punishment in education

• Our Mission

Aiming for Discipline Instead of Punishment

Brain-aligned discipline isn’t compliance-driven or punitive—it’s about supporting students in creating sustainable changes in behavior.

There are many perspectives on the topic of discipline in our classrooms and schools, and I’d like to explore the idea of using brain-aligned discipline with students who have adverse childhood experiences (ACEs). 

Traditional punishment with these students only escalates power struggles and conflict cycles, breeding an increased stress response in the brain and body. Punishment is used to try to force compliance. The vast majority of school discipline procedures are forms of punishment that work best with the students who need them the least.

With our most difficult students, the current way schools try to discipline students does not change their behavior, and often it escalates the problems.

Discipline, unlike punishment, is proactive and begins before there are problems. It means seeing conflict as an opportunity to problem solve. Discipline provides guidance, focuses on prevention, enhances communication, models respect, and embraces natural consequences. It teaches fairness, responsibility, life skills, and problem solving. 

There are times when students need to be removed from the classroom and school for aggressive, volatile actions, but upon re-entry we should make a plan of action that begins to address these actions in these brain-aligned ways.

The neurobiological changes caused by chronic negative experiences and a history of adversity can trigger a fear response in the brain. As Pam Leo says, “A hurtful child is a hurt-filled child. Trying to change her behavior with punishment is like trying to pull off only the top part of the weed. If we don’t get to the root, the hurtful behavior pops up elsewhere.” In children the fear response often looks aggressive, defiant, and oppositional.

Young people with ACEs have brains that are in a constant state of alarm. In this alarm state, consequences don’t register properly. Discipline can only be done when both the educator and the student are calm and self-regulated. If they aren’t, behavioral difficulties will escalate. 

In a brain-aligned model of discipline, we must teach the behaviors we want to see, laying the groundwork for prevention systems and strategies. 

Preventive Brain-Aligned Strategies

Preventive systems are taught as procedures and routines. They are collaborative and filled with choice. Their purpose is to create a sustainable behavioral change, not just compliance or obedience for a short period of time. 

I teach students about their neuroanatomy, so they understand what happens in their brains when they become stressed, angry, or anxious. When we understand this, we feel relieved and empowered. 

In morning meetings or whole class time, I discuss the prefrontal cortex, amygdala, and neuroplasticity with students. We identify and make lists of our emotional triggers and coping strategies, and I teach students to use their breath and movement to calm their stress response systems. 

Is there an adult in the school who connects with this student and has a space where the student can go if they need to regroup and calm their stress response systems? Are you teaching these procedures ahead of a time when a student needs to regulate away from the class? 

Could your school create a area for both teachers and students to go to when they need to reset their emotional state? This area could be stocked with paper, markers, crayons, water, soft music and lighting, a jump rope, a stationary bike, lavender scented cotton balls, jars for affirmations or worries, or a rocking chair. Students will need to be taught ahead of time how to use this area, which they should need for just two to five minutes in order to feel refocused and ready to return to class.

Examples of Natural, Non-Punitive Consequences 

Name-calling: Have the student create a book of positive affirmations for the class, or have them create a list of “kind words” and teach them to a younger class.

Low-level physical aggression (pushing, kicking, hitting): Some consequences could include giving the student a new learning space in the room or a new spot in line, or they could be tasked with performing an act of kindness or service for the hurt person.

If this occurs at recess, the student could be tasked with assisting a teacher on recess duty in monitoring the playground, noticing everything that is going well. They can roam around the playground, still getting the exercise they need. Or again they could perform an act of kindness toward the student who they hit.

Inappropriate language: This calls for a discussion when both student and teacher are in a calm brain state. Sometimes words that are inappropriate at school are used at home, so we need to understand the cultural context and have a discussion with the student.

An older student could research the words they used and report to you on why they’re not school words; younger students could try to write out what they were trying to convey using school-friendly language or drawings. 

Incomplete assignments: Have a one-on-one discussion to convey what this behavior communicates to you. Ask if something has changed at home or school, or if the student doesn’t understand what is required. Make a plan with the student and possibly a parent for making up the work that has been missed. And consider assigning a student mentor to help the student.

The research is clear. Our brains learn best in a state of relaxed alertness. Our discipline systems must begin to shift toward creating this state in all the members of our school community.

• High contrast
• Take action

Search UNICEF

Ending corporal punishment in schools to transform education for all children, schools are meant to be transformative spaces for children to learn and develop..

Schools are meant to be transformative spaces for children to learn and develop. But sadly, vast numbers of children around the world are subjected to violence in education settings, particularly as a disciplinary method. 

Corporal punishment, or violent forms of discipline, is a common practice at schools in many countries, administered by teachers and other staff. Evidence has revealed that this violence has no positive benefits, and is in fact a hindrance to learning – negatively impacting children’s cognitive development, contributing to lower academic achievement, and school dropout. This also carries the risk of long-term harm to mental and physical health and future prospects of individuals, families and societies. 

A new landmark report on school corporal punishment has been released by End Violence in partnership with Safe to Learn and the Coalition for Good Schools. The report explores children’s experiences of school corporal punishment, identifying where action is needed, and describing how progress can be achieved. 

THE SCALE OF CORPORAL PUNISHMENT IN SCHOOLS

School corporal punishment is still lawful in 63 states worldwide – comprising approximately 793 million children or half of the global school-age population. 

The report highlights the many factors and dynamics that influence the prevalence of corporal punishment. 

It finds that the practice has been  prevalent across regions . For example, an analysis of research studies between 1980 and 2017 found that 70 percent of children in Africa and Central America had experienced corporal punishment in schools at least once in their lives. 

Corporal punishment is  influenced by gender . Most studies find that boys are more likely to be subjected to school corporal punishment, with male teachers tending to be more violent toward male students. For girls, violent punishment may be used to control behaviour and encourage timidity. LGBTQI students have consistently reported a higher prevalence of violence and bullying in schools. 

Education is of particular importance to marginalised and disadvantaged children, but corporal punishment is often  more prevalent in low-resource settings and schools, harming the education prospects of the children who need it most . Children with disabilities, refugees, migrant and racially marginalised children are also disproportionately subjected to violent punishment in school.

Safe schools can provide a protective barrier for continued learning despite a difficult external context such as a humanitarian crisis, giving children access to the knowledge that can lead to increased empowerment and better future opportunities. But sadly, violence reverses these possibilities. 

Research has found an  association between experiencing violent punishment in childhood with aggression, anti-social behaviour, perpetration of physical assault and criminality in adulthood . Children subject to corporal punishment in childhood are more likely to use it on their children when they become parents, creating cycles of inter-generational violence.

And this comes at a great cost to society. The World Bank and Safe to Learn investment case reported that  the cost of inaction on school violence including corporal punishment amounts to around $11 trillion globally in lost lifetime earnings . Its prevalence combined with its harmful impacts mean that investments in the vital benefits of education for children and societies do not always generate the best possible returns. 

LEGAL REFORM AND ITS IMPLEMENTATION 

The report stresses the importance of effectively implementing law reform. Prohibiting corporal punishment by law sends the clearest message that violent punishment of children is no longer acceptable in society. And legal reform is effective. Many countries with previously high levels of violent punishment in school have now ended or are close to ending the practice, helping transform attitudes to violence against children at scale. 

Alongside laws banning violent punishment in schools, it is also key to put prohibition into practice. Based on evidence and existing solutions, the report draws out best practices to implement law reform, including:

• creating awareness of the law, 
• adopting ‘whole school’ interventions that engage all stakeholders, from teachers to parents to address the issue 
• adopting positive discipline methods and 
• engaging adults and children to challenge harmful norms. 

Related topics

More to explore, safe to learn - an essay collection.

Violence against children occurs on an unimaginable scale.

NCMEC launches upgraded Cybertipline

The National Centre for Missing and Exploited Children (NCMEC) has launched its new and improved CyberTipline

A new comic to help guide voices of young survivors

Facing childhood sexual abuse and exploitation is a traumatic experience that has devastating and long-term consequences.

What the metaverse and extended reality means

The Metaverse is on the horizon. 

Punishment in Social Learning Theory

• Living reference work entry
• First Online: 24 January 2018
• Cite this living reference work entry

• Jinsook Song 4 ,
• Maxine Notice 4 &
• Janet Robertson 4  

380 Accesses

Name of Strategy or Intervention

Aversive stimuli

Introduction

Punishment in social learning theory is designed to reduce and eliminate certain behaviors. Punishment is not considered a behavior; instead, it has a role of mediating the learning process (Bandura 1977 ; Skinner 1976 ). Bandura described punishment as a stimulus or reinforcer in a learning process. People can experience punishment in two forms, positive and negative. Negative reinforcement and positive punishment are often confused. Negative reinforcement is to take something aversive away in order to increase a response. Positive punishment is to add something aversive to modify behavior (Bandura 1977 ).

Theoretical Framework

Punishment is often discussed as a part of operant conditioning in behavioral psychology attributed to the work of B.F. Skinner ( 1976 ). Skinner stated that behavior is strengthened by its consequences or reinforcements.

Bandura added the cognitive approach –...

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Alampay, L. P., Godwin, J., Lansford, J. E., Bombi, A. S., Bornstein, M. H., Chang, L., & ... Bacchini, D. (2017). Severity and justness do not moderate the relation between corporal punishment and negative child outcomes: A multicultural and longitudinal study. International Journal of Behavioral Development , 41 (4), 491–502.

Article   Google Scholar  

Bandura, A. (1977). Social learning theory , Prentice-Hall series in social learning theory . Englewood Cliffs: Prentice Hall.

Google Scholar  

Baucom, D. H., & Epstein, N. (1990). Cognitive behavioral marital therapy . New York: Brunner, Mazel.

Rodriguez, C. M. (2003). Parental discipline and abuse potential effects on child depression, anxiety, and attributions. Journal of Marriage and Family, 65 (4), 809–817.

Skinner, B. (1976). About behaviorism . New York: Vintage Books.

Download references

Author information

Authors and affiliations.

Antioch University New England, Keene, NH, USA

Jinsook Song, Maxine Notice & Janet Robertson

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Maxine Notice .

Editor information

Editors and affiliations.

The Family Institute at Northwestern, Evanston, Illinois, USA

Anthony Chambers

Douglas C. Breunlin

Section Editor information

University of Utah, Salt Lake City, UT, USA

Brian Baucom Ph.D.

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this entry

Cite this entry.

Song, J., Notice, M., Robertson, J. (2018). Punishment in Social Learning Theory. In: Lebow, J., Chambers, A., Breunlin, D. (eds) Encyclopedia of Couple and Family Therapy. Springer, Cham. https://doi.org/10.1007/978-3-319-15877-8_51-1

Download citation

DOI : https://doi.org/10.1007/978-3-319-15877-8_51-1

Received : 30 September 2017

Accepted : 31 December 2017

Published : 24 January 2018

Publisher Name : Springer, Cham

Print ISBN : 978-3-319-15877-8

Online ISBN : 978-3-319-15877-8

eBook Packages : Springer Reference Behavioral Science and Psychology Reference Module Humanities and Social Sciences Reference Module Business, Economics and Social Sciences

• Publish with us

Policies and ethics

• Find a journal
• Track your research

• Follow us on Facebook
• Follow us on Twitter
• Criminal Justice
• Environment
• Politics & Government
• Race & Gender

Expert Commentary

Corporal punishment in schools: Research and reporting tips to guide your coverage

Two scholars offer guidance on covering school corporal punishment, which can result in serious injuries and has, for years, been used disproportionately on Black students and children with disabilities.

Republish this article

This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License .

by Denise-Marie Ordway, The Journalist's Resource August 31, 2023

This <a target="_blank" href="https://journalistsresource.org/education/corporal-punishment-schools-discipline-research/">article</a> first appeared on <a target="_blank" href="https://journalistsresource.org">The Journalist's Resource</a> and is republished here under a Creative Commons license.<img src="https://journalistsresource.org/wp-content/uploads/2020/11/cropped-jr-favicon-150x150.png" style="width:1em;height:1em;margin-left:10px;">

This tip sheet on covering corporal punishment in schools, originally published in March 2023, was updated on Aug. 31, 2023 to reflect the number of states that allow the practice and the results of a new study on public support for laws banning physical forms of child discipline. We also added a link to a policy statement the American Academy of Pediatrics released Aug. 21, 2023.

Despite academic studies noting the harms associated with corporal punishment, U.S. public schools use it to discipline tens of thousands of students a year, data from the U.S. Department of Education show .  

Public schools in 22 states reported using physical discipline on students during the 2017-18 academic year, the most recent year for which national data is available. The practice was most common in Texas, Mississippi, Alabama, Arkansas and Oklahoma. Today, 18 states allow public school personnel to spank, hit or otherwise inflict pain on children to control their behavior, according to Elizabeth Gershoff , a professor in the Department of Human Development and Family Sciences at the University of Texas at Austin.

Corporal punishment is legal in private schools in all but three states: Iowa, Maryland and New Jersey.

It’s not yet clear whether schools have relied on this type of discipline more or less often amid the COVID-19 pandemic. However, school district officials reported a marked increase in student misbehavior in 2021-22, compared with before the coronavirus arrived in the U.S. in 2019. News stories and research studies have documented the pandemic’s widespread effects on kids’ mental and physical health .

When the U.S. Department of Education surveyed public school districts in 2022, 84% agreed or strongly agreed the pandemic has negatively affected students’ behavioral development.

Almost 6 out of 10 public schools reported “increased incidents of classroom disruptions from student misconduct” and 48% reported increased “acts of disrespect towards teachers and staff.” About half reported more “rowdiness outside of the classroom.”

Even if the number of children physically punished at school has fallen in recent years, the issue warrants journalists’ attention considering the serious injuries students sometimes suffer and the fact that Black children and children with mental or physical disabilities have, for many years, received a disproportionate share of school corporal punishment.

The federal government requires public schools and public preschools to report the number of students who receive physical punishment. In 2017-18, public schools physically disciplined a total of 69,492 students at least once — down from 92,479 kids in 2015-16.

That year, public preschool programs, which are often housed within public elementary schools, reported using corporal punishment on a combined 851 children aged 3 to 5 years.

It’s unclear how common corporal punishment is in private schools because the federal government does not require them to report their numbers. Gershoff, one of the country’s foremost experts on corporal punishment, says she knows of no government agency or organization that tracks that information.

She urges journalists to help their audiences understand the various ways schools use physical discipline and its potential impacts on student behavior, mental and physical health, and academic achievement.

“Physical punishment in schools typically involves an adult hitting a child with a two-foot-long wooden board, known euphemistically as a ‘paddle,'” Gershoff writes in an essay published last week in The Hill. “Consider this: If a principal were to hit an adult, say a teacher or a parent, with a two-foot-long board, that person would be charged with assault with a weapon or aggravated assault. School personnel are hitting children with boards that, in any other context, would be considered weapons — and they do so legally.”

The global use of school corporal punishment

The U.S. is the only member of the United Nations that has not yet ratified the Convention on the Rights of the Child , an international treaty adopted in 1989 that, among other things, protects children “from all forms of physical or mental violence, injury or abuse, neglect or negligent treatment, maltreatment or exploitation.” Somalia ratified the convention in 2015 — the 196 th country to do so.

