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Psychosocial Skills in Large-Scale Assessments: Trends, Challenges, and Policy Implications

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Psychosocial Skills and School Systems in the 21st Century

Abstract

In this chapter, we discuss the changing role of large-scale educational assessments, specifically their increased focus on measuring psychosocial skills in addition to student achievement. We present a schema that can serve as a helpful guide for distinguishing the different kinds of variables measured in large-scale assessments. In addition, historic and current trends on the shifting role of psychosocial skills in large-scale assessments are discussed, such as the increased focus on noncognitive student factors as additional outcomes and measures of constructs of their own interest. We also present examples of policies aimed at promoting psychosocial skills that have been or are currently being implemented in several countries around the globe. Finally, we review key challenges in measuring psychosocial skills in large-scale assessments and present three promising directions in improved measurement, namely, the introduction of new item formats, improved questionnaire pretesting processes, and new questionnaire designs for digital environments. A shared goal of these innovations is increasing validity and subgroup comparability under the constraint of keeping student burden low. Policy interest is shifting from monitoring student literacy in core subjects to promoting lifelong learners who are able as well as eager to face the demands and challenges of a truly global society. We illustrate the important role that the outlined new directions in noncognitive measurement will play to help ensure that large-scale assessments continue to play a vital role in global education.

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Notes

  1. 1.

    http://www.oecd.org/pisa/

  2. 2.

    In 2000 and 2009, the main domain assessed was reading, in 2003 and 2012 it was mathematics, and in 2006 and 2015 it was science.

  3. 3.

    http://www.nationsreportcard.gov/

  4. 4.

    http://nces.ed.gov/nationsreportcard/naepdata/

References

  • Abedi, J. (2006). Psychometric issues in the ELL assessment and special education eligibility. The Teachers College Record, 108, 2282–2303.

    Article  Google Scholar 

  • Abraham, C. (2012). Mapping change mechanisms and behavior change techniques: A systematic approach to promoting behavior change through text. In C. Abraham & M. Kools (Eds.), Writing health communication: An evidence-based guide for professionals (pp. 99–116). London: Sage.

    Google Scholar 

  • Ackerman, P. L., & Ellingsen, V. J. (2014). Vocabulary overclaiming. A complete approach: Ability, personality, self-concept correlates, and gender differences. Intelligence, 46, 2016–2227.

    Article  Google Scholar 

  • Adams, R. J., Lietz, P., & Berezner, A. (2013). On the use of rotated context questionnaires in conjunction with multilevel item response models. Large-Scale Assessments in Education, 1(1), 1–27.

    Article  Google Scholar 

  • Agasisti, T., & Cordero-Ferrera, J. M. (2013). Educational disparities across regions: A multilevel analysis for Italy and Spain. Journal of Policy Modeling, 35(6), 1079–1102.

    Article  Google Scholar 

  • Alegre, J. M., Almonte, D. E., Anthony, J. S., & Bertling, J. P. (2015, March). Key findings from NAEP survey questionnaire cognitive interviews. Presentation at the NAEP Questionnaire Standing Committee Meeting, Washington, DC.

    Google Scholar 

  • Almlund, M., Duckworth, A., Heckman, J. J., & Kautz, T. (2011). Personality psychology and economics (no. w16822). National Bureau of Economic Research.

    Google Scholar 

  • Almonte, D. E., McCullough, J., Lei, M., & Bertling, J. P. (2014, April). Spiraling of contextual questionnaires in the NAEP TEL pilot assessment. In J. P. Bertling (Chair), Spiraling contextual questionnaires in educational large-scale assessments. Symposium conducted at the meeting of the National Council on Measurement in Education, Philadelphia.

    Google Scholar 

  • Ashford, S., Edmunds, J., & French, D. P. (2010). What is the best way to change self-efficacy to promote lifestyle and recreational physical activity? A systematic review with meta-analysis. British Journal of Health Psychology, 15(2), 265–288.

