2,007
Views
1
CrossRef citations to date
0
Altmetric
Articles

Insights from Two Decades of PISA-related Studies in the New Century: A Systematic Review

ORCID Icon, ORCID Icon & ORCID Icon
Pages 371-388 | Received 13 Jan 2022, Accepted 31 Oct 2022, Published online: 29 Nov 2022

References

  • Agasisti, T. (2014). The efficiency of public spending on education: An empirical comparison of EU countries. European Journal of Education, 49(4), 543–557. https://doi.org/10.1111/ejed.12069
  • Ainley, M., & Ainley, J. (2011). Student engagement with science in early adolescence: The contribution of enjoyment to students’ continuing interest in learning about science. Contemporary Educational Psychology, 36(1), 4–12. https://doi.org/10.1016/j.cedpsych.2010.08.001
  • Aksu, G., & Guzeller, C. O. (2016). Classification of PISA 2012 mathematical literacy scores using decision-tree method: Turkey sampling. Education and Science, 41(185), 101–122. https://doi.org/10.15390/EB.2016.4766
  • Anders, J., Jerrim, J., & McCulloch, A. (2016). How much progress do children in Shanghai make over one academic year? Evidence from PISA AERA Open, 2(4), 233285841667884. https://doi.org/10.1177/2332858416678841
  • Bidegain, G., & Lukas, J. F. (2020). Exploring the relationship between attitudes toward science and PISA scientific performance. Revista de Psicodidactica (English ed.), 25(1), 1–12. https://doi.org/10.1016/j.psicoe.2019.08.002
  • Bybee, R. W., & Stage, E. (2005). No country left behind. Issues in Science and Technology, 21(2), 69–75. https://www.jstor.org/stable/43314255
  • Cairns, D., & Areepattamannil, S. (2019). Exploring the relations of inquiry-based teaching to science achievement and dispositions in 54 countries. Research in Science Education, 49(1), 1–23. https://doi.org/10.1007/s11165-017-9639-x
  • Callan, G. L., Marchant, G. J., Finch, W. H., & Flegge, L. (2017). Student and school SES, gender, strategy use, and achievement. Psychology in the Schools, 54(9), 1106–1122. https://doi.org/10.1002/pits.22049
  • Cheung, K. C., Mak, S. K., Sit, P. S., & Soh, K. C. (2016). A typology of student reading engagement: Preparing for response to intervention in the school curriculum. Studies in Educational Evaluation, 48, 32–42. https://doi.org/10.1016/j.stueduc.2015.12.001
  • Cheung, K. C., Sit, P. S., Soh, K. C., Ieong, M. K., & Mak, S. K. (2014). Predicting academic resilience with reading engagement and demographic variables: Comparing Shanghai, Hong Kong, Korea, and Singapore from the PISA perspective. The Asia-Pacific Education Researcher, 23(4), 895–909. https://doi.org/10.1007/s40299-013-0143-4
  • Chiu, M. M. (2015). Family inequality, school inequalities, and mathematics achievement in 65 countries: Microeconomic mechanisms of rent seeking and diminishing marginal returns. Teachers College Record, 117(1), 1–32. https://doi.org/10.1177/016146811511700105
  • Deng, Z., & Gopinathan, S. (2016). PISA and high-performing education systems: Explaining Singapore’s education success. Comparative Education, 52(4), 449–472. https://doi.org/10.1080/03050068.2016.1219535
  • Domínguez, M., Vieira, M. J., & Vidal, J. (2012). The impact of the Programme for International Student Assessment on academic journals. Assessment in Education: Principles, Policy & Practice, 19(4), 393–409. https://doi.org/10.1080/0969594X.2012.659175
  • Eriksson, K., Björnstjerna, M., & Vartanova, I. (2020). The relation between gender egalitarian values and gender differences in academic achievement. Frontiers in Psychology, 11(236). https://doi.org/10.3389/fpsyg.2020.00236
  • Fang, Z., Grant, L. W., Xu, X., Stronge, J. H., & Ward, T. J. (2013). An international comparison investigating the relationship between national culture and student achievement. Educational Assessment, Evaluation and Accountability, 25(3), 159–177. https://doi.org/10.1007/s11092-013-9171-0
  • Galloway, N., & Rose, H. (2015). Introducing global Englishes. Routledge.
