centre for quality assessment in higher education

Centre for Quality Assessment in Higher Education (SKVC)

The SKVC is an independent organisation, founded in 1995, established by the Ministry of Education and Science of the Republic of Lithuania. Agency’s role: to increase awareness of the quality of higher education and promote its improvement. Evaluation of the quality of higher education (by institutions and by programmes), credential evaluation (of foreign HE qualifications and qualifications giving access to HE); provision of information on HE systems and qualifications’ recognition; other functions in accordance with legal acts.

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Center for Quality Assessment in Higher Education

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SKVC - Centre for Quality Assessment in Higher Education

Studijų kokybės vertinimo centras.

• Substantial compliance with the ESG
• View 1969 reports on 47 institutions
• Registration valid until 30/06/2027 (listed since 01/06/2012)

SKVC has been listed on EQAR since 01/06/2012 based on the decision by EQAR Register Committee from 01/12/2012 (Ref. RC9/012/06). As stipulated in the EQAR Procedures for Applications §3.25 "the agency shall be included in the Register for five years from the date of the external review report " SKVC is considered to have continuous listing on the Register since its official acceptance on the Register based on  §4.5 of the EQAR Procedures for Applications which stipulates that once an agency applies for renewal of registration its registration remains fully valid, until decision of renewal has been made.

• Website http://www.skvc.lt
• Reports by the agency https://www.skvc.lt/default/en/valuations
• Permalink https://data.deqar.eu/agency/42

Information on the agency's work

The main objectives of SKVC are to promote the quality of activities of higher education institutions and to contribute to creation of favourable conditions for the free movement of persons. Established in 1995 as an independent state institution, SKVC is the only external quality assurance agency responsible for all types of higher education institutions in Lithuania (state and private, university type and college of higher education type). SKVC also acts as a local ENIC/NARIC office carrying out academic diploma recognition.

Activities within the scope of ESG

• Ex-ante evaluation and accreditation of residency studies in Lithuania Documentation
• Ex-ante institutional review in Lithuania Documentation
• Ex-ante study programme external evaluation and accreditation in Lithuania View 7 reports Documentation
• Ex-post evaluation and accreditation of study fields View 557 reports Documentation
• Ex-post evaluation and accreditation of the residency studies in Lithuania Documentation
• Ex-post institutional review abroad Documentation
• Ex-post institutional review in Lithuania View 107 reports Documentation
• Ex-post institutional review of higher education in exile Documentation
• Ex-post study programmes evaluation abroad View 5 reports Documentation
• Archived entry - activity that was carried out in the past External evaluation and accreditation of study programmes in Lithuania View 1293 reports Documentation
• Joint programme accreditation

Higher education systems where SKVC carried out external QA activities

Slovenia EHEA

Ukraine EHEA View 5 reports on 2 institutions

Contact details

A. Gostauto g. 12 01108 Vilnius

• Contact Person Aurelija Valeikienė
• Phone +370-5 2105402
• Email [email protected] [email protected]
• ENQA membership ENQA member

11.2 Quality assurance in higher education

On this page, responsible bodies, approaches and methods for quality assurance.

Assessment of the quality of studies and research in Lithuanian higher education was initiated in 1995 after establishment of the Lithuanian Centre for Quality Assessment in Higher Education. One of the functions of the Centre is to organise quality assessment of studies in Lithuanian higher education institutions (HEIs). It goes without saying that the quality of studies was always a matter of great concern. This function, however, was performed by higher education institutions themselves. The newly established Lithuanian Centre for Quality Assessment in Higher Education is an institution entirely independent of higher schools. It organises the external evaluation of the quality of research and studies. Experts invited from other institutions can take a more critical look at the object to be evaluated and see the shortcomings that might escape the attention of employees who are delivering the study programmes or taking care of their quality in the institution under evaluation.

Institutions or divisions to be evaluated are advised on how to prepare a summary of the self-evaluation findings for external evaluators. The Centre for Quality Assessment in Higher Education organises seminars, prepares various handouts as well as provides advice by telephone and e-mail on all matters related to the preparation of the self-evaluation findings summary.

Under the Law on Higher Education and Research , higher education institutions may deliver only accredited study programmes. Study programmes are accredited for a period not exceeding six years.

An external evaluation of study programmes for accreditation purposes started in 1999–2000. The evaluation is aimed at continuous improvement of HEI study programmes and provision of information to the public about the quality of studies. The external evaluation of study programmes is conducted with the help of Lithuanian or international groups of experts.

HEIs are authorised to carry out only accredited study programmes. Study programmes are accredited at least once in six years. In view of the findings of the external evaluation of a particular study programme, the Centre for Quality Assessment in Higher Education pronounces one of the following judgements: to accredit the study programme for six years; accredit the study programme for three years; refuse to accredit the study programme.

External evaluation of HEI study programmes is performed by the Centre for Quality Assessment in Higher Education or any other higher education quality assessment agency included in the European Quality Assurance Register for Higher Education.

Evaluation of research (artistic) output of Lithuanian institutions of higher education and research is carried out in accordance with the Methodology for the Evaluation of Research (Artistic) Output of Lithuanian Institutions of Higher Education and Research .The results of the education institutions’ research (artistic) output evaluation are available publicly.

In December 2012, the Government adopted the Procedure for National Higher Education Institutions’ Supervision . The purpose of the Procedure is to monitor the availability and quality of higher education and research, encourage higher education institutions to seek for improvement, consult them and evaluate their performance. Continuous monitoring will allow assessment of systemic changes in higher education and help the process take the right direction. The Procedure identifies the existing measures as well as suggests new instruments to monitor and supervise higher education institutions, such as external evaluation and accreditation, monitoring of how expert recommendations are being implemented, supervision of compliance with laws and regulations currently in force, consultations on new legislation and potential means of its implementation.

According to the Law on Higher Education and Research , as amended in 2012, national higher education institutions’ supervision is performed by the Ministry of Education, Science and Sport, Research Council of Lithuania, Research and Higher Education Monitoring and Analysis Centre, Centre for Quality Assessment in Higher Education, Council of Higher Education and other institutions. 

Evaluation of research (artistic) output is organised by the Research Council of Lithuania. 

On 22 December 2010, the Minister of Education and Science issued an order authorising the Centre for Quality Assessment in Higher Education to organise the external evaluation of HEIs performance. External evaluation of HEIs study programmes may be performed by the Centre for Quality Assessment in Higher Education or any other higher education quality assessment agency included in the European Quality Assurance Register for Higher Education (EQAR).

In 2012, the Lithuanian Centre for Quality Assessment in Higher Education (in Lithuanian, abbreviated as SKVC) applied for inclusion in the European Quality Assurance Register for Higher Education. Following the positive assessment, SKVC was listed in EQAR for the period of 2012–2017.

In March 2012, the Lithuanian Centre for Quality Assessment in Higher Education became a member of the elitist European Association for Quality Assurance in Higher Education (ENQA). The decision to grant SKVC full membership in ENQA was based on the positive findings of the external review. (the report of the ENQA panel of the SKVC external review can be found here .) Joining the ENQA group means that the requirements for higher education in Lithuania comply with the European standards. Membership in ENQA and inclusion in EQAR amount to recognition that SKVC activities are open and transparent and its procedures appropriate and correct.

In institutions of higher education, self-evaluation is performed in accordance with the Methodology for Self-Evaluation of Higher Education Institutions . The self-evaluation of a particular institution is based on the evaluation results of its available resources, purpose-specific evaluation results, summary of self-analysis and other documents, data obtained during the site visits of experts to the institution, findings of the previous evaluation and recommendations and data on how and to what effect they were implemented, as well as other information about the activities of the higher education institution.

The performance of a higher education institution is evaluated according to its activities in the following four areas: 1. strategic management; 2. organisation of studies and lifelong learning; 3. research and (or) artistic activities; 4. effect on regional and country-wide development.

A higher education institution is responsible for conducting self-evaluation and preparing a self-evaluation report. The report should reveal the ability of a HEI to analyse and critically evaluate its performance and outline the prospects for its further development. Statements contained in the self-evaluation report must be based on both quantitative and qualitative evidence. The self-evaluation report should present the purpose-specific information necessary for the external evaluation.

Higher education institutions have an opportunity to apply for and receive targeted support for the development of internal quality management systems (e.g. system’s development, personnel trainings, system’s testing and improvement), implementation of best practices and promotion of social and economic partners’ involvement in the quality management process. These actions called ‘Development and Implementation of Internal Quality Management Mechanisms’ are an integral part of the National Study Programme .