    Article  PubMed  Google Scholar 

  • Atkinson, J. W. (1957). Motivational determinants of risk-taking behavior. Psychological Review, 64(6, Pt. 1), 359–372.

    Article  PubMed  Google Scholar 

  • Bandura, A. (1994). Self-efficacy. New York: Wiley.

    Google Scholar 

  • Bertling, J. P. (2012, October). Students’ approaches to problem solving-comparison of MTMM models for SJT data from PISA 2012. Technical report presented at the PISA 2012 Questionnaire Expert Group and Problem Solving Expert Group Meeting, Heidelberg, Germany.

    Google Scholar 

  • Bertling, J. P. (2014, May). Improving the contextual questionnaires for the National Assessment of Educational Progress: Plans for NAEP Core contextual modules. White paper presented at the meeting of the National Assessment Governing Board, Boston.

    Google Scholar 

  • Bertling, J. P., & Almonte, D. E. (2014). Anchoring vignettes to improve the measurement of students’ familiarity with computers and digital technology in the National Assessment of Educational Progress (Internal technical memo). Princeton, NJ: Educational Testing Service.

    Google Scholar 

  • Bertling, J. P., & Kyllonen, P. C. (2012). Domain-general student attitudes and behaviors: Constructs and items for PISA 2015 (Module 10). Technical report presented at PISA 2012 Questionnaire Expert Group meeting, Heidelberg, Germany.

    Google Scholar 

  • Bertling, J. P., & Kyllonen, P. C. (2013, August). Using anchoring vignettes to detect and correct for response styles in PISA questionnaires. In M. Prenzel (Chair), The attitudes-achievement-paradox: How to interpret correlational patterns in cross-cultural studies. Symposium conducted at the EARLI 2013 conference, Munich, Germany.

    Google Scholar 

  • Buchmann, C., & Dalton, B. (2002). Interpersonal influences and educational aspirations in 12 countries: The importance of institutional context. Sociology of Education, 75, 99–122.

    Article  Google Scholar 

  • Buchmann, C., & Park, H. (2009). Stratification and the formation of expectations in highly differentiated educational system. Research in Social Stratification and Mobility, 27(4), 245–267.

    Article  Google Scholar 

  • Buckley, J. (2009). Cross-national response styles in international educational assessments: Evidence from PISA 2006. Retrieved from https://edsurveys.rti.org/PISA/documents/Buckley_PISAresponsestyle.pdf

  • Callahan, R. M. (2005). Tracking and high school English learners: Limiting opportunity to learn. American Educational Research Journal, 42(2), 305–328.

    Article  Google Scholar 

  • Carroll, J. (1963). A model of school learning. The Teachers College Record, 64(8), 723–733.

    Google Scholar 

  • Cheung, G. W., & Rensvold, R. B. (2000). Assessing extreme and acquiescence response sets in cross-cultural research using structural equations modeling. Journal of Cross-Cultural Psychology, 31, 187–212.

    Article  Google Scholar 

  • Cogan, L. S., & Schmidt, W. H. (2015). The Concept of Opportunity to Learn (OTL). In K. Stacey & R. Turner (Eds.), International Comparisons of Education. In Assessing Mathematical Literacy (pp. 207–216). Cham: Springer International Publishing.

    Google Scholar 

  • Chmielewski, K., Dumont, H., & Trautwein, U. (2013). Tracking effects depend on tracking type: An international comparison of academic self-concept. American Educational Research Journal, 50, 925–957.

    Google Scholar 

  • Christenson, S., Reschly, A. L., & Wylie, C. (2012). Handbook of research on student engagement. New York: Springer.

    Book  Google Scholar 

  • Ciccone, A., & Garcia-Fontes, W. (2009). The quality of the Catalan and Spanish education systems: A perspective from PISA (IESE Business School working paper WP-810). Retrieved from http://ssrn.com/abstract=1513214

  • Comber, L. C., & Keeves, J. P. (1973). Science education in nineteen countries: An empirical study. Stockholm: Almqvist & Wiksell.