Globally, about half of all children aged 6 to 17 years live in countries where school corporal punishment is “not fully prohibited,” according to the World Health Organization.

But legal bans do not necessarily mean corporal punishment ceases to exist, a team of researchers from the University of Cape Town learned after examining 53 peer-reviewed studies conducted in various parts of the planet and published between 1980 and 2017.

In South Africa, for instance, half of students reported being corporally punished at school despite a ban instituted in 1996, the researchers note.

“There is also concern that school staff and administrators may underreport school corporal punishment even where it is legal,” they write, adding that a study in Tanzania found that students tended to report twice as much corporal punishment as teachers.

While there’s limited research on corporal punishment in U.S. schools, numerous studies of corporal punishment in U.S. homes have determined it is associated with a range of harms. When Gershoff and fellow researcher Andrew Grogan-Kaylor combined and analyzed the results of 75 research studies on parental spanking published before June 1, 2014, they found no evidence it improves children’s behavior.

In fact, they discovered that kids spanked by their parents have a greater likelihood of experiencing 13 detrimental outcomes, including aggression, antisocial behavior, impaired cognitive ability and low self-esteem during childhood and antisocial behavior and mental health problems in adulthood.

Gershoff says children who are physically disciplined at school likely are affected in similar ways.

“There’s nothing to make me think that wouldn’t hold for corporal punishment in schools,” she tells The Journalist’s Resource. “In fact, I think it might be more problematic in schools because of the lack of a strong relationship in the schools between the children and the person who’s doing the paddling.”

Other research by Gershoff offers insights into the types of misbehavior that lead to corporal punishment. She found that public school principals, teachers and other staff members have used physical punishment for a range of offenses, including tardiness, disrespecting teachers, running in the hallways and receiving bad grades.

Some children have been disciplined so harshly they suffered injuries, “including bruises, hematomas, nerve and muscle damage, cuts, and broken bones,” Gershoff and colleague Sarah Font write in the journal Social Policy Report in 2016.

The Society for Adolescent Medicine estimated in 2003 that 10,000 to 20,000 students require medical attention each year in the U.S. as a result of school corporal punishment. The organization has not updated its estimate since then, however.

Black students disciplined disproportionately

James B. Pratt Jr. , an associate professor of criminal justice at Fisk University who also researches corporal punishment, encourages news outlets to dig deeper into the reasons schools in many states still use pain as punishment.

He says reporters should press state legislators to explain why they allow it to continue, even as public health organizations such as the American Academy of Child and Adolescent Psychiatry and U.S. Centers for Disease Control and Prevention oppose its use. Last week, the American Academy of Pediatrics released a policy statement stressing that corporal punishment “is not an effective or ethical method for management of behavior concerns” and calling for it to be abolished in all school settings.

News coverage of corporal punishment needs historical context as well, Pratt says. His research finds that school corporal punishment, which is most concentrated in the U.S. South, plays a role in sustaining a long history of racialized violence in the region.

“Tell the story of corporal punishment as a form of social control,” Pratt says. “There is research to illustrate how corporal punishment has been used historically and today.”

In the U.S., enslaved Black people were whipped, as were Black prisoners in the early 20 th century and Black children who went before juvenile courts in the 1930s, Pratt and his fellow researchers write in “ Historic Lynching and Corporal Punishment in Contemporary Southern Schools ,” published in 2021 in the journal Social Problems.

For generations after emancipation, white supremacists in the South whipped and lynched Black people to intimidate and control them.

When Pratt and his colleagues examined data on student discipline in 10 southern states in 2013-14 and lynchings between 1865 and 1950, they learned that school corporal punishment was more common for all students — but especially Black students — in areas where lynchings had occurred.

Pratt and his coauthors write that banning school corporal punishment “would help dismantle systemic racism, promoting youth and community well-being in a region still haunted by histories of racial terror.”

Guidance from academic scholars

Both Pratt and Gershoff have lots of ideas for helping journalists frame and strengthen their coverage of corporal punishment in schools. Here are some of the tips they shared with The Journalist’s Resource.

1. Find out whether or how schools in your area use corporal punishment, and who administers it.

Public schools generally share only basic information about corporal punishment to the U.S. Department of Education. School officials submit the total number of students they corporally punish in a given academic year and they break down that number according to students’ sex and race and whether they had a disability, were Hispanic or were enrolled in special programs teaching them to speak English.

Not only does the data lack detail — it does not indicate the type of corporal punishment used, for example, or the type of disability the student had — the information is several years old by the time the federal government finishes collecting it and releases it to the public.

Pratt says journalists can help researchers, parents and the public get a clearer picture of what’s happening in local communities by seeking out more details. To get a sense of how often and how local schools use corporal punishment, ask public school districts for copies of disciplinary reports and policies governing the use of corporal punishment.

Interview teacher union leaders and individual teachers to better understand what’s happening in classrooms and what teachers have seen and learned. Reach out to parents whose children have been disciplined to ask about student experiences.

“We know there’s something there, but how it functions on the ground is what we need to understand,” Pratt says.

Some questions to investigate:

• Which misbehaviors lead to corporal punishment?
• Who administers physical discipline?
• What are children hit with and how many times?
• Where on their bodies are they struck?
• How often have children been seriously injured and how were those situations handled?
• Have local schools been sued over corporal punishment?
• In areas where corporal punishment is banned, have school employees been disciplined or terminated for using corporal punishment?

2. Ask how schools’ use of corporal punishment and other forms of discipline changed during the COVID-19 pandemic.

Students, teachers and other school staff members experienced a lot of stress during the pandemic, as schools struggled to provide instruction and other student services while also monitoring and responding to COVID-19.

At the start of the pandemic, many schools closed their campuses temporarily and taught lessons online. When everyone returned to campus, the situation was, at times, confusing or somewhat chaotic. Many schools discovered they needed to rely more heavily on substitute teachers , who often do not have classroom management training, to fill in when regular teachers were sick, in quarantine or caring for loved ones.

It’s a good idea for journalists to try to gauge how such changes have affected student behavior and discipline. Local school districts and state departments of education should be able to provide more recent records than the U.S. Department of Education. Another source of data: colleges and universities where faculty are studying school discipline.

A September 2022 analysis from the University of Arkansas, for example, shows a sharp decline in several types of student discipline in that state since before the pandemic began. However, the authors write that they “cannot tell if the decline is the result of improved student behavior or inconsistent reporting by schools.”

“Corporal punishment was used [as] a consequence for 16% of infractions in 2008-09 and declined to being used in 3% of infractions in 2020-21,” they write.

Gershoff expects corporal punishment numbers to continue to fall nationally.

“69,000 is still too many kids being traumatized at school,” she says.

There are parts of the country where school officials in recent months have reinstated corporal punishment or voiced support for it, however. In 2022, the school board in Cassville, Missouri, voted to bring it back after two decades of not using it. And a school board member in Collier County, Florida , announced after his election last November that he wanted schools across the region to reintroduce physical discipline.

3. Learn the legal history of school corporal punishment in the U.S.

It’s important that journalists covering corporal punishment understand the history of the practice , including the stance the U.S. Supreme Court and lower courts have taken on the issue.

Individual states have the authority to create and enforce discipline policies for children attending schools within their borders. Generally speaking, Supreme Court justices have been reluctant to intervene in the day-to-day operations of public schools, so long as educators do not heavily infringe on students’ constitutional rights.

Two Supreme Court cases decided in the late 1970s reinforced public schools’ right to use physical discipline. In 1975, in Baker v. Owen , justices ruled that public schools have the right to use corporal punishment without parents’ permission. In Ingraham v. Wright , decided in 1977, the court decided that corporal punishment, regardless of severity, does not violate the Constitution’s Eighth Amendment, which prohibits cruel and unusual punishment.

In writing the majority opinion for Ingraham v. Wright, Justice Lewis Powell asserts that “corporal punishment serves important educational interests.”

“At common law a single principle has governed the use of corporal punishment since before the American Revolution: Teachers may impose reasonable but not excessive force to discipline a child,” Powell writes.

The Supreme Court did not, however, explain what actions would be considered “excessive.” In 1980, the U.S. Court of Appeals for the Fourth Circuit established a test for determining that. Since then, circuit courts in several federal districts have required lawsuits challenging schools’ use of corporal punishment to meet that threshold, often referred to as the “shocking to the conscience” test.

Under that very high standard, corporal punishment is deemed excessive if “the force applied caused injury so severe, was so disproportionate to the need presented, and was so inspired by malice or sadism rather than a merely careless or unwise excess of zeal that it amounted to a brutal and inhumane abuse of official power literally shocking to the conscience.”

An example of corporal punishment a U.S. appeals court decided was excessive : A football coach in Fulton County, Georgia, struck a 14-year-old freshman so hard in the face with a metal lock, the boy’s left eye “was knocked completely out of its socket,” leaving it “destroyed and dismembered.”  

An example of corporal punishment an appeals court did not consider excessive : A teacher in Richmond, Virginia, allegedly jabbed a straight pin into a student’s upper left arm, requiring medical care. The court, in its ruling, notes that “most persons are with some degree of frequency jabbed in the arm or the hip with a needle by physicians or nurses. While it is uncommon for a teacher to do the jabbing, being jabbed is commonplace.”

Over the years, legal scholars have written multiple law journal articles examining the Ingraham v. Wright decision and its implications. An article by Michigan State University law professor Susan H. Bitensky , for example, looks specifically at its impact on Black children .

She argues corporal punishment has impeded Black children’s educations, undercutting the commitment to social progress the Supreme Court made when it decided in 1954, in the landmark civil rights case Brown v. Board of Education of Topeka , that segregating public schools by race was unconstitutional.

“The whole foundation for [the Brown v. Board of Education] holding on segregated schools is a fervent concern that the schools should imbue children, especially black children, with a positive sense of their intellectual worth and should provide them with a commensurate quality of educational experience,” Bitensky writes in the Loyola University Chicago Law Review in 2004.

4. Explain that corporal punishment is a form of social control and that public schools use various types of discipline disproportionately on Black children.

Pratt stresses the importance of putting corporal punishment reports into context.

For many years, public schools have used that disciplinary approach disproportionately on Black youth, according to U.S. Department of Education records . But Black students also are disproportionately suspended, expelled, physically restrained and arrested on suspicion of school-related offenses.

According to the education department’s Civil Rights Data Collection ,  37.3% of public school students who were spanked, paddled or otherwise struck by school employees in 2017-18 were Black. Meanwhile, Black kids comprised 15.3% of public school enrollment nationwide that year.

As a comparison, 50.4% of corporally punished students and 47.3% of all public school students were white.

In public preschools, black children and children with mental and physical disabilities were disproportionately expelled.

Pratt says journalists need to help the public understand how school discipline and other forms of social control such as targeted policing programs and laws prohibiting saggy pants are connected. He encourages reporters to incorporate research into their stories to illustrate how implicit bias and misperceptions about Black children can influence how educators view and interact with Black students.

Research, for example, suggests white adults perceive Black boys to be older than they are and that prospective teachers are more likely to perceive Black children as angry than white children.

“All of [these factors] relate to one another and set the tone,” Pratt says. “This is a collection of harms, and a nefarious one.”

5. Check for errors in school disciplinary reports.

Several news reports in 2021 and 2022 indicate the U.S. government’s tally of children receiving corporal punishment at school may be incorrect.

An investigation the Times Union of Albany published in September reveals hundreds of New York public school students have been physically disciplined in recent years, even though the practice has been generally banned since 1985. State and local government agencies received a total of 17,819 complaints of school corporal punishment from 2016 to 2021, 1,623 of which were determined to be substantiated or founded, the news outlet reported.

“The substantiated cases documented in state Education Department records include incidents where teachers or other staff members pushed, slapped, hit, pinched, spanked, dragged, choked or forcefully grabbed students,” Times Union journalists Emilie Munson , Joshua Solomon and Matt Rocheleau write.

A May 2021 analysis from The 74 , a nonprofit news outlet that focuses on education issues, shows that schools in six states where corporal punishment had been banned reported using it in 2017-18.

Miriam Rollin, a director at the National Center for Youth Law, told The 74 that national figures “are likely a significant undercount.”

“Every school district in the country self-reports its data to the federal government and they’ve long been accused of underreporting data on the use of restraint and seclusion and other forms of harsh discipline,” Rollin told The 74 investigative journalist Mark Keierleber .

6. Press state legislators to explain why they allow school corporal punishment.

Gershoff and Pratt agree journalists should ask legislators in states that allow schools to use physical discipline why they have not stopped the practice.

“Tell the legislative story — who’s legislating this?” Pratt says. “Examine the people doing the work to end [corporal punishment] and also those wanting to maintain it.”

While a handful of members of Congress have introduced bills aimed at eradicating corporal punishment in recent years, none were successful.

In February 2021, U.S. Rep. Alcee Hastings of Florida introduced the Ending Corporal Punishment in Schools Act of 2021 . But Hastings died two months later, and the bill never made it out of the House Committee on Education and Labor.

U.S. Sen. Chris Murphy of Connecticut introduced the Protecting Our Students in Schools Act in 2020 and 2021 without success. He reintroduced the legislation again in May.

Gershoff notes that many Americans want to ban school corporal punishment. More than 65% of U.S. adults who participated in a national survey on the issue in late 2020 indicated they agree or strongly agree with a federal ban, she and other researchers write in a paper that appears in the September 2023 edition of Public Health. At the same time, only 18% of survey participants believed most other adults feel the same way.

“Americans underestimate support for a ban, which may explain why folks have not been more vocal in calling for a ban even though they agree we should have one,” Gershoff wrote in an email to The Journalist’s Resource.

7. Look for stories in corporal punishment data.

Browse around the U.S. Department of Education’s Civil Rights Data Collection , which provides data on corporal punishment in public schools at the national, state and local levels as of the 2017-18 academic year. Notice trends, disparities and where there are unusually high numbers of corporal punishment cases.

For more recent data, reach out to schools, school districts and state education departments. Also, ask researchers for help explaining whether and how data from 2017-18 are still relevant.

Here are some data points worth looking into from the 2017-18 academic year, the most recent available at the national level:

• Mississippi led the country in corporal punishment cases as of that year. Public schools there reported using it at least once on a total of 20,309 students. In Texas, which had the second-highest number, public schools corporally punished 13,892 kids at least one time each.
• More than 30% of public school students who experienced corporal punishment in Indiana, Ohio, South Carolina and Wisconsin had mental or physical disabilities.
• North Carolina public schools didn’t administer corporal punishment often. But when they did, they used it primarily on Native American students. Of the 57 students disciplined this way, about half were categorized as American Indian or Alaska Native. Native American kids made up less than 1% of public school enrollment in North Carolina.
• Oklahoma is the only other state where a large proportion of corporally punished students were Native American. Schools there used corporal punishment on a total of 3,968 students, 24.4% of whom were categorized as American Indian or Alaska Native. Statewide, 6.6% of public school students were Native American.
• Illinois public schools reported using corporal punishment on a total of 202 students, 80.2% of whom were “English language learners,” or children enrolled in programs to learn English.

8. Familiarize yourself with academic research on corporal punishment at schools and in homes.

Gershoff points journalists toward a large and growing body of research on the short- and long-term consequences of corporal punishment at home and in schools. It’s important they know what scholars have learned to date and which questions remain unanswered.

