research and development, capacity-building and networking to share information across 727 biosphere reserves in 131 countries around the world (in 2021), where 260 million people call their biosphere reserves their home. The experiences and Biosphere reserves are "learning places for sustainable development". They provide evidence that living in harmony with nature is possible, and they develop practices and skills to reconcile the people and the planet.

How do scientists collaborate? Science for peace in the Middle East

Middle Eastern countries share many unifying attributes, such as language, religion, history, culture and common aspirations. Throughout recent history, however, development in the region has been held back by political instability and conflict.

Bringing them together to establish an intergovernmental organization that could push aside historical and political differences in the name of science became UNESCO’s mission in the new millennium.

Despite numerous challenges, the International Centre for Synchrotron Light for Experimental Science and Applications in the Middle East ( SESAME ) became a reality in 2017.

Based in Jordan, the laboratory helps Members of the region’s scientific community carry out world-class scientific research in several fields ranging from biology to archaeology.

Such high-level scientific cooperation is helping to foster a culture of peace in the region. Scientists from the eight full member countries – Cyprus, Egypt, Iran, Israel, Jordan, Pakistan, Palestine and Turkey – are working together within the SESAME community, proving that science can be a common language.

We are trying to build, with the use of science, understanding in the region. The project is very special. Each of us brings its own history, its own wounds, its own scars. Each of us has its own interests, yet we have a common vision, which is to benefit the people of the region and the whole of humanity.

Open science collaboration and innovation for a sustainable future

Humanity continues to face complex challenges that governments and communities cannot solve alone.

The COVID-19 pandemic has highlighted the need to reinforce cooperation, as it has once again reminded us that we all live on one planet. The record speed with which COVID-19 vaccines were developed is due in part to global scientific collaboration.

The dominant view among global leaders is that scientific collaboration is essential to tackle imminent threats such as biodiversity loss, pollution, poverty reduction and the introduction of disruptive new technologies, including artificial intelligence.

To address the complex challenges of the 21st century, science needs to be more transparent, accessible and inclusive. It needs to become open.

Nearly 70% of scientific publications in the world have paid or restricted access. During the health crisis, this proportion dropped to 30% for publications dedicated to COVID-19. This is proof that science can be more transparent and better shared to accelerate research for the benefit of all.

Sharing scientific data on a global scale is a formidable research accelerator - it only took 3 days to decode the genome of the Coronavirus, thanks to an unprecedented collaboration of researchers across borders.

With open science, scientists and engineers can use open licences to share their publications, data, research materials and infrastructure more widely.

By opening traditional science to other knowledge systems, science can be enriched by exchanges with indigenous and marginalized groups for the benefit of all people in every corner of the world.

In 2021, UNESCO adopted the first global recommendation for open science, so that knowledge is no longer the privilege of a minority, but a common good accessible in a more equitable way.

Many scientists have already joined UNESCO in developing the first International Recommendation on Open Science, setting global standards for making open science a reality that leaves no one behind.

However, unrestrained scientific progress is not always ethically acceptable.

The rapid pace of scientific development is not necessarily matched by the various dialogues about its potential impact on society. To address these concerns, since the 1970s, UNESCO has been involved in promoting international reflections on the ethics of life sciences, culminating in the creation of the Programme on Ethics of Science and Technology in the 1990s.

UNESCO regards the human genome as the "heritage of humanity", which should be protected and passed on to future generations. All advances in science need to be considered in the light of human rights.

UNESCO’s initiatives for science

A timeline of our initiatives

CERN - Advancing the frontiers of technology

Every day, thousands of engineers, technicians and scientists work on developing novel  technologies and expertise that can be shared with society.

CERN also collaborates with industry – including large companies, SMEs or recent start-ups – and engages with other stakeholders, such as policy-makers, especially those acting in CERN’s Member States.

UNESCO-FAO Soil Map of the World

The FAO Digital Soil Map of the World is the digitized version of the  FAO-UNESCO Soil Map of the World   produced in a paper version at a scale of 1:5 million. It shows 4,931 mapping units consisting of soil associations, which are mixtures of different soil types.

The Abdus Salam International Centre for Theoretical Physics is an international research institute for physical and mathematical sciences that operates under a tripartite agreement between the Italian Government, the United Nations Educational, Scientific and Cultural Organization (UNESCO), and the International Atomic Energy Agency (IAEA).

World Network of Biosphere Reserves

The World Network of Biosphere Reserves of the UNESCO MAB Programme  is a network of Biosphere reserves offering solutions for sustainable development in diverse ecological, social and economic contexts. They foster the harmonious integration of people and nature for sustainable development through participatory dialogue; knowledge sharing; poverty reduction and human well-being improvements; respect for cultural values and society’s ability to cope with change – thus contributing to the 2030 Agenda and its Sustainable Development Goals (SDGs).

The SESAME international centre for scientific research, a competitive synchrotron light source and the first in the Middle East and neighbouring countries, was inaugurated in Allan, Jordan, on 16 May 2017. This pioneering project, established under the auspices of UNESCO, is the result of fourteen years of hard work, uniting eight countries around a twofold goal – to consolidate scientific excellence in the region and to build cross-border collaboration, dialogue and understanding between scientists with diverse cultural, political and religious backgrounds.

The first international framework on open science was adopted by 193 countries attending UNESCO’s General Conference in November 2021. By making science more transparent and more accessible, the UNESCO Recommendation on Open Science will make science more equitable and inclusive. Through open science, scientists and engineers use open licenses to share their publications and data, software and even hardware more widely. Open science should, thus, enhance international scientific cooperation.

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• Natural sciences

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Biology library

Course: biology library   >   unit 1, the scientific method.

• Controlled experiments
• The scientific method and experimental design

Introduction

• Make an observation.
• Ask a question.
• Form a hypothesis , or testable explanation.
• Make a prediction based on the hypothesis.
• Test the prediction.
• Iterate: use the results to make new hypotheses or predictions.

Scientific method example: Failure to toast

1. make an observation..

• Observation: the toaster won't toast.

2. Ask a question.

• Question: Why won't my toaster toast?

3. Propose a hypothesis.

• Hypothesis: Maybe the outlet is broken.

4. Make predictions.

• Prediction: If I plug the toaster into a different outlet, then it will toast the bread.

5. Test the predictions.

• Test of prediction: Plug the toaster into a different outlet and try again.
• If the toaster does toast, then the hypothesis is supported—likely correct.
• If the toaster doesn't toast, then the hypothesis is not supported—likely wrong.

Logical possibility

Practical possibility, building a body of evidence, 6. iterate..

• Iteration time!
• If the hypothesis was supported, we might do additional tests to confirm it, or revise it to be more specific. For instance, we might investigate why the outlet is broken.
• If the hypothesis was not supported, we would come up with a new hypothesis. For instance, the next hypothesis might be that there's a broken wire in the toaster.

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Scientific Reports

What this handout is about.

This handout provides a general guide to writing reports about scientific research you’ve performed. In addition to describing the conventional rules about the format and content of a lab report, we’ll also attempt to convey why these rules exist, so you’ll get a clearer, more dependable idea of how to approach this writing situation. Readers of this handout may also find our handout on writing in the sciences useful.

Background and pre-writing

Why do we write research reports.

You did an experiment or study for your science class, and now you have to write it up for your teacher to review. You feel that you understood the background sufficiently, designed and completed the study effectively, obtained useful data, and can use those data to draw conclusions about a scientific process or principle. But how exactly do you write all that? What is your teacher expecting to see?

To take some of the guesswork out of answering these questions, try to think beyond the classroom setting. In fact, you and your teacher are both part of a scientific community, and the people who participate in this community tend to share the same values. As long as you understand and respect these values, your writing will likely meet the expectations of your audience—including your teacher.

So why are you writing this research report? The practical answer is “Because the teacher assigned it,” but that’s classroom thinking. Generally speaking, people investigating some scientific hypothesis have a responsibility to the rest of the scientific world to report their findings, particularly if these findings add to or contradict previous ideas. The people reading such reports have two primary goals:

• They want to gather the information presented.
• They want to know that the findings are legitimate.

Your job as a writer, then, is to fulfill these two goals.

How do I do that?

Good question. Here is the basic format scientists have designed for research reports:

• Introduction

Methods and Materials

This format, sometimes called “IMRAD,” may take slightly different shapes depending on the discipline or audience; some ask you to include an abstract or separate section for the hypothesis, or call the Discussion section “Conclusions,” or change the order of the sections (some professional and academic journals require the Methods section to appear last). Overall, however, the IMRAD format was devised to represent a textual version of the scientific method.

The scientific method, you’ll probably recall, involves developing a hypothesis, testing it, and deciding whether your findings support the hypothesis. In essence, the format for a research report in the sciences mirrors the scientific method but fleshes out the process a little. Below, you’ll find a table that shows how each written section fits into the scientific method and what additional information it offers the reader.

Thinking of your research report as based on the scientific method, but elaborated in the ways described above, may help you to meet your audience’s expectations successfully. We’re going to proceed by explicitly connecting each section of the lab report to the scientific method, then explaining why and how you need to elaborate that section.

Although this handout takes each section in the order in which it should be presented in the final report, you may for practical reasons decide to compose sections in another order. For example, many writers find that composing their Methods and Results before the other sections helps to clarify their idea of the experiment or study as a whole. You might consider using each assignment to practice different approaches to drafting the report, to find the order that works best for you.

What should I do before drafting the lab report?