    Google Scholar 

  • Converse, J. M., & Presser, S. (1986). Survey questions: Handcrafting the standardized questionnaire. Beverly Hills, CA: Sage.

    Book  Google Scholar 

  • Dillman, D. A., Smyth, J. D., & Christian, L. M. (2014). Internet, phone, mail, and mixed-mode surveys: The tailored design method (4th ed.). Hoboken, NJ: Wiley.

    Google Scholar 

  • Duckworth, A. L., & Yeager, D. S. (2015). Measurement matters: Assessing personal qualities other than cognitive ability for educational purposes. Educational Researcher, 44, 237–251.

    Article  Google Scholar 

  • Duncan, G. J., & Murnane, R. J. (Eds.). (2011). Whither opportunity? Rising inequality, school, and children’s life chances. New York: Russell Sage.

    Google Scholar 

  • Dweck, C. S., Walton, G. M., & Cohen, G. L. (2011). Academic tenacity: Mindsets and skills that promote long–term learning. White paper prepared for the Gates Foundation, Seattle, WA.

    Google Scholar 

  • Eccles, J. S., Adler, T. F., Futterman, R., Goff, S. B., Kaczala, C. M., Meece, J. L., et al. (1983). Expectancies, values, and academic behaviors. In J. T. Spence (Ed.), Achievement and achievement motivation (pp. 75–146). San Francisco: Freeman.

    Google Scholar 

  • Eccles, J. S., Wigfield, A., Midgley, C., Reuman, D., MacIver, D., & Feldlaufer, H. (1993). Negative effects of traditional middle schools on students’ motivation. Elementary School Journal, 93, 553–574.

    Article  Google Scholar 

  • Farrington, C. A., Roderick, M., Allensworth, E., Nagaoka, J., Keyes, T. S., Johnson, D. W., et al. (2012). Teaching adolescents to become learners. The role of noncognitive factors in shaping school performance: A critical literature review. Chicago: University of Chicago Consortium on Chicago School Research.

    Google Scholar 

  • Feeney, J. R., & Goffin, R. D. (2015). The overclaiming questionnaire: A good way to measure faking? Personality and Individual Differences, 82, 248–252.

    Article  Google Scholar 

  • Forster, M. (2004). Measuring the social outcomes of schooling: What does ACER research tell? Retrieved from http://research.acer.edu.au/research_conference_2004/4/

  • Fowler, F. J. (2009). Survey research methods (4th ed.). Thousand Oaks, CA: Sage.

    Google Scholar 

  • Freedman, D. A. (1999). Ecological inference and the ecological fallacy. International Encyclopedia of the Social & Behavioral Sciences, 6, 4027–4030.

    Google Scholar 

  • Gabrieli, C. (2015, March). Non-cognitive skills and education policy: Research and practice considerations. In: M. R. West & G. J. Whitehurst (Chairs), Ready to be counted? Incorporating noncognitive skills into education policy. Symposium at the Brown Center on Education Policy, Washington, DC.

    Google Scholar 

  • Galesic, M., & Bosnjak, M. (2009). Effects of questionnaire length on participation and indicators of response quality in a web survey. Public Opinion Quarterly, 73(2), 349–360.

    Article  Google Scholar 

  • Gehlbach, H. (2015a, April 15). Name that baby: Why ‘non-cognitive’ factors need a new name. Education Week Blog. Retrieved from http://blogs.edweek.org/edweek/rick_hess_straight_up/2015/04/non-cognitive_factors_need_new_name.html

  • Gehlbach, H. (2015b). Seven survey sins. The Journal of Early Adolescence. doi:10.1177/0272431615578276.

    Google Scholar 

  • Ginsburg, A., & Smith, M. S. (2013, December). Key education indicators (KEI): Making sense of NAEP contextual variables. Presentation at the National Assessment Governing Board Meeting, Baltimore.

    Google Scholar 

  • Gorey, K. M. (2001). Early childhood education: A meta-analytic affirmation of the short-and long-term benefits of educational opportunity. School Psychology Quarterly, 16(1), 9.