To get started, check out these five studies:

Punitive School Discipline as a Mechanism of Structural Marginalization With Implications for Health Inequity: A Systematic Review of Quantitative Studies in the Health and Social Sciences Literature Catherine Duarte; et al. Annals of the New York Academy of Sciences, January 2023. This is one of the most recent papers examining the relationship between school discipline and student health in the U.S. The authors reviewed 19 studies published between 1990 and 2020 on punitive school discipline, which includes corporal punishment as well as suspension and expulsion. They find punitive school discipline is linked to “greater risk for numerous health outcomes, including persistent depressive symptoms, depression, drug use disorder in adulthood, borderline personality disorder, antisocial behavior, death by suicide, injuries, trichomoniasis, pregnancy in adolescence, tobacco use, and smoking, with documented implications for racial health inequity.” School Corporal Punishment in Global Perspective: Prevalence, Outcomes, and Efforts at Intervention Elizabeth Gershoff. Psychology, Health & Medicine, 2017.

In this paper, Gershoff summarizes what was known at that point in time about the prevalence of school corporal punishment worldwide and the potential consequences for students. She also discusses the various ways schools administer corporal punishment, including forcing students to stand in painful positions, ingest noxious substances and kneel on small objects such as stones or rice. She includes a chart offering estimates for the percentage of students who receive corporal punishment in dozens of countries, including China, India, Indonesia, Jamaica and Peru.

Spanking and Child Outcomes: Old Controversies and New Meta-Analyses Elizabeth Gershoff and Andrew Grogan-Kaylor. Journal of Family Psychology, 2016.

Gershoff and Grogan-Kaylor analyze the results of 75 peer-reviewed studies published before June 1, 2014 on parental spanking, or “hitting a child on their buttocks or extremities using an open hand.” They state that they find “no evidence that spanking does any good for children and all evidence points to the risk of it doing harm.”

Other big takeaways: “In childhood, parental use of spanking was associated with low moral internalization, aggression, antisocial behavior, externalizing behavior problems, internalizing behavior problems, mental health problems, negative parent-child relationships, impaired cognitive ability, low self-esteem, and risk of physical abuse from parents. In adulthood, prior experiences of parental use of spanking were significantly associated with adult antisocial behavior, adult mental health problems, and with positive attitudes about spanking.” Historic Lynching and Corporal Punishment in Contemporary Southern Schools Geoff Ward, Nick Petersen, Aaron Kupchik and James Pratt. Social Problems, February 2021.

School corporal punishment is linked to histories of racial violence in the southeastern U.S., this study finds. The authors analyzed data on school corporal punishment in 10 states in that region during the 2013-2014 academic year and matched it with data on confirmed lynchings between 1865 to 1950. “Of the counties that reported one or more incidents of corporal punishment, 88% had at least one historic lynching and the average number of lynching incidents in these counties is 7.07,” the authors write. They add that banning school corporal punishment in these states would “help dismantle systemic racism, promoting youth and community well-being in a region still haunted by histories of racial terror.”

Disproportionate Corporal Punishment of Students With Disabilities and Black and Hispanic Students Ashley MacSuga-Gage; et al. Journal of Disability Policy Studies, 2021.

When researchers looked at student discipline in the 2,456 U.S. public schools that had used corporal punishment at least 10 times during the 2015-16 academic year, they discovered that children with disabilities were almost two times as likely to receive corporal punishment as students without disabilities. The finding is troubling, they write, considering the U.S. Individuals with Disabilities Education Act recommends schools use a behavior modification strategy known as Positive Behavior Interventions and Supports when students with disabilities misbehave.

The researchers, from the University of Florida and Clemson University, also found that Black students without disabilities were twice as likely to be physically disciplined as white students without disabilities. Meanwhile, schools were less likely to use corporal punishment on Hispanic students than white, non-Hispanic students.  

About The Author

Denise-Marie Ordway

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• My Account Login
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Open access
• Published: 27 October 2016

The impact of reward and punishment on skill learning depends on task demands

• Adam Steel 1 , 2   na1 ,
• Edward H. Silson 2   na1 ,
• Charlotte J. Stagg 1 , 3   na1 &
• Chris I. Baker 2   na1  

Scientific Reports volume  6 , Article number:  36056 ( 2016 ) Cite this article

67k Accesses

34 Citations

10 Altmetric

Metrics details

Reward and punishment motivate behavior, but it is unclear exactly how they impact skill performance and whether the effect varies across skills. The present study investigated the effect of reward and punishment in both a sequencing skill and a motor skill context. Participants trained on either a sequencing skill (serial reaction time task) or a motor skill (force-tracking task). Skill knowledge was tested immediately after training, and again 1 hour, 24–48 hours, and 30 days after training. We found a dissociation of the effects of reward and punishment on the tasks, primarily reflecting the impact of punishment. While punishment improved serial reaction time task performance, it impaired force-tracking task performance. In contrast to prior literature, neither reward nor punishment benefitted memory retention, arguing against the common assumption that reward ubiquitously benefits skill retention. Collectively, these results suggest that punishment impacts skilled behavior more than reward in a complex, task dependent fashion.

Similar content being viewed by others

Interactive effects of incentive value and valence on the performance of discrete action sequences

Intention to learn modulates the impact of reward and punishment on sequence learning

Dissipation of reactive inhibition is sufficient to explain post-rest improvements in motor sequence learning

Introduction.

Reward and punishment, including biological reinforcers such as food, water, or pain, are important motivators for both human and animal behavior. The majority of neuroscience research has focused on studying the effects of reward and punishment on decision-making 1 , 2 , 3 . However, in recent years interest in using reward and punishment to augment motor skill learning has surged 4 , 5 , 6 , 7 , 8 , 9 raising the enticing possibility that valenced feedback could be implemented in rehabilitation settings to improve physical therapy outcomes 10 , 11 , 12 , 13 . However, the variation in methodologies, performance metrics, and retention timescales used across different studies make establishing general principles challenging.

The present study examines the impact of reward and punishment on two different skill learning tasks: the serial reaction time task (SRTT), a sequencing task wherein participants press buttons in response to a stimulus appearing on a screen 14 ; and the force tracking task (FTT) 15 , 16 , 17 , a motor task wherein participants squeeze a force transducer to follow a cursor on screen ( Fig. 1A–D ). The two tasks were implemented in as similar a manner as possible as possible to facilitate comparison between them. In an initial training session, participants trained on either the SRTT or FTT and received valenced feedback (monetary reward, monetary punishment, or motivated control [see methods]) based on their performance (calculated as [Mean Reaction Time/Accuracy per block] for SRTT; mean distance from the target per block in the FTT). In both tasks probe trials, during which stimuli were presented in either a fixed or a random order, were presented before and after training. General skill learning was assessed by comparing initial performance to performance after training, regardless of the probe block type. Sequence-specific skill learning was distinguished from general skill learning by comparing performance on fixed versus random probe blocks. Skill retention was then probed in the absence of feedback at 1 hour, 24 hours, and 30 days after completion of the training.

( A ) Experimental design. Seventy-two participants were divided between two skill learning tasks: a task that demands integration of multiple memory systems, the serial reaction time task (SRTT), and a task that is learned primarily by the motor network, the force-tracking task (FTT). Within each task, participants were randomly assigned to three different feedback groups (reward, punishment, control). ( B ) Experimental timeline. For each task, trials were grouped into blocks of trials. Unbeknownst to the participants, during some blocks (“fixed sequence blocks”) the stimulus would appear according to a repeating pattern. During other periods the appearance of the stimulus was randomly determined (“random sequence blocks”). Following familiarization blocks, participants were trained on the task with valenced feedback. To assess sequence knowledge, training was bookended by early and late probes in which participants performed three blocks arranged random - sequence - random. Participants were then tested for sequence knowledge without feedback 1-hour, 24-hours, and 30-days after learning. ( C ) Serial reaction time task. Participants were presented with four locations on a screen denoted by “O’s”. A trial began when one “O” changed to an “X”. Participants were instructed to press the corresponding button on a controller as fast and accurately as possible. After 800 ms, the X changed back to an O, and participants were given valenced feedback for their performance on that trial. Performance in the SRTT was based on reaction time and accuracy of the button press. If participants were accurate and faster than they performed on their previous 96 trials, a participant would receive positive feedback (reward, or absence of punishment) on that trial. If they were slower or inaccurate, they would receive the negative outcome (either punishment or absence of reward). ( D ) Force-tracking task. Participants held a force transducer in their right hand and saw a black circle (start position), a blue circle (target), and a white circle (cursor). Participants were instructed to squeeze the force transducer to keep the cursor as close to the center of the target as possible. The target moved continuously during the trial (12 seconds), followed by a 2 second break between trials. The distance of the cursor from the target was the measure of performance. If the participant was closer to the center of the target than he were on their previous 8 trials, they would receive positive feedback. During sequence blocks the target followed one of six trajectories, (D, left) whereas during random blocks the target would follow a random trajectory.

Participants were able to learn both tasks successfully and the skill learned was almost entirely retained at 30 days. Overall, we saw little effect of reward on either learning or retention. Punishment had no effect on skill retention, but had significant, task-dependent effects on learning. In the SRTT punishment improved speed with minimal impact on accuracy. In contrast, punishment impaired performance on the FTT. These results suggest that the effect of feedback varies depending on the skill being learned, and while feedback impacts online performance, the benefit of reward reported to retention may be less robust than previously demonstrated.

Punishment improves online performance of the serial reaction time task

We investigated the impact of reward and punishment on SRTT sequence learning in three different ways. First, we compared sequence knowledge during sequence knowledge probes either early in learning (immediately following familiarization when valenced feedback was first introduced) or late in learning (at the end of the training session) (see Fig. 1 ). During these probes, we estimated sequence knowledge by calculating the reaction time (RT) difference between fixed and random blocks ( Fig. 2 ). A repeated measures ANOVA, with Group (reward, punishment, control), Sequence (fixed, random) and Time-point (early, late) as factors revealed a significant three-way interaction between Group, Sequence, and Time-point (F (2,33)  = 5.370, p < 0.01). Follow-up analyses indicated that both punishment and reward groups acquired more skill knowledge during the early sequence knowledge probe than control (F (2,33)  = 5.213, p < 0.05; punishment v control: t (22)  = 3.455, p < 0.005, reward v control: t (22)  = 2.545, p < 0.02), but did not differ from each other (reward v punishment: t (22)  = 0.707, p = 0.487). Further, the control group evidenced a greater gain in sequence knowledge from the early- to late sequence knowledge probe compared to reward (t (22)  = 2.884, p < 0.01), although this comparison was not significant for control versus punishment when correcting for multiple comparisons (t (22)  = 2.075, p = 0.05), in part reflecting the benefit of feedback to early learning. These results suggest that feedback facilitates rapid sequence learning on the SRTT.

Punishment improves performance of the SRTT.

During the training period, the punishment group was significantly faster than control overall (upper inset; Main effect Group: F (2,33)  = 3.286, p < 0.05; t (22)  = 2.884, p < 0.012). There was no difference between reward and control (t (22)  = 0.480, p = 0.636) or reward and punishment (t (22)  = 1.757, p = 0.093) during the training period. The reward group showed a greater reduction in average RT from pre- to post-training than control [Group x Time point interaction: F (2,33)  = 5.370, p < 0.01; Reward v Control: t (22)  = 3.730, p < 0.001; Punishment v Control: t (22)  = 2.199, p = 0.039, not significant considering multiple comparisons (α: 0.05/3 = 0.0167)]. There was also a significant Group x Timepoint x Sequence interaction (F (2,33)  = 5.370, p < 0.01). Both punishment and reward acquired more skill knowledge during the early sequence knowledge probe than control (F (2,33)  = 5.213, p < 0.05; punishment v control: t (22)  = 3.455, p < 0.005, reward v control: t (22)  = 2.545, p < 0.02), but did not differ from each other (reward v punishment: t (22)  = 0.707, p = 0.487). The reward group evidenced less sequence learning in the post-training probe than the pre-training probe (t (22)  = 2.884, p < 0.01), possibly due to the benefit of reward during the early learning period. The punishment group did not differ from control when correcting for multiple comparisons [t (22)  = 2.075, p = 0.05 (α: 0.05/3 = 0.0167)]. Feedback did not affect retention at any time point (lower right panel). Main panel shows mean ± SEM. Box plots show median, crosses show within group outliers. Asterisks denote periods with significant effects of feedback (p < 0.05).

Second, to examine the effect of valenced feedback on learning rate, we compared the median reaction time across the six consecutive sequence training blocks immediately following the early sequence knowledge probe using a repeated measures ANOVA with Block (1–6) and Group as factors. Participants showed improvement over the course of training (Main effect of Block: F (5,33)  = 11.224, p < 0.001). We also found a main effect of Group (F (2,33)  = 3.286, p < 0.05) and follow up tests indicated that the punishment group was significantly faster than control overall (punishment versus control: t (22)  = 2.884, p < 0.012), but there was no difference between reward and control (t (22)  = 0.480, p = 0.636), or reward and punishment (t (22)  = 1.757, p = 0.093, two-tailed) during the training period. The lack of a significant Group by Sequence interaction in the post- probe highlights that this is a general, rather than sequence-specific, improvement.

Finally, we examined the impact of valenced feedback on retention. All groups demonstrated retention of sequence knowledge at all time-points (Main effect Sequence: F (1,33)  = 100.245, p < 0.001; t (35)  = 10.036, p < 0.001). There was no influence of feedback Group on retention.

Collectively, these results show that both reward and punishment increased early learning of the sequence with punishment additionally having a marked effect on performance during training.

Punishment impaired performance of the force-tracking task

We conducted the same three analyses on data from FTT ( Fig. 3A,B ). A description of the trial-by-trial performance in the FTT is available in the supplemental materials . First, sequence knowledge during the feedback period was evaluated by comparing the mean squared error during sequence and random blocks in the early and late sequence knowledge probes using repeated measures ANOVA (Time-point x Sequence x Group). There was a significant interaction between Time-point and Group (F (2,33)  = 3.526, p < 0.05), but in contrast to the SRTT, no three-way interaction with Sequence (F (2,33)  = 1.212, p = 0.310). Follow-up analyses indicated that only reward improved from pre- to post- training time-point (pre- versus post- probe, 1-sample t-test, reward: t (11)  = 4.250, p < 0.001, punishment: t (11)  = 0.100, p = 0.922, control: t (11)  = 2.292, p = 0.043 [n.s. corrected for multiple comparisons]). Punishment showed significantly less improvement than the reward group from the pre- to post- training probe (t (35)  = 2.372, p < 0.03) but was not significantly worse than control (t (35)  = 1.206, p = 0.241). There was no difference between reward and control (t (35)  = 1.688, p = 0.106). Unlike the SRTT, there was no significant Time-Point x Sequence x Group interaction, suggesting that feedback modulated general, rather than sequence-specific, learning on the FTT.

Punishment impairs to performance on the FTT.