The best way to prepare to write the lab report is to make sure that you fully understand everything you need to about the experiment. Obviously, if you don’t quite know what went on during the lab, you’re going to find it difficult to explain the lab satisfactorily to someone else. To make sure you know enough to write the report, complete the following steps:

• What are we going to do in this lab? (That is, what’s the procedure?)
• Why are we going to do it that way?
• What are we hoping to learn from this experiment?
• Why would we benefit from this knowledge?
• Consult your lab supervisor as you perform the lab. If you don’t know how to answer one of the questions above, for example, your lab supervisor will probably be able to explain it to you (or, at least, help you figure it out).
• Plan the steps of the experiment carefully with your lab partners. The less you rush, the more likely it is that you’ll perform the experiment correctly and record your findings accurately. Also, take some time to think about the best way to organize the data before you have to start putting numbers down. If you can design a table to account for the data, that will tend to work much better than jotting results down hurriedly on a scrap piece of paper.
• Record the data carefully so you get them right. You won’t be able to trust your conclusions if you have the wrong data, and your readers will know you messed up if the other three people in your group have “97 degrees” and you have “87.”
• Consult with your lab partners about everything you do. Lab groups often make one of two mistakes: two people do all the work while two have a nice chat, or everybody works together until the group finishes gathering the raw data, then scrams outta there. Collaborate with your partners, even when the experiment is “over.” What trends did you observe? Was the hypothesis supported? Did you all get the same results? What kind of figure should you use to represent your findings? The whole group can work together to answer these questions.
• Consider your audience. You may believe that audience is a non-issue: it’s your lab TA, right? Well, yes—but again, think beyond the classroom. If you write with only your lab instructor in mind, you may omit material that is crucial to a complete understanding of your experiment, because you assume the instructor knows all that stuff already. As a result, you may receive a lower grade, since your TA won’t be sure that you understand all the principles at work. Try to write towards a student in the same course but a different lab section. That student will have a fair degree of scientific expertise but won’t know much about your experiment particularly. Alternatively, you could envision yourself five years from now, after the reading and lectures for this course have faded a bit. What would you remember, and what would you need explained more clearly (as a refresher)?

Once you’ve completed these steps as you perform the experiment, you’ll be in a good position to draft an effective lab report.

Introductions

How do i write a strong introduction.

For the purposes of this handout, we’ll consider the Introduction to contain four basic elements: the purpose, the scientific literature relevant to the subject, the hypothesis, and the reasons you believed your hypothesis viable. Let’s start by going through each element of the Introduction to clarify what it covers and why it’s important. Then we can formulate a logical organizational strategy for the section.

The inclusion of the purpose (sometimes called the objective) of the experiment often confuses writers. The biggest misconception is that the purpose is the same as the hypothesis. Not quite. We’ll get to hypotheses in a minute, but basically they provide some indication of what you expect the experiment to show. The purpose is broader, and deals more with what you expect to gain through the experiment. In a professional setting, the hypothesis might have something to do with how cells react to a certain kind of genetic manipulation, but the purpose of the experiment is to learn more about potential cancer treatments. Undergraduate reports don’t often have this wide-ranging a goal, but you should still try to maintain the distinction between your hypothesis and your purpose. In a solubility experiment, for example, your hypothesis might talk about the relationship between temperature and the rate of solubility, but the purpose is probably to learn more about some specific scientific principle underlying the process of solubility.

For starters, most people say that you should write out your working hypothesis before you perform the experiment or study. Many beginning science students neglect to do so and find themselves struggling to remember precisely which variables were involved in the process or in what way the researchers felt that they were related. Write your hypothesis down as you develop it—you’ll be glad you did.

As for the form a hypothesis should take, it’s best not to be too fancy or complicated; an inventive style isn’t nearly so important as clarity here. There’s nothing wrong with beginning your hypothesis with the phrase, “It was hypothesized that . . .” Be as specific as you can about the relationship between the different objects of your study. In other words, explain that when term A changes, term B changes in this particular way. Readers of scientific writing are rarely content with the idea that a relationship between two terms exists—they want to know what that relationship entails.

Not a hypothesis:

“It was hypothesized that there is a significant relationship between the temperature of a solvent and the rate at which a solute dissolves.”

Hypothesis:

“It was hypothesized that as the temperature of a solvent increases, the rate at which a solute will dissolve in that solvent increases.”

Put more technically, most hypotheses contain both an independent and a dependent variable. The independent variable is what you manipulate to test the reaction; the dependent variable is what changes as a result of your manipulation. In the example above, the independent variable is the temperature of the solvent, and the dependent variable is the rate of solubility. Be sure that your hypothesis includes both variables.

Justify your hypothesis

You need to do more than tell your readers what your hypothesis is; you also need to assure them that this hypothesis was reasonable, given the circumstances. In other words, use the Introduction to explain that you didn’t just pluck your hypothesis out of thin air. (If you did pluck it out of thin air, your problems with your report will probably extend beyond using the appropriate format.) If you posit that a particular relationship exists between the independent and the dependent variable, what led you to believe your “guess” might be supported by evidence?

Scientists often refer to this type of justification as “motivating” the hypothesis, in the sense that something propelled them to make that prediction. Often, motivation includes what we already know—or rather, what scientists generally accept as true (see “Background/previous research” below). But you can also motivate your hypothesis by relying on logic or on your own observations. If you’re trying to decide which solutes will dissolve more rapidly in a solvent at increased temperatures, you might remember that some solids are meant to dissolve in hot water (e.g., bouillon cubes) and some are used for a function precisely because they withstand higher temperatures (they make saucepans out of something). Or you can think about whether you’ve noticed sugar dissolving more rapidly in your glass of iced tea or in your cup of coffee. Even such basic, outside-the-lab observations can help you justify your hypothesis as reasonable.

Background/previous research

This part of the Introduction demonstrates to the reader your awareness of how you’re building on other scientists’ work. If you think of the scientific community as engaging in a series of conversations about various topics, then you’ll recognize that the relevant background material will alert the reader to which conversation you want to enter.

Generally speaking, authors writing journal articles use the background for slightly different purposes than do students completing assignments. Because readers of academic journals tend to be professionals in the field, authors explain the background in order to permit readers to evaluate the study’s pertinence for their own work. You, on the other hand, write toward a much narrower audience—your peers in the course or your lab instructor—and so you must demonstrate that you understand the context for the (presumably assigned) experiment or study you’ve completed. For example, if your professor has been talking about polarity during lectures, and you’re doing a solubility experiment, you might try to connect the polarity of a solid to its relative solubility in certain solvents. In any event, both professional researchers and undergraduates need to connect the background material overtly to their own work.

Organization of this section

Most of the time, writers begin by stating the purpose or objectives of their own work, which establishes for the reader’s benefit the “nature and scope of the problem investigated” (Day 1994). Once you have expressed your purpose, you should then find it easier to move from the general purpose, to relevant material on the subject, to your hypothesis. In abbreviated form, an Introduction section might look like this:

“The purpose of the experiment was to test conventional ideas about solubility in the laboratory [purpose] . . . According to Whitecoat and Labrat (1999), at higher temperatures the molecules of solvents move more quickly . . . We know from the class lecture that molecules moving at higher rates of speed collide with one another more often and thus break down more easily [background material/motivation] . . . Thus, it was hypothesized that as the temperature of a solvent increases, the rate at which a solute will dissolve in that solvent increases [hypothesis].”

Again—these are guidelines, not commandments. Some writers and readers prefer different structures for the Introduction. The one above merely illustrates a common approach to organizing material.

How do I write a strong Materials and Methods section?

As with any piece of writing, your Methods section will succeed only if it fulfills its readers’ expectations, so you need to be clear in your own mind about the purpose of this section. Let’s review the purpose as we described it above: in this section, you want to describe in detail how you tested the hypothesis you developed and also to clarify the rationale for your procedure. In science, it’s not sufficient merely to design and carry out an experiment. Ultimately, others must be able to verify your findings, so your experiment must be reproducible, to the extent that other researchers can follow the same procedure and obtain the same (or similar) results.

Here’s a real-world example of the importance of reproducibility. In 1989, physicists Stanley Pons and Martin Fleischman announced that they had discovered “cold fusion,” a way of producing excess heat and power without the nuclear radiation that accompanies “hot fusion.” Such a discovery could have great ramifications for the industrial production of energy, so these findings created a great deal of interest. When other scientists tried to duplicate the experiment, however, they didn’t achieve the same results, and as a result many wrote off the conclusions as unjustified (or worse, a hoax). To this day, the viability of cold fusion is debated within the scientific community, even though an increasing number of researchers believe it possible. So when you write your Methods section, keep in mind that you need to describe your experiment well enough to allow others to replicate it exactly.

With these goals in mind, let’s consider how to write an effective Methods section in terms of content, structure, and style.

Sometimes the hardest thing about writing this section isn’t what you should talk about, but what you shouldn’t talk about. Writers often want to include the results of their experiment, because they measured and recorded the results during the course of the experiment. But such data should be reserved for the Results section. In the Methods section, you can write that you recorded the results, or how you recorded the results (e.g., in a table), but you shouldn’t write what the results were—not yet. Here, you’re merely stating exactly how you went about testing your hypothesis. As you draft your Methods section, ask yourself the following questions:

• How much detail? Be precise in providing details, but stay relevant. Ask yourself, “Would it make any difference if this piece were a different size or made from a different material?” If not, you probably don’t need to get too specific. If so, you should give as many details as necessary to prevent this experiment from going awry if someone else tries to carry it out. Probably the most crucial detail is measurement; you should always quantify anything you can, such as time elapsed, temperature, mass, volume, etc.
• Rationale: Be sure that as you’re relating your actions during the experiment, you explain your rationale for the protocol you developed. If you capped a test tube immediately after adding a solute to a solvent, why did you do that? (That’s really two questions: why did you cap it, and why did you cap it immediately?) In a professional setting, writers provide their rationale as a way to explain their thinking to potential critics. On one hand, of course, that’s your motivation for talking about protocol, too. On the other hand, since in practical terms you’re also writing to your teacher (who’s seeking to evaluate how well you comprehend the principles of the experiment), explaining the rationale indicates that you understand the reasons for conducting the experiment in that way, and that you’re not just following orders. Critical thinking is crucial—robots don’t make good scientists.
• Control: Most experiments will include a control, which is a means of comparing experimental results. (Sometimes you’ll need to have more than one control, depending on the number of hypotheses you want to test.) The control is exactly the same as the other items you’re testing, except that you don’t manipulate the independent variable-the condition you’re altering to check the effect on the dependent variable. For example, if you’re testing solubility rates at increased temperatures, your control would be a solution that you didn’t heat at all; that way, you’ll see how quickly the solute dissolves “naturally” (i.e., without manipulation), and you’ll have a point of reference against which to compare the solutions you did heat.