    Article  Google Scholar 

  • Heckman, J. J., & Kautz, T. (2013). Fostering and measuring skills: Interventions that improve character and cognition (IZA discussion paper no. 7750). Bonn, Germany: Institute for the Study of Labor.

    Google Scholar 

  • Heckman, J. J., Stixrud, J., & Urzua, S. (2006). The effects of cognitive and noncognitive abilities on labor market outcomes and social behavior. Journal of Labor Economics, 24, 411–482.

    Article  Google Scholar 

  • Heine, S. J., Kitayama, S., Lehman, D. R., Takata, T., Ide, E., Leung, C., et al. (2001). Divergent consequences of success and failure in Japan and North America: An investigation of self-improving motivations and malleable selves. Journal of Personality and Social Psychology, 81(4), 599–615.

    Article  PubMed  Google Scholar 

  • Hiebert, J., & Grouws, D. A. (2007). The effects of classroom mathematics teaching on students’ learning. In F. K. Lester (Ed.), Second handbook of research on mathematics teaching and learning (pp. 371–404). Charlotte, NC: Information Age.

    Google Scholar 

  • Hopkins, D., & King, G. (2010). Improving anchoring vignettes: Designing surveys to correct interpersonal incomparability. Public Opinion Quarterly, 74(2), 201–222.

    Article  Google Scholar 

  • Jakubowski, M., Patrinos, H. A., Porta, E. E., & Wisniewski, J. (2010). The impact of the 1999 education reform in Poland (Policy research working paper 5263). Human Development Network Education. Washington, DC: The World Bank.

    Google Scholar 

  • Jencks, C. (1979). Who gets ahead? The determinants of economic success in America. New York: Basic Books.

    Google Scholar 

  • Kamenetz, A. (2015, May 28). Nonacademic skills are key to success. But what should we call them? nprEd. Retrieved from http://npr.org/sections/ed/2015/05/28/4046847/non-academic-skills-are-key-to-success-but-what-should-we-call-them

  • Kaplan, D., & Wu, D. (2014, April). Imputation issues relevant to context questionnaire rotation. In J. P. Bertling (Chair), Spiraling contextual questionnaires in educational large-scale assessments. Symposium conducted at the meeting of the National Council on Measurement in Education, Philadelphia.

    Google Scholar 

  • Kapteyn, A., Smith, J. P., & Van Soest, A. (2007). Vignettes and self-reports of work disability in the US and the Netherlands. American Economic Review, 97, 461–473.

    Article  Google Scholar 

  • Kautz, T., Heckman, J. J., Diris, R., ter Weel, B., & Borghans, L. (2014). Fostering and measuring skills: Improving cognitive and non-cognitive skills to promote lifetime success. Cambridge, MA: National Bureau of Economic Research.

    Book  Google Scholar 

  • Keehner, M., Agard, C., Berger, M., Shu, Z., Bertling, J., & Carney, L. (2014). Analyzing data from the NAEP TEL Wells task: Potential reporting insights from interactions, context, and scores (Research memorandum on NAEP TEL Task Component). Princeton, NJ: Educational Testing Service.

    Google Scholar 

  • King, G., & Wand, J. (2007). Comparing incomparable survey responses: Evaluating and selecting anchoring vignettes. Political Analysis, 15, 46–66.

    Article  Google Scholar 

  • Kristensen, N., & Johansson, E. (2008). New evidence on cross-country differences in job satisfaction using anchoring vignettes. Labour Economics, 15, 96–117.

    Article  Google Scholar 

  • Kunter, M., Baumert, J., & Köller, O. (2007). Effective classroom management and the development of subject-related interest. Learning and Instruction, 17(5), 494–509.

    Article  Google Scholar 

  • Kyllonen, P. C., & Bertling, J. P. (2013). Innovative questionnaire assessment methods to increase cross-country comparability. In L. Rutkowski, M. von Davier, & D. Rutkowski (Eds.), Handbook of international large-scale assessment: Background, technical issues, and methods of data analysis (pp. 277–286). Boca Raton, FL: CRC Press.