Compared to reward, punishment impaired general performance improvement from the pre- to post- training probe (Probe x Group interaction (F (2,33)  = 3.526, p < 0.05; t (35)  = 2.372, p < 0.03). Reward was not beneficial compared to control (t (35)  = 1.688, p = 0.106. Punishment did not impair performance compared to control (t (35)  = 1.206, p = 0.241). Unlike the SRTT, feedback had no influence on sequence specific knowledge (lower left) or performance during the training period (inset). As was found in the SRTT, feedback did not affect performance during the retention probes (lower right). Main panel shows mean ± SEM. Box plots show median, crosses show within group outliers. Asterisks denote periods with significant effects of feedback (p < 0.05). One outlier from punishment in the post-training period is not pictured in the boxplot [Random – Sequence sq err. = −7 cm sq err].

Second, we examined performance during the six consecutive sequence training blocks using repeated measures ANOVA, with Block and Group as factors. All feedback groups showed improvement across the training period (Main effect of Block: F (5,165)  = 8.478, p < 0.001; S2 versus S7: t (35)  = 2.836, p < 0.01). Although reward tended to outperform punishment during training, there was no effect of Group on learning rate in the FTT (Group x Block: F (10,165)  = 1.186, p = 0.156).

Finally, we examined the effect of valenced feedback on retention in the FTT. Five participants did not complete the retention probes due to timetabling. This left us with 10 control, 9 reward, and 11 punishment participants for retention analyses. All groups demonstrated retention of sequence knowledge at all time-points (Main effect of Sequence, F (1, 27) = 86.387, p < 0.001; t (35)  = 9.030, p < 0.001). There was no main effect or interaction with feedback Group on retention.

Collectively, these results show that the primary effect of feedback in FTT was for punishment to impair learning from the pre- to post-training probe time points.

This study sought to determine whether the impact of reward and punishment generalizes across different types of motor skill learning, as implemented using a Serial Reaction Time Task (SRTT) and a Force Tracking Task (FTT). We found that punishment had opposing effects on performance of the two skills. During performance of the SRTT, training with punishment led to improved reaction times overall with minimal detriment to accuracy. In contrast, punishment impaired performance of the FTT. These effects were only present whilst feedback was being given; there was no effect of training with feedback on general or sequence-specific retention measured at 1 hour, 24 hours, and 30 days in either task. Our results refute any simple model of the interaction between feedback and performance. Instead, we show that the impact of feedback depends on the training environment and the skill being learned.

There may be a number of reasons for this task-specific effect of feedback. While both tasks rely on sequence learning, they differ with respect to the mechanism that facilitates improvement. The motivational salience of punishment (i.e. loss aversion) may explain the performance benefit seen on the SRTT, where the added attention facilitated by punishment has been hypothesized to recruit additional neural resources to aid SRTT performance 8 , 18 . However, a purely motivational account cannot explain the deleterious effect of punishment to performance on the FTT. Therefore, we need to consider alternative explanations that may account for the differential effects of reward and punishment to performance these two tasks.

The two tasks also differ with respect to their motor demands. Specifically, in our implementation, performance on the FTT relies on more precise motor control than the SRTT. Within the motor system, others have reported that reward-related dopaminergic activity reduces motor noise 19 , while dopaminergic activity associated with punishment leads to an increase in motor variability, i.e. noise 20 . We found that punishment impaired general (i.e. non sequence-specific) performance on the FTT. After one-hour, during the retention test without feedback, the punishment group performed as well as the reward and control groups. We think that our findings are consistent with the hypothesis that punishment may increase motor noise, which may have led to impaired performance by the punishment group during training. Because increased motor variability was not directly measured in our implementation of the SRTT, participants would not be penalized for any variation in movement that did not impact reaction time directly. If an assessment of motor variability was considered in the evaluation of SRTT performance, one might find that punishment impairs this dimension of performance. Our implementation of the SRTT and the FTT do not have a direct measure of motor variability and we cannot explicitly address this issue in the present study. Future work should examine this question.

The implementations of the tasks used here also differed with respect to the information content of a given instance of feedback. Ordinarily, learning on the SRTT relies on the positive prediction error encoded in the striatum that occurs on fixed-sequence trials 8 , 21 . The reward or punishment in the SRTT may augment this positive prediction error and facilitate performance and learning. In contrast, the moment-to-moment feedback given on the FTT is not associated with an instantaneous positive prediction error signal. Rather, our implementation of the FTT is similar to discontinuous motor tasks that rely on the cerebellum and may therefore not benefit from moment-to-moment feedback 22 (but also see Galea, et al. 4 for an additional account of cerebellar learning with feedback). Finally, although information content was not intentionally manipulated, this difference may also alter effect the reward and punishment on these tasks.

Unlike prior studies, we saw no benefit of reward to retention 4 , 7 , 8 , 10 . Most studies that have looked at reward and punishment in skill learning have only examined immediate recall 4 , 8 , 10 , and only one study has shown a benefit of reward to long-term retention of a motor skill 7 . In their study, Abe, et al. 7 observed that the control and punishment groups evidenced diminished performance after 30-days compared to their post-training time-point. Importantly, Abe, et al. 7 also found that the reward group showed offline gains from the immediate time point to 24-hours after training, and this effect persisted through 30-days. So, while in our study the punishment and control group did not evidence forgetting from 24-hours to 30-days, potentially limiting our sensitivity to the effect of reward, the reward group in our study also did not show any offline-gains. As such, we are confident in our finding that reward did not impact retention.

While not discussed at length by Abe and colleagues, their punishment group performed significantly worse during training, suggesting that the skill was not learned as effectively by participants in that group. Therefore, it is unclear whether the difference in memory observed in their study can be attributed to a benefit of reward to consolidation or to ineffective acquisition when training with punishment. Our study design differed from the implementation used by Abe and colleagues 7 with respect to the input device (whole-hand grip force in our study, precision pinch force by Abe and colleagues), feedback timing, and trial duration. However, our result questions robustness of the finding that reward benefits skill retention. We maximized our design to be sensitive to differences in online-learning rather than retention, and future studies should examine other factors that influence the effect of feedback on retention of skill memories.

With respect to the SRTT, it is worth considering that our participants evidenced less sequence-specific learning than some others have found in unrewarded versions of this task, where the difference between sequence and random trials can be up to 80 ms 23 , 24 , 25 . However, there is considerable variability in the difference between sequence and random trials on the SRTT reported in the literature, and some groups have reported sequence-specific learning effects on the SRTT to be between 10 and 30 ms 26 , 27 . The difference reported after learning by the Control, Reward, and Punishment groups in our study is approximately equal to the difference for the rewarded group reported by Wachter, et al. 8 (~30 ms) and more than observed in their control and punishment groups. This is evidence of substantially less sequence-specific knowledge than we observed in our study, and we are therefore confident that participants were able to learn and express sequence-specific knowledge in all three feedback conditions.

Finally, we recognize that there are difficulties in comparing performance across tasks. Because the tasks used here vary in performance outcome (response time in the SRTT, tracking error in the FTT), comparing them in a quantitative way is not possible. However, the dissociation in the effect of punishment in these contexts provides compelling evidence that the effect does depend on task. Moreover, our study brings together the previously disparate literature examining the effects of reward and punishment on skill learning. This result shines light on the challenge of extrapolating from a single experiment in a specific context to a more general account of skill learning.

Overall, we have demonstrated that punishment modulates on-line performance in a task-specific manner and in our study we found that neither reward nor punishment modulates long-term retention of skill memories. These findings cast doubt on the commonly held hypothesis that reward is ubiquitously beneficial to memory, and, suggest that the interaction between feedback and learning should be better understood before feedback can be fully exploited in clinical situations.

Materials and Methods

The study design was the same for both tasks ( Fig. 1A ). Participants trained on either the serial reaction time task (SRTT), or the force-tracking task (FTT). For both tasks, trials were presented over 15 blocks. A 30-second break (minimum) separated each block of trials. Unbeknownst to the participants, during some blocks (“fixed sequence blocks”) the stimulus would appear according to a repeating pattern (described below for each task). During other periods the appearance of the stimulus was randomly determined (“random sequence blocks”).

Familiarization and training blocks were conducted in the bore of an MRI scanner. To acclimatize participants to the task, and establish their baseline level of performance, the task began with three random-sequence blocks without feedback (“familiarization blocks”). Participants were unaware of the forthcoming feedback manipulation during these familiarization blocks. Then the feedback period began, starting with a pre-training probe (three blocks, random – fixed – random), then the training blocks (six consecutive fixed-sequence blocks), and, finally, a post-training probe (three blocks, random – fixed – random). The difference in performance between the average of the two random blocks, versus the fixed sequence block, during the probes was used to index sequence knowledge 28 .

To test the impact of reward and punishment on skill learning, participants were randomised into one of 3 feedback groups: reward, punishment, or uninformative (control). During the feedback period, reward, punishment, or control feedback was provided based on the participant’s ongoing performance. The feedback paradigm for each task is outlined separately below.

Participants were given retention probes at one-hour, 24–48 hours, and 30 days after training. No feedback was delivered during the retention probes. The second probe always occurred after at least one night’s sleep.

The initial visit (Familiarization, Early probe, Learning, and Late Probe) took place while participants underwent MRI scanning.

Participants

78 participants (47 female, mean age = 25 years ± 4.25 std.) participated in this experiment. All participants were right-handed, free from neurological disorders, and had normal or corrected-to-normal vision. All participants gave informed consent and the study was performed with National Institutes of Health Institutional Review Board approval in accordance with the Declaration of Helsinki (93-M-0170, NCT00001360). Data from six individuals were removed from the study due to inattention (defined as non-responsive or inaccurate on greater than 50% of trials during training) or inability to complete the training session.

Serial reaction time task (SRTT)

The version of the SRTT used here adds feedback to the traditional implementation. At the beginning of each block participants were presented with four “O”s, arranged in a line, at the centre of the screen. These stimuli were presented in white on a grey background ( Fig. 1B ). A trial began when one of the “O”s changed to an “X”. Participants were instructed to respond as quickly and accurately as possible, using the corresponding button, on a four-button response device held in their right hand. The “X” remained on screen for 800 ms regardless of whether the participant made a response, followed by a 200 ms fixed inter-trial interval, during which time the four “O”s were displayed.

A block consisted of 96 trials. During fixed-sequence blocks, the stimuli appeared according to a fixed 12-item sequence repeated 8 times (e.g. 3–4–1–2–3–1–4–3–2–4–2–1). Each fixed block began at a unique position within the sequence, to help prevent explicit knowledge of the sequence from developing 29 . In the random blocks, the stimuli appeared according to a randomly generated sequence, without repeats on back-to-back trials, so, for example, participants would never see the triplet 1–1–2.

Between each block, participants saw the phrase “Nice job, take a breather”. After five seconds, a black fixation-cross appeared on the screen for 25 seconds. Five seconds before the next block began, the cross turned blue to cue the participants that the block was about to start.

During the retention probes, participants performed three blocks (random – fixed – random on a 15-inch Macbook Pro using a button box identical to the one used during training. During these retention probes, the next trial began 200 ms after the participant initiated their response. No feedback was given during the retention blocks. The first button press made after stimulus presentation was considered the participant’s response. All responses were included in the analysis. Any missed trial was counted as an error, and only correct trials were considered for analysis of RTs.

Force-tracking task

In the force-tracking task (FTT), participants continuously modulated their grip force to match a target force output 16 , 17 . In the traditional implementation, participants are exposed to a single pattern of force modulation repeated each trial. This design does not allow discrimination between general improvement (i.e. familiarization with the task and/or the force transducer) and improvement specific to the trained sequence of force modulation. Therefore, we decided to adapt the traditional FTT method to align it with the experimental design that is traditional for the SRTT, i.e. by including random sequence blocks.

A given trial consisted of a 14 second continuous pattern of grip modulation. At the beginning of a trial, participants were presented with three circles on a grey background projected onto a screen: a white circle (Cursor, 0.5 cm diameter), a blue circle (Target, 1.5 cm diameter), and a black circle (bottom of the screen, 2 cm diameter, indicating the position corresponding to minimum pressure; Fig. 1C ). Participants held the force transducer (Current Designs, Inc., Philadelphia, PA) in the right hand between the four fingers and palm ( Fig. 1D , right). Participants were instructed to squeeze the force transducer (increasing force moving the cursor upwards) to keep the cursor as close to the center of the target as possible as the target moved vertically on the screen. During fixed blocks, participants were randomly assigned to one of six sequences ( Fig. 1D , left). During random blocks, the target followed a trajectory generated by the linear combination of four waveforms, with periods between 0.01 and 3 Hz. These waveforms were constrained to have identical average amplitude (target height), and the number and value of local maxima and minima were constant across the random blocks.

For data analysis, the squared distance from the cursor to the target was calculated at each frame refresh (60 Hz). The first 10 frames were removed from each trial. The mean of the remaining time points was calculated to determine performance, and trials were averaged across blocks.

All participants were paid a base remuneration of $80 for participating in the study. At the start of the feedback period, participants were informed they could earn more money based on their performance.

During the feedback period, participants were given either reward, punishment, or control feedback. The presence of reward or the absence of punishment was based on participant’s performance. In both the SRTT and the FTT, an initial criterion was defined, based on the participant’s median performance during the final familiarization block. As participants progressed through training, this criterion was re-evaluated after each block, to encourage continuous improvement. In the reward group, the feedback indicated that the participant’s performance was getting better at the task. In the punishment group, the feedback indicated they were getting worse. Because the frequency of feedback events differed between the reward and punishment groups (reward from high-to-low as training progressed, punishment from low-to-high), the control group was split into two different sub-groups (control-reward and control-punishment). The control groups received feedback at a frequency that matched the corresponding feedback group but was not related to their performance. Participants in the control group were made aware that the feedback was not meaningful. We considered the reward and punishment control groups together in the analyses, as is typical in these studies 7 , 8 .

In the SRTT, performance was defined as the accuracy (correct or incorrect) and reaction time (RT) of a given trial. Feedback was given on a trial-by-trial basis ( Fig. 1C ). This was indicated to the participant when the white frame around the stimulus changed to green (reward) or red (punishment). In the reward group, the participants were given feedback if their response was accurate and their RT was faster than their criterion RT, which indicated that they earned money ($0.05 from a starting point of $0) on that trial. In the punishment group, participants were given feedback if they were incorrect, or their RT was slower than their criterion, which indicated that they lost money ($0.05 deducted from a starting point of $55) on that trial. Participants in the control-reward and control-punishment groups saw red or green colour changes, respectively, at a frequency matched to punishment and reward, respectively. Control participants were told that they would be paid based on their speed and accuracy. Importantly, to control for the motivational differences between gain and loss, participants were not told the precise value of a given trial. This allowed us to assess the hedonic value of the feedback, rather than the level on a perceived-value function. Between blocks, for the reward and punishment groups, the current earning total was displayed (e.g. “You have earned $5.00”). Control participants saw the phrase, “You have earned money”. The criterion RT was calculated as median performance in the first familiarization block. After each block, the median + standard deviation of performance was calculated, and compared with the criterion. If this test criterion was faster (SRTT) or more accurate (FTT) than the previous criterion, the criterion was updated. During the SRTT, only the correct responses were considered when establishing the criterion reaction time.