External evaluation of higher education institutions is performed by expert groups set up by the Centre for Quality Assessment in Higher Education. The final findings of the evaluation are publicly available in the reference publications of the Centre for Quality Assessment in Higher Education. Within a specified period of time, institutions of higher education and research are required to correct the deficiencies pointed out by experts. In a higher education and research institution of very poor quality, its activities (or those of its unit, study programmes, etc.) may be restricted or even completely terminated. In order to avoid unfavourable findings of external evaluations, institutions should do everything possible to make their performance efficient and assure its quality.

Under the Law on Higher Education and Research , institutions of higher education can carry out only accredited study programmes which are accredited for a maximum period of six years. Study programmes are accredited in accordance with the findings of the external evaluation (except for study programmes that are intended to be delivered, in which case they can be accredited without undertaking the external evaluation procedure). This means that over a period of six years all higher education study programmes will be evaluated and accredited.

Subject to the Procedure for the External Evaluation and Accreditation of Study Programmes  the currently delivered study programmes are evaluated according to six areas, viz. the objectives and expected learning outcomes of the study programme, its structure, staffing, material resources, the course of studies and its assessment and programme management. Each of the areas evaluated are assessed on a four-point scale. Based on the assessment of each area and the overall scores, study programmes are accredited according to the Procedure for the External Evaluation and Accreditation of Study Programmes.

Since 2010, Lithuania has been implementing the project ‘Development and Implementation of the Higher Education Admission System’. The purpose of the project is to improve the higher education admission system through enhancing its technical and functional capacity, developing the professional competences of people involved in the system and assuring the effectiveness and transparency of the admission process.The results of the Project: the system of general admission was developed and implemented; the central co-ordination reception for the admission to Lithuanian high schools established; the system’s operators-consultants and high schools’ admission committees membersprepared to develop efficient work; the trial experience of the common entrance examinations in art and pedagogical study programs realized; new system introduced to graduates and public; the general admission system’s effectiveness evaluation systemdeveloped and implemented.

Higher Education Quality Assessment and University Change: A Theoretical Approach

• First Online: 04 May 2016

Cite this chapter

• Shuiyun Liu 6  

Part of the book series: Higher Education in Asia: Quality, Excellence and Governance ((HEAQEG))

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5 Citations

This chapter is devoted to finding theoretical approaches to understand how quality assessment causes transformation of higher education institutions. Firstly, studies on quality assessment in higher education are reviewed. The context in which quality assessment emerged in the higher education system, its purposes and the approaches to operating it are discussed. Based on previous empirical studies, the main impact of quality assessment on evaluated universities is summarised, and the factors determining the impact are tentatively proposed. Then, the focus turns to a theoretical exploration of how quality assessment, as an external force, causes university change. Theories about organisational change, the working processes and structures of higher education systems and the operating mechanism of quality assessment are examined. Building on these theories, a perspective is proposed to help to understand the ways in which quality assessment processes interact with universities to generate change.

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Accountability is “the obligation to report to others, to explain, to justify, to answer questions about how resources have been used and to what effect” (Trow 1996 , pp. 311).

In the context of organisational change, compliance means conforming to a rule, such as a specification, policy, standard or law.

Argyris, C. (1982). How learning and reasoning processes affect organisational change. In P. S. Goodman (Ed.), Change in organisations . San Francisco: Jossey-Bass.

Google Scholar  

Argyris, C. (1999). On organisational learning (2nd ed.). Oxford: Blackwell.

Askling, B. (1997). Quality monitoring as an institutional enterprise. Quality in Higher Education, 3 (1), 17–26.

Article   Google Scholar  

Askling, B., & Stensaker, B. (2002). Academic leadership: Prescriptions, practices and paradoxes. Tertiary Education and Management, 8 (2), 113–125.

Baldwin, G. (1997). Quality assurance in Australian higher education: The case of Monash University. Quality in Higher Education, 3 (1), 51–61.

Banta, T. W. (2010). Impact of addressing accountability demands in the United States. Quality in Higher Education, 16 (2), 181–183.

Barnetson, B., & Cutright, M. (2000). Performance indicators as conceptual technologies. Higher Education, 40 (3), 277–292.

Barnett, R. (1992). Improving higher education: Total quality care . Buckingham: SRHE and Open University Press.

Barnett, R. (1994). Power, enlightenment and quality evaluation. European Journal of Education, 29 (2), 165–179.

Barnett, R. (2003). Beyond all reason: Living with ideology in the university . Buckingham: SRHE and the Open University Press.

Becher, T., & Kogan, M. (1992). Process and structure in higher education (2nd ed.). London: Routledge.

Billing, D. (2004). International comparisons and trends in external quality assurance of higher education: Commonality or diversity. Higher Education, 47 (1), 113–137.

Birnbaum, R. (2000). Management fads in higher education . San Francisco: Jossey-Bass.

Bovens, M. (2007). Analysing and assessing accountability: A conceptual framework. European Law Journal, 13 (4), 447–468.

Brennan, J., & Shah, T. (2000). Managing quality in higher education: An international perspective on institutional assessment and change . Buckingham: OECD, SRHE and Open University Press.

Brown, R. (2004). Quality assurance in higher education: The UK experience since 1992 . London: Routledge Falmer.

Book   Google Scholar  

Burnes, B. (1996). Managing change: A strategic approach to organisational dynamics . London: Pitman.

Cartwright, M. J. (2007). The rhetoric and reality of ‘quality’ in higher education: An investigation into staff perceptions of quality in post 1992 universities. Quality Assurance in Education, 15 (3), 287–301.

Chaffee, E. (1983). Three models of strategy. Academy of Management Review, 10 (1), 89–98.

Cheng, M. (2011). ‘Transforming the learner’ versus ‘passing the exam’: Understanding the gap between academic and student definitions of quality. Quality in Higher Education, 17 (1), 3–17.

Cheng, M. (2012). Accountability and professionalism: A contradiction in terms? Higher Education Research and Development, 31 (6), 785–795.

Clark, B. R. (1983). The higher education system: Academic organisation in cross-national perspective . Berkeley: University of California Press.

Clark, B. R. (1998). Creating entrepreneurial universities: Organizational pathways of transformation . New York: International Association of Universities Press.

Clegg, C., & Walsh, S. (2004). Change management: Time for a change! European Journal of Work and Organisational Psychology, 13 (2), 217–239.

Cohen, D. K., Moffitt, S. L., & Goldin, S. (2007). Policy and practice: The dilemma. American Journal of Education, 113 (4), 515–548.

Cohen, M. D., & March, J. G. (1974). Leadership and ambiguity: The American college presidency . New York: McGraw Hill.

Collins, D. (1998). Organisational change: Sociological perspectives . London: Routledge.

Daniel, J. (2004). Incentives and accountability: Instruments of change in higher education. Higher Education Management and Policy, 16 (1), 9–18.

De Weert, E. (1990). A macro-analysis of quality assessment in higher education. Higher Education, 19 (1), 57–72.

Dill, D. D. (2010). We can’t go home again: Insights from a quarter century of experiments in external academic quality assurance. Quality in Higher Education, 16 (2), 159–161.

Dill, D. D., & Beerkens, M. (2013). Designing the framework conditions for assuring academic standards: Lessons learned about professional, market, and government regulation of academic quality. Higher Education, 65 (3), 341–357.

Eaton, J. S. (2012). The future of accreditation? Planning for Higher Education, 40 (3), 8–15.

Eckel, P., & Kezar, A. (2003). Taking the reins: Institutional transformation in higher education . Phoenix, AZ: ACE-ORYX Press.

El-Khawas, E. (2000). The impetus for organisational change: An exploration. Tertiary Education and Management, 6 (1), 37–46.

Ewell, P. T. (2007). The ‘quality game’: External review and institutional reaction over three decades in the United States. In D. F. Westerheijden, B. Stensaker & M. J. Rosa (Eds.), Quality assurance in higher education: Trends in regulation, translation and transformation . Dordrecht: Springer.

Ewell, P. T. (2010). Twenty years of quality assurance in higher education: What’s happened and what’s different? Quality in Higher Education, 16 (2), 173–175.

Ferlie, E., Ashburner, L., Fitzgerald, L., & Pettigrew, A. (1996). The new public management in action . Oxford: Oxford University Press.

Findlow, S. (2008). Accountability and innovation in higher education: A disabling tension? Studies in Higher Education, 33 (3), 313–329.