Describe the control in the Methods section. Two things are especially important in writing about the control: identify the control as a control, and explain what you’re controlling for. Here is an example:

“As a control for the temperature change, we placed the same amount of solute in the same amount of solvent, and let the solution stand for five minutes without heating it.”

Structure and style

Organization is especially important in the Methods section of a lab report because readers must understand your experimental procedure completely. Many writers are surprised by the difficulty of conveying what they did during the experiment, since after all they’re only reporting an event, but it’s often tricky to present this information in a coherent way. There’s a fairly standard structure you can use to guide you, and following the conventions for style can help clarify your points.

• Subsections: Occasionally, researchers use subsections to report their procedure when the following circumstances apply: 1) if they’ve used a great many materials; 2) if the procedure is unusually complicated; 3) if they’ve developed a procedure that won’t be familiar to many of their readers. Because these conditions rarely apply to the experiments you’ll perform in class, most undergraduate lab reports won’t require you to use subsections. In fact, many guides to writing lab reports suggest that you try to limit your Methods section to a single paragraph.
• Narrative structure: Think of this section as telling a story about a group of people and the experiment they performed. Describe what you did in the order in which you did it. You may have heard the old joke centered on the line, “Disconnect the red wire, but only after disconnecting the green wire,” where the person reading the directions blows everything to kingdom come because the directions weren’t in order. We’re used to reading about events chronologically, and so your readers will generally understand what you did if you present that information in the same way. Also, since the Methods section does generally appear as a narrative (story), you want to avoid the “recipe” approach: “First, take a clean, dry 100 ml test tube from the rack. Next, add 50 ml of distilled water.” You should be reporting what did happen, not telling the reader how to perform the experiment: “50 ml of distilled water was poured into a clean, dry 100 ml test tube.” Hint: most of the time, the recipe approach comes from copying down the steps of the procedure from your lab manual, so you may want to draft the Methods section initially without consulting your manual. Later, of course, you can go back and fill in any part of the procedure you inadvertently overlooked.
• Past tense: Remember that you’re describing what happened, so you should use past tense to refer to everything you did during the experiment. Writers are often tempted to use the imperative (“Add 5 g of the solid to the solution”) because that’s how their lab manuals are worded; less frequently, they use present tense (“5 g of the solid are added to the solution”). Instead, remember that you’re talking about an event which happened at a particular time in the past, and which has already ended by the time you start writing, so simple past tense will be appropriate in this section (“5 g of the solid were added to the solution” or “We added 5 g of the solid to the solution”).
• Active: We heated the solution to 80°C. (The subject, “we,” performs the action, heating.)
• Passive: The solution was heated to 80°C. (The subject, “solution,” doesn’t do the heating–it is acted upon, not acting.)

Increasingly, especially in the social sciences, using first person and active voice is acceptable in scientific reports. Most readers find that this style of writing conveys information more clearly and concisely. This rhetorical choice thus brings two scientific values into conflict: objectivity versus clarity. Since the scientific community hasn’t reached a consensus about which style it prefers, you may want to ask your lab instructor.

How do I write a strong Results section?

Here’s a paradox for you. The Results section is often both the shortest (yay!) and most important (uh-oh!) part of your report. Your Materials and Methods section shows how you obtained the results, and your Discussion section explores the significance of the results, so clearly the Results section forms the backbone of the lab report. This section provides the most critical information about your experiment: the data that allow you to discuss how your hypothesis was or wasn’t supported. But it doesn’t provide anything else, which explains why this section is generally shorter than the others.

Before you write this section, look at all the data you collected to figure out what relates significantly to your hypothesis. You’ll want to highlight this material in your Results section. Resist the urge to include every bit of data you collected, since perhaps not all are relevant. Also, don’t try to draw conclusions about the results—save them for the Discussion section. In this section, you’re reporting facts. Nothing your readers can dispute should appear in the Results section.

Most Results sections feature three distinct parts: text, tables, and figures. Let’s consider each part one at a time.

This should be a short paragraph, generally just a few lines, that describes the results you obtained from your experiment. In a relatively simple experiment, one that doesn’t produce a lot of data for you to repeat, the text can represent the entire Results section. Don’t feel that you need to include lots of extraneous detail to compensate for a short (but effective) text; your readers appreciate discrimination more than your ability to recite facts. In a more complex experiment, you may want to use tables and/or figures to help guide your readers toward the most important information you gathered. In that event, you’ll need to refer to each table or figure directly, where appropriate:

“Table 1 lists the rates of solubility for each substance”

“Solubility increased as the temperature of the solution increased (see Figure 1).”

If you do use tables or figures, make sure that you don’t present the same material in both the text and the tables/figures, since in essence you’ll just repeat yourself, probably annoying your readers with the redundancy of your statements.

Feel free to describe trends that emerge as you examine the data. Although identifying trends requires some judgment on your part and so may not feel like factual reporting, no one can deny that these trends do exist, and so they properly belong in the Results section. Example:

“Heating the solution increased the rate of solubility of polar solids by 45% but had no effect on the rate of solubility in solutions containing non-polar solids.”

This point isn’t debatable—you’re just pointing out what the data show.

As in the Materials and Methods section, you want to refer to your data in the past tense, because the events you recorded have already occurred and have finished occurring. In the example above, note the use of “increased” and “had,” rather than “increases” and “has.” (You don’t know from your experiment that heating always increases the solubility of polar solids, but it did that time.)

You shouldn’t put information in the table that also appears in the text. You also shouldn’t use a table to present irrelevant data, just to show you did collect these data during the experiment. Tables are good for some purposes and situations, but not others, so whether and how you’ll use tables depends upon what you need them to accomplish.

Tables are useful ways to show variation in data, but not to present a great deal of unchanging measurements. If you’re dealing with a scientific phenomenon that occurs only within a certain range of temperatures, for example, you don’t need to use a table to show that the phenomenon didn’t occur at any of the other temperatures. How useful is this table?

As you can probably see, no solubility was observed until the trial temperature reached 50°C, a fact that the text part of the Results section could easily convey. The table could then be limited to what happened at 50°C and higher, thus better illustrating the differences in solubility rates when solubility did occur.

As a rule, try not to use a table to describe any experimental event you can cover in one sentence of text. Here’s an example of an unnecessary table from How to Write and Publish a Scientific Paper , by Robert A. Day:

As Day notes, all the information in this table can be summarized in one sentence: “S. griseus, S. coelicolor, S. everycolor, and S. rainbowenski grew under aerobic conditions, whereas S. nocolor and S. greenicus required anaerobic conditions.” Most readers won’t find the table clearer than that one sentence.

When you do have reason to tabulate material, pay attention to the clarity and readability of the format you use. Here are a few tips:

• Number your table. Then, when you refer to the table in the text, use that number to tell your readers which table they can review to clarify the material.
• Give your table a title. This title should be descriptive enough to communicate the contents of the table, but not so long that it becomes difficult to follow. The titles in the sample tables above are acceptable.
• Arrange your table so that readers read vertically, not horizontally. For the most part, this rule means that you should construct your table so that like elements read down, not across. Think about what you want your readers to compare, and put that information in the column (up and down) rather than in the row (across). Usually, the point of comparison will be the numerical data you collect, so especially make sure you have columns of numbers, not rows.Here’s an example of how drastically this decision affects the readability of your table (from A Short Guide to Writing about Chemistry , by Herbert Beall and John Trimbur). Look at this table, which presents the relevant data in horizontal rows:

It’s a little tough to see the trends that the author presumably wants to present in this table. Compare this table, in which the data appear vertically:

The second table shows how putting like elements in a vertical column makes for easier reading. In this case, the like elements are the measurements of length and height, over five trials–not, as in the first table, the length and height measurements for each trial.

• Make sure to include units of measurement in the tables. Readers might be able to guess that you measured something in millimeters, but don’t make them try.
• Don’t use vertical lines as part of the format for your table. This convention exists because journals prefer not to have to reproduce these lines because the tables then become more expensive to print. Even though it’s fairly unlikely that you’ll be sending your Biology 11 lab report to Science for publication, your readers still have this expectation. Consequently, if you use the table-drawing option in your word-processing software, choose the option that doesn’t rely on a “grid” format (which includes vertical lines).

How do I include figures in my report?

Although tables can be useful ways of showing trends in the results you obtained, figures (i.e., illustrations) can do an even better job of emphasizing such trends. Lab report writers often use graphic representations of the data they collected to provide their readers with a literal picture of how the experiment went.

When should you use a figure?

Remember the circumstances under which you don’t need a table: when you don’t have a great deal of data or when the data you have don’t vary a lot. Under the same conditions, you would probably forgo the figure as well, since the figure would be unlikely to provide your readers with an additional perspective. Scientists really don’t like their time wasted, so they tend not to respond favorably to redundancy.

If you’re trying to decide between using a table and creating a figure to present your material, consider the following a rule of thumb. The strength of a table lies in its ability to supply large amounts of exact data, whereas the strength of a figure is its dramatic illustration of important trends within the experiment. If you feel that your readers won’t get the full impact of the results you obtained just by looking at the numbers, then a figure might be appropriate.

Of course, an undergraduate class may expect you to create a figure for your lab experiment, if only to make sure that you can do so effectively. If this is the case, then don’t worry about whether to use figures or not—concentrate instead on how best to accomplish your task.

Figures can include maps, photographs, pen-and-ink drawings, flow charts, bar graphs, and section graphs (“pie charts”). But the most common figure by far, especially for undergraduates, is the line graph, so we’ll focus on that type in this handout.

At the undergraduate level, you can often draw and label your graphs by hand, provided that the result is clear, legible, and drawn to scale. Computer technology has, however, made creating line graphs a lot easier. Most word-processing software has a number of functions for transferring data into graph form; many scientists have found Microsoft Excel, for example, a helpful tool in graphing results. If you plan on pursuing a career in the sciences, it may be well worth your while to learn to use a similar program.