    Google Scholar 

  • Kyllonen, P. C., & Bertling, J. P. (2015, April). Advances in measuring 21st century skills: Constructs, development, and scoring. Training session presented at the meeting of the National Council on Measurement in Education, Chicago.

    Google Scholar 

  • Ladd, G. W., Kochenderfer-Ladd, B. K., Visconti, K. J., & Ettekal, I. (2012). Classroom peer relations and children’s social and scholastic development: Risk factors and resources. In A. M. Ryan & G. W. Ladd (Eds.), Peer relationships and adjustment at school (pp. 11–49). Charlotte, NC: Information Age Press.

    Google Scholar 

  • Lareau, A. (2011). Unequal childhoods: Class, race, and family life (2nd ed.). Berkeley, CA: University of California Press.

    Google Scholar 

  • Lareau, A., & Weininger, E. B. (2003). Cultural capital in educational research: A critical assessment. Theory and Society, 32, 567–606.

    Article  Google Scholar 

  • Lent, R. W., & Brown, S. D. (2006). On conceptualizing and assessing social cognitive constructs in career research: A measurement guide. Journal of Career Assessment, 14(1), 12–35.

    Article  Google Scholar 

  • Levin, H. M. (2012). More than just test scores. Prospects, 42(3), 269–284.

    Article  Google Scholar 

  • Lipowsky, F., Rakoczy, K., Pauli, C., Drollinger-Vetter, B., Klieme, E., & Reusser, K. (2009). Quality of geometry instruction and its short-term impact on students’ understanding of the Pythagorean Theorem. Learning and Instruction, 19(6), 527–537.

    Article  Google Scholar 

  • Maaz, K., Baumert, J., Neumann, M., Becker, M., & Dumont, H. (Eds.). (2013). Die Berliner Schulstrukturreform: Bewertung duch die beteiligten Akteure und Konsequenzen des neuen Uebergangsverfahrens von der Grundschule in die weiterfuehrenden Schulen. Muenchen: Waxmann.

    Google Scholar 

  • Magnuson, K. A., & Votruba-Drzal, E. (2009). Enduring influences of childhood poverty. In S. Danziger & M. Cancian (Eds.), Changing poverty changing policies (pp. 153–179). New York: Russell Sage.

    Google Scholar 

  • Maitland, A., Sun, H., Tourangeau, R., Almonte, D. E., & Bertling, J. P.(2015, March). Exploration of matrix questions on fourth-grade students using eye-tracking. Presentation at the NAEP Questionnaire Standing Committee Meeting, Washington, DC.

    Google Scholar 

  • McDaniel, M. A., Hartman, N. S., Whetzel, D. L., & Grubb, W. (2007). Situational judgment tests, response instructions, and validity: A meta-analysis. Personnel Psychology, 60(1), 63–91.

    Article  Google Scholar 

  • McDonnell, L. M. (1995). Opportunity to learn as a research concept and a policy instrument. Educational Evaluation and Policy Analysis, 17(3), 305–322.

    Article  Google Scholar 

  • Mickelson, R. A. (1990). The attitude-achievement paradox among black adolescents. Sociology of Education, 63(1), 44–61.

    Article  Google Scholar 

  • Milfont, T. L., & Fischer, R. (2010). Testing measurement invariance across groups: Applications in cross-cultural research. International Journal of Psychological Research, 3, 112–131.

    Google Scholar 

  • Minor, E. C., Desimone, L. M., Spencer, K., & Phillips, K. J. (2015). A new look at the opportunity-to-learn gap across race and income. American Journal of Education, 121(2), 241–269.

    Article  Google Scholar 

  • Monseur, C., & Bertling, J. P. (2014, April). Questionnaire rotation in international surveys: Findings from PISA. In J. P. Bertling (Chair), Spiraling contextual questionnaires in educational large-scale assessments. Symposium conducted at the meeting of the National Council on Measurement in Education, Philadelphia.