Fumasoli, T., & Stensaker, B. (2013). Organizational studies in higher education: A reflection on historical themes and prospective trends. Higher Education Policy, 26 (4), 479–496.

Gioia, D. A., & Thomas, J. B. (1996). Identity, image, and issue interpretation: Sensemaking during strategic change in academia. Administrative Science Quarterly, 41 (3), 370–403.

Green, D. (1994). What is quality in higher education? Concepts, policy and practice. In D. Green (Ed.), What is quality in higher education ? Buckingham: SRHE and Open University Press.

Haapakorpi, A. (2011). Quality assurance processes in Finnish universities: Direct and indirect outcomes and organisational conditions. Quality in Higher Education, 17 (1), 69–81.

Harvey, L. (1995). Editorial. Quality in Higher Education, 1 (1), 5–12.

Harvey, L., & Green, D. (1993). Define quality. Assessment and Evaluation in Higher Education, 18 (1), 9–34.

Harvey, L., & Newton, J. (2004). Transforming quality evaluation. Quality in Higher Education, 10 (2), 149–165.

Harvey, L., & Williams, J. (2010). Editorial: Fifteen years of quality in higher education (part two). Quality in Higher Education, 16 (2), 81–113.

Hayes, D., & Winyard, R. (2002). The Mcdonaldisation of higher education . Westport: Bergin & Garvey.

Hazelkorn, E. (2011). Rankings and the reshaping of higher education. The battle for world-class excellence . Basingstoke: Palgrave Macmillan.

Henkel, M. (2000). Academic identities and policy change in higher education . London: Jessica Kingsley.

Hodson, P., & Thomas, H. (2003). Quality assurance in higher education: Fit for the new millennium or simply year 2000 compliant? Higher Education, 45 (3), 375–387.

Hoecht, A. (2006). Quality assurance in UK higher education: Issues of trust, control, professional autonomy and accountability. Higher Education, 51 (4), 541–563.

Hou, Y., Morse, R., Ince, M., Chen, H., Chiang, C., & Chan, Y. (2015). Is the Asian quality assurance system for higher education going glonacal? Assessing the impact of three types of program accreditation on Taiwanese universities. Studies in Higher Education, 40 (1), 83–105.

Houston, D. (2008). Rethinking quality and improvement in higher education. Quality Assurance in Education, 16 (1), 61–79.

Houston, D. (2010). Achievements and consequences of two decades of quality assurance in higher education: A personal view from the edge. Quality in Higher Education, 16 (2), 177–180.

Huisman, J., & Currie, J. (2004). Accountability in higher education: Bridge over troubled water? Higher Education, 48 (4), 529–551.

Huisman, J., Rebora, G., & Turri, M. (2007). The effects of quality assurance in universities: Empirical evidence from three cases. In L. Purser, L. Wilson & E. Froment (Eds.), Introducing Bologna objectives and tools . Stuttgart: Raabe.

Iacovidou, M., Gibbs, P., & Zopiatis, A. (2009). An exploratory use of the stakeholder approach to defining and measuring quality: The case of a Cypriot higher education institution. Quality in Higher Education, 15 (2), 147–165.

Keller, G. (1997). Examining what works in strategic planning. In M. W. Peterson, D. D. Dill & L. A. Mets (Eds.), Planning and management for a changing environment: A handbook in redesigning postsecondary institutions . San Francisco: Jossey-Bass.

Kezar, A. (2001). Understanding and facilitating organisational change in the 21st century: Recent research and conceptualisations. ASHE-ERIC higher education report, 28. San Francisco: Jossey-Bass.

Kezar, A. (2013). Understanding sensemaking/sensegiving in transformational change processes from the bottom up. Higher Education, 65 (6), 761–780.

Kezar, A., & Eckel, P. (2002). Examining institutional transformation process: The importance of sensemaking, interrelated strategies, and balance. Research in Higher Education, 43 (3), 295–328.

Kogan, M., & Hanney, S. (2000). Reforming higher education . London: Jessica Kingsley.

Kondakci, Y., & Van den Broeck, H. (2009). Institutional imperatives versus emergent dynamics: A case study on continuous change in higher education. Higher Education, 58 (4), 439–464.

Levy, A., & Merry, U. (1986). Organisational transformation: Approaches, strategies, theories . New York: Praeger.

Locke, W., Cummings, W. K., & Fisher, D. (Eds.). (2011). Changing governance and management in higher education: The perspectives of the academy . Dordrecht: Springer.

Maassen, P. A. M., & Stensaker, B. (2003). Interpretations of self-regulation: The changing state-higher education relationship in Europe. In R. Begg (Ed.), The dialogue between higher education research and practice . Dordrecht: Kluwer.

MacDonald, G. P. (2013). Theorizing university identity development: Multiple perspectives and common goals. Higher Education, 65 (2), 153–166.

Malau-Aduli, B. S., Zimitat, C., & Malau-Aduli, A. O. (2011). Quality assured assessment processes: Evaluating staff response to change. Higher Education Management and Policy, 23 (1), 1–24.

Massy, W. (1999). Energizing quality work: Higher education quality evaluation in Sweden and Denmark . Stanford: National Centre for Postsecondary Improvement.

McLaughlin, M. W. (1987). Learning from experience: Lessons from policy implementation. Educational Evaluation and Policy Analysis, 9 (2), 171–178.

Meek, V. L. (2003). Introduction. In A. Amaral, V. L. Meek & I. M. Larsen (Eds.), The higher education managerial revolution? . Dordrecht: Kluwer Academic Publishers.

Melrose, M. (1998). Exploring paradigms of curriculum evaluation and concepts of quality. Quality in Higher Education, 4 (1), 37–43.

Milliken, J., & Colohan, G. (2004). Quality or control? Management in higher education. Journal on Higher Education Policy and Management, 26 (3), 381–391.

Minelli, E., Rebora, G., Turri, M., & Huisman, J. (2006). The impact of research and teaching evaluation at universities: Comparing an Italian and a Dutch case. Quality in Higher Education, 12 (2), 109–124.

Morgan, G. (1986). Images of organisation . Newbury Park, CA: Sage.

Morley, L. (2003). Quality and power in higher education . Berkshire: SRHE and Open University Press.

Neave, G., & Van Vught, F. A. (1994). Government and higher education relationships across three continents . Oxford: Pergamon Press.

Newton, J. (2000). Feeding the beast or improving quality? Academics’ perceptions of quality assurance and quality monitoring. Quality in Higher Education, 6 (2), 153–163.

Newton, J. (2002). Barriers to effective quality management and leadership: Case study of two academic departments. Higher Education, 44 (2), 182–212.

Newton, J. (2010). A tale of two ‘qualitys’: Reflections on the quality revolution in higher education. Quality in Higher Education, 16 (1), 51–53.

Olaskoaga-Larrauri, J., González-Laskibar, X., & Barrenetxea-Ayesta, M. (2015). Political nature and socio-professional determinants of the concept of quality. Higher Education, 69 (4), 673–691.

Olsen, J. P. (2005). The institutional dynamics of the European University. Arena working paper, 15. Arena: University of Oslo.

Pearce, R. A. (1995). Maintaining the quality of university education . Buckingham: University of Buckingham.

Pfeffer, J., & Salancik, G. (2003). The external control of organizations: A resource dependence perspective . Stanford: Stanford University Press.

Pirsig, R. (1974). Zen & the art of motorcycle maintenance: An inquiry into values . New York: William Morrow and Company.

Power, M. (1997). The audit society . Oxford: Oxford University Press.

Power, M. (2003). Auditing and the production of legitimacy. Accounting, Organisations and Society, 28 (4), 379–394.

Pratasavitskaya, H., & Stensaker, B. (2010). Quality management in higher education: Towards a better understanding of an emerging field. Quality in Higher Education, 16 (1), 37–50.

Ramirez, F. O., & Christensen, T. (2013). The formalization of the university: Rules, roots and routes. Higher Education, 65 (6), 695–708.

Rebora, G., & Turri, M. (2011). Critical factors in the use of evaluation in Italian universities. Higher Education, 61 (5), 531–544.

Reed, M. I., Meek, L. V., & Jones, G. A. (2002). Introduction. In A. Amaral, G. A. Jones & B. Karseth (Eds.), Governing higher education: National perspectives on institutional governance . Dordrecht: Kluwer.