Computers can’t, however, decide for you how your graph really works; you have to know how to design your graph to meet your readers’ expectations. Here are some of these expectations:

• Keep it as simple as possible. You may be tempted to signal the complexity of the information you gathered by trying to design a graph that accounts for that complexity. But remember the purpose of your graph: to dramatize your results in a manner that’s easy to see and grasp. Try not to make the reader stare at the graph for a half hour to find the important line among the mass of other lines. For maximum effectiveness, limit yourself to three to five lines per graph; if you have more data to demonstrate, use a set of graphs to account for it, rather than trying to cram it all into a single figure.
• Plot the independent variable on the horizontal (x) axis and the dependent variable on the vertical (y) axis. Remember that the independent variable is the condition that you manipulated during the experiment and the dependent variable is the condition that you measured to see if it changed along with the independent variable. Placing the variables along their respective axes is mostly just a convention, but since your readers are accustomed to viewing graphs in this way, you’re better off not challenging the convention in your report.
• Label each axis carefully, and be especially careful to include units of measure. You need to make sure that your readers understand perfectly well what your graph indicates.
• Number and title your graphs. As with tables, the title of the graph should be informative but concise, and you should refer to your graph by number in the text (e.g., “Figure 1 shows the increase in the solubility rate as a function of temperature”).
• Many editors of professional scientific journals prefer that writers distinguish the lines in their graphs by attaching a symbol to them, usually a geometric shape (triangle, square, etc.), and using that symbol throughout the curve of the line. Generally, readers have a hard time distinguishing dotted lines from dot-dash lines from straight lines, so you should consider staying away from this system. Editors don’t usually like different-colored lines within a graph because colors are difficult and expensive to reproduce; colors may, however, be great for your purposes, as long as you’re not planning to submit your paper to Nature. Use your discretion—try to employ whichever technique dramatizes the results most effectively.
• Try to gather data at regular intervals, so the plot points on your graph aren’t too far apart. You can’t be sure of the arc you should draw between the plot points if the points are located at the far corners of the graph; over a fifteen-minute interval, perhaps the change occurred in the first or last thirty seconds of that period (in which case your straight-line connection between the points is misleading).
• If you’re worried that you didn’t collect data at sufficiently regular intervals during your experiment, go ahead and connect the points with a straight line, but you may want to examine this problem as part of your Discussion section.
• Make your graph large enough so that everything is legible and clearly demarcated, but not so large that it either overwhelms the rest of the Results section or provides a far greater range than you need to illustrate your point. If, for example, the seedlings of your plant grew only 15 mm during the trial, you don’t need to construct a graph that accounts for 100 mm of growth. The lines in your graph should more or less fill the space created by the axes; if you see that your data is confined to the lower left portion of the graph, you should probably re-adjust your scale.
• If you create a set of graphs, make them the same size and format, including all the verbal and visual codes (captions, symbols, scale, etc.). You want to be as consistent as possible in your illustrations, so that your readers can easily make the comparisons you’re trying to get them to see.

How do I write a strong Discussion section?

The discussion section is probably the least formalized part of the report, in that you can’t really apply the same structure to every type of experiment. In simple terms, here you tell your readers what to make of the Results you obtained. If you have done the Results part well, your readers should already recognize the trends in the data and have a fairly clear idea of whether your hypothesis was supported. Because the Results can seem so self-explanatory, many students find it difficult to know what material to add in this last section.

Basically, the Discussion contains several parts, in no particular order, but roughly moving from specific (i.e., related to your experiment only) to general (how your findings fit in the larger scientific community). In this section, you will, as a rule, need to:

Explain whether the data support your hypothesis

• Acknowledge any anomalous data or deviations from what you expected

Derive conclusions, based on your findings, about the process you’re studying

• Relate your findings to earlier work in the same area (if you can)

Explore the theoretical and/or practical implications of your findings

Let’s look at some dos and don’ts for each of these objectives.

This statement is usually a good way to begin the Discussion, since you can’t effectively speak about the larger scientific value of your study until you’ve figured out the particulars of this experiment. You might begin this part of the Discussion by explicitly stating the relationships or correlations your data indicate between the independent and dependent variables. Then you can show more clearly why you believe your hypothesis was or was not supported. For example, if you tested solubility at various temperatures, you could start this section by noting that the rates of solubility increased as the temperature increased. If your initial hypothesis surmised that temperature change would not affect solubility, you would then say something like,

“The hypothesis that temperature change would not affect solubility was not supported by the data.”

Note: Students tend to view labs as practical tests of undeniable scientific truths. As a result, you may want to say that the hypothesis was “proved” or “disproved” or that it was “correct” or “incorrect.” These terms, however, reflect a degree of certainty that you as a scientist aren’t supposed to have. Remember, you’re testing a theory with a procedure that lasts only a few hours and relies on only a few trials, which severely compromises your ability to be sure about the “truth” you see. Words like “supported,” “indicated,” and “suggested” are more acceptable ways to evaluate your hypothesis.

Also, recognize that saying whether the data supported your hypothesis or not involves making a claim to be defended. As such, you need to show the readers that this claim is warranted by the evidence. Make sure that you’re very explicit about the relationship between the evidence and the conclusions you draw from it. This process is difficult for many writers because we don’t often justify conclusions in our regular lives. For example, you might nudge your friend at a party and whisper, “That guy’s drunk,” and once your friend lays eyes on the person in question, she might readily agree. In a scientific paper, by contrast, you would need to defend your claim more thoroughly by pointing to data such as slurred words, unsteady gait, and the lampshade-as-hat. In addition to pointing out these details, you would also need to show how (according to previous studies) these signs are consistent with inebriation, especially if they occur in conjunction with one another. To put it another way, tell your readers exactly how you got from point A (was the hypothesis supported?) to point B (yes/no).

Acknowledge any anomalous data, or deviations from what you expected

You need to take these exceptions and divergences into account, so that you qualify your conclusions sufficiently. For obvious reasons, your readers will doubt your authority if you (deliberately or inadvertently) overlook a key piece of data that doesn’t square with your perspective on what occurred. In a more philosophical sense, once you’ve ignored evidence that contradicts your claims, you’ve departed from the scientific method. The urge to “tidy up” the experiment is often strong, but if you give in to it you’re no longer performing good science.

Sometimes after you’ve performed a study or experiment, you realize that some part of the methods you used to test your hypothesis was flawed. In that case, it’s OK to suggest that if you had the chance to conduct your test again, you might change the design in this or that specific way in order to avoid such and such a problem. The key to making this approach work, though, is to be very precise about the weakness in your experiment, why and how you think that weakness might have affected your data, and how you would alter your protocol to eliminate—or limit the effects of—that weakness. Often, inexperienced researchers and writers feel the need to account for “wrong” data (remember, there’s no such animal), and so they speculate wildly about what might have screwed things up. These speculations include such factors as the unusually hot temperature in the room, or the possibility that their lab partners read the meters wrong, or the potentially defective equipment. These explanations are what scientists call “cop-outs,” or “lame”; don’t indicate that the experiment had a weakness unless you’re fairly certain that a) it really occurred and b) you can explain reasonably well how that weakness affected your results.

If, for example, your hypothesis dealt with the changes in solubility at different temperatures, then try to figure out what you can rationally say about the process of solubility more generally. If you’re doing an undergraduate lab, chances are that the lab will connect in some way to the material you’ve been covering either in lecture or in your reading, so you might choose to return to these resources as a way to help you think clearly about the process as a whole.

This part of the Discussion section is another place where you need to make sure that you’re not overreaching. Again, nothing you’ve found in one study would remotely allow you to claim that you now “know” something, or that something isn’t “true,” or that your experiment “confirmed” some principle or other. Hesitate before you go out on a limb—it’s dangerous! Use less absolutely conclusive language, including such words as “suggest,” “indicate,” “correspond,” “possibly,” “challenge,” etc.

Relate your findings to previous work in the field (if possible)

We’ve been talking about how to show that you belong in a particular community (such as biologists or anthropologists) by writing within conventions that they recognize and accept. Another is to try to identify a conversation going on among members of that community, and use your work to contribute to that conversation. In a larger philosophical sense, scientists can’t fully understand the value of their research unless they have some sense of the context that provoked and nourished it. That is, you have to recognize what’s new about your project (potentially, anyway) and how it benefits the wider body of scientific knowledge. On a more pragmatic level, especially for undergraduates, connecting your lab work to previous research will demonstrate to the TA that you see the big picture. You have an opportunity, in the Discussion section, to distinguish yourself from the students in your class who aren’t thinking beyond the barest facts of the study. Capitalize on this opportunity by putting your own work in context.

If you’re just beginning to work in the natural sciences (as a first-year biology or chemistry student, say), most likely the work you’ll be doing has already been performed and re-performed to a satisfactory degree. Hence, you could probably point to a similar experiment or study and compare/contrast your results and conclusions. More advanced work may deal with an issue that is somewhat less “resolved,” and so previous research may take the form of an ongoing debate, and you can use your own work to weigh in on that debate. If, for example, researchers are hotly disputing the value of herbal remedies for the common cold, and the results of your study suggest that Echinacea diminishes the symptoms but not the actual presence of the cold, then you might want to take some time in the Discussion section to recapitulate the specifics of the dispute as it relates to Echinacea as an herbal remedy. (Consider that you have probably already written in the Introduction about this debate as background research.)

This information is often the best way to end your Discussion (and, for all intents and purposes, the report). In argumentative writing generally, you want to use your closing words to convey the main point of your writing. This main point can be primarily theoretical (“Now that you understand this information, you’re in a better position to understand this larger issue”) or primarily practical (“You can use this information to take such and such an action”). In either case, the concluding statements help the reader to comprehend the significance of your project and your decision to write about it.

Since a lab report is argumentative—after all, you’re investigating a claim, and judging the legitimacy of that claim by generating and collecting evidence—it’s often a good idea to end your report with the same technique for establishing your main point. If you want to go the theoretical route, you might talk about the consequences your study has for the field or phenomenon you’re investigating. To return to the examples regarding solubility, you could end by reflecting on what your work on solubility as a function of temperature tells us (potentially) about solubility in general. (Some folks consider this type of exploration “pure” as opposed to “applied” science, although these labels can be problematic.) If you want to go the practical route, you could end by speculating about the medical, institutional, or commercial implications of your findings—in other words, answer the question, “What can this study help people to do?” In either case, you’re going to make your readers’ experience more satisfying, by helping them see why they spent their time learning what you had to teach them.