    Google Scholar 

  • Monseur, C., & Lafontaine, D. (2012). Structure des systèmes éducatifs et équité : un éclairage international. In M. Crahay (Ed.), Pour une école juste et efficace (pp. 185–219). Brussels, Belgium: De Broeck.

    Google Scholar 

  • Mõttus, R., Allik, J., Realo, A., Pullmann, H., Rossier, J., Zecca, G., et al. (2012). The effect of response style on self-reported conscientiousness across 20 countries. Personality and Social Psychology Bulletin, 38, 1423–1436.

    Article  PubMed  Google Scholar 

  • Naemi, B., Gonzalez, E., Bertling, J. P., Betancourt, A., Burrus, J., Kyllonen, P. C., et al. (2013). Large-scale group score assessments: Past, present, and future. In D. Saklofske & V. Schwean (Eds.), Oxford handbook of psychological assessment of children and adolescents. Cambridge, MA: Oxford University Press.

    Google Scholar 

  • National Assessment Governing Board. (2012). Policy statement on NAEP background questions and the use of contextual data in NAEP reporting. Washington, DC: U.S. Department of Education, National Assessment Governing Board.

    Google Scholar 

  • National Council of Teachers of Mathematics. Commission on Standards for School Mathematics. (1989). Curriculum and evaluation standards for school mathematics. Reston, VA: NCTM.

    Google Scholar 

  • Nyhus, E. K., & Pons, E. (2005). The effects of personality on earnings. Journal of Economic Psychology, 26(3), 363–384.

    Article  Google Scholar 

  • O’Connor, M. C., & Paunonen, S. V. (2007). Big five personality predictors of post-secondary academic performance. Personality and Individual Differences, 43(5), 971–990.

    Article  Google Scholar 

  • OECD. (2010). Pathways to success: How knowledge and skills at age 15 shape future lives in Canada. Paris: OECD Publishing.

    Book  Google Scholar 

  • OECD. (2011). How do education systems and schools select and group students? In PISA 2009 at a Glance. Paris: OECD Publishing.

    Google Scholar 

  • OECD. (2012). Learning beyond fifteen: Ten years after PISA. Paris: OECD Publishing.

    Book  Google Scholar 

  • OECD. (2013a). Education at a glance 2013: OECD indicators. Paris: OECD Publishing.

    Google Scholar 

  • OECD. (2013b). PISA 2012 Assessment and analytical framework: Mathematics, reading, science, problem solving and financial literacy. Paris: OECD Publishing.

    Book  Google Scholar 

  • OECD. (2013c). PISA 2012 results: Excellence through equity: Giving every student the chance to succeed (Volume II). Paris: OECD Publishing.

    Book  Google Scholar 

  • OECD. (2013d). PISA 2012 results: Ready to learn: Students’ engagement, drive and self-beliefs (Volume III). Paris: OECD Publishing.

    Book  Google Scholar 

  • OECD. (2013e). PISA 2012 results: What makes schools successful? Resources, policies and practices (Volume IV). Paris: OECD Publishing.

    Book  Google Scholar 

  • OECD. (2013f). PISA 2015: Draft questionnaire framework. Paris: OECD Publishing. Retrieved from http://www.oecd.org/pisa/pisaproducts/PISA-2015-draft-questionnaire-framework.pdf.

    Google Scholar 

  • OECD. (2014a). Education at a glance 2014: OECD indicators. Paris: OECD Publishing.

    Google Scholar 

  • OECD. (2014b). PISA 2012 technical report. Paris: OECD Publishing.

    Google Scholar 

  • Oostrom, J. K., De Soete, B., & Lievens, F. (2015). Situational judgment testing. In I. Nikolaou & J. K. Oostrom (Eds.), Employee recruitment, selection, and assessment: Contemporary issues for theory and practice (pp. 172–189). New York: Psychology Press.