Rosa, M. J., Tavares, D., & Amaral, A. (2006a). Assessment as a tool for different kinds of action: From quality management to compliance and control. Retrieved November 24, 2008 from http://www.unicam.it/sgq/Forum%20Monaco/PS%201%20-%20Alberto%20Amaral.pdf

Rosa, M. J., Tavares, D., & Amaral, A. (2006b). Institutional consequences of quality assessment. Quality in Higher Education, 12 (2), 145–159.

Rowan, B. (2006). The new institutionalism and the study of educational organisations: Changing ideas for changing times. In H. Meyer & B. Rowan (Eds.), The new institutionalism in education . NY: State University of New York Press.

Rowley, J. (1995). A new lecturer’s simple guide to quality issues in higher education. International Journal of Educational Management, 9 (1), 24–27.

Schwarz, S., & Westerheijden, D. F. (2004). Accreditation in the framework of evaluation activities: A comparative study in the European higher education area. In S. Schwarz & D. F. Westerheijden (Eds.), Accreditation and evaluation in the European higher education area . Dordrecht: Kluwer.

Chapter   Google Scholar  

Scott, R. (1995). Institutions and organisations . London: Sage.

Shah, M. (2012). Ten years of external quality audit in Australia: Evaluating its effectiveness and success. Assessment and Evaluation in Higher Education, 37 (6), 761–772.

Shattock, M. (2010). Managing successful universities . Maidenhead: SRHE/Open University Press.

Shin, J. (2010). Impacts of performance-based accountability on institutional performance in the U.S. Higher Education, 60 (1), 47–68.

Sporn, B. (1999). Adaptive university structures: An analysis of adaptation to socioeconomic environments of US and European universities . London: Jessica Kingsley Publishers.

Stensaker, B. (2003). Trance, transparency and transformation: The impact of external quality monitoring on higher education. Quality in Higher Education, 9 (2), 151–159.

Stensaker, B. (2006). Governmental policy, organisational ideals, and institutional adaptation in Norwegian higher education. Studies in Higher Education, 31 (1), 43–56.

Stensaker, B. (2007). Impact of quality processes. In L. Bollaert, S. Brus, B. Curvale, L. Harvey, E. Helle, H. T. Jensen, J. Komljenovic, A. Orhanides & A. Sursock (Eds.), Embedding quality culture in higher education . Brussels: European University Association.

Stensaker, B. (2008). Outcomes of quality assurance: A discussion of knowledge, methodology and validity. Quality in Higher Education, 14 (1), 3–13.

Stensaker, B., Langfeldt, L., Harvey, L., Huisman, J., & Westerheijden, D. (2011). An in-depth study on the impact of external quality assurance. Assessment & Evaluation in Higher Education, 36 (4), 465–478.

Stensaker, B. (2015). Organisational identity as a concept for understanding university dynamics. Higher Education, 69 (1), 103–115.

Tam, M. (2001). Measuring quality and performance in higher education. Quality in Higher Education, 7 (1), 47–54.

Trow, M. (1996). Trust, markets and accountability in higher education: A comparative perspective. Higher Education Policy, 9 (4), 309–324.

Van Kemenade, E., Pupius, M., & Hardjono, T. W. (2008). More value to defining quality. Quality in Higher Education, 14 (2), 175–185.

van Vught, F. A., & Westerheijden, D. F. (1994). Towards a general model of quality assessment in higher education. Higher Education, 28 (3), 355–371.

Vroeijenstijn, A. I. (1995). Improvement and accountability: Navigating between Scylla and Charybdis . Higher Education Policy Series (Vol. 30). London: Jessica Kingsley.

Wahlen, S. (2004). Does national quality monitoring make a difference? Quality in Higher Education, 10 (2), 139–147.

Watson, D. (2009). The question of morale: Searching for happiness and unhappiness in university life . Berkshire: Open University Press.

Weick, K. E. (1976). Educational organisations as loosely coupled systems. Administrative Science Quarterly, 21 (1), 1–19.

Weick, K. E. (1995). Sensemaking in organisations . Thousand Oaks, CA: Sage.

Weerts, D. J., Freed, G., & Morphew, C. C. (2014). Organisational identity in higher education: Conceptual and empirical perspectives. In M. B. Paulsen (Ed.), Higher education: Handbook of theory and research . Dordrecht: Springer.

Westerheijden, D. F. (1990). Peers, performance, and power: Quality assessment in the Netherlands. In L. C. J. Goedegebuure, P. A. M. Maassen & D. F. Westerheijden (Eds.), Peer review and performance indicators: Quality assessment in British and Dutch higher education . Lemma: Utrecht.

Westerheijden, D. F. (2007). States and Europe and quality of higher education. In D. F. Westerheijden, B. Stensaker & M. J. Rosa (Eds.), Quality assurance in higher education: Trends in regulation, translation and transformation . Dordrecht: Springer.

Westerheijden, D. F., Stensaker, B., & Rosa, M. J. (2007a). Introduction. In D. F. Westerheijden, B. Stensaker & M. J. Rosa (Eds.), Quality assurance in higher education: Trends in regulation, translation and transformation . Dordrecht: Springer.

Westerheijden, D. F., Stensaker, B., & Rosa, M. J. (2007b). Is there a logic in the development of quality assurance schemes? From comparative history to theory. Paper presented at INQAAHE Conference, April 2–5, 2007, Toronto.

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Shuiyun Liu

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Liu, S. (2016). Higher Education Quality Assessment and University Change: A Theoretical Approach. In: Quality Assurance and Institutional Transformation. Higher Education in Asia: Quality, Excellence and Governance. Springer, Singapore. https://doi.org/10.1007/978-981-10-0789-7_2

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Quality assurance for higher education in a changing world

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From changing labour market needs to shifting online at the onset of the pandemic, higher education institutions have to keep pace with the changing environment in which they function. The same goes for External Quality Assurance (EQA) systems, which must also innovate and adapt their practices to remain relevant and useful for a rapidly expanding higher education sector. 

In a new book, A New Generation of External Quality Assurance , IIEP explores how external quality assurance has evolved since becoming a prominent feature of higher education reforms worldwide. At the start of the millennium, a global quality assurance model emerged as regional and international networks of quality assurance agencies cooperated. Setting pre-defined quality standards and criteria for self-assessments and peer reviews of study programmes and institutions became the global model for EQA.  

However, criticism of this model grew over time, and the authors explain how this led to innovations in external quality assurance. “The global model was increasingly seen as bureaucratic, heavy, expensive, and with uncertain benefits regarding quality improvement,” explains co-author Stamenka Uvalić-Trumbić, former head of section for higher education at UNESCO. “With this book, we wanted to collect the new trends of the decade that respond to these criticisms.” 

An international approach 

From Australia, Brazil, Egypt, across Europe, to India and beyond, the book documents emerging approaches in EQA through six main themes. By bringing these trends to the forefront, the book adds new value to conversations on how EQA should evolve internationally to remain relevant and address long-standing challenges and criticisms. 

"At a time when everything around us and in our lives are challenged, when all levels of our education systems are disrupted, this book comes out as a great addition to fill a gap in the field of quality assurance.  It offers a variety of different and innovative approaches to Quality Assurance and Accreditation of Higher Education.” - Dr. Youhansen Y. Eid, President of the National Authority for Quality Assurance and Accreditation of Education, Egypt.

An over-arching theme of the book is how to sustain quality assurance over time. “When the same processes are repeated over and over, the gains of EQA diminish,” says co-author Michaela Martin, interim head of IIEP research and development. “Therefore, it is important for quality assurance to focus on new issues and to adopt new ways of functioning.” One way quality assurance has responded to this is by embracing a lighter or risk-based approach to reduce the number of external reviews and better cope with rapidly expanding higher education systems. And, as individual institutions strive for greater autonomy, external quality assurance agencies have also taken on a greater role in assessing and supporting internal quality assurance in institutions.   

Student learning at the centre 

Another new development is the focus on quality teaching and learning, as well as using a student-centred approach and focusing on learning outcomes. Reinforced by national qualifications frameworks, this aims to measure and evaluate learning and teaching through various qualitative and quantitative metrics. More broadly, the Sustainable Development Goals have highlighted the importance of using quality assurance to advance inclusiveness, equity, and lifelong learning within the sector. Having this reflected in quality assurance is new. 

The authors also explore trends surrounding the rapid development of micro-credentials and ways to assure quality of Open and Distance Learning (ODL), such as Massive Open Online Courses (MOOCs). “This is not likely to be a passing fad, so more systematic approaches to micro-credentialing are being developed, which in turn raise the issue of more relevant and suitable QA procedures,” explain the authors. This includes looking at ways to turn micro-credentials into stackable units, which could ultimately become full qualifications that are quality assured. 