Works consulted

We consulted these works while writing this handout. This is not a comprehensive list of resources on the handout’s topic, and we encourage you to do your own research to find additional publications. Please do not use this list as a model for the format of your own reference list, as it may not match the citation style you are using. For guidance on formatting citations, please see the UNC Libraries citation tutorial . We revise these tips periodically and welcome feedback.

American Psychological Association. 2010. Publication Manual of the American Psychological Association . 6th ed. Washington, DC: American Psychological Association.

Beall, Herbert, and John Trimbur. 2001. A Short Guide to Writing About Chemistry , 2nd ed. New York: Longman.

Blum, Deborah, and Mary Knudson. 1997. A Field Guide for Science Writers: The Official Guide of the National Association of Science Writers . New York: Oxford University Press.

Booth, Wayne C., Gregory G. Colomb, Joseph M. Williams, Joseph Bizup, and William T. FitzGerald. 2016. The Craft of Research , 4th ed. Chicago: University of Chicago Press.

Briscoe, Mary Helen. 1996. Preparing Scientific Illustrations: A Guide to Better Posters, Presentations, and Publications , 2nd ed. New York: Springer-Verlag.

Council of Science Editors. 2014. Scientific Style and Format: The CSE Manual for Authors, Editors, and Publishers , 8th ed. Chicago & London: University of Chicago Press.

Davis, Martha. 2012. Scientific Papers and Presentations , 3rd ed. London: Academic Press.

Day, Robert A. 1994. How to Write and Publish a Scientific Paper , 4th ed. Phoenix: Oryx Press.

Porush, David. 1995. A Short Guide to Writing About Science . New York: Longman.

Williams, Joseph, and Joseph Bizup. 2017. Style: Lessons in Clarity and Grace , 12th ed. Boston: Pearson.

You may reproduce it for non-commercial use if you use the entire handout and attribute the source: The Writing Center, University of North Carolina at Chapel Hill

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• Manuscript Preparation

A Must-see for Researchers! How to Ensure Inclusivity in Your Scientific Writing

• 4 minute read

Table of Contents

Highly influential research findings have several real-world implications that affect the public’s perception of individuals and communities to some extent. The way science is communicated shapes people’s behavior, interactions, and even related policies. As a result, in recent years there has been a growing recognition of the need to foster inclusive language within scholarly communication, which can help avoid bias or misunderstanding.  

Researchers, especially the younger generation, are becoming increasingly aware of the significance of using inclusive language in academic writing. This approach helps create a collaborative global academic landscape, while fostering respect for diverse perspectives. It is also conducive to the wide dissemination of papers and supports researchers in their long-term academic endeavors.  

This article will explain why and how to use inclusive language in your manuscript. Also, it will help researchers improve their ability to choose words with precision when writing by providing examples of appropriate inclusive terms. Let’s have a look!  

1. Referring to Persons with Disabilities¹  

When referring to someone with a disability, it is important to focus on the person first, not highlight their condition . Avoid using the terms “disabled person” or “handicapped person.” Instead, use person-first language, such as “a person with disability,” “a person with hearing loss,” etc.  

Additionally, when referring to individuals without disabilities, avoid using terms such as “normal” or “typical.” Instead, use phrases like “individuals without disabilities” or “people without disabilities.”  

Example of inclusive language : Students with disabilities often encounter distinct challenges in academic settings. These can range from physical barriers like inaccessible buildings to difficulties accessing educational materials in suitable formats. In contrast, students without disabilities typically navigate the educational environment with fewer hindrances.  

2. Using Gendered Nouns  

Gendered nouns such as “man” or words ending in “-man” can exclude certain groups, so it is best to avoid them² . Fortunately, they can be easily substituted with neutral terms . For instance, instead of writing “man”, write “person” or “individual” and instead of writing “mankind,” write “humanity” or “human beings.”  

When discussing people’s occupational roles, using neutral language is essential. For example, instead of writing “policeman,” write “police officer,” and instead of writing “chairman,” write “chairperson.”  

Example of gendered noun use:  The chairman oversees the company’s operations.  

Example of inclusive language:  The chairperson oversees the company’s operations.  

3. Using Pronouns  

When you know a person’s preferred pronoun, it is easy to incorporate it into writing. For example, most people use the pronouns he/him or she/her. However, using pronouns can become tricky in neutral or ambiguous contexts. In the past, it was common to use the  generic he   in these situations³ . However, it is best to avoid this practice as it can be exclusionary .  

Here are some tips to avoid the  generic he³ :  

Don’t only use he/his, add she/her  

For example, do not write:  An early career researcher needs mentors. He can learn the secrets to making an impact in academia with someone more experienced.  

Instead, write:  An early career researcher needs mentors. He or she can learn the secrets to making an impact in academia with someone more experienced.  

Eliminate the pronoun if possible  

For example, do not write:  We returned his manuscript two days after submission.  

Instead, write:  We returned the manuscript two days after submission.  

Use a plural term  

For example, do not write:  When an author revises his manuscript , he should consider the feedback provided by the peer reviewers.  

Instead, write:  When authors revise their manuscripts , they should consider the feedback provided by the peer reviewers.  

4. Describing Age  

As a general rule, refrain from mentioning a person’s age unless it is absolutely necessary for the context . In scientific writing, it is acceptable to use broad terms , such as infants, children, young adults, or older adults, to categorize age groups⁴ . This approach maintains inclusivity and respects individuals regardless of their age.   

Conclusion  

Embracing inclusive language in scholarly communication fosters a more welcoming environment for scholars from diverse backgrounds. It ensures that everyone, regardless of their life experiences, can equally benefit from advancements in science. It is worth noting that inclusive language constantly evolves with social development, which poses a great challenge for authors in terms of their English skills and the ability to pay attention to social trends.  

If you would like to achieve more efficient and inclusive expression in your papers, please choose Elsevier Language Services . Our professional editors, all native English speakers, with editing experience in more than 100 disciplines, can help you achieve professional, authentic, and inclusive academic expression in your papers, improve the chances of successful publication, and achieve long-term academic success.  

References:  

• University of Idaho Inclusive Writing Guide. (n.d.). https://www.uidaho.edu/brand/print-digital-content/inclusive-writing-guide  
• UNC-Chapel Hill Writing Center. (2023, December 8). Gender-Inclusive Language – The Writing Center. University of North Carolina at Chapel Hill. https://writingcenter.unc.edu/tips-and-tools/gender-inclusive-language/  
• Leu, P. (2020, July 2). Academic Writing: How do we use gender-inclusive language in academic writing? – Explorations in English Language Learning. Explorations in English Language Learning. https://englishexplorations.check.uni-hamburg.de/academic-writing-how-do-we-use-gender-inclusive-language-in-academic-writing/  
• Inclusive writing | York St John University. (n.d.). York St John University. https://www.yorksj.ac.uk/brand/our-writing-style/inclusive-writing/#age  

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A Groundbreaking Scientific Discovery Just Created the Instruction Manual for Light-Speed Travel

In a first for warp drives, this research actually obeys the laws of physics.

If a superluminal—meaning faster than the speed of light—warp drive like Alcubierre’s worked, it would revolutionize humanity’s endeavors across the universe , allowing us, perhaps, to reach Alpha Centauri, our closest star system, in days or weeks even though it’s four light years away.

The clip above from the 2016 film Star Trek Beyond showcases the effect of a starship zipping through space inside a faster-than-light warp bubble. You can see the imagined but hypothetically accurate warping of spacetime.

However, the Alcubierre drive has a glaring problem: the force behind its operation, called “negative energy,” involves exotic particles—hypothetical matter that, as far as we know, doesn’t exist in our universe. Described only in mathematical terms, exotic particles act in unexpected ways, like having negative mass and working in opposition to gravity (in fact, it has “anti-gravity”). For the past 30 years, scientists have been publishing research that chips away at the inherent hurdles to light speed revealed in Alcubierre’s foundational 1994 article published in the peer-reviewed journal Classical and Quantum Gravity .

Now, researchers at the New York City-based think tank Applied Physics believe they’ve found a creative new approach to solving the warp drive’s fundamental roadblock. Along with colleagues from other institutions, the team envisioned a “positive energy” system that doesn’t violate the known laws of physics . It’s a game-changer, say two of the study’s authors: Gianni Martire, CEO of Applied Physics, and Jared Fuchs, Ph.D., a senior scientist there. Their work, also published in Classical and Quantum Gravity in late April, could be the first chapter in the manual for interstellar spaceflight.

Positive energy makes all the difference. Imagine you are an astronaut in space, pushing a tennis ball away from you. Instead of moving away, the ball pushes back, to the point that it would “take your hand off” if you applied enough pushing force, Martire tells Popular Mechanics . That’s a sign of negative energy, and, though the Alcubierre drive design requires it, there’s no way to harness it.

Instead, regular old positive energy is more feasible for constructing the “ warp bubble .” As its name suggests, it’s a spherical structure that surrounds and encloses space for a passenger ship using a shell of regular—but incredibly dense—matter. The bubble propels the spaceship using the powerful gravity of the shell, but without causing the passengers to feel any acceleration. “An elevator ride would be more eventful,” Martire says.

That’s because the density of the shell, as well as the pressure it exerts on the interior, is controlled carefully, Fuchs tells Popular Mechanics . Nothing can travel faster than the speed of light, according to the gravity-bound principles of Albert Einstein’s theory of general relativity . So the bubble is designed such that observers within their local spacetime environment—inside the bubble—experience normal movement in time. Simultaneously, the bubble itself compresses the spacetime in front of the ship and expands it behind the ship, ferrying itself and the contained craft incredibly fast. The walls of the bubble generate the necessary momentum, akin to the momentum of balls rolling, Fuchs explains. “It’s the movement of the matter in the walls that actually creates the effect for passengers on the inside.”

Building on its 2021 paper published in Classical and Quantum Gravity —which details the same researchers’ earlier work on physical warp drives—the team was able to model the complexity of the system using its own computational program, Warp Factory. This toolkit for modeling warp drive spacetimes allows researchers to evaluate Einstein’s field equations and compute the energy conditions required for various warp drive geometries. Anyone can download and use it for free . These experiments led to what Fuchs calls a mini model, the first general model of a positive-energy warp drive. Their past work also demonstrated that the amount of energy a warp bubble requires depends on the shape of the bubble; for example, the flatter the bubble in the direction of travel, the less energy it needs.