    Google Scholar 

  • Parker, P. D., Marsh, H. W., Ciarrochi, J., Marshall, S., & Abduljabbar, A. S. (2014). Juxtaposing math self-efficacy and self-concept as predictors of long-term achievement outcomes. Educational Psychology, 34(1), 29–48.

    Article  Google Scholar 

  • Paulhus, D. L., & Dubois, P. J. (2014). Application of the overclaiming technique to scholastic assessment. Educational and Psychological Measurement, 74, 975–990.

    Article  Google Scholar 

  • Paulhus, D. L., Harms, P. D., Bruce, M. N., & Lysy, D. C. (2003). The over-claiming technique: Measuring self-enhancement independent of ability. Journal of Personality and Social Psychology, 84(4), 890–904.

    Article  PubMed  Google Scholar 

  • Paunonen, S. V., & Ashton, M. C. (2001). Big five factors and facets and the prediction of behavior. Journal of Personality and Social Psychology, 81(3), 524–539.

    Article  PubMed  Google Scholar 

  • Pekrun, R., vom Hofe, R., Blum, W., Frenzel, A. C., Götz, T., & Wartha, S. (2007). Development of mathematical competencies in adolescence: The PALMA longitudinal study. In M. Prenzel (Ed.), Studies on the educational quality of schools: The final report on the DFG priority programme (pp. 17–37). Münster, Germany: Waxmann.

    Google Scholar 

  • Pintrich, P. R., Marx, R. W., & Boyle, R. A. (1993). Beyond cold conceptual change: The role of motivational beliefs and classroom contextual factors in the process of conceptual change. Review of Educational Research, 63(2), 167–199.

    Article  Google Scholar 

  • Poropat, A. E. (2009). A meta-analysis of the five-factor model of personality and academic performance. Psychological Bulletin, 135(2), 322–338.

    Article  PubMed  Google Scholar 

  • Prenzel, M. (2012). Empirische Bildungsforschung morgen: Reichen unsere bisherigen Forschungsansätze aus? In M. Gläser-Zikuda, T. Seidel, C. Rohlfs, A. Gröschner, & S. Ziegelbauer (Eds.), Mixed Methods in der empirischen Bildungsforschung (pp. 273–285). Münster, Germany: Waxmann.

    Google Scholar 

  • Richardson, M., Abraham, C., & Bond, R. (2012). Psychological correlates of university students’ academic performance: A systematic review and meta–analysis. Psychological Bulletin, 138(2), 353–387.

    Article  PubMed  Google Scholar 

  • Roberts, B. W., Kuncel, N. R., Shiner, R., Caspi, A., & Goldberg, L. R. (2007). The power of personality: The comparative validity of personality traits, socioeconomic status, and cognitive ability for predicting important life outcomes. Perspectives on Psychological Science, 2, 313–345.

    Article  PubMed  PubMed Central  Google Scholar 

  • Robinson, W. S. (1950). Ecological correlations and the behavior of individuals. American Sociological Review, 15, 351–357.

    Article  Google Scholar 

  • Rychen, D. S., & Salganik, L. H. (Eds.). (2003). Defining and selecting key competencies. Cambridge, MA: Hogrefe & Huber.

    Google Scholar 

  • Salomon, J. A., Tandon, A., & Murray, C. J. L. (2004). Comparability of self-rated health: Cross-sectional multi-country survey using anchoring vignettes. British Medical Journal, 328, 258–261.

    Article  PubMed  PubMed Central  Google Scholar 

  • Santos, D., & Primi, R. (2014). Social and emotional development and school learning. A measurement proposal in support of public policy. São Paulo, Brazil: Ayrton Senna Institute.

    Google Scholar 

  • Schiepe-Tiska, A., Heine, J. -H., Lüdtke, O., Seidel, T., & Prenzel, M. (2015). Cognitive and noncognitive outcomes in mathematics classrooms and their relationship with instructional quality. Unterrichtswissenschaft. Manuscript submitted for publication.