Feedback in the FTT was based on the distance of the cursor from the target ( Fig. 1C ). For the reward group, participants began with $0. As participants performed the task, their cursor turned from white to green when the distance from the target was less than their criterion. This indicated that they were gaining money at that time. In the punishment group, participants began with $45, and the cursor turned red if it was outside their criterion distance. This indicated that they were losing money. For reward-control and punishment control, the cursor changed to green or red, respectively, but was unrelated to their performance. For control, the duration of each feedback instance, as well as cumulative feedback given on each trial, was matched to the appropriate group. Between each block, participants were shown their cumulative earnings. Control participants saw the phrase “You have money”.

Statistical analyses

In both tasks, the six training blocks were compared using a repeated-measures ANOVA to establish differences in learning rate (Block x Group). Learning was indexed by comparing the performance (RT and accuracy separately for SRTT; squared distance from the target [squared error] for FTT) on the sequence blocks to the average of the two random blocks at the pre and post training time points using a repeated-measures ANOVA (Time point x Sequence x Group). Memory for the sequence was evaluated by comparing the fixed block, to the mean of the two random blocks, at each retention time point using a repeated-measures ANOVA (Time point x Sequence x Group). A Bonferroni correction was applied for post-hoc analyses to correct for multiple comparisons. If sphericity was violated, the Hyunh-Feldt correction was applied.

Additional Information

How to cite this article : Steel, A. et al. The impact of reward and punishment on skill learning depends on task demands. Sci. Rep. 6 , 36056; doi: 10.1038/srep36056 (2016).

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Maddox, W. T., Ashby, F. G. & Bohil, C. J. Delayed feedback effects on rule-based and information-integration category learning. Journal of experimental psychology. Learning, memory, and cognition 29, 650–662 (2003).

Article   PubMed   Google Scholar  

Frank, M. J. Dynamic dopamine modulation in the basal ganglia: a neurocomputational account of cognitive deficits in medicated and nonmedicated Parkinsonism. Journal of cognitive neuroscience 17, 51–72, doi: 10.1162/0898929052880093 (2005).

Freedberg, M., Glass, B., Filoteo, J. V., Hazeltine, E. & Maddox, W. T. Comparing the effects of positive and negative feedback in information-integration category learning. Memory & cognition, doi: 10.3758/s13421-016-0638-3 (2016).

Galea, J. M., Mallia, E., Rothwell, J. & Diedrichsen, J. The dissociable effects of punishment and reward on motor learning. Nature neuroscience 18, 597–602, doi: 10.1038/nn.3956 (2015).

Article   CAS   PubMed   Google Scholar  

Gajda, K., Sulzenbruck, S. & Heuer, H. Financial incentives enhance adaptation to a sensorimotor transformation. Experimental brain research, doi: 10.1007/s00221-016-4688-3 (2016).

Hasson, C. J., Manczurowsky, J. & Yen, S. C. A reinforcement learning approach to gait training improves retention. Front Hum Neurosci 9, 459, doi: 10.3389/fnhum.2015.00459 (2015).

Article   PubMed   PubMed Central   Google Scholar  

Abe, M. et al. Reward Improves Long-Term Retention of a Motor Memory through Induction of Offline Memory Gains. Curr Biol 21, 557–562, doi: 10.1016/j.cub.2011.02.030 (2011).

Article   CAS   PubMed   PubMed Central   Google Scholar  

Wachter, T., Lungu, O. V., Liu, T., Willingham, D. T. & Ashe, J. Differential effect of reward and punishment on procedural learning. The Journal of neuroscience: the official journal of the Society for Neuroscience 29, 436–443, doi: 10.1523/JNEUROSCI.4132-08.2009 (2009).

Article   CAS   Google Scholar  

van der Kooij, K. & Overvliet, K. E. Rewarding imperfect motor performance reduces adaptive changes. Experimental brain research 234, 1441–1450, doi: 10.1007/s00221-015-4540-1 (2016).

Wilkinson, L. et al. Online feedback enhances early consolidation of motor sequence learning and reverses recall deficit from transcranial stimulation of motor cortex. Cortex; a journal devoted to the study of the nervous system and behavior 71, 134–147, doi: 10.1016/j.cortex.2015.06.012 (2015).

Therrien, A. S., Wolpert, D. M. & Bastian, A. J. Effective reinforcement learning following cerebellar damage requires a balance between exploration and motor noise. Brain 139, 101–114, doi: 10.1093/brain/awv329 (2016).

Censor, N., Sagi, D. & Cohen, L. G. Common mechanisms of human perceptual and motor learning. Nature reviews. Neuroscience 13, 658–664, doi: 10.1038/nrn3315 (2012).

Dayan, E. & Cohen, L. G. Neuroplasticity subserving motor skill learning. Neuron 72, 443–454, doi: 10.1016/j.neuron.2011.10.008 (2011).

Nissen, M. J. & Bullemer, P. Attentional Requirements of Learning - Evidence from Performance-Measures. Cognitive Psychol 19, 1–32, doi: Doi 10.1016/0010-0285(87)90002-8 (1987).

Article   Google Scholar  

Floyer-Lea, A. & Matthews, P. M. Changing brain networks for visuomotor control with increased movement automaticity. J Neurophysiol 92, 2405–2412, doi: 10.1152/jn.01092.2003 (2004).

Floyer-Lea, A. & Matthews, P. M. Distinguishable brain activation networks for short- and long-term motor skill learning. J Neurophysiol 94, 512–518, doi: 10.1152/jn.00717.2004 (2005).

Floyer-Lea, A., Wylezinska, M., Kincses, T. & Matthews, P. M. Rapid modulation of GABA concentration in human sensorimotor cortex during motor learning. J Neurophysiol 95, 1639–1644, doi: 10.1152/jn.00346.2005 (2006).

Tversky, A. & Kahneman, D. The framing of decisions and the psychology of choice. Science 211, 453–458 (1981).

Article   CAS   ADS   MathSciNet   MATH   PubMed   Google Scholar  

Manohar, S. G. et al. Reward Pays the Cost of Noise Reduction in Motor and Cognitive Control. Curr Biol 25, 1707–1716, doi: 10.1016/j.cub.2015.05.038 (2015).

Galea, J. M., Ruge, D., Buijink, A., Bestmann, S. & Rothwell, J. C. Punishment-induced behavioral and neurophysiological variability reveals dopamine-dependent selection of kinematic movement parameters. The Journal of neuroscience: the official journal of the Society for Neuroscience 33, 3981–3988, doi: 10.1523/JNEUROSCI.1294-12.2013 (2013).

Wilkinson, L., Khan, Z. & Jahanshahi, M. The role of the basal ganglia and its cortical connections in sequence learning: evidence from implicit and explicit sequence learning in Parkinson’s disease. Neuropsychologia 47, 2564–2573, doi: 10.1016/j.neuropsychologia.2009.05.003 (2009).

Spencer, R. M., Zelaznik, H. N., Diedrichsen, J. & Ivry, R. B. Disrupted timing of discontinuous but not continuous movements by cerebellar lesions. Science 300, 1437–1439, doi: 10.1126/science.1083661 (2003).

Article   CAS   ADS   PubMed   Google Scholar  

Robertson, E. M., Pascual-Leone, A. & Press, D. Z. Awareness modifies the skill-learning benefits of sleep. Curr Biol 14, 208–212, doi: 10.1016/j.cub.2004.01.027 (2004).

Tunovic, S., Press, D. Z. & Robertson, E. M. A physiological signal that prevents motor skill improvements during consolidation. The Journal of neuroscience: the official journal of the Society for Neuroscience 34, 5302–5310, doi: 10.1523/JNEUROSCI.3497-13.2014 (2014).

Shanks, D. R., Wilkinson, L. & Channon, S. Relationship between priming and recognition in deterministic and probabilistic sequence learning. Journal of experimental psychology. Learning, memory, and cognition 29, 248–261 (2003).

Witt, J. K., Ashe, J. & Willingham, D. T. An egocentric frame of reference in implicit motor sequence learning. Psychological research 72, 542–552, doi: 10.1007/s00426-007-0129-z (2008).

Song, S. & Cohen, L. G. Practice and sleep form different aspects of skill. Nature communications 5, 3407, doi: 10.1038/ncomms4407 (2014).

Robertson, E. M. The serial reaction time task: implicit motor skill learning? The Journal of neuroscience: the official journal of the Society for Neuroscience 27, 10073–10075, doi: 10.1523/JNEUROSCI.2747-07.2007 (2007).

Schendan, H. E., Searl, M. M., Melrose, R. J. & Stern, C. E. An FMRI study of the role of the medial temporal lobe in implicit and explicit sequence learning. Neuron 37, 1013–1025 (2003).

Download references

Acknowledgements

C.I.B. and A.D.S. are funded by NIH intramural program number ZIA MH002893-10. C.J.S. is funded by the Wellcome Trust and the Royal Society 102584/Z/13/Z.

Author information

Stagg Charlotte J. and Baker Chris I. jointly supervised this work.

Authors and Affiliations

Nuffield Department of Clinical Neurosciences, FMRIB Centre, University of Oxford, Oxford, UK

Adam Steel & Charlotte J. Stagg

Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, 20814, MD, USA

Adam Steel, Edward H. Silson & Chris I. Baker

University Department of Psychiatry, Oxford Centre for Human Brain Activity (OHBA), University of Oxford, Oxford, UK

• Charlotte J. Stagg

You can also search for this author in PubMed   Google Scholar

Contributions

A.S., C.J.S. and C.I.B. designed the experiment. A.S. and E.H.S. collected the data. A.S. analyzed the data. A.S., C.J.S. and C.I.B. wrote the paper. All authors reviewed the manuscript.

Ethics declarations

Competing interests.

The authors declare no competing financial interests.

Electronic supplementary material

Supplementary information, rights and permissions.

This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Reprints and permissions

About this article

Cite this article.

Steel, A., Silson, E., Stagg, C. et al. The impact of reward and punishment on skill learning depends on task demands. Sci Rep 6 , 36056 (2016). https://doi.org/10.1038/srep36056

Download citation

Received : 15 July 2016

Accepted : 11 October 2016

Published : 27 October 2016

DOI : https://doi.org/10.1038/srep36056

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

This article is cited by

• Tyler J. Adkins
• Bradley S. Gary
• Taraz G. Lee

Scientific Reports (2021)

• Chris I. Baker

Scientific Reports (2020)

Correcting for natural visuo-proprioceptive matching errors based on reward as opposed to error feedback does not lead to higher retention

• Irene A. Kuling
• Anouk J. de Brouwer
• J. Randall Flanagan

Experimental Brain Research (2019)

Probability differently modulating the effects of reward and punishment on visuomotor adaptation

• Yanlong Song
• Ann L. Smiley-Oyen

Experimental Brain Research (2017)

By submitting a comment you agree to abide by our Terms and Community Guidelines . If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

• NAEYC Login
• Member Profile
• Hello Community
• Accreditation Portal
• Online Learning
• Online Store

Popular Searches:   DAP ;  Coping with COVID-19 ;  E-books ;  Anti-Bias Education ;  Online Store

Instead of Discipline, Use Guidance

You are here

We all know that we shouldn’t punish young children when they exhibit challenging behaviors. The children in our preschool classrooms are just beginning to learn the complex skills of getting along with others. These are skills that we humans work on our entire lives.

Children are going to have disagreements—sometimes dramatic ones—as they interact with others. They really don’t “know better” because they haven’t learned the “better” yet. After all, a 4-year-old has only 48 months of on-the-ground experience! It’s our job to teach children positive lessons from their mistakes—and to make sure we don’t hold their mistakes against them.

Conventional discipline too easily slides into punishment. For example, if we embarrass children by singling them out as part of our discipline strategy, this is punishment. Punishment makes young children feel stressed, hurt, rejected, and angry; these feelings make it harder for children to learn emotional and social skills.

When we punish children, we are actually making life more difficult for

• the child, who feels rejected and unworthy and becomes more challenged in learning social skills
• other children who worry for themselves and the punished child
• adults who are not being the leaders they want to be

Using guidance

Guidance is about building an encouraging setting for every person in the group. It means helping young children understand they can learn from their mistakes, and it starts with showing them how. To give this help successfully, we need to build relationships with every child—especially with the children we find difficult to connect with and understand. We build these relationships from day one, outside of conflict situations. It is only when children know and trust us in day-to-day interactions that they will listen to us when conflicts happen (after we have helped everyone calm down).

So what do you do when conflicts arise and you want to use guidance? This article gives two illustrations of guidance at work. The first one might surprise you.

Illustration 1: Jeremiah comes through

This example comes from former preschool teacher Beth Wallace.

When I first started working with Jeremiah, he had a lot of angry outbursts. The center used time-out at that point (the dreaded “green chair”), and Jeremiah spent considerable time there. While I was at the center, we moved away from using time-outs and introduced a system called peer problem-solving. By the time Jeremiah graduated to kindergarten, we had been using the system for three years, and he was one of the experts.

One day, I overheard a fracas in the block corner. I stood up to see what was going on, ready to intervene. Jordan, just 26 months old and only talking a little bit, had a truck. Franklin, 50 months old, decided it was his turn to use the truck. I took a step forward, ready to go to their aid, but paused when I saw Jeremiah (then 60 months old) approach them.

“What’s going on, guys?” Jeremiah asked (my standard opening line). He then facilitated a five-minute discussion between the two children. He made sure both got a chance to speak, interpreting for the little one. “Jordan, what do you think of that idea?” he asked. Jordan shook his head and clutched the truck tighter. “I don’t think Jordan’s ready to give up the truck yet,” Jeremiah told Franklin.

After helping his classmates negotiate an agreement, Jeremiah’s competence was without question, and his pride was evident.

On this day, Beth knew that three years of building relationships and teaching children how to resolve their conflicts through mediation was paying off.

Illustration 2: Playdough politics

In preschool, three common sources of conflicts are property, territory, and privilege. The following illustration is a combination of dozens of property-related conflicts I have worked with teachers to address. I put a magnifying glass to this one so you can see up close what guidance is and isn’t, and how it teaches young children to learn from mistaken behavior.

Jason, age 42 months, is the only one at the playdough table. He gets a grin on his face and pulls the whole chunk of dough in front of him. He starts working the dough and mutters, “Makin’ a dinosaur nest and eggs.”

Daeisha, age 52 months, sits at the table and sees Jason has all the dough. She says, “Hey, give me some!” Jason hands Daeisha a tiny bit and circles his arms around the big mound. Daeisha responds by grabbing a large handful of dough out from under Jason’s arm. Jason screams. When he tries to grab the dough back, Daeisha pushes him and starts kneading the playdough. Teacher Kris sees Jason on the floor, yowling, and Daeisha using playdough as if nothing has happened.

Pause for a few minutes to think about how you would address this situation. Then read on to consider two possible intervention choices.

Conventional discipline: Kris walks over to Daeisha, stands above her, and says loudly, “You’ve taken something from another person again, Daeisha. You need to sit on the time-out chair so you will remember how to share.” Kris takes Daeisha to the chair.

Daeisha is not thinking, “I am glad the teacher has temporarily prevented me from playing. Now I will be a better child and use friendly words instead of forcing my will on others.” Instead, Daeisha is embarrassed, hurt, and angry. She feels rejected by Kris and unwelcome in the group. Daeisha is thinking how to get back at Jason.