☄️ DID YOU KNOW? People have been imagining traveling as fast as light for nearly a century, if not longer. The 1931 novel Islands of Space by John W. Campbell mentions a “warp” method in the context of superluminal space travel.

This latest advancement suggests fresh possibilities for studying warp travel design, Erik Lentz, Ph.D., tells Popular Mechanics . In his current position as a staff physicist at Pacific Northwest National Laboratory in Richland, Washington, Lentz contributes to research on dark matter detection and quantum information science research. His independent research in warp drive theory also aims to be grounded in conventional physics while reimagining the shape of warped space. The topic needs to overcome many practical hurdles, he says.

Controlling warp bubbles requires a great deal of coordination because they involve enormous amounts of matter and energy to keep the passengers safe and with a similar passage of time as the destination. “We could just as well engineer spacetime where time passes much differently inside [the passenger compartment] than outside. We could miss our appointment at Proxima Centauri if we aren’t careful,” Lentz says. “That is still a risk if we are traveling less than the speed of light.” Communication between people inside the bubble and outside could also become distorted as it passes through the curvature of warped space, he adds.

While Applied Physics’ current solution requires a warp drive that travels below the speed of light, the model still needs to plug in a mass equivalent to about two Jupiters. Otherwise, it will never achieve the gravitational force and momentum high enough to cause a meaningful warp effect. But no one knows what the source of this mass could be—not yet, at least. Some research suggests that if we could somehow harness dark matter , we could use it for light-speed travel, but Fuchs and Martire are doubtful, since it’s currently a big mystery (and an exotic particle).

Despite the many problems scientists still need to solve to build a working warp drive, the Applied Physics team claims its model should eventually get closer to light speed. And even if a feasible model remains below the speed of light, it’s a vast improvement over today’s technology. For example, traveling at even half the speed of light to Alpha Centauri would take nine years. In stark contrast, our fastest spacecraft, Voyager 1—currently traveling at 38,000 miles per hour—would take 75,000 years to reach our closest neighboring star system.

Of course, as you approach the actual speed of light, things get truly weird, according to the principles of Einstein’s special relativity . The mass of an object moving faster and faster would increase infinitely, eventually requiring an infinite amount of energy to maintain its speed.

“That’s the chief limitation and key challenge we have to overcome—how can we have all this matter in our [bubble], but not at such a scale that we can never even put it together?” Martire says. It’s possible the answer lies in condensed matter physics, he adds. This branch of physics deals particularly with the forces between atoms and electrons in matter. It has already proven fundamental to several of our current technologies, such as transistors, solid-state lasers, and magnetic storage media.

The other big issue is that current models allow a stable warp bubble, but only for a constant velocity. Scientists still need to figure out how to design an initial acceleration. On the other end of the journey, how will the ship slow down and stop? “It’s like trying to grasp the automobile for the first time,” Martire says. “We don’t have an engine just yet, but we see the light at the end of the tunnel.” Warp drive technology is at the stage of 1882 car technology, he says: when automobile travel was possible, but it still looked like a hard, hard problem.

The Applied Physics team believes future innovations in warp travel are inevitable. The general positive energy model is a first step. Besides, you don’t need to zoom at light speed to achieve distances that today are just a dream, Martire says. “Humanity is officially, mathematically, on an interstellar track.”

Before joining Popular Mechanics , Manasee Wagh worked as a newspaper reporter, a science journalist, a tech writer, and a computer engineer. She’s always looking for ways to combine the three greatest joys in her life: science, travel, and food.

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The 5 most popular scientific papers of August 2020 in the Nature Index journals

A gruesome escape artist and ingenious dolphin behaviour feature in these stand-out studies from August.

The Indo-Pacific bottlenose dolphin ( Tursiops aduncus ). Credit: Blue Planet Archive/Alamy Stock Photo

27 October 2020

Blue Planet Archive/Alamy Stock Photo

The Indo-Pacific bottlenose dolphin ( Tursiops aduncus ).

Animals adapt to their environments in remarkable ways. Whether they’re figuring out how to pass through the digestive systems of predators unscathed, or sharing clever methods for ferreting out a snack, these newly discovered behaviours demonstrate how much there is left to discover, even about the most widely-studied species.

Understanding certain adaptions, such as how disease-carrying animals respond to landscapes that are being progressively developed into farmland, can be crucial to human survival too.

These findings feature among the most popular natural sciences studies of August, published in the 82 high-quality journals tracked by the Nature Index.

Also included below are two studies that offer insights into the body’s immune response to COVID-19.

1. “Selective and cross-reactive SARS-CoV-2 T cell epitopes in unexposed humans”

Immune cells called memory T cells remain in the body long after an infection has been eliminated. This ‘memory’ is thought to give the cells a head-start in recognizing and fighting off repeat invaders.

A widely read study published in Science found that memory T cells that recognize common cold coronaviruses also appear to recognize elements of SARS-CoV-2, the virus that causes COVID-19.

The team behind the research, co-led by Daniela Weiskopf and Alessandro Sette from the Center for Infectious Disease and Vaccine Research at the La Jolla Institute for Immunology in California, found that some people who have not been exposed to SARS-CoV-2 have pre-existing reactivity to SARS-CoV-2 sequences.

“The immunological mechanisms underlying this preexisting reactivity are not clear, but previous exposure to widely circulating common cold coronaviruses might be involved,” the study states.

The researchers suggest that this could explain why some people have milder COVID-19 cases than others, but emphasized that more data is needed to know for sure.

The study has more than double the Altmetric score of the second most-discussed paper in this list. It has been covered by more than 200 news outlets so far, and has reached an audience of roughly 25 million people on Twitter.

2. “Active escape of prey from predator vent via the digestive tract”

Current Biology

It’s one thing for prey to evade a predator’s attacks. It’s quite another to escape from the predator after being digested.

This study, authored solely by Sugiura Shinji, an ecologist from Kobe University in Japan, describes how the Japanese water scavenger beetle ( Regimbartia attenuate ) manages to extricate itself from inside several species of frog within 6 hours of being swallowed.

While some prey animals unwittingly hitch a ride through their predator’s gut to be ultimately excreted through the vent (or cloaca) with the the faeces (referred to as “passive”), this aquatic beetle appears to take a more “active” approach.

“Swallowed beetles likely used their legs to move through the digestive tract toward the frog vent, hastening their escape,” the paper describes.

Remarkably, the strategy results in significantly more escapes than failures:

Credit: Sugiura Shinji

The paper reached an audience of almost 10 million on Twitter, and was covered by publications such as The New York Times and NPR.

3. “Sex differences in immune responses that underlie COVID-19 disease outcomes”

There is increasing evidence that COVID-19 produces more severe symptoms and higher mortality among men than among women. This study set out to investigate whether immune responses against the virus SARS-CoV-2 (which causes COVID-19) differ by gender, and whether such differences can help explain the progression of COVID-19 in male and female patients.

Led by a team at Yale University in New Haven, Connecticut, the study analyzed nasal, saliva, and blood samples from COVID-19 patients and a control (non-infected) group and found key differences in the immune response between male and female patients during the early phases of infection.

“We now have clear data suggesting that the immune landscape in COVID-19 patients is considerably different between the sexes and that these differences may underlie heightened disease susceptibility in men,” one of the study authors, Akiko Iwasaki, from the Howard Hughes Medical Institute in Maryland, said in a press statement.

“Collectively, these data suggest we need different strategies to ensure that treatments and vaccines are equally effective for both women and men.”

The paper has been covered by 145 online news outlets to date, and has reached an audience of more than 7 million on Twitter, according to Altmetric.

4. “Integrating Genetic, Environmental, and Social Networks to Reveal Transmission Pathways of a Dolphin Foraging Innovation”

Observations of Indo-Pacific bottlenose dolphins ( Tursiops aduncus ) in Shark Bay, Western Australia have shown that they can learn foraging techniques outside the mother-calf bond, which suggests they have a similar cultural nature to great apes.

Researchers observed young dolphins learning ‘shelling’ behaviour – using their beaks to bring empty shells to the surface and shaking out the prey hiding within – from their peers.

The study, led by Sonja Wild when she was a PhD candidate at the University of Leeds in the United Kingdom, challenges conventional wisdom about how dolphins pass on knowledge.

"These results were quite surprising, as dolphins tend to be conservative, with calves following a 'do-as-mother-does' strategy for learning foraging behaviours,” Wild, now at the Centre for the Advanced Study of Collective Behaviour at the University of Konstanz, Germany, said in a press statement.

“This opens the door to a new understanding of how dolphins may be able to behaviourally adapt to changing environments, as learning from one's peers allows for a rapid spread of novel behaviour across populations." The paper has been covered by 269 online news outlets to date, according to Altmetric.

5. “Zoonotic host diversity increases in human-dominated ecosystems”

Animals that carry disease-causing micro-organisms, or pathogens, thrive in human habitats, according to this paper led by a team at University College London, in the United Kingdom.

The study, based on a dataset of 184 studies incorporating almost 7,000 species, 376 of which are known to carry human-shared pathogens, found that the disruptions caused by global changes in land use appear to benefit disease-carrying species. Changes in land use include clearing natural forest to make space for farmland or housing developments.

“We … show that mammal species that harbour more pathogens overall (either human-shared or non-human-shared) are more likely to occur in human-managed ecosystems,” the paper concludes.

“Our results suggest that global changes in the mode and the intensity of land use are creating expanding hazardous interfaces between people, livestock and wildlife reservoirs of zoonotic [pathogen-caused] disease.”

The paper has been covered by more than 150 online news outlets, and reached more than 5 million people on Twitter.

Research Question

Ai generator.

A research question serves as the foundation of any academic study, driving the investigation and framing the scope of inquiry. It focuses the research efforts, ensuring that the study addresses pertinent issues systematically. Crafting a strong research question is essential as it directs the methodology, data collection, and analysis, ultimately shaping the study’s conclusions and contributions to the field.

What is a Research Question?