    Google Scholar 

  • Schunk, D. H., & Mullen, C. A. (2013). Motivation. In J. Hattie & E. M. Anderman (Eds.), International guide to student achievement (pp. 67–69). New York: Routledge.

    Google Scholar 

  • Seidel, T., & Reiss, K. (2014). Lerngelegenheiten im Unterricht. In T. Seidel & A. Krapp (Eds.), Paedagogische Psychologie (pp. 253–276). Weinheim, Germany: Beltz.

    Google Scholar 

  • SES Expert Panel. (2012). Improving the measurement of socioeconomic status for the National Assessment of Educational Progress: A theoretical foundation (White Paper prepared for the National Center for Education Statistics). Washington, DC: U.S. Department of Education.

    Google Scholar 

  • Smith, M. S., Chudowsky, N., Ginsburg, A., Hauser, R., Jennings, J., & Lewis, S. (2012). NAEP background questions: An underused national resource. Report to the National Assessment Governing Board by the expert panel on strengthening the NAEP background questions. Retrieved from http://www.nagb.org/content/nagb/assets/documents/publications/expert-panel-naep-bq-report.pdf

  • Specht, J., Egloff, B., & Schmukle, S. C. (2011). Stability and change of personality across the life course: The impact of age and major life events on mean–level and rank–order stability of the Big Five. Journal of Personality and Social Psychology, 101, 862–882.

    Article  PubMed  Google Scholar 

  • Stiglitz, J. E., Sen, A., & Fitoussi, J. P. (2010). Report by the commission on the measurement of economic performance and social progress. Paris: Commission on the Measurement of Economic Performance and Social Progress.

    Google Scholar 

  • Stock, J., & Cervone, D. (1990). Proximal goal-setting and self-regulatory processes. Cognitive Therapy and Research, 14(5), 483–498.

    Article  Google Scholar 

  • United Nations Educational Scientific and Cultural Organization. (2014). Teaching and learning: Achieving quality for all. EFA global monitoring report. Paris: UNESCO.

    Google Scholar 

  • van de Gaer, E., Grisay, A., Schulz, W., & Gebhardt, E. (2012). The reference group effect: An explanation of the paradoxical relationship between academic achievement and self-confidence across countries. Journal of Cross-Cultural Psychology, 43(8), 1205–1228.

    Article  Google Scholar 

  • von Davier, M. (2014). Imputing proficiency data under planned missingness in population models. In L. Rutkowski, M. von Davier, & D. Rutkowski (Eds.), Handbook of international large-scale assessment: Background, technical issues, and methods of data analysis. Boca Raton, FL: CRC Press.

    Google Scholar 

  • Weekley, J. A., & Ployhart, R. E. (Eds.). (2006). Situational judgment tests: Theory, measurement, and application. Mahway, NJ: Erlbaum.

    Google Scholar 

  • Whetzel, D. L., & McDaniel, M. A. (2009). Situational judgment tests: An overview of current research. Human Resource Management Review, 19(3), 188–202.

    Article  Google Scholar 

  • White, K. R. (1982). The relation between socioeconomic status and academic achievement. Psychological Bulletin, 91, 461–481.

    Article  Google Scholar 

  • Wise, S. L., & Kong, X. (2005). Response time effort: A new measure of examinee motivation in computer-based tests. Applied Measurement in Education, 18, 163–183.

    Article  Google Scholar 

  • Ziegler, M., Kemper, C., & Rammstedt, B. (2015). The vocabulary and overclaiming test (VOC-T). Journal of Individual Differences, 34(1), 32–40.

    Article  Google Scholar 

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Bertling, J.P., Borgonovi, F., Almonte, D.E. (2016). Psychosocial Skills in Large-Scale Assessments: Trends, Challenges, and Policy Implications. In: Lipnevich, A., Preckel, F., Roberts, R. (eds) Psychosocial Skills and School Systems in the 21st Century. The Springer Series on Human Exceptionality. Springer, Cham. https://doi.org/10.1007/978-3-319-28606-8_14

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