In 2019, the European MOOC Consortium launched the Common Microcredential Framework . One benefit is that mirco-credentials can be recognized between different higher education institutions, allowing learners to move from one institution to another, and progress to a larger qualification, such as a bachelor’s or master’s degree. 

As for online learning, there is now widespread recognition that different external quality assurance processes for traditional higher education and ODL is not appropriate. For example, in the United Arab Emirates the Commission for Academic Accreditation formerly had special standards for e-learning. However, the criteria for e-learning standards are now interwoven within the standards for face-to-face teaching. And in India, about 15% of  universities will soon be able to provide existing degree programmes exclusively online,  so  long  as  the  programmes  are  not  in  disciplines  that  require  lab  courses  or  other  forms  of  hands-on  study.  

Improving the efficiency of EQA 

Online aspects are also permeating quality assurance processes themselves. The book explores new trends in this area, including online submission of self-assessment reports to reduce the documentation load. While these were in place prior to COVID-19, the authors say more blended models of quality assurance will likely become permanent features to reduce costs and improve efficiency. 

In Egypt, the National Authority for Quality Assurance and Accreditation of Education introduced a new user-friendly electronic application system that will increase the efficiency of the accreditation process. While they need to create a strong back up and security system, the benefits have been far-reaching. The new system has made quality assurance work easier, reduced paperwork, and produced more reliable results. 

Looking forward 

Finally, the authors conclude with a warning for the future. As job markets continue to evolve, so will quality assurance. Ongoing digitization and robotization will affect both the demand for skills and the supply of qualifications. New skills profiles will emerge, and some jobs will either take on new forms, or disappear completely. Therefore, the authors write, “for qualifications to remain relevant, their quality needs  to  be  trusted,  and  QA  needs  to  adapt  to  the  quickly  evolving job market.”

“Over the next few years, I believe this book will be an asset to both higher education institutions and quality assurance agencies to face the inevitable transformations and challenges in the higher education ecosystem."   - Dr. Youhansen Y. Eid.

6 key themes in quality assurance (QA) innovation:

• Renewed focus on quality of teaching and learning
• QA of Open and Distance Learning
• QA of internationalization
• Societal impact and engagement
• Strengthening management of higher education institutions through QA
• Enhancing the efficiency and cost-effectiveness of external QA operations
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Bloom’s taxonomy.

Background Information | The Original Taxonomy | The Revised Taxonomy | Why Use Bloom’s Taxonomy? | Further Information

The above graphic is released under a Creative Commons Attribution license. You’re free to share, reproduce, or otherwise use it, as long as you attribute it to the Vanderbilt University Center for Teaching. For a higher resolution version, visit our Flickr account and look for the “Download this photo” icon.

Background Information

In 1956, Benjamin Bloom with collaborators Max Englehart, Edward Furst, Walter Hill, and David Krathwohl published a framework for categorizing educational goals: Taxonomy of Educational Objectives . Familiarly known as Bloom’s Taxonomy , this framework has been applied by generations of K-12 teachers and college instructors in their teaching.

The framework elaborated by Bloom and his collaborators consisted of six major categories: Knowledge, Comprehension, Application, Analysis, Synthesis, and Evaluation. The categories after Knowledge were presented as “skills and abilities,” with the understanding that knowledge was the necessary precondition for putting these skills and abilities into practice.

While each category contained subcategories, all lying along a continuum from simple to complex and concrete to abstract, the taxonomy is popularly remembered according to the six main categories.

The Original Taxonomy (1956)

Here are the authors’ brief explanations of these main categories in from the appendix of Taxonomy of Educational Objectives ( Handbook One , pp. 201-207):

• Knowledge “involves the recall of specifics and universals, the recall of methods and processes, or the recall of a pattern, structure, or setting.”
• Comprehension “refers to a type of understanding or apprehension such that the individual knows what is being communicated and can make use of the material or idea being communicated without necessarily relating it to other material or seeing its fullest implications.”
• Application refers to the “use of abstractions in particular and concrete situations.”
• Analysis represents the “breakdown of a communication into its constituent elements or parts such that the relative hierarchy of ideas is made clear and/or the relations between ideas expressed are made explicit.”
• Synthesis involves the “putting together of elements and parts so as to form a whole.”
• Evaluation engenders “judgments about the value of material and methods for given purposes.”

The 1984 edition of Handbook One is available in the CFT Library in Calhoun 116. See its ACORN record for call number and availability.

Barbara Gross Davis, in the “Asking Questions” chapter of Tools for Teaching , also provides examples of questions corresponding to the six categories. This chapter is not available in the online version of the book, but Tools for Teaching is available in the CFT Library. See its ACORN record for call number and availability.

The Revised Taxonomy (2001)

A group of cognitive psychologists, curriculum theorists and instructional researchers, and testing and assessment specialists published in 2001 a revision of Bloom’s Taxonomy with the title A Taxonomy for Teaching, Learning, and Assessment . This title draws attention away from the somewhat static notion of “educational objectives” (in Bloom’s original title) and points to a more dynamic conception of classification.

The authors of the revised taxonomy underscore this dynamism, using verbs and gerunds to label their categories and subcategories (rather than the nouns of the original taxonomy). These “action words” describe the cognitive processes by which thinkers encounter and work with knowledge:

• Recognizing
• Interpreting
• Exemplifying
• Classifying
• Summarizing
• Implementing
• Differentiating
• Attributing

In the revised taxonomy, knowledge is at the basis of these six cognitive processes, but its authors created a separate taxonomy of the types of knowledge used in cognition:

• Knowledge of terminology
• Knowledge of specific details and elements
• Knowledge of classifications and categories
• Knowledge of principles and generalizations
• Knowledge of theories, models, and structures
• Knowledge of subject-specific skills and algorithms
• Knowledge of subject-specific techniques and methods
• Knowledge of criteria for determining when to use appropriate procedures
• Strategic Knowledge
• Knowledge about cognitive tasks, including appropriate contextual and conditional knowledge
• Self-knowledge

Mary Forehand from the University of Georgia provides a guide to the revised version giving a brief summary of the revised taxonomy and a helpful table of the six cognitive processes and four types of knowledge.

Why Use Bloom’s Taxonomy?

The authors of the revised taxonomy suggest a multi-layered answer to this question, to which the author of this teaching guide has added some clarifying points:

• Objectives (learning goals) are important to establish in a pedagogical interchange so that teachers and students alike understand the purpose of that interchange.
• Organizing objectives helps to clarify objectives for themselves and for students.
• “plan and deliver appropriate instruction”;
• “design valid assessment tasks and strategies”;and
• “ensure that instruction and assessment are aligned with the objectives.”

Citations are from A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives .

Further Information

Section III of A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives , entitled “The Taxonomy in Use,” provides over 150 pages of examples of applications of the taxonomy. Although these examples are from the K-12 setting, they are easily adaptable to the university setting.

Section IV, “The Taxonomy in Perspective,” provides information about 19 alternative frameworks to Bloom’s Taxonomy, and discusses the relationship of these alternative frameworks to the revised Bloom’s Taxonomy.

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• Top universities pursuing sustainable development goals in 2024

Top universities for promoting quality education in 2024

University impact rankings for un sdg 4: quality education.

Times Higher Education has rigorously evaluated 1,681 universities from 122 countries/regions to rank those making a significant contribution toward the United Nations’ Sustainable Development Goal 4: quality education. These top institutions are recognised for their commitment to advancing the right to education and ensuring access to education at all levels, from childhood development through secondary education and beyond. By focusing on sustainable education practices, they equip students with relevant skills and foster effective learning outcomes that are essential for the future workforce.

The top universities excel in offering equitable quality education, promoting vocational training and providing lifelong learning opportunities. Their innovative approaches ensure that education is not only accessible but adaptable to the evolving needs of society, thereby supporting sustainable development and reducing inequalities within and among countries.

Summary of findings

The ranking for SDG 4: quality education is led by Aalborg University in Denmark. The top 10 is largely dominated by Asia, with two institutions from Hong Kong, two from Turkey, two from Pakistan, one from India and one from Bahrain.

Pakistan has the highest number of universities in the table at 86.