Guidance: Kris moves between the two children, kneels down, and takes the following five firm, friendly actions . Kris

1. Describes the scene. “I see Jason on the floor very upset. I see Daeisha using a big bunch of playdough. We need to solve this problem.”

2. Calms who needs calming. “Jason, we need to help you cool down so we can make this better. Let’s get you back on the chair.” Taking the playdough, Kris looks at Daeisha and says to both children, “I will hold the playdough. Take some deep breaths or just close your eyes to get calm.”

3. Leads each child to describe the conflict, often starting with the younger child.

Kris: Jason, what do you think happened?

Jason: I was making a dinosaur nest and Daeisha took my playdough!

Kris: Anything else?

Jason: I gave her some, but she still took mine.

Kris: Daeisha, what do you think happened?

Daeisha: He had all the playdough and just shared a little. So I took some so I could play too.

Jason: Daeisha had some. (He points to the little glob he gave her.)

Kris: Let’s let Daeisha finish.

Daeisha: I needed more to play, so I took it.

Kris: Let’s see, is this right? Jason, you were making a big nest with the playdough. Daeisha came and didn’t have any. Jason gave Daeisha some. Daeisha, you didn’t have enough, so you took more so you could play too?

Both children nod, which assures Kris that they both feel like they have been heard and are ready to move forward.

4. Solves the problem with the children—not for them.

Kris: So how can we fix this so you can both play?

Daeisha: He can share more.

Jason: But not too much.

Kris sets the playdough in front of Jason. Jason gives Daeisha a bit more. Daeisha and Kris both look at Jason. He grimaces but hands over enough to satisfy the other two.

Kris: Thank you, Jason. Can you still make a dinosaur nest or maybe just an eagle nest?

Jason: A littler dinosaur nest.

Kris: Daeisha, Jason was on the floor and he was upset. He has given you more playdough. Seems like you need to do something here to make things better. (Instead of forcing Daeisha to apologize, Kris guides the child to think about what would make Jason feel better.)

Daeisha: Thank you, Jason. Sorry. Can I make you some eggs?

Jason: Yeah, a whole bunch.

5. Follows up with one or both children by having a guidance talk Sitting next to Daeisha, Kris thanks her for helping to solve the problem and talks with her about what to do next time so no one is hurt. They agree that if a classmate won’t share, Daeisha will ask a teacher for help.

Although guidance may seem time-consuming, a scene like this can play out in just five minutes. If you truly do not have time to engage in all five steps at that moment, do steps 1 and 2 right away and tell the children when you will get together to finish the mediation. Don’t forget! If the problem is no longer a big deal to both children when you get together, skip to step 5 for a guidance talk. Help each child learn how to get along better next time.

Seeing the value of guidance

Why is guidance well worth the time it takes? Here are four reasons.

First, the teacher does not make one child seem like a perpetrator and the other seem like a victim. Adults can actually start bully-victim patterns if they consistently comfort the “helpless” victim and punish the “guilty” perpetrator. Kris handled this situation so both children felt they were worthy individuals who belonged in the class and were capable of solving their problems and of learning from their mistakes.

Second, Kris worked with Daeisha. Children who have the boldness to take things from others most often also have the individual strength to become leaders who can work cooperatively with others (like Jeremiah), if we support them in developing their emotional and social skills. This change requires belief in the child and firm, friendly, and consistent guidance (with an emphasis on the friendly).

Third, every use of guidance provides powerful lessons in language arts and social studies. Children who learn to put strong emotions into non-hurtful words gain vocabulary and communication skills that serve them well for their entire lives. Children who learn the social studies lessons of overcoming differences and solving problems together are gaining democratic life skills.

Finally, every time members of an encouraging classroom see guidance at work, children and adults together learn the vital lesson that everyone is a worthy individual, belongs in the group, and can participate in solving problems. For all of us, this is important learning for making our democracy “more perfect.”

Closing thoughts

Guidance should not be thought of as a weak alternative to traditional discipline—it’s being a good coach who doesn’t give up on any member of the team. Your efforts at guidance don’t have to be perfect, but if you persist and reflect, you will get good results. Like Beth and Kris, we learn even as we teach. Do these things and you will feel positively about yourself as a teacher—and that will help with the inner calm you need to guide children toward healthy emotional and social skills.

Photographs: © Getty Images

Dan Gartrell,  EdD, is a former Head Start teacher for the Red Lake Band of Ojibwe in northern Minnesota. During the 1970s, Dan completed his master’s degree at Bemidji State University in northern Minnesota, where he was a CDA (Child Development Associate) credential adviser for the Child Development Training Program. Dan received his EdD from the University of North Dakota in 1977. For 40 years, Dan was director of the Child Development Training Program and professor of early childhood education at Bemidji State University. He is now a professor emeritus. To learn more, visit www.dangartrell.net .

Vol. 13, No. 3

Print this article

Punishment in Education

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• J Environ Public Health
• v.2022; 2022

This article has been retracted.

Educational reward and punishment and the effect of psychological intervention on adolescent depression, wensheng wu.

1 Jing Hengyi, School of Education, HangZhou Normal University, HangZhou, Zhejiang 311121, China

2 Ginco Inc., Tokyo 104-0032, Japan

Associated Data

The data used to support the findings of this study are available from the corresponding author upon request.

Teenage depression, also known as TD, is a common mental illness that is characterized by symptoms such as hopelessness, helplessness, pessimism, depression, and decreased energy. It has always been a hot topic to discuss how rewards and punishments work in education. In order to prevent and treat adolescent depression, this study examines the mechanisms of educational reinforcement and punishment as well as psychological interventions. In this study, the activated brain regions are analyzed using data mining (DM) technology to determine whether they are significantly more or less active than the rest of the brain of students who are not experiencing negative emotions. When the word vector has 90 dimensions, the results demonstrate that the average F 1 value of the weighted word vector method is 81.3 percent. It has been established that the approach taken in this work offers a reliable way to diagnose TD.

1. Introduction

Reward and punishment have always played a significant role in teacher preparation and classroom instruction. How to use rewards and punishments reasonably has become a very important topic as a result of the passage of time, the evolution of history, and the ongoing reinterpretation of educational concepts. The behavioral allocation of behaviors can be known and understood scientifically thanks to the behaviorism theory in psychology's research findings. Giving students excessive rewards will therefore lead to psychological dependence. Rewards that are not necessary will reduce students' intrinsic motivation to learn. Students who lack or lack intrinsic motivation for learning can be encouraged with external rewards so they can develop that motivation. According to studies, 65 percent of adolescents experience one or more major depressive episodes at some point in their lives [ 1 ]. Depression is the main risk factor for teen suicide [ 2 ]. Adolescence is when most patients experience their first depressive episode. As a result, TD (Teen Depression) started to show up in medical professionals' clinical diagnoses, and its use in treating children and adolescents has gained widespread acceptance.

At present, the direct goal of depression intervention research is to reduce and eliminate adolescents' depression experience, but the prevention of depression is seldom considered. This study focuses on the intervention of school sense of belonging, which can promote the generation of positive emotions, and explore whether its influence on depression is mediated by neurotic personality traits, so as to provide more information for preventing adolescent depression to a greater extent. The necessity and possibility of punishment in the field of education, the educational purpose pursued by punishment, and the effectiveness of punishment as an educational means. The incidence of TD is high and the prognosis is poor, but the cause of depression has not been fully clarified. It is generally believed that it is the result of the interaction of biological, psychological, and social factors. Kessler et al. found that positive coping is a common influencing factor of depression and anxiety, and positive coping has a protective effect on depression and anxiety [ 3 ]. Mcpeak et al.' s research on adolescent patients with mental illness also found that people with high menstrual quality have a tendency to develop spermatic diseases [ 4 ]. Related studies have found that adolescents with childhood trauma experience are more likely to have emotional and behavioral problems such as anxiety, suicidal ideation, drug abuse, self-harm, and aggressive behavior [ 5 ].

With the continuous development of the times, the growth and development of teenagers in our country are changing into a long-term trend, the age of puberty development is constantly advancing, the rapid physical and mental changes experienced by individuals, childhood stress events, external pressure and the relative lack of effective psychological adjustment methods will further lead to the development of mental disorders such as depression. Reward helps to reinforce correct behavior. Behaviorists believe that reinforcement is divided into positive and negative. Both positive reinforcement and negative reinforcement are rewards for increasing the probability of target behavior, thus consolidating behavior. Students are also rewarded to cultivate self-confidence, self-improvement, and positive enterprising belief. This study attempts to systematically investigate the evolution of the recognition of rewards and punishments in education, reveal the various influences of rewards and punishments on students' psychology and behavior, and put forward the principles and countermeasures of rational application of rewards and punishments in practice.

The research contribution of this study:

• At present, there are few research results on depression prevention, and there are few studies on neuroticism, an important personality factor, and there is a lack of individual differences in the intervention effect of depression. Combining these two factors that have important influence on depression, this study supplements the theoretical research in this field and provides some theoretical background and guidance.
• The psychological well-being of people has changed dramatically over time, particularly that of modern teenagers, as society and science and technology have developed and advanced continuously. Exploring the causes of adolescent negative emotions and deriving patterns of brain activity from psychological issues are now crucial research areas. The psychological data of teenagers is analyzed and extracted using DM technology, and a structural model is built using the appropriate DM algorithms. Potential clusters are then identified.

2. Related Work

2.1. a correlation study on the influencing factors of td.

Depression is a mental illness with depression as its main symptom, which is caused by many reasons. It is a common disease that easily recurs, and can lead to mental disability and suicide. The pathogenesis of TD is still unclear, and many factors are at work, including biological, psychological, and social factors. At present, the treatment of TD tends to be the comprehensive treatment of drugs and psychotherapy.

Freitas et al. summarized stress as events that affect the mental or physical health of individuals of a certain age in a specific social environment, and these events play a very important role in the pathogenesis of TD [ 6 ]. Merry et al. found that stressful life events, as the most important stressor, are positively related to suicidal ideation [ 7 ]. Dalen et al. think that, compared with the normal control group, negative life events such as low socioeconomic status and unsound families are all related to depression [ 8 ]. Podeszwa et al. found that positive thinking was related to the improvement of depressive symptoms, and its effect was significantly higher than that of the control group. Therefore, both negative thinking and positive thinking are related to depression. Positive thinking can alleviate depression, while negative thinking leads to depression [ 9 ].

With the increase and deepening of research, people have discovered the protective factors that can promote disadvantaged children to achieve good development results, and put forward the concept of “resilience.” Jebeile et al. believe that environmental risk factors and protective factors independently influence individual development results, with protective factors playing a positive role, risk factors playing a negative role, and protective factors and risk factors having no effect on each other [ 10 ]. Sansom-Daly et al.' s research shows that nearly 91% of people with depressive disorder have experienced stress events before their illness, and adolescents have experienced stress events before the onset, recurrence, and symptom deterioration of depression [ 11 ]. The results of Brown et al. show that adolescent depression often happens together with other psychological and behavioral problems, among which the comorbidity rate with anxiety is the highest and the two are closely related, which further aggravates its harm to adolescents [ 12 ]. Cox et al. pointed out that the occurrence and development of depression are closely related to stress events, and there is a dose-response relationship between stress intensity and depression degree. However, not all individuals who encounter stressful events will suffer from depression [ 13 ].

2.2. Research Status of DM Technology

In order to extract more useful knowledge and potential structural models from a large amount of psychological data, it is necessary to combine the characteristics of psychological data and related algorithms in DM(data mining) technology for research. There are two main aspects, one is from the algorithm with structural characteristics, and the other is from the algorithm that can find potential aggregation.

Kahalnik et al. applied the Bayesian network to the analysis of primary liver cirrhosis and tested their hypothesis with a 95% confidence level [ 14 ]. Robles et al. assume that all points in a given cluster family obey the same probability distribution, and the objects in the data set are determined according to the highest probability value belonging to the distribution, which is also a highly organized clustering technique [ 15 ]. Frownfelter et al. proposed an improved algorithm, which is an extreme measure of the tree structure. Algorithms combined with clustering have been widely studied in recent years, but algorithms combined with hierarchical clustering are rare [ 16 ]. Modarres et al. combined fuzzy similarity matrix with hierarchical clustering and proposed an improved algorithm to make the aggregation faster [ 17 ]. Subspace clustering is an extension of the traditional clustering algorithm, which tries to find groups of different subspaces in the data set.

In natural language processing, emotion analysis is a popular area of study. The main concept behind it is to analyze a text, draw out the emotional information contained therein, and then use that information to categorize texts or sentences and divide emotional polarity. Hobden et al. classified documents using the NB (Naive Bayes) method after building a feature vector space model based on the feature words from the training set text [ 18 ]. In order to perform a regression analysis using the data in accordance with the statistical information, Saxena et al. collected data from Twitter on patients who had and did not have depression [ 19 ]. They then used the least square method to do so. In order to predict the behavioral characteristics of 45 users' mental health status, Cole et al. used multi-task regression learning. In order to examine the internal relationships between depression and anxiety, they used multi-task regression and correlation coefficient methods [ 20 ]. Pain uses a backpropagation neural network (BPNN) to classify 147 severe TD using features selected by a genetic algorithm (GA) (Genetic Algorithm) with an accuracy rate of 89.12 percent [ 21 ].

3. Methodology

3.1. an analysis of educational reward and disciplinary intervention of adolescent depression.

Rewards can have both favorable and unfavorable effects. The benefit of rewards is that they can satisfy needs, give people a sense of success, encourage students to reach their full potential, and pursue new objectives, all of which contribute to the development of positive relationships between teachers and students. As a result, there are some conditions we must meet when using rewards in education. In addition to material rewards, we must prioritize spiritual rewards. Awards, not materials or other extras, should be used to recognize students' abilities directly. This type of discipline can help students recognize their errors, rather than harboring teacher resentment, and correct them quickly, which is very advantageous to teachers' practical service in management and educational practice. Only when rewards and penalties are applied promptly can they have the desired impact. Students who engage in inappropriate behavior are subject to discipline, not those who engage in appropriate behavior. It cannot directly increase the frequency of appropriate student behavior; it can only decrease the frequency of inappropriate student behavior. Negative feelings can also result from punishment. For instance, fear of punishment will ruin students' learning moods and lower their learning effectiveness. Discipline should only be used when absolutely necessary. Even when discipline is used, it serves to first temporarily stop undesirable behavior and then reward good behavior.

A large number of experiments in behavioral psychology show that whether in animals or people, the rewarded reaction or behavior will increase the possibility of its occurrence in the future. This situation can be observed in school situations. Students who are often praised are more likely to lose motivation than other students when they are not praised. Therefore, punishment can only play a role in overcoming bad behaviors when it signals appropriate or correct behaviors and punishes incorrect choices or behaviors.

It is one of the predictors of depression. Neuroticism is the source of negative emotions, which is characterized by emotional instability. Individuals are emotionally unstable due to excessive attention and sensitivity to negative and negative events. This personality trait often leads to psychopathological problems such as depression. In a large number of studies on depression, researchers have noticed that for some people, even in the face of great difficulties and great pressure, they are not necessarily depressed; In this model, risk factors are usually stronger than protective factors.