  • Gamazo, A., & Martínez-Abad, F. (2020). An exploration of factors linked to academic performance in PISA 2018 through data mining techniques. Frontiers in Psychology, 11, 3365. https://doi.org/10.3389/fpsyg.2020.575167
  • Han, S. W., Borgonovi, F., & Guerriero, S. (2020). Why don’t more boys want to become teachers? The effect of a gendered profession on students’ career expectations. International Journal of Educational Research, 103, Article 101645. https://doi.org/10.1016/j.ijer.2020.101645
  • Hermann, Z., & Kopasz, M. (2021). Educational policies and the gender gap in test scores: A cross-country analysis. Research Papers in Education, 36(4), 461–482. https://doi.org/10.1080/02671522.2019.1678065
  • Hopfenbeck, T. N., Lenkeit, J., El Masri, Y., Cantrell, K., Ryan, J., & Baird, J. A. (2018). Lessons learned from PISA: A systematic review of peer-reviewed articles on the Programme for International Student Assessment. Scandinavian Journal of Educational Research, 62(3), 333–353. https://doi.org/10.1080/00313831.2016.1258726
  • Howie, S., & Plomp, T. (2005). International comparative studies of education and large-scale change. In N. Bascia, A. Cumming, A. Datnow, K. Leithwood, & D. Livingstone (Eds.), International handbook of educational policy (pp. 75–79). Springer. http://doi.org/10.1007/1-4020-3201-3_4
  • Hu, X., Leung, F. K., & Teng, Y. (2018). The influence of culture on students’ mathematics achievement across 51 countries. International Journal of Science and Mathematics Education, 16(1), 7–24. https://doi.org/10.1007/s10763-018-9899-6
  • Huang, L. (2020). Peer victimization, teacher unfairness, and adolescent life satisfaction: The mediating roles of sense of belonging to school and schoolwork-related anxiety. School Mental Health, 12(3), 556–566. https://doi.org/10.1007/s12310-020-09365-y
  • Huang, L. (2021). Bullying victimization, self-efficacy, fear of failure, and adolescents’ subjective well-being in China. Children and Youth Services Review, 127, 106084. https://doi.org/10.1016/j.childyouth.2021.106084
  • Huang, X., Wilson, M., & Wang, L. (2016). Exploring plausible causes of differential item functioning in the PISA science assessment: Language, curriculum or culture. Educational Psychology, 36(2), 378–390. https://doi.org/10.1080/01443410.2014.946890
  • Hutchison, D., & Schagen, I. (2007). Comparisons between PISA and TIMSS: Are we the man with two watches. In T. Loveless (Ed.), Lessons learned: What international assessments tell us about math achievement (pp. 227–261). Brookings. https://www.iea.nl/sites/default/files/2019-04/IRC2006_Hutchison_Schagen.pdf
  • Hwang, J., Choi, K. M., Bae, Y., & Shin, D. H. (2018). Do teachers’ instructional practices moderate equity in mathematical and scientific literacy: An investigation of the PISA 2012 and 2015. International Journal of Science and Mathematics Education, 16(1), 25–45. https://doi.org/10.1007/s10763-018-9909-8
  • İleritürk, D., & Yavaş Kıncal, R. (2016). The review of variables related to problem solving skills in PISA 2003-2012 of Turkey. Sakarya University Journal of Education, 6(3), 40–53. https://doi.org/10.19126/suje.220179
  • Jansen, M., Scherer, R., & Schroeders, U. (2015). Students’ self-concept and self-efficacy in the sciences: Differential relations to antecedents and educational outcomes. Contemporary Educational Psychology, 41, 13–24. https://doi.org/10.1016/j.cedpsych.2014.11.002
  • Jensen, P., & Rasmussen, A. W. (2011). The effect of immigrant concentration in schools on native and immigrant children's Reading and math skills. Economics of Education Review, 30(6), 1503–1515. https://doi.org/10.1016/j.econedurev.2011.08.002
  • Julià, A. (2016). School context and gender inequalities in reading achievement. Revista Española de Investigaciones Sociológicas (REIS), 156, 41–56. https://doi.org/10.5477/cis/reis.156.41
  • Kang, J., & Keinonen, T. (2017). The effect of inquiry-based learning experiences on adolescents’ science-related career aspiration in the Finnish context. International Journal of Science Education, 39(12), 1669–1689. https://doi.org/10.1080/09500693.2017.1350790