Methodology

Our methodology for SDG 4: quality education incorporates a comprehensive set of indicators to assess universities' contributions to education and learning across multiple dimensions:

Research on early years and lifelong learning education (27%)

• Number of studies on effective learning strategies and educational methodologies
• Proportion of education-related papers that are viewed or downloaded
• Proportion of education-related research in top journals

Proportion of graduates with a teaching qualification (15.4%)

• Proportion of graduates qualified to teach, reflecting the university's commitment to producing capable educators

Lifelong learning measures (26.8%)

• Provision of vocational training and career-oriented programmes
• Facilities and programmes for adult education and lifelong learning opportunities

Proportion of first-generation students (30.8%)

• Proportion of students who identify as being the first person in their immediate family to attend university, demonstrating the university’s commitment to education for disadvantaged groups and ensuring no group is left behind

The Impact Rankings are inherently dynamic: they are growing rapidly each year as many more universities seek to demonstrate their commitment to delivering the SDGs by joining our database; and they allow institutions to demonstrate rapid improvement year-on-year, by introducing clear new policies, for example, or by providing clearer and more open evidence of their progress. Therefore, we expect and welcome regular change in the ranked order of institutions (and we discourage year-on-year comparisons) as universities continue to drive this urgent agenda.

View the overall Impact Rankings 2024

Read our analysis of the Impact Rankings 2024 results

Download a free copy of the Impact Rankings 2024 digital report

Register to participate in next year’s Impact Rankings

To raise your university’s global profile with  Times Higher Education , contact  [email protected]

To unlock the data behind  THE ’s Impact Rankings and access a range of analytical and benchmarking tools,  click here  

Explore Impact Rankings for individual SDGs

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• Progress towards quality education was already slower than required before the pandemic, but COVID-19 has had devastating impacts on education, causing learning losses in four out of five of the 104 countries studied.

Without additional measures, an estimated 84 million children and young people will stay out of school by 2030 and approximately 300 million students will lack the basic numeracy and literacy skills necessary for success in life.

In addition to free primary and secondary schooling for all boys and girls by 2030, the aim is to provide equal access to affordable vocational training, eliminate gender and wealth disparities, and achieve universal access to quality higher education.

Education is the key that will allow many other Sustainable Development Goals (SDGs) to be achieved. When people are able to get quality education they can break from the cycle of poverty.

Education helps to reduce inequalities and to reach gender equality. It also empowers people everywhere to live more healthy and sustainable lives. Education is also crucial to fostering tolerance between people and contributes to more peaceful societies.

• To deliver on Goal 4, education financing must become a national investment priority. Furthermore, measures such as making education free and compulsory, increasing the number of teachers, improving basic school infrastructure and embracing digital transformation are essential.

What progress have we made so far?

While progress has been made towards the 2030 education targets set by the United Nations, continued efforts are required to address persistent challenges and ensure that quality education is accessible to all, leaving no one behind.

Between 2015 and 2021, there was an increase in worldwide primary school completion, lower secondary completion, and upper secondary completion. Nevertheless, the progress made during this period was notably slower compared to the 15 years prior.

What challenges remain?

According to national education targets, the percentage of students attaining basic reading skills by the end of primary school is projected to rise from 51 per cent in 2015 to 67 per cent by 2030. However, an estimated 300 million children and young people will still lack basic numeracy and literacy skills by 2030.

Economic constraints, coupled with issues of learning outcomes and dropout rates, persist in marginalized areas, underscoring the need for continued global commitment to ensuring inclusive and equitable education for all. Low levels of information and communications technology (ICT) skills are also a major barrier to achieving universal and meaningful connectivity.

Where are people struggling the most to have access to education?

Sub-Saharan Africa faces the biggest challenges in providing schools with basic resources. The situation is extreme at the primary and lower secondary levels, where less than one-half of schools in sub-Saharan Africa have access to drinking water, electricity, computers and the Internet.

Inequalities will also worsen unless the digital divide – the gap between under-connected and highly digitalized countries – is not addressed .

Are there groups that have more difficult access to education?

Yes, women and girls are one of these groups. About 40 per cent of countries have not achieved gender parity in primary education. These disadvantages in education also translate into lack of access to skills and limited opportunities in the labour market for young women.

What can we do?  

Ask our governments to place education as a priority in both policy and practice. Lobby our governments to make firm commitments to provide free primary school education to all, including vulnerable or marginalized groups.

Facts and figures

Goal 4 targets.

• Without additional measures, only one in six countries will achieve the universal secondary school completion target by 2030, an estimated 84 million children and young people will still be out of school, and approximately 300 million students will lack the basic numeracy and literacy skills necessary for success in life.
• To achieve national Goal 4 benchmarks, which are reduced in ambition compared with the original Goal 4 targets, 79 low- and lower-middle- income countries still face an average annual financing gap of $97 billion.

Source: The Sustainable Development Goals Report 2023

4.1  By 2030, ensure that all girls and boys complete free, equitable and quality primary and secondary education leading to relevant and Goal-4 effective learning outcomes

4.2  By 2030, ensure that all girls and boys have access to quality early childhood development, care and preprimary education so that they are ready for primary education

4.3  By 2030, ensure equal access for all women and men to affordable and quality technical, vocational and tertiary education, including university

4.4  By 2030, substantially increase the number of youth and adults who have relevant skills, including technical and vocational skills, for employment, decent jobs and entrepreneurship

4.5  By 2030, eliminate gender disparities in education and ensure equal access to all levels of education and vocational training for the vulnerable, including persons with disabilities, indigenous peoples and children in vulnerable situations

4.6  By 2030, ensure that all youth and a substantial proportion of adults, both men and women, achieve literacy and numeracy

4.7  By 2030, ensure that all learners acquire the knowledge and skills needed to promote sustainable development, including, among others, through education for sustainable development and sustainable lifestyles, human rights, gender equality, promotion of a culture of peace and non-violence, global citizenship and appreciation of cultural diversity and of culture’s contribution to sustainable development

4.A  Build and upgrade education facilities that are child, disability and gender sensitive and provide safe, nonviolent, inclusive and effective learning environments for all

4.B  By 2020, substantially expand globally the number of scholarships available to developing countries, in particular least developed countries, small island developing States and African countries, for enrolment in higher education, including vocational training and information and communications technology, technical, engineering and scientific programmes, in developed countries and other developing countries

4.C  By 2030, substantially increase the supply of qualified teachers, including through international cooperation for teacher training in developing countries, especially least developed countries and small island developing states

UN Educational, Scientific and Cultural Organization

UN Children’s Fund

UN Development Programme

Global Education First Initiative

UN Population Fund: Comprehensive sexuality education

UN Office of the Secretary General’s Envoy on Youth

Fast Facts: Quality Education

Infographic: Quality Education

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The 10 NAEYC Program Standards

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NAEYC has set 10 standards for early childhood programs that can help families make the right choice when they are looking for a child care center, preschool, or kindergarten. The standards and criteria are also the foundation of the NAEYC Accreditation system for early childhood programs. To earn accreditation, programs must meet all 10 standards.

Based on research on the development and education of young children, the standards were created with input from experts and educators from around the country. The standards define what NAEYC—the world’s largest organization of early childhood professionals—believes all early childhood programs should provide.

Review this guide to help identify programs that meet NAEYC standards for high-quality programs.

The Standards

Standard 1: relationships, standard 2: curriculum, standard 3: teaching, standard 4: assessment of child progress, standard 5: health.

• Standard 6: Staff Competencies, Preparation, and Support  

Standard 7: Families

Standard 8: community relationships, standard 9: physical environment, standard 10: leadership and management.

Warm, sensitive, and responsive relationships help children feel secure. The safe and secure environments built by positive relationships help children thrive physically, benefit from learning experiences, and cooperate and get along with others.

What to look for in a program:

• Children and adults feel welcome when they visit the program. Teachers help new children adjust to the program environment and make friends with other children.
• Teaching staff engage in warm, friendly conversations with the children and encourage and recognize children’s work and accomplishments.
• Children are encouraged to play and work together.
• Teachers help children resolve conflicts by identifying feelings, describing problems, and trying alternative solutions. Teaching staff never physically punish children.

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A well-planned written curriculum provides a guide for teachers and administrators. It helps them work together and balance different activities and approaches to maximize children’s learning and development. The curriculum includes goals for the content that children are learning, planned activities linked to these goals, daily schedules and routines, and materials to be used.

NAEYC and the NAEYC Accreditation system do not prescribe a specific curriculum; programs can design their own or choose a commercially available curriculum that meets NAEYC’s guidelines.