Natural language processing is the mathematical modeling of human language, which converts words into mathematical forms that can be recognized and processed by computers. The n − gram model assumes that the probability of the current word is related to the first n − 1 words, but not to the following words [ 21 ]. Therefore, the simplified language model of this model can be expressed as:

When different numbers of nn are taken, different language models can be obtained, such as the univariate model for n =1, binary model for n =2, and ternary model for n =3.

There are many methods of distributed word vector representation, such as word vector representation in matrix form, word vector representation in cluster form, and word vector representation in neural network training [ 18 ]. At present, it has become a trend to use neural network training to obtain word vectors, which can make full use of the context information of words. The vectors of n − 1 words are spliced, and the spliced vectors are used for hidden layer input. The hidden layer calculation formula is as follows:

b is the bias term, and H is the weight matrix of the hidden layer. In this study, the author uses the hyperbolic function tanh.

The correlation between feature sets will increase with the increase of the correlation coefficient between features and categories, and decrease with the increase of correlation coefficient between features. The formula is:

Merit s is a heuristic index of feature subset S with k feature items, namely correlation coefficient, r c f ¯ is the average of correlation coefficients between features and classes, and r f f ¯ is the average of correlation coefficients between features.

SEM (Structural equation model) is the most important tool to measure the relationship between potential variables by analyzing and using several related observable indicators. In traditional SEM, these two components are average regression models, so they are easily affected by outliers or non-normality in response distribution. SEM's hypothetical model of depression established three variables: environment, stress, and self-quality.

According to our hypothesis, depression is an endogenous variable, while environment, stress, and personal quality are exogenous variables. Analyze the influence of stress on depression, which is affected by environment and self-quality, as shown in Figure 1 below.

Hypothetical model of depression.

If you encounter psychological and social factors from family, school, and society, if you do not get help from others in time, you cannot solve them yourself and it is easy to cause depression and anxiety due to psychological imbalance. The occurrence of TD is not only related to gender and age, but also to bad cognitive behavior. Comprehensive treatment can improve patients' medication compliance, and depression-related symptoms are relieved more obviously at the end of treatment. Cognitive therapy combined with drug therapy can quickly relieve depression-related symptoms in the early stage of treatment intervention.

3.2. DM Clustering of Adolescent Depression

The meaning of punishment and criticism is that punishment is not simply suppressing the punished behavior. The reaction in the case of reward and light punishment is often more difficult to calm than that in the case of reward alone. Cognitive psychologists use the results of animal experiments to explain the design of human behavior to behaviorists. They strongly criticize that human behavior is not a simple connection between stimulus and response, and external stimuli must be perceived and explained by individuals to have an impact on individual responses. It plays a dual role in strengthening and consolidating behavior and stimulating sports.

In education, we can use punishment, but we should use it carefully. When being punished, teachers should express their unwillingness but helplessness. After being punished, they should help students in time to avoid causing physical and mental harm to students. The purpose of teacher's punishment is to eliminate some improper behaviors of students, but students may associate such behaviors with situations and people. Simply rewarding the students' union leads to the students only accepting rewards and lacking the courage to face setbacks. On the contrary, if only punishment is given without reward, students' self-confidence will be damaged. Therefore, reward and punishment must be properly combined.

Clustering technology is generally used in unsupervised learning. DM clustering technology automatically divides similar examples through a series of calculations, thus dividing different examples into different categories. Clustering technology in DM is also very useful for teenagers with negative psychological problems. We can use clustering technology to describe some potential characteristics of groups with psychological problems, and then make corresponding countermeasures according to the characteristics of money to improve the psychological level of college students in China.

Since no single taxonomy is suitable for all applications, it is often useful to try multiple methods. The bayesian network has an important property, that is, each node is independent of all its indirect predecessor nodes after the value of its direct predecessor node is set. The joint conditional probability distribution of any combination of random variables can be simplified as:

where P ( x 1 , x 2 ,…, x n ) is the probability of a specific combination of values of X , and the value of P ( x i | Parents( Y i )) corresponds to the set of conditional probability tables of Y i .

KNN is based on analogy learning, and its purpose is to assign unknown tuples to most of its k nearest neighbors in the training set. Euclidean distance is used in this paper. The Euclidean distance of two points or tuples X 1 ( x 11 , x 12 ,…, x 1 n ), X 2 ( x 21 , x 22 ,…, x 2 n ) is:

In order to reduce the influence of noise in the text, this study uses the dictionary fused with the previous articles to construct the vector space of users with these emotional words. In this study, the number of words in the dictionary appearing in users' discourse is counted, and word frequency is used as the weight of words. The word frequency of a word i of the user a can be expressed as:

In this study, the Min-Max normalization strategy is adopted to eliminate the influence of the inconsistency between different variable dimensions and speed up the classification speed of machine learning algorithms. This method maps all features to an interval, and the formula is given as follows:

In the formula, x is the input feature, and x min , x max is the minimum value and maximum value in the feature data. The output is a normalized feature. This formula will map all features to the interval between 0 and 1.

This study presents a depression classification algorithm based on bimodal data fusion. The algorithm proposed in this paper mainly classifies the fusion features of the bimodal data of the subjects to identify whether the subjects are healthy or TD. After preprocessing the data, the algorithm is divided into three steps: feature extraction, feature fusion, and feature classification. The flow chart of the algorithm is shown in Figure 2 .

Flow chart of depression classification algorithm.

First, a multi-scale functional brain network is constructed to extract fMRI (Functional Magnetic Resonance Imaging) and sMRI (Structural Magnetic Resonance Imaging) features. Merge two features, and finally classify the merged features using KNN. Through merging strategies such as concatenation or addition, not only feature merging is realized, but also redundant features are eliminated to some extent, and feature dimension reduction is realized.

Inverse EEG problem is a process of estimating the position of endogenous sources in the brain according to the known potential distribution observed in the scalp. At present, there are two main methods to solve the inverse problem of EEG: the parameter location method based on equivalent dipole; the image reconstruction method based on the current distribution model. There have been some algorithms to solve the inverse EEG problem, such as low-resolution EEG and normalized low-resolution EEG. The calculation process is given as:

J MN is the current density value obtained under the minimum norm algorithm, where V is the signal vector measured at N electrode positions; “+”means Moore-Penrose pseudo-inverse, and T means transpose matrix.

A method of measuring the root mean square of the ratio of slope change to the ideal curve is often used to estimate the bandwidth of a signal. If the signal is very similar to the ideal signal, the value will converge to 1:

where y ( t ) represents the amplitude of the signal at time t .

Finally, a new feature vector is merged by series fusion, and the fused feature is marked as F CC , which can be expressed as:

where A ⟶ best , B ⟶ best is the set of two linear relationships, and U ⟶ , V ⟶ is two eigenvectors. The fused feature F CC contains the features of two modal data, therefore, compared with the single modal feature, the fused feature can achieve a more accurate classification effect.

The traditional user model is basically built by feature customization. The disadvantage of this method is that the text features must be defined manually, and the features must be simplified and dimensionalized. In order to solve this problem, this paper uses the word vector trained by deep learning as the minimum granularity feature, that is, vocabulary feature. The workflow of this chapter is shown in Figure 3 .

User vector classification process.

Text preprocessing includes symbol, expression and punctuation filtering, and only the text content is kept. Secondly, this paper segments the text, using hyphenation in the python environment to segment the text. Use word2vec to convert these words into vector representations of words. The training set and test set of users are still divided by ten times, and the classifier uses logistic regression, SVM, and perceptron neural network. Finally, the experimental results of different methods are compared.

4. Experiment and Results

The relationship between teenagers and their families is very close. As one of the direct and important growth environments for teenagers, families play a more important role in cultivating, supporting and influencing teenagers' physical and mental growth. This study found that the scores of family financial difficulties and internal conflicts of depressed adolescents in the adolescent life events scale were higher than those of the normal control group, and the difference was highly significant. TD and father-son relationships are a more normal poor control group. Table 1 shows that positive coping is negatively correlated with stress, while negative coping is positively correlated with total stress.

Correlation between coping style, stress, and social support in depression group.

The scores of the neuroticism dimension of the adolescent personality questionnaire for depression were significantly higher than those of the normal control group, while the scores of introversion and extroversion dimensions were significantly lower, and the scores of adolescents aged 16 and above were also higher than those of the normal control group. Extroversion is also a very important personality dimension. Introverts focus on their inner activities, tend to be lost in thought and focus on the meaning and significance of their depressed emotions, thus developing severe and persistent depressive symptoms.

Depression can inhibit the related functions of the prefrontal cortex and basal ganglia, which are related to the reward circuit of the brain. The persistent inactivity of the reward circuit of the brain may be the main cause of depression. Between the selection of characteristic variables, the correlation analysis of all data is carried out. A total of 200 pieces of data were selected. Table 2 shows the analysis results of depression.

Correlation analysis of depression emotion.

When the value of Person is 0, variables are positively correlated with depression and anxiety. The higher the value of the Person, the greater the correlation. Significant ((bilateral) > 0.05, and there is no significant difference between variables. As shown in Table 2, all variables are positively or negatively related to depression to some extent. Learning stress, economic stress, work stress, coping style, and social support are closely related to depression and anxiety, so they are selected as predictive attributes when constructing the depression and anxiety model.

It is often observed in educational practice that when some altruistic behaviors of students are praised or over-praised, the tendency of altruistic behaviors does not increase. Therefore, in education, even those good behaviors that we expect students to show often need to be properly praised. It is not to make him feel that praise puts pressure on him, but to make him understand that his behavior is correct so that this kind of behavior can happen.

In terms of age, the detection rates of emotional abuse, physical abuse, and emotional neglect among different age groups are statistically significant ( P < 0.01). Among them, the detection rate of emotional abuse and emotional neglect in the 14-year-old group is higher than that in other age groups, and the detection rate of physical abuse in the 10-year-old group is the highest. In all age groups, the detection rate of physical neglect and emotional neglect is higher than in other types of childhood trauma, as shown in Figure 4 .

Comparison of detection rates of various types of childhood trauma among adolescents of different ages.

The results show that with the increase in age and grade, the detection rate of TD symptoms increases. The reason may be that teenagers are in a critical period of physical and mental development, and they are prone to confusion, doubt, or conflict with themselves and the world. At the same time, with the increase in age and grade, teenagers face more and more learning pressure, which can easily lead to depression [ 11 ]. Families with poor economic status have more TD symptoms, which is consistent with previous research results [ 3 ]. The reason may be that people with poor family economic conditions are prone to inner inferiority complexes and difficulties, leading to depression.

The classification effects of word vectors obtained using various word vector training methods and different word vector dimensions are examined in this section based on experiments carried out using the user vectors that were obtained. In this section, classification experiments are conducted using SVM (support vector machine), KNN, and BPNN, and the F 1 value is obtained as the classification index using the ten-fold cross method. The word vector's dimension ranges from 10 to 300, and the word vector training method used is cbow. The weighted word vector method's experimental results are displayed in Figure 5 .

Experimental results of weighted word vector.

It is clear that, among the two user vector construction techniques, the multilayer perceptron produces the best results. When the word vector has 90 dimensions, the weighted word vector method's average F 1 value is 81.3 percent. KNN has a general effect in comparison to the experimental results of the classification algorithm, whereas SVM divides precisely using the hyperplane because the obtained end-user vector is a vector representation in high-dimensional space. Multilayer perceptrons use numerous multilayer nonlinear activation functions in order to fit nonlinear data, and neural networks have a certain level of fault tolerance. In this section, the multilayer perceptron has the best classification performance.

All dimensions of the data come from different questionnaires, and the scores of each psychological condition are calculated by different calculation methods. These calculation processes are automatically completed by the background psychological evaluation system. The data involved in the analysis come from two tables, one of which records the personal information of the subjects, and the other of which records the psychological status of the students, including anxiety, depression, and school fatigue rate. Set the value of k to 7. The coordinates of the center point of the k-means execution result are shown in Figure 6 .

K mean center point.

In the cluster group, the incidence of self-reported anxiety and depression is significantly higher than the average, and the incidence of other negative emotions is higher than the average, especially the incidence of school aversion and stress. Among the people belonging to the cluster, the scores of positive energy, social support, and problem-solving ability are higher than the normal values, while the negative emotions are anxiety, anger, hostility, fatigue, stress, poor health, and so on. All negative emotions are lower than the average level, so this group of people can be classified as people with normal psychology.

In Figures ​ Figures7 7 and ​ and8, 8 , AUC (area under the receiver operating characteristic curve) and ROC (receiver operating characteristic curve) under KNN are basically similar, both of which are greater than 0.9. However, the number of features required by the BPNN classifier to obtain the highest accuracy is greater than that required by the KNN classifier, and the BPNN classifier takes more time than the KNN classifier. Therefore, KNN + BPNN is the best combination method in this paper.

ROC curves of mild depression groups with different classifiers (data set 1).

ROC curves of mild depression groups with different classifiers (data set 2).

Moderate stress and adversity can help people learn to make use of internal and external resources, exercise their social skills, and improve their coping ability [ 10 ]. With the increase of stress and adversity, their negative influence on personal development results also increases. Students should be educated to treat rewards and punishments correctly, and not be complacent when they get rewards, and not discouraged when they get rewards. Use self-esteem and self-confidence to overcome your own shortcomings, so in school, you cannot praise students unconditionally or be too generous. Especially when students' behaviors that meet the educational requirements are motivated by intrinsic motivation, they do not need to be praised so as not to weaken their intrinsic motivation.

5. Conclusions

Patients with TD must take into account their psychological and social needs. Family environment conflicts, nervousness and psychosis in personality, and poor coping mechanisms are the factors that have an impact on TD. The principle of operant conditioning must be correctly understood in order to choose and apply different reinforcement and punishment strategies sensibly and comprehensively in accordance with the unique circumstances of each student. In this study, the negative emotions experienced by teenagers are examined using DM analysis technology. Of the two methods for creating user vectors, multilayer perceptron has produced the best results. The average F 1 value for the weighted word vector method when the word vector has 90 dimensions is 81.3 percent. The opposite is also true: the wrong reward can be turned into punishment and the right punishment back into reward. As a result, encouragement and reprimand are the education's wings. Students can only soar higher and farther by always maintaining their balance.

Acknowledgments

This study was supported by the National Social Science Fund of China 2020 Pedagogy general research topic “A study of educational discipline from a phenomenological perspective” (topic no. BAA200027).

Data Availability

Conflicts of interest.

The authors declare that there are no conflicts of interest regarding the publication of this paper.

The mentality of Reward and Punishment in Education

Our memories of school are tinted with anecdotes which, hopefully for the most part, would bring a nostalgic smile to our faces.  Dark memories, though, always seem more vivid and punishments we received are sometimes hard to forget.  Is it because we learnt a valuable lesson and can now see how effective that was or is it that marks to our pride are indelible?  Do we remember praise as easily?  The debate on reward versus punishment as the most effective way to educate children is ongoing.  It reflects the global mentality of a given education system.

The case for Action-Reaction

Punishing children for bad behaviour is present in all schools.  It reflects how society works and teaches them that for every action there is a consequence.  You can’t hit your classmate in the same way as you can’t later attack someone in the street.  However, children are still developing and must first understand what is or isn’t acceptable behaviour before they can be punished for it.  Prevention works wonders.  Imagine you have already told a group of children they will only have 2 sweets each so that it is fair.  If one child takes someone else’s too, you can refer back to your initial statement, then punish that child if you deem it necessary.  The important thing is to give a clear explanation for the punishment, so that the child can associate it with the bad behaviour.