  • Lara-Porras, A. M., del Mar Rueda-García, M., & Molina-Muñoz, D. (2019). Identifying the factors influencing mathematical literacy in several Spanish regions. South African Journal of Education, 39(1), 1–12. https://doi.org/10.15700/saje.v39ns2a1630
  • Lau, K. C. (2009). A critical examination of PISA’s assessment on scientific literacy. International Journal of Science and Mathematics Education, 7(6), 1061–1088. https://doi.org/10.1007/s10763-009-9154-2
  • Livinski, A., Joubert, D., & Terry, N. (2015). Undertaking a systematic review: What you need to know. National Institutes of Health, U.S. Department of Health and Human Services. https://www.nihlibrary.nih.gov/sites/default/files/SR_Training_oct2015.pdf
  • Lv, Y. Z. (2018). New trend of PISA participation and the discussion of its essence. International and Comparative Education, 6, 99–105.
  • Ma, L., Luo, H., & Xiao, L. (2021). Perceived teacher support, self-concept, enjoyment and achievement in reading: A multilevel mediation model based on PISA 2018. Learning and Individual Differences, 85, 101947. https://doi.org/10.1016/j.lindif.2020.101947
  • Mak, S. K., Cheung, K. C., Soh, K. C., Sit, P. S., & Ieong, M. K. (2017). An examination of student- and across-level mechanisms accounting for gender differences in reading performance: A multilevel analysis of reading engagement. Educational Psychology, 37(10), 1206–1221. https://doi.org/10.1080/01443410.2016.1242712
  • Marks, G. N. (2006). Are between- and within-school differences in student performance largely due to socio-economic background? Evidence from 30 countries. Educational Research, 48(1), 21–40. https://doi.org/10.1080/00131880500498396
  • Martínez-Abad, F., Gamazo, A., & Rodríguez-Conde, M. J. (2020). Educational data mining: Identification of factors associated with school effectiveness in PISA assessment. Studies in Educational Evaluation, 66, 100875. https://doi.org/10.1016/j.stueduc.2020.100875
  • Morris, P. (2015). Comparative education, PISA, politics and educational reform: A cautionary note. Compare: A Journal of Comparative and International Education, 45(3), 470–474. https://doi.org/10.1080/03057925.2015.1027510
  • Nagengast, B., & Marsh, H. W. (2012). Big fish in little ponds aspire more: Mediation and cross-cultural generalizability of school-average ability effects on self-concept and career aspirations in science. Journal of Educational Psychology, 104(4), 1033–1053. https://doi.org/10.1037/a0027697
  • Ning, B. (2020). Discipline, motivation, and achievement in mathematics learning: An exploration in Shanghai. School Psychology International, 41(6), 595–611. https://doi.org/10.1177/0143034320961465
  • Ning, B., Van Damme, J., Van Den Noortgate, W., Yang, X., & Gielen, S. (2015). The influence of classroom disciplinary climate of schools on Reading achievement: A cross-country comparative study. School Effectiveness and School Improvement, 26(4), 586–611. https://doi.org/10.1080/09243453.2015.1025796
  • Odell, B., Cutumisu, M., & Gierl, M. (2020). A scoping review of the relationship between students’ ICT and performance in mathematics and science in the PISA data. Social Psychology of Education, 23(6), 1–33. https://doi.org/10.1007/s11218-020-09591-x
  • Organization for Economic Co-operation and Development (OECD). (2014). PISA 2012 results in focus: What 15-year-olds know and what they can do with what they know. OECD Publishing. https://www.oecd.org/pisa/keyfindings/pisa-2012-results-overview.pdf
  • Organization for Economic Co-operation and Development (OECD). (2019). PISA 2018 results: Combined executive summaries, Volume I, II, III. OECD Publishing. https://www.oecd.org/pisa/Combined_Executive_Summaries_PISA_2018.pdf
  • Owens, T. L. (2013). Thinking beyond league tables: A review of key PISA research questions. In H. D. Meyer & A. Benavot (Eds.), PISA, power and policy: The emergence of global educational governance (pp. 27-49). University of Oxford.
  • Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., … Moher, D. (2021). Updating guidance for reporting systematic reviews: Development of the PRISMA 2020 statement. Journal of Clinical Epidemiology, 134, 103–112. https://doi.org/10.1016/j.jclinepi.2021.02.003
  • Põder, K., Lauri, T., & Veski, A. (2017). Does school admission by zoning affect educational inequality? A study of family background effect in Estonia, Finland, and Sweden. Scandinavian Journal of Educational Research, 61(6), 668–688. https://doi.org/10.1080/00313831.2016.1173094
  • Pons, X. (2017). Fifteen years of research on PISA effects on education governance: A critical review. European Journal of Education, 52(2), 131–144. https://doi.org/10.1111/ejed.12213
  • Qiao, X., & Jiao, H. (2018). Data mining techniques in analyzing process data: A didactic. Frontiers in Psychology, 9, 2231. https://doi.org/10.3389/fpsyg.2018.02231
  • Salinas-Jimenez, J., & Santin, D. (2012). School choice and the influence of immigration on Spanish educational achievements in the 2006 PISA. Revista de Educación (Madrid), 358, 382–405. https://doi.org/10.4438/1988-592X-RE-2011-358-083
  • Santibañez, L., & Fagioli, L. (2016). Nothing succeeds like success? Equity, student outcomes, and opportunity to learn in high-and middle-income countries. International Journal of Behavioral Development, 40(6), 517–525. https://doi.org/10.1177/0165025416642050
  • Santos, Í, & Centeno, V. G. (2021). Inspirations from abroad: The impact of PISA on countries’ choice of reference societies in education. Compare: A Journal of Comparative and International Education, 1–18. https://doi.org/10.1080/03057925.2021.1906206
  • Sasiwuttiwat, S., & Tangkitvanich, S. (2019). Is there an “East Asian education model”? A study on varieties of education regimes. Asian Economic Papers, 18(1), 123–146. https://doi.org/10.1162/asep_a_00666
  • Schmidt, W. H., Guo, S., & Houang, R. T. (2021). The role of opportunity to learn in ethnic inequality in mathematics. Journal of Curriculum Studies, 53(5), 579–600. https://doi.org/10.1080/00220272.2020.1863475
  • Siddaway, A. P., Wood, A. M., & Hedges, L. V. (2019). How to do a systematic review: A best practice guide for conducting and reporting narrative reviews, meta-analyses, and meta-syntheses. Annual Review of Psychology, 70(1), 747–770. https://doi.org/10.1146/annurev-psych-010418-102803
  • Skryabin, M., Zhang, J., Liu, L., & Zhang, D. (2015). How the ICT development level and usage influence student achievement in reading, mathematics, and science. Computers & Education, 85, 49–58. https://doi.org/10.1016/j.compedu.2015.02.004
  • Soh, K. (2014). Finland and Singapore in PISA 2009: Similarities and differences in achievements and school management. Compare: A Journal of Comparative and International Education, 44(3), 455–471. https://doi.org/10.1080/03057925.2013.787286
  • Spörlein, C., & Schlueter, E. (2018). How education systems shape cross-national ethnic inequality in math competence scores: Moving beyond mean differences. PLoS ONE, 13(3), e0193738. https://doi.org/10.1371/journal.pone.0193738
  • Stoet, G., Bailey, D. H., Moore, A. M., & Geary, D. C. (2016). Countries with higher levels of gender equality show larger national sex differences in mathematics anxiety and relatively lower parental mathematics valuation for girls. PLoS ONE, 11(4), e0153857. https://doi.org/10.1371/journal.pone.0153857