• Ask about the program’s curriculum and how it addresses all aspects of child development. The curriculum should not focus on just one area of development.
• Children are given opportunities to learn and develop through exploration and play, and teachers have opportunities to work with individual children and small groups on specific skills.
• Materials and equipment spark children’s interest and encourage them to experiment and learn.
• Activities are designed to help children get better at reasoning, solving problems, getting along with others, using language, and developing other skills.
• Infants and toddlers play with toys and art materials that “do something” based on children’s actions, such as jack-in-the-box, cups that fit inside one another, and playdough.

Children have different learning styles, needs, capacities, interests, and backgrounds. By recognizing these differences and using instructional approaches that are appropriate for each child, teachers and staff help all children learn.

• Teachers carefully supervise all children.
• Teachers provide time each day for indoor and outdoor activities (weather permitting) and organize time and space so that children have opportunities to work or play individually and in groups.
• Children’s recent work (for example, art and emergent writing) is displayed in the classroom to help children reflect on and extend their learning.
• Teachers modify strategies and materials to respond to the needs and interests of individual children, engaging each child and enhancing learning.

Assessment results benefit children by informing sound decisions, teaching, and program improvement.

Assessments help teachers plan appropriately challenging curriculum and tailor instruction that responds to each child’s strengths and needs. Assessments can also help teachers identify children with disabilities and ensuring that they receive needed services.

• The program supports children’s learning using a variety of assessment methods, such as observations, checklists, and rating scales.
• Assessment methods are appropriate for each child’s age and level of development and encompass all areas of development, including math, science, and other cognitive skills; language; social-emotional; and physical.
• Teachers use assessment methods and information to design goals for individual children and monitor their progress, as well as to improve the program and its teaching strategies.
• Families receive information about their child’s development and learning on a regular basis, including through meetings or conferences.

• Teaching staff have training in pediatric first aid.
• Infants are placed on their backs to sleep.
• The program has policies regarding regular hand washing and routinely cleans and sanitizes all surfaces in the facility.
• There is a clear plan for responding to illness, including how to decide whether a child needs to go home and how families will be notified.
• Snacks and meals are nutritious, and food is prepared and stored safely.

Standard 6: Staff Competencies, Preparation, and Support 

Teachers who have specific preparation, knowledge, and skills in child development and early childhood education are more likely to provide positive interactions, richer language experiences, and quality learning environments.

• Teaching staff have educational qualifications and specialized knowledge about young children and early childhood development. Ask, for example, how many teachers have Child Development Associate (CDA) credentials, associate’s degrees, or higher degrees.
• The program makes provisions for ongoing staff development, including orientations for new staff and opportunities for continuing education.
• Teaching staff have training in the program’s curriculum and work as a teaching team.

• All families are welcome and encouraged to be involved in all aspects of the program.
• Teachers and staff talk with families about their family structure and their views on childrearing and use that information to adapt the curriculum and teaching methods to the families served.
• The program uses a variety of strategies to communicate with families, including family conferences, new family orientations, and individual conversations.
• Program information—including policies and operating procedures—is provided in a language that families can understand.

• The program connects with and uses museums, parks, libraries, zoos, and other resources in the community.
• Representatives from community programs, such as musical performers and local artists, are invited to share their interests and talents with the children.
• The staff develop professional relationships with community agencies and organizations that further the program’s capacity to meet the needs and interests of children and families.

An organized, properly equipped, and well-maintained program environment facilitates the learning, comfort, health, and safety of the children and adults who use the program.

• The facility is designed so that staff can supervise all children by sight and sound.
• The program has necessary furnishings, such as hand-washing sinks, child-size chairs and tables, and cots, cribs, beds, or sleeping pads.
• A variety of materials and equipment appropriate for children’s ages, skills and abilities is available and kept clean, safe, and in good repair.
• Outdoor play areas have fences or natural barriers that prevent access to streets and other hazards.
• First-aid kits, fire extinguishers, fire alarms, and other safety equipment are installed and available.

Effective management and operations, knowledgeable leaders, and sensible policies and procedures are essential to building a quality program and maintaining the quality over time.

• The program administrator has the necessary educational qualifications, including a degree from a four-year college and specialized courses in early childhood education, child development, or related fields.
• The program is licensed and/or regulated by the applicable state agency.
• The program’s written policies and procedures are shared with families and address issues such as the program’s philosophy and curriculum goals, policies on guidance and discipline, and health and safety procedures.
• Appropriate group sizes and ratios of teaching staff to children are maintained (for example, infants—no more than 8 children in a group, with 2 teaching staff; toddlers—no more than 12 children in a group, with 2 teaching staff; and 4-year-olds—no more than 20 children in a group, with 2 teaching staff).

Families on NAEYC-Accredited programs

“Valued teachers lead to valued children … Accredited programs tend to attract employees who not only view themselves as educators, they consider themselves child advocates.” — Kate in San Antonio, Texas. Her child attends an NAEYC-Accredited program.

“Choosing a preschool for my first child was somewhat overwhelming, so when you find a program accredited by NAEYC, it adds peace of mind that you’re making a good choice for your child.” — Jen in Torrance, California. Her child attends an NAEYC-Accredited program.

“NAEYC is an organization that can be trusted with the future of my child’s education … That is why I chose an NAEYC-Accredited center—nothing but the best.” — Jennifer in Newark, New Jersey. Her child attends an NAEYC-Accredited program.

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The state of AI in 2023: Generative AI’s breakout year

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The latest annual McKinsey Global Survey  on the current state of AI confirms the explosive growth of generative AI (gen AI) tools . Less than a year after many of these tools debuted, one-third of our survey respondents say their organizations are using gen AI regularly in at least one business function. Amid recent advances, AI has risen from a topic relegated to tech employees to a focus of company leaders: nearly one-quarter of surveyed C-suite executives say they are personally using gen AI tools for work, and more than one-quarter of respondents from companies using AI say gen AI is already on their boards’ agendas. What’s more, 40 percent of respondents say their organizations will increase their investment in AI overall because of advances in gen AI. The findings show that these are still early days for managing gen AI–related risks, with less than half of respondents saying their organizations are mitigating even the risk they consider most relevant: inaccuracy.

The organizations that have already embedded AI capabilities have been the first to explore gen AI’s potential, and those seeing the most value from more traditional AI capabilities—a group we call AI high performers—are already outpacing others in their adoption of gen AI tools. 1 We define AI high performers as organizations that, according to respondents, attribute at least 20 percent of their EBIT to AI adoption.

The expected business disruption from gen AI is significant, and respondents predict meaningful changes to their workforces. They anticipate workforce cuts in certain areas and large reskilling efforts to address shifting talent needs. Yet while the use of gen AI might spur the adoption of other AI tools, we see few meaningful increases in organizations’ adoption of these technologies. The percent of organizations adopting any AI tools has held steady since 2022, and adoption remains concentrated within a small number of business functions.

Table of Contents

• It’s early days still, but use of gen AI is already widespread
• Leading companies are already ahead with gen AI
• AI-related talent needs shift, and AI’s workforce effects are expected to be substantial
• With all eyes on gen AI, AI adoption and impact remain steady

About the research

1. it’s early days still, but use of gen ai is already widespread.

The findings from the survey—which was in the field in mid-April 2023—show that, despite gen AI’s nascent public availability, experimentation with the tools  is already relatively common, and respondents expect the new capabilities to transform their industries. Gen AI has captured interest across the business population: individuals across regions, industries, and seniority levels are using gen AI for work and outside of work. Seventy-nine percent of all respondents say they’ve had at least some exposure to gen AI, either for work or outside of work, and 22 percent say they are regularly using it in their own work. While reported use is quite similar across seniority levels, it is highest among respondents working in the technology sector and those in North America.

Organizations, too, are now commonly using gen AI. One-third of all respondents say their organizations are already regularly using generative AI in at least one function—meaning that 60 percent of organizations with reported AI adoption are using gen AI. What’s more, 40 percent of those reporting AI adoption at their organizations say their companies expect to invest more in AI overall thanks to generative AI, and 28 percent say generative AI use is already on their board’s agenda. The most commonly reported business functions using these newer tools are the same as those in which AI use is most common overall: marketing and sales, product and service development, and service operations, such as customer care and back-office support. This suggests that organizations are pursuing these new tools where the most value is. In our previous research , these three areas, along with software engineering, showed the potential to deliver about 75 percent of the total annual value from generative AI use cases.