Teachers work to understand what causes bad behaviour in an individual child because it is sometimes leads to a deeper issue which requires attention rather than punishment.  These days, we have obviously moved away from corporal punishment.  The old fashioned writing a hundred times what one must not do is rare and doesn’t teach students anything. Sanctions more often than not take the form of detention.  In cases of bad behaviour, time alone at break or after school serves as an opportunity for reflection and a cooling off period; detention given for missed homework will eventually help the student take responsibility for their own learning.

Discipline can be enforced without punishment

Catch them being good.  This is the motto in progressive education, promoted in Switzerland’s International, British and American schools.  Praising children for good behaviour has been proven to reverse bad behaviour.  Praising boosts self-esteem and a confident individual is more likely to be tolerant of others, calm and willing to comply.  Bad behaviour does, indeed, often stem from frustration and a feeling of social inadequacy.  Punishment works by instilling fear and aims to force students to conform and obey, but it does not necessarily help educate them.  Punishment and negative feedback demotivate people.  Surely, the role of schools is to help students find their own motivation to learn and behave in a socially acceptable manner.  Too much punishment breeds bitterness and resentment, which in turn prevent learning from taking place effectively.

Most schools will find a balance between positive and punishing discipline.  This is most obvious in the common point system, where points are taken away for bad behaviour (very much like driving licences) but also added to reward good behaviour.  This leaves the door open for children to redeem themselves and so, rather than feeling discouraged by a definite punishment, they seek to put things right all the time.  Some schools, especially British ones, only use the point system for rewards, whereas others, often more traditional French ones, use points solely as penalty.

The cultural factor

Rewarding or punishing isn’t just about discipline.  It is a philosophy that will seep into all aspects of the school life, including assessment methods.  The local Swiss and French marking methods fall into the punishing category.  Students are expected to match certain criteria in their assignments and marks are taken away where errors are made.  Pages riddled with their work crossed out and only their mistakes highlighted in red can only demotivate a child.

The IB programme and English curriculum, on the other hand, base the assessment criteria on awarding marks for good work.  Students’ answers will be marked against a set of criteria which builds up the number of points.  In such a system, feedback will mainly be given on what has been done correctly. This is so the student can reproduce what he has done right, and will be given advice on how to boost his marks in future assignments.

Ultimately, what works for one child may not work for another, and the success of an education system will depend on the quality of the balance between reward and punishment, which most teachers naturally provide, regardless of culture. Punishment suits children who seek firm guidance, reward helps fragile individuals blossom. The role of parents, teachers and schools is to find the right approach for each particular situation.

When children grow up, they go out in life as the product of their education.  As the late poet U. A. Fanthorpe illustrates in her poem, the way we were disciplined at school marks us deeply and the puzzled child we were remains within us, wide-eyed and seeking answers.

More from International School Parent

• Mark Making in the Early Years
• How your child can avoid the summer slide – 7 top tips for parents
• Risk and your finances
• How To Improve Long-Term Memory
• Why Choose Barcelona For Your Child’s Study Abroad Experience

Find more articles like this here: www.internationalschoolparent.com/articles/

Want to write for us? If so, you can submit an article here: www.internationalschoolparent.submittable.com

Explore international schools

• Switzerland
• United Kingdom
• View all schools

Explore international camps

• View all camps

Read our latest magazine for free

Also available in our apps.

‘No place in our educational system’: OK Senate passes bill prohibiting the use of corporal punishment on students with disabilities

O KLAHOMA CITY ( KFOR ) – Despite a multitude of biblical reasoning to allow the use of corporal punishment on students with disabilities, the Senate has passed a proposal that would prohibit it.

House Bill 1028 , co-authored by Representative John Talley (R-Stillwater) and Senator Dave Rader (R-Tulsa), states, “ School district personnel shall be prohibited from using corporal punishment on students identified with the most significant cognitive disabilities according to criteria established by the State Department of Education unless addressed in an annual individualized education program (IEP) developed in accordance with the Individuals with Disabilities Education Act (IDEA) .

According to Sen. Rader, the “most significant cognitive disabilities” include:

• Emotional Disturbance
• Hearing Impairment
• Intellectual Disability
• Multiple Disabilities
• Orthopedic Impairment
• Speech/Language Impairment
• Traumatic Brain Injury
• Other health impairment

House Bill 1028 failed the first go-round in 2023, but Rep. Talley brought the legislation up once more before last year’s session adjourned. It passed.

The bill was then sent over to the Senate, but it wasn’t heard until Tuesday morning.

“Proverbs 13:24. Whoever spares the rod hates their child, but he who loves them, disciplines them,” said Sen. Shane Jett (R-Shawnee). “Are children who are differently abled capable of misbehaving?”

Sen. Rader responded by saying, “[Jesus] also said that if you harm one, these little ones, you’d be better off to have a stone cast around your neck and thrown into the water. I don’t want to be thrown in the water with a stone around my neck. I want to protect these kids.”

“Yesterday, the Senate recognized that there is no need for schools to use corporal punishment to discipline disabled students,” Rader said. “The support of fellow senators for backing this important bill that protects some of our most vulnerable children is most appreciated.”

Sen. Rader added the capabilities of one student may not be the same for another student and the definition of “capable” cannot be applied to all.

We’re talking about the schools here. We’re not talking about the parents and how they raise their children.

Sen. Jett said, “We’re removing it from the parent’s prerogative and saying… ‘The state of Oklahoma knows what’s best for your child and we’re removing an entire motivational tool from discipline in the classroom right now.'”

Rep. John Talley, R-Stillwater, said corporal punishment towards these students makes school appear hostile, limiting their ability to grow.

“Students with disabilities may not be able to control their actions or understand why they’re being punished,” Talley said. “When a teacher administers corporal punishment to these students, it sends the message that school is a hostile environment and limits their ability to thrive emotionally, socially and academically. I’m grateful my colleagues in the Senate saw fit to approve legislation protecting Oklahoma students with disabilities from corporal punishment at school, and I look forward to continuing to advocate for these students before the House again.”

Currently, there is no state law regulating the use of corporal punishment on students with disabilities. There is an Oklahoma State Department of Education administrative rule prohibiting it.

However, as provided by OSDE to News 4 , 43 school districts used corporal punishment on students with disabilities 247 times during the 2021-2022 school year. These 247 times were allegedly with a legal guardian’s permission.

The four school districts who used corporal punishment against kids with disabilities during the 2021-2022 school year the most include:

• Holly Creek Public Schools, 20 times
• Albion Public Schools, 23 times
• Blair Public Schools, 23 times
• Calera Public Schools, 29 times

“Hitting, slapping, paddling, or any other means of inflicting physical pain have no place in our educational system,” said Sen. Carrie Hicks (D-OKC).

Senator Blake Stephens (R-Tahlequah) said the legislature needs to step in and help educators with the lack of discipline.

With a vote of 31 for and 11 against, the bill passed the Senate Tuesday morning.

Because there was an amendment to the proposal, it will have to go back to the House for another vote before heading to the Governor’s desk.

For the latest news, weather, sports, and streaming video, head to KFOR.com Oklahoma City.

• Education News

TN education dept orders setting up of school-specific committees to prevent corporal punishment

Visual Stories

Support for capital punishment is strongly associated with the view that it is morally justified in certain cases. Nine-in-ten of those who favor the death penalty say it is morally justified when someone commits a crime like murder; only a quarter of those who oppose capital punishment see it as morally justified.

A majority of Americans have concerns about the fairness of the death penalty and whether it serves as a deterrent against serious crime. More than half of U.S. adults (56%) say Black people are more likely than White people to be sentenced to death for committing similar crimes. About six-in-ten (63%) say the death penalty does not deter people from committing serious crimes, and nearly eight-in-ten (78%) say there is some risk that an innocent person will be executed.

Opinions about the death penalty vary by party, education and race and ethnicity. Republicans and Republican-leaning independents are much more likely than Democrats and Democratic leaners to favor the death penalty for convicted murderers (77% vs. 46%). Those with less formal education are also more likely to support it: Around two-thirds of those with a high school diploma or less (68%) favor the death penalty, compared with 63% of those with some college education, 49% of those with a bachelor’s degree and 44% of those with a postgraduate degree. Majorities of White (63%), Asian (63%) and Hispanic adults (56%) support the death penalty, but Black adults are evenly divided, with 49% in favor and 49% opposed.

Views of the death penalty differ by religious affiliation . Around two-thirds of Protestants in the U.S. (66%) favor capital punishment, though support is much higher among White evangelical Protestants (75%) and White non-evangelical Protestants (73%) than it is among Black Protestants (50%). Around six-in-ten Catholics (58%) also support capital punishment, a figure that includes 61% of Hispanic Catholics and 56% of White Catholics.

Opposition to the death penalty also varies among the religiously unaffiliated. Around two-thirds of atheists (65%) oppose it, as do more than half of agnostics (57%). Among those who say their religion is “nothing in particular,” 63% support capital punishment.

Support for the death penalty is consistently higher in online polls than in phone polls. Survey respondents sometimes give different answers depending on how a poll is conducted. In a series of contemporaneous Pew Research Center surveys fielded online and on the phone between September 2019 and August 2020, Americans consistently expressed more support for the death penalty in a self-administered online format than in a survey administered on the phone by a live interviewer. This pattern was more pronounced among Democrats and Democratic-leaning independents than among Republicans and GOP leaners, according to an analysis of the survey results .

Phone polls have shown a long-term decline in public support for the death penalty. In phone surveys conducted by Pew Research Center between 1996 and 2020, the share of U.S. adults who favor the death penalty fell from 78% to 52%, while the share of Americans expressing opposition rose from 18% to 44%. Phone surveys conducted by Gallup found a similar decrease in support for capital punishment during this time span.

A majority of states have the death penalty, but far fewer use it regularly. As of July 2021, the death penalty is authorized by 27 states and the federal government – including the U.S. Department of Justice and the U.S. military – and prohibited in 23 states and the District of Columbia, according to the Death Penalty Information Center . But even in many of the jurisdictions that authorize the death penalty, executions are rare: 13 of these states, along with the U.S. military, haven’t carried out an execution in a decade or more. That includes three states – California , Oregon and Pennsylvania – where governors have imposed formal moratoriums on executions.

A growing number of states have done away with the death penalty in recent years, either through legislation or a court ruling. Virginia, which has carried out more executions than any state except Texas since 1976, abolished capital punishment in 2021. It followed Colorado (2020), New Hampshire (2019), Washington (2018), Delaware (2016), Maryland (2013), Connecticut (2012), Illinois (2011), New Mexico (2009), New Jersey (2007) and New York (2004).

Death sentences have steadily decreased in recent decades. There were 2,570 people on death row in the U.S. at the end of 2019, down 29% from a peak of 3,601 at the end of 2000, according to the Bureau of Justice Statistics (BJS). New death sentences have also declined sharply: 31 people were sentenced to death in 2019, far below the more than 320 who received death sentences each year between 1994 and 1996. In recent years, prosecutors in some U.S. cities – including Orlando and Philadelphia – have vowed not to seek the death penalty, citing concerns over its application.

Nearly all (98%) of the people who were on death row at the end of 2019 were men. Both the mean and median age of the nation’s death row population was 51. Black prisoners accounted for 41% of death row inmates, far higher than their 13% share of the nation’s adult population that year. White prisoners accounted for 56%, compared with their 77% share of the adult population. (For both Black and White Americans, these figures include those who identify as Hispanic. Overall, about 15% of death row prisoners in 2019 identified as Hispanic, according to BJS.)

Annual executions are far below their peak level. Nationally, 17 people were put to death in 2020, the fewest since 1991 and far below the modern peak of 98 in 1999, according to BJS and the Death Penalty Information Center. The COVID-19 outbreak disrupted legal proceedings in much of the country in 2020, causing some executions to be postponed .

Even as the overall number of executions in the U.S. fell to a 29-year low in 2020, the federal government ramped up its use of the death penalty. The Trump administration executed 10 prisoners in 2020 and another three in January 2021; prior to 2020, the federal government had carried out a total of three executions since 1976.

The Biden administration has taken a different approach from its predecessor. In July 2021, Attorney General Merrick Garland ordered a halt in federal executions while the Justice Department reviews its policies and procedures.

The average time between sentencing and execution in the U.S. has increased sharply since the 1980s. In 1984, the average time between sentencing and execution was 74 months, or a little over six years, according to BJS . By 2019, that figure had more than tripled to 264 months, or 22 years. The average prisoner awaiting execution at the end of 2019, meanwhile, had spent nearly 19 years on death row.

A variety of factors explain the increase in time spent on death row, including lengthy legal appeals by those sentenced to death and challenges to the way states and the federal government carry out executions, including the drugs used in lethal injections. In California, more death row inmates have died from natural causes or suicide than from executions since 1978, according to the state’s Department of Corrections and Rehabilitation .

Note: This is an update to a post originally published May 28, 2015.

• Criminal Justice
• Death Penalty

John Gramlich is an associate director at Pew Research Center

What the data says about crime in the U.S.

8 facts about black lives matter, #blacklivesmatter turns 10, support for the black lives matter movement has dropped considerably from its peak in 2020, fewer than 1% of federal criminal defendants were acquitted in 2022, most popular.

1615 L St. NW, Suite 800 Washington, DC 20036 USA (+1) 202-419-4300 | Main (+1) 202-857-8562 | Fax (+1) 202-419-4372 |  Media Inquiries

Research Topics

• Age & Generations
• Coronavirus (COVID-19)
• Economy & Work
• Family & Relationships
• Gender & LGBTQ
• Immigration & Migration
• International Affairs
• Internet & Technology
• Methodological Research
• News Habits & Media
• Non-U.S. Governments
• Other Topics
• Politics & Policy
• Race & Ethnicity
• Email Newsletters

ABOUT PEW RESEARCH CENTER  Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of  The Pew Charitable Trusts .

Copyright 2024 Pew Research Center

Terms & Conditions

Privacy Policy

Cookie Settings

Reprints, Permissions & Use Policy

Several George Washington U. students suspended as Gaza solidarity encampment continues

by CARL WILLIS | WJLA Staff

WASHINGTON (WJLA) — Several students were suspended Friday , a full 24 hours past the stop time George Washington University officials told Gaza cease-fire advocates and demonstrators they had to end their encampment and protest on campus .

The scene was much different than the first night with protestors sitting in a newly blocked-off section of the street with metal barricades up around the tents set up on University Yard.

On Friday night, the university announced that several students who remained in the encampment received their punishment. Protestors announced to the crowd that seven students had been suspended.

"I would rather be banned knowing I'm doing something for my family, for my country, than doing nothing at all," one student organizer from George Mason University, who wished to remain anonymous, told WJLA Friday afternoon.

With the free flow of traffic through the area restricted — and no clear sign that police planned further action — those in the protest zone settled in Friday as demonstrations and chants carried on through the night.

Protesters are calling for an end to the Israel-Hamas war and Washington, D.C. universities to divest from businesses that support Israel.