A research question is the central query that guides a study, focusing on a specific problem or issue. It defines the purpose and direction of the research, influencing the methodology and analysis. A well-crafted research question ensures the study remains relevant, systematic, and contributes valuable insights to the field.

Types of Research Questions

Research questions are a crucial part of any research project. They guide the direction and focus of the study. Here are the main types of research questions:

1. Descriptive Research Questions

These questions aim to describe the characteristics or functions of a specific phenomenon or group. They often begin with “what,” “who,” “where,” “when,” or “how.”

• What are the common symptoms of depression in teenagers?

2. Comparative Research Questions

These questions compare two or more groups or variables to identify differences or similarities.

• How do the academic performances of students in private schools compare to those in public schools?

3. Correlational Research Questions

These questions seek to identify the relationships between two or more variables. They often use terms like “relationship,” “association,” or “correlation.”

• Is there a relationship between social media usage and self-esteem among adolescents?

4. Causal Research Questions

These questions aim to determine whether one variable causes or influences another. They are often used in experimental research.

• Does a new teaching method improve student engagement in the classroom?

5. Exploratory Research Questions

These questions are used when the researcher is exploring a new area or seeking to understand a complex phenomenon. They are often open-ended.

• What factors contribute to the success of start-up companies in the tech industry?

6. Predictive Research Questions

These questions aim to predict future occurrences based on current or past data. They often use terms like “predict,” “forecast,” or “expect.”

• Can high school GPA predict college success?

7. Evaluative Research Questions

These questions assess the effectiveness or impact of a program, intervention, or policy .

• How effective is the new community outreach program in reducing homelessness?

8. Ethnographic Research Questions

These questions are used in qualitative research to understand cultural phenomena from the perspective of the participants.

• How do cultural beliefs influence healthcare practices in rural communities?

9. Case Study Research Questions

These questions focus on an in-depth analysis of a specific case, event, or instance.

• What were the critical factors that led to the failure of Company X?

10. Phenomenological Research Questions

These questions explore the lived experiences of individuals to understand a particular phenomenon.

• What is the experience of living with chronic pain?

Research Question Format

A well-formulated research question is essential for guiding your study effectively. Follow this format to ensure clarity and precision:

• Begin with a broad subject area.
• Example: “Education technology”
• Define a specific aspect or variable.
• Example: “Impact of digital tools”
• Decide if you are describing, comparing, or investigating relationships.
• Example: “Effectiveness”
• Identify who or what is being studied.
• Example: “High school students”
• Formulate the complete question.
• Example: “How effective are digital tools in enhancing the learning experience of high school students?”

Sample Format: “How [specific aspect] affects [target population] in [context]?” Example: “How does the use of digital tools affect the academic performance of high school students in urban areas?”

Research Question Examples

Research questions in business.

• “What are the primary factors influencing customer loyalty in the retail industry?”
• “How does employee satisfaction differ between remote work and in-office work environments in tech companies?”
• “What is the relationship between social media marketing and brand awareness among small businesses?”
• “How does implementing a four-day workweek impact productivity in consulting firms?”
• “What are the emerging trends in consumer behavior post-COVID-19 in the e-commerce sector?”
• “Why do some startups succeed in attracting venture capital while others do not?”
• “How effective is corporate social responsibility in enhancing brand reputation for multinational companies?”
• “How do decision-making processes in family-owned businesses differ from those in publicly traded companies?”
• “What strategies do successful entrepreneurs use to scale their businesses in competitive markets?”
• “How does supply chain management affect the operational efficiency of manufacturing firms?”

Research Questions in Education

• “What are the most common challenges faced by first-year teachers in urban schools?”
• “How do student achievement levels differ between traditional classrooms and blended learning environments?”
• “What is the relationship between parental involvement and student academic performance in elementary schools?”
• “How does the implementation of project-based learning affect critical thinking skills in middle school students?”
• “What are the emerging trends in the use of artificial intelligence in education?”
• “Why do some students perform better in standardized tests than others despite similar instructional methods?”
• “How effective is the flipped classroom model in improving student engagement and learning outcomes in high school science classes?”
• “How do teachers’ professional development programs impact teaching practices and student outcomes in rural schools?”
• “What strategies can be employed to reduce the dropout rate among high school students in low-income areas?”
• “How does classroom size affect the quality of teaching and learning in elementary schools?”

Research Questions in Health Care

• “What are the most common barriers to accessing mental health services in rural areas?”
• “How does patient satisfaction differ between telemedicine and in-person consultations in primary care?”
• “What is the relationship between diet and the incidence of type 2 diabetes in adults?”
• “How does regular physical activity influence the recovery rate of patients with cardiovascular diseases?”
• “What are the emerging trends in the use of wearable technology for health monitoring?”
• “Why do some patients adhere to their medication regimen while others do not despite similar health conditions?”
• “How effective are community-based health interventions in reducing obesity rates among children?”
• “How do interdisciplinary team meetings impact patient care in hospitals?”
• “What strategies can be implemented to reduce the spread of infectious diseases in healthcare settings?”
• “How does nurse staffing level affect patient outcomes in intensive care units?”

Research Questions in Computer Science

• “What are the key features of successful machine learning algorithms used in natural language processing?”
• “How does the performance of quantum computing compare to classical computing in solving complex optimization problems?”
• “What is the relationship between software development methodologies and project success rates in large enterprises?”
• “How does the implementation of cybersecurity protocols impact the frequency of data breaches in financial institutions?”
• “What are the emerging trends in blockchain technology applications beyond cryptocurrency?”
• “Why do certain neural network architectures outperform others in image recognition tasks?”
• “How effective are different code review practices in reducing bugs in open-source software projects?”
• “How do agile development practices influence team productivity and product quality in software startups?”
• “What strategies can improve the scalability of distributed systems in cloud computing environments?”
• “How does the choice of programming language affect the performance and maintainability of enterprise-level software applications?”

Research Questions in Psychology

• “What are the most common symptoms of anxiety disorders among adolescents?”
• “How does the level of job satisfaction differ between remote workers and in-office workers?”
• “What is the relationship between social media use and self-esteem in teenagers?”
• “How does cognitive-behavioral therapy (CBT) affect the severity of depression symptoms in adults?”
• “What are the emerging trends in the treatment of post-traumatic stress disorder (PTSD)?”
• “Why do some individuals develop resilience in the face of adversity while others do not?”
• “How effective are mindfulness-based interventions in reducing stress levels among college students?”
• “How does group therapy influence the social skills development of children with autism spectrum disorder?”
• “What strategies can improve the early diagnosis of bipolar disorder in young adults?”
• “How do sleep patterns affect cognitive functioning and academic performance in high school students?”

More Research Question Examples

Research question examples for students.

• “What are the primary study habits of high-achieving college students?”
• “How do academic performances differ between students who participate in extracurricular activities and those who do not?”
• “What is the relationship between time management skills and academic success in high school students?”
• “How does the use of technology in the classroom affect students’ engagement and learning outcomes?”
• “What are the emerging trends in online learning platforms for high school students?”
• “Why do some students excel in standardized tests while others struggle despite similar study efforts?”
• “How effective are peer tutoring programs in improving students’ understanding of complex subjects?”
• “How do different teaching methods impact the learning process of students with learning disabilities?”
• “What strategies can help reduce test anxiety among middle school students?”
• “How does participation in group projects affect the development of collaboration skills in university students?”

Research Question Examples for College Students

• “What are the most common stressors faced by college students during final exams?”
• “How does academic performance differ between students who live on campus and those who commute?”
• “What is the relationship between part-time employment and GPA among college students?”
• “How does participation in study abroad programs impact cultural awareness and academic performance?”
• “What are the emerging trends in college students’ use of social media for academic purposes?”
• “Why do some college students engage in academic dishonesty despite awareness of the consequences?”
• “How effective are university mental health services in addressing students’ mental health issues?”
• “How do different learning styles affect the academic success of college students in online courses?”
• “What strategies can be employed to improve retention rates among first-year college students?”
• “How does participation in extracurricular activities influence leadership skills development in college students?”

Research Question Examples in Statistics

• “What are the most common statistical methods used in medical research?”
• “How does the accuracy of machine learning models compare to traditional statistical methods in predicting housing prices?”
• “What is the relationship between sample size and the power of a statistical test in clinical trials?”
• “How does the use of random sampling affect the validity of survey results in social science research?”
• “What are the emerging trends in the application of Bayesian statistics in data science?”
• “Why do some datasets require transformation before applying linear regression models?”
• “How effective are bootstrapping techniques in estimating the confidence intervals of small sample data?”
• “How do different imputation methods impact the results of analyses with missing data?”
• “What strategies can improve the interpretation of interaction effects in multiple regression analysis?”
• “How does the choice of statistical software affect the efficiency of data analysis in academic research?”

Research Question Examples in Socialogy

• “What are the primary social factors contributing to urban poverty in major cities?”
• “How does the level of social integration differ between immigrants and native-born citizens in urban areas?”
• “What is the relationship between educational attainment and social mobility in different socioeconomic classes?”
• “How does exposure to social media influence political participation among young adults?”
• “What are the emerging trends in family structures and their impact on child development?”
• “Why do certain communities exhibit higher levels of civic engagement than others?”
• “How effective are community policing strategies in reducing crime rates in diverse neighborhoods?”
• “How do socialization processes differ in single-parent households compared to two-parent households?”
• “What strategies can be implemented to reduce racial disparities in higher education enrollment?”
• “How does the implementation of public housing policies affect the quality of life for low-income families?”

Research Question Examples in Biology

• “What are the primary characteristics of the various stages of mitosis in eukaryotic cells?”
• “How do the reproductive strategies of amphibians compare to those of reptiles?”
• “What is the relationship between genetic diversity and the resilience of plant species to climate change?”
• “How does the presence of pollutants in freshwater ecosystems impact the growth and development of aquatic organisms?”
• “What are the emerging trends in the use of CRISPR technology for gene editing in agricultural crops?”
• “Why do certain bacteria develop antibiotic resistance more rapidly than others?”
• “How effective are different conservation strategies in protecting endangered species?”
• “How do various environmental factors influence the process of photosynthesis in marine algae?”
• “What strategies can enhance the effectiveness of reforestation programs in tropical rainforests?”
• “How does the method of seed dispersal affect the spatial distribution and genetic diversity of plant populations?”