In these early days, expectations for gen AI’s impact are high : three-quarters of all respondents expect gen AI to cause significant or disruptive change in the nature of their industry’s competition in the next three years. Survey respondents working in the technology and financial-services industries are the most likely to expect disruptive change from gen AI. Our previous research shows  that, while all industries are indeed likely to see some degree of disruption, the level of impact is likely to vary. 2 “ The economic potential of generative AI: The next productivity frontier ,” McKinsey, June 14, 2023. Industries relying most heavily on knowledge work are likely to see more disruption—and potentially reap more value. While our estimates suggest that tech companies, unsurprisingly, are poised to see the highest impact from gen AI—adding value equivalent to as much as 9 percent of global industry revenue—knowledge-based industries such as banking (up to 5 percent), pharmaceuticals and medical products (also up to 5 percent), and education (up to 4 percent) could experience significant effects as well. By contrast, manufacturing-based industries, such as aerospace, automotives, and advanced electronics, could experience less disruptive effects. This stands in contrast to the impact of previous technology waves that affected manufacturing the most and is due to gen AI’s strengths in language-based activities, as opposed to those requiring physical labor.

Responses show many organizations not yet addressing potential risks from gen AI

According to the survey, few companies seem fully prepared for the widespread use of gen AI—or the business risks these tools may bring. Just 21 percent of respondents reporting AI adoption say their organizations have established policies governing employees’ use of gen AI technologies in their work. And when we asked specifically about the risks of adopting gen AI, few respondents say their companies are mitigating the most commonly cited risk with gen AI: inaccuracy. Respondents cite inaccuracy more frequently than both cybersecurity and regulatory compliance, which were the most common risks from AI overall in previous surveys. Just 32 percent say they’re mitigating inaccuracy, a smaller percentage than the 38 percent who say they mitigate cybersecurity risks. Interestingly, this figure is significantly lower than the percentage of respondents who reported mitigating AI-related cybersecurity last year (51 percent). Overall, much as we’ve seen in previous years, most respondents say their organizations are not addressing AI-related risks.

2. Leading companies are already ahead with gen AI

The survey results show that AI high performers—that is, organizations where respondents say at least 20 percent of EBIT in 2022 was attributable to AI use—are going all in on artificial intelligence, both with gen AI and more traditional AI capabilities. These organizations that achieve significant value from AI are already using gen AI in more business functions than other organizations do, especially in product and service development and risk and supply chain management. When looking at all AI capabilities—including more traditional machine learning capabilities, robotic process automation, and chatbots—AI high performers also are much more likely than others to use AI in product and service development, for uses such as product-development-cycle optimization, adding new features to existing products, and creating new AI-based products. These organizations also are using AI more often than other organizations in risk modeling and for uses within HR such as performance management and organization design and workforce deployment optimization.

AI high performers are much more likely than others to use AI in product and service development.

Another difference from their peers: high performers’ gen AI efforts are less oriented toward cost reduction, which is a top priority at other organizations. Respondents from AI high performers are twice as likely as others to say their organizations’ top objective for gen AI is to create entirely new businesses or sources of revenue—and they’re most likely to cite the increase in the value of existing offerings through new AI-based features.

As we’ve seen in previous years , these high-performing organizations invest much more than others in AI: respondents from AI high performers are more than five times more likely than others to say they spend more than 20 percent of their digital budgets on AI. They also use AI capabilities more broadly throughout the organization. Respondents from high performers are much more likely than others to say that their organizations have adopted AI in four or more business functions and that they have embedded a higher number of AI capabilities. For example, respondents from high performers more often report embedding knowledge graphs in at least one product or business function process, in addition to gen AI and related natural-language capabilities.

While AI high performers are not immune to the challenges of capturing value from AI, the results suggest that the difficulties they face reflect their relative AI maturity, while others struggle with the more foundational, strategic elements of AI adoption. Respondents at AI high performers most often point to models and tools, such as monitoring model performance in production and retraining models as needed over time, as their top challenge. By comparison, other respondents cite strategy issues, such as setting a clearly defined AI vision that is linked with business value or finding sufficient resources.

The findings offer further evidence that even high performers haven’t mastered best practices regarding AI adoption, such as machine-learning-operations (MLOps) approaches, though they are much more likely than others to do so. For example, just 35 percent of respondents at AI high performers report that where possible, their organizations assemble existing components, rather than reinvent them, but that’s a much larger share than the 19 percent of respondents from other organizations who report that practice.

Many specialized MLOps technologies and practices  may be needed to adopt some of the more transformative uses cases that gen AI applications can deliver—and do so as safely as possible. Live-model operations is one such area, where monitoring systems and setting up instant alerts to enable rapid issue resolution can keep gen AI systems in check. High performers stand out in this respect but have room to grow: one-quarter of respondents from these organizations say their entire system is monitored and equipped with instant alerts, compared with just 12 percent of other respondents.

3. AI-related talent needs shift, and AI’s workforce effects are expected to be substantial

Our latest survey results show changes in the roles that organizations are filling to support their AI ambitions. In the past year, organizations using AI most often hired data engineers, machine learning engineers, and Al data scientists—all roles that respondents commonly reported hiring in the previous survey. But a much smaller share of respondents report hiring AI-related-software engineers—the most-hired role last year—than in the previous survey (28 percent in the latest survey, down from 39 percent). Roles in prompt engineering have recently emerged, as the need for that skill set rises alongside gen AI adoption, with 7 percent of respondents whose organizations have adopted AI reporting those hires in the past year.

The findings suggest that hiring for AI-related roles remains a challenge but has become somewhat easier over the past year, which could reflect the spate of layoffs at technology companies from late 2022 through the first half of 2023. Smaller shares of respondents than in the previous survey report difficulty hiring for roles such as AI data scientists, data engineers, and data-visualization specialists, though responses suggest that hiring machine learning engineers and AI product owners remains as much of a challenge as in the previous year.

Looking ahead to the next three years, respondents predict that the adoption of AI will reshape many roles in the workforce. Generally, they expect more employees to be reskilled than to be separated. Nearly four in ten respondents reporting AI adoption expect more than 20 percent of their companies’ workforces will be reskilled, whereas 8 percent of respondents say the size of their workforces will decrease by more than 20 percent.

Looking specifically at gen AI’s predicted impact, service operations is the only function in which most respondents expect to see a decrease in workforce size at their organizations. This finding generally aligns with what our recent research  suggests: while the emergence of gen AI increased our estimate of the percentage of worker activities that could be automated (60 to 70 percent, up from 50 percent), this doesn’t necessarily translate into the automation of an entire role.

AI high performers are expected to conduct much higher levels of reskilling than other companies are. Respondents at these organizations are over three times more likely than others to say their organizations will reskill more than 30 percent of their workforces over the next three years as a result of AI adoption.

4. With all eyes on gen AI, AI adoption and impact remain steady

While the use of gen AI tools is spreading rapidly, the survey data doesn’t show that these newer tools are propelling organizations’ overall AI adoption. The share of organizations that have adopted AI overall remains steady, at least for the moment, with 55 percent of respondents reporting that their organizations have adopted AI. Less than a third of respondents continue to say that their organizations have adopted AI in more than one business function, suggesting that AI use remains limited in scope. Product and service development and service operations continue to be the two business functions in which respondents most often report AI adoption, as was true in the previous four surveys. And overall, just 23 percent of respondents say at least 5 percent of their organizations’ EBIT last year was attributable to their use of AI—essentially flat with the previous survey—suggesting there is much more room to capture value.

Organizations continue to see returns in the business areas in which they are using AI, and they plan to increase investment in the years ahead. We see a majority of respondents reporting AI-related revenue increases within each business function using AI. And looking ahead, more than two-thirds expect their organizations to increase their AI investment over the next three years.

The online survey was in the field April 11 to 21, 2023, and garnered responses from 1,684 participants representing the full range of regions, industries, company sizes, functional specialties, and tenures. Of those respondents, 913 said their organizations had adopted AI in at least one function and were asked questions about their organizations’ AI use. To adjust for differences in response rates, the data are weighted by the contribution of each respondent’s nation to global GDP.

The survey content and analysis were developed by Michael Chui , a partner at the McKinsey Global Institute and a partner in McKinsey’s Bay Area office, where Lareina Yee is a senior partner; Bryce Hall , an associate partner in the Washington, DC, office; and senior partners Alex Singla and Alexander Sukharevsky , global leaders of QuantumBlack, AI by McKinsey, based in the Chicago and London offices, respectively.

They wish to thank Shivani Gupta, Abhisek Jena, Begum Ortaoglu, Barr Seitz, and Li Zhang for their contributions to this work.

This article was edited by Heather Hanselman, an editor in the Atlanta office.

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