  • Stoet, G., & Geary, D. C. (2013). Sex differences in mathematics and reading achievement are inversely related: Within-and across-nation assessment of 10 years of PISA data. PLoS ONE, 8(3), e57988. https://doi.org/10.1371/journal.pone.0057988
  • Sullivan, K., Perry, L. B., & McConney, A. (2014). How do school learning environments differ across Australia’s rural, regional and metropolitan communities? The Australian Educational Researcher, 41(5), 521–540. https://doi.org/10.1007/s13384-014-0144-1
  • Tan, C. Y., Liu, P., & Wong, W. L. V. (2020). Different patterns of relationships between principal leadership and 15-year-old students’ science learning: How school resources, teacher quality, and school socioeconomic status make a difference. Frontiers in Psychology, 11, 2257. https://doi.org/10.3389/fpsyg.2020.02257
  • Tang, X., & Zhang, D. (2020). How informal science learning experience influences students’ science performance: A cross-cultural study based on PISA 2015. International Journal of Science Education, 42(4), 598–616. https://doi.org/10.1080/09500693.2020.1719290
  • Tao, H. L., & Michalopoulos, C. (2018). Gender equality and the gender gap in mathematics. Journal of Biosocial Science, 50(2), 227–243. https://doi.org/10.1017/S0021932017000141
  • Teltemann, J., & Schunck, R. (2016). Education systems, school segregation, and second-generation immigrants’ educational success: Evidence from a country-fixed effects approach using three waves of PISA. International Journal of Comparative Sociology, 57(6), 401–424. https://doi.org/10.1177/0020715216687348
  • Välijärvi, J., Linnakylä, P., Kupari, P., Reinikainen, P., & Arffman, I. (2002). The Finnish success in PISA-and some reasons behind it. Institute for Educational Research, University of Jyväskylä.
  • Van Hek, M., Kraaykamp, G., & Pelzer, B. (2018). Do schools affect girls’ and boys’ reading performance differently? A multilevel study on the gendered effects of school resources and school practices. School Effectiveness and School Improvement, 29(1), 1–21. https://doi.org/10.1080/09243453.2017.1382540
  • Willms, D. J., Tramonte, L., Duarte, J., & Bos, M. S. (2012). Assessing educational equality and equity with large-scale assessment data: Brazil as a case study. The Inter-American Development Bank Technical Notes. IDB.
  • Willms, J. D. (2011). Quality, equality, and equity in Latin American schools. Presentación en el ICFES, Bogotá, 21.
  • Wu, J. Y. (2014). Gender differences in online reading engagement, metacognitive strategies, navigation skills and reading literacy. Journal of Computer Assisted Learning, 30(3), 252–271. https://doi.org/10.1111/jcal.12054
  • Xu, D., & Dronkers, J. (2016). Migrant children in Shanghai: A research note on the PISA-Shanghai controversy. Chinese Sociological Review, 48(3), 271–295. https://doi.org/10.1080/21620555.2016.1165605
  • Zhang, L. C., & Sheu, T. M. (2013). Effective investment strategies on mathematics performance in rural areas. Quality & Quantity, 47(5), 2999–3017. https://doi.org/10.1007/s11135-012-9752-x
  • Zhang, Z. Y., & Jia, Y. (2020). Confidence and reflection: The trend of China’s basic education reform from the perspective of PISA 2018. Journal of the Chinese Society of Education, 1, 1–6.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.