Research Question Examples in History

• “What were the key social and economic factors that led to the Industrial Revolution in Britain?”
• “How did the political systems of ancient Athens and ancient Sparta differ in terms of governance and citizen participation?”
• “What is the relationship between the Renaissance and the subsequent scientific revolution in Europe?”
• “How did the Treaty of Versailles contribute to the rise of Adolf Hitler and the onset of World War II?”
• “What are the emerging perspectives on the causes and impacts of the American Civil Rights Movement?”
• “Why did the Roman Empire decline and eventually fall despite its extensive power and reach?”
• “How effective were the New Deal programs in alleviating the effects of the Great Depression in the United States?”
• “How did the processes of colonization and decolonization affect the political landscape of Africa in the 20th century?”
• “What strategies did the suffragette movement use to secure voting rights for women in the early 20th century?”
• “How did the logistics and strategies of the D-Day invasion contribute to the Allied victory in World War II?”

Importance of Research Questions

Research questions are fundamental to the success and integrity of any study. Their importance can be highlighted through several key aspects:

• Research questions provide a clear focus and direction for the study, ensuring that the researcher remains on track.
• Example: “How does online learning impact student engagement in higher education?”
• They establish the boundaries of the research, determining what will be included or excluded.
• Example: “What are the effects of air pollution on respiratory health in urban areas?”
• Research questions dictate the choice of research design, methodology, and data collection techniques.
• Example: “What is the relationship between physical activity and mental health in adolescents?”
• They make the objectives of the research explicit, providing clarity and precision to the study’s goals.
• Example: “Why do some startups succeed in securing venture capital while others fail?”
• Well-crafted research questions emphasize the significance and relevance of the study, justifying its importance.
• Example: “How effective are public health campaigns in increasing vaccination rates among young adults?”
• They enable a systematic approach to inquiry, ensuring that the study is coherent and logically structured.
• Example: “What are the social and economic impacts of remote work on urban communities?”
• Research questions offer a framework for analyzing and interpreting data, guiding the researcher in making sense of the findings.
• Example: “How does social media usage affect self-esteem among teenagers?”
• By addressing specific gaps or exploring new areas, research questions ensure that the study contributes meaningfully to the existing body of knowledge.
• Example: “What are the emerging trends in the use of artificial intelligence in healthcare?”
• Clear and precise research questions increase the credibility and reliability of the research by providing a focused approach.
• Example: “How do educational interventions impact literacy rates in low-income communities?”
• They help in clearly communicating the purpose and findings of the research to others, including stakeholders, peers, and the broader academic community.
• Example: “What strategies are most effective in reducing youth unemployment in developing countries?”

Research Question vs. Hypothesis

Chracteristics of research questions.

Research questions are fundamental to the research process as they guide the direction and focus of a study. Here are the key characteristics of effective research questions:

1. Clear and Specific

• The question should be clearly articulated and specific enough to be understood without ambiguity.
• Example: “What are the effects of social media on teenagers’ mental health?” rather than “How does social media affect people?”

2. Focused and Researchable

• The question should be narrow enough to be answerable through research and data collection.
• Example: “How does participation in extracurricular activities impact academic performance in high school students?” rather than “How do activities affect school performance?”

3. Complex and Analytical

• The question should require more than a simple yes or no answer and should invite analysis and discussion.
• Example: “What factors contribute to the success of renewable energy initiatives in urban areas?” rather than “Is renewable energy successful?”

4. Relevant and Significant

• The question should address an important issue or problem in the field of study and contribute to knowledge or practice.
• Example: “How does climate change affect agricultural productivity in developing countries?” rather than “What is climate change?”

5. Feasible and Practical

• The question should be feasible to answer within the constraints of time, resources, and access to information.
• Example: “What are the challenges faced by remote workers in the tech industry during the COVID-19 pandemic?” rather than “What are the challenges of remote work?”

6. Original and Novel

• The question should offer a new perspective or explore an area that has not been extensively studied.
• Example: “How do virtual reality technologies influence empathy in healthcare training?” rather than “What is virtual reality?”
• The question should be framed in a way that ensures the research can be conducted ethically.
• Example: “What are the impacts of privacy laws on consumer data protection in the digital age?” rather than “How can we collect personal data more effectively?”

8. Open-Ended

• The question should encourage detailed responses and exploration, rather than limiting answers to a simple yes or no.
• Example: “In what ways do cultural differences affect communication styles in multinational companies?” rather than “Do cultural differences affect communication?”

9. Aligned with Research Goals

• The question should align with the overall objectives of the research project or study.
• Example: “How do early childhood education programs influence long-term academic achievement?” if the goal is to understand educational impacts.

10. Based on Prior Research

• The question should build on existing literature and research, identifying gaps or new angles to explore.
• Example: “What strategies have proven effective in reducing urban air pollution in European cities?” after reviewing current studies on air pollution strategies.

Benefits of Research Question

Research questions are fundamental to the research process and offer numerous benefits, which include the following:

1. Guides the Research Process

A well-defined research question provides a clear focus and direction for your study. It helps in determining what data to collect, how to collect it, and how to analyze it.

Benefit: Ensures that the research stays on track and addresses the specific issue at hand.

2. Clarifies the Purpose of the Study

Research questions help to articulate the purpose and objectives of the study. They make it clear what the researcher intends to explore, describe, compare, or test.

Benefit: Helps in communicating the goals and significance of the research to others, including stakeholders and funding bodies.

3. Determines the Research Design

The type of research question informs the research design, including the choice of methodology, data collection methods, and analysis techniques.

Benefit: Ensures that the chosen research design is appropriate for answering the specific research question, enhancing the validity and reliability of the results.

4. Enhances Literature Review

A well-crafted research question provides a framework for conducting a thorough literature review. It helps in identifying relevant studies, theories, and gaps in existing knowledge.

Benefit: Facilitates a comprehensive understanding of the topic and ensures that the research is grounded in existing literature.

5. Focuses Data Collection

Research questions help in identifying the specific data needed to answer them. This focus prevents the collection of unnecessary data and ensures that all collected data is relevant to the study.

Benefit: Increases the efficiency of data collection and analysis, saving time and resources.

6. Improves Data Analysis

Having a clear research question aids in the selection of appropriate data analysis methods. It helps in determining how the data will be analyzed to draw meaningful conclusions.

Benefit: Enhances the accuracy and relevance of the findings, making them more impactful.

7. Facilitates Hypothesis Formation

In quantitative research, research questions often lead to the development of hypotheses that can be tested statistically.

Benefit: Provides a basis for hypothesis testing, which is essential for establishing cause-and-effect relationships.

8. Supports Result Interpretation

Research questions provide a lens through which the results of the study can be interpreted. They help in understanding what the findings mean in the context of the research objectives.

Benefit: Ensures that the conclusions drawn from the research are aligned with the original aims and objectives.

9. Enhances Reporting and Presentation

A clear research question makes it easier to organize and present the research findings. It helps in structuring the research report or presentation logically.

Benefit: Improves the clarity and coherence of the research report, making it more accessible and understandable to the audience.

10. Encourages Critical Thinking

Formulating research questions requires critical thinking and a deep understanding of the subject matter. It encourages researchers to think deeply about what they want to investigate and why.

Benefit: Promotes a more thoughtful and analytical approach to research, leading to more robust and meaningful findings.

How to Write a Research Question

Crafting a strong research question is crucial for guiding your study effectively. Follow these steps to write a clear and focused research question:

Identify a Broad Topic:

Start with a general area of interest that you are passionate about or that is relevant to your field. Example: “Climate change”

Conduct Preliminary Research:

Explore existing literature and studies to understand the current state of knowledge and identify gaps. Example: “Impact of climate change on agriculture”

Narrow Down the Topic:

Focus on a specific aspect or issue within the broad topic to make the research question more manageable. Example: “Effect of climate change on crop yields”

Consider the Scope:

Ensure the question is neither too broad nor too narrow. It should be specific enough to be answerable but broad enough to allow for thorough exploration. Example: “How does climate change affect corn crop yields in the Midwest United States?”

Determine the Research Type:

Decide whether your research will be descriptive, comparative, relational, or causal, as this will shape your question. Example: “How does climate change affect corn crop yields in the Midwest United States over the past decade?”

Formulate the Question:

Write a clear, concise question that specifies the variables, population, and context. Example: “What is the impact of increasing temperatures and changing precipitation patterns on corn crop yields in the Midwest United States from 2010 to 2020?”

Ensure Feasibility:

Make sure the question can be answered within the constraints of your resources, time, and data availability. Example: “How have corn crop yields in the Midwest United States been affected by climate change-related temperature increases and precipitation changes between 2010 and 2020?”

Review and Refine:

Evaluate the question for clarity, focus, and relevance. Revise as necessary to ensure it is well-defined and researchable. Example: “What are the specific impacts of temperature increases and changes in precipitation patterns on corn crop yields in the Midwest United States from 2010 to 2020?”

What is a research question?

A research question is a specific query guiding a study’s focus and objectives, shaping its methodology and analysis.

Why is a research question important?

It provides direction, defines scope, ensures relevance, and guides the methodology of the research.

How do you formulate a research question?

Identify a topic, narrow it down, conduct preliminary research, and ensure it is clear, focused, and researchable.

What makes a good research question?

Clarity, specificity, feasibility, relevance, and the ability to guide the research effectively.

Can a research question change?

Yes, it can evolve based on initial findings, further literature review, and the research process.

What is the difference between a research question and a hypothesis?

A research question guides the study; a hypothesis is a testable prediction about the relationship between variables.

How specific should a research question be?

It should be specific enough to provide clear direction but broad enough to allow for comprehensive investigation.

What are examples of good research questions?

Examples include: “How does social media affect academic performance?” and “What are the impacts of climate change on agriculture?”

Can a research question be too broad?

Yes, a too broad question can make the research unfocused and challenging to address comprehensively.

What role does a research question play in literature reviews?

It helps identify relevant studies, guides the search for literature, and frames the review’s focus.

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