2015 | 3(134) | 26–47
Article title

Learning strategies as predictors for academic achievement in 15-year-olds. Comparisons between Poland, the Czech Republic, Germany, Hungary and Slovakia

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The paper reports a study addressing influence of learning strategies on academic achievement in mathe matics, reading and science internationally, with comparisons between Poland’s neighbouring countries. Data from the PISA 2009 study was used to build multiple multilevel hierarchical regression models, with control variables for student, school and at country level. Based on the model developed by Chiu, Chow and McBride-Chang (2007), prior achievement, student family background, school environmental characteristics and national economic and cultural contexts were controlled for, allowing assessment of the effects of learning strategies. Higher dependency on memorisation was associated with lower scores in all domains, elaboration was a negative predictor of reading and positive of mathematics and science, while use of metacognitive strategies was associated with higher scores in all domains investigated. The effect of metacognitive strategies was particularly strong in Poland, as compared with neighbouring countries.
Physical description
  • Institute of Psychology, Jagiellonian University
  • Institute of Pedagogy, Jagiellonian University
  • Allen, S. (2003). An analytic comparison of three models of reading strategy instruction. IRAL, 41(4), 319–338.
  • Areepattamannil, S. (2014). International note: what factors are associated with reading, mathematics and science literacy of Indian adolescents? A multilevel examination. Journal of adolescence, 37(4), 367–372.
  • Baeten, M., Kyndt, E., Struyven, K. and Dochy, F. (2010). Using student-centred learning environments to stimulate deep approaches to learning: Factors encouraging or discouraging their effectiveness. Educational Research Review, 5(3), 243–260.
  • Beckman, P. (2002). Strategy instruction. ERIC Digest, ED474302. Retrieved from
  • Berkemeyer, V. C. (1995). The metacognitive processing strategies of nonnative readers of German. Die Unterrichtspraxis/Teaching German, 28(2), 176–184.
  • Billing, D. (2007). Teaching for transfer of core/key skills in higher education: cognitive skills. Higher Education, 53(4), 483–516.
  • Boulware‐Gooden, R., Carreker, S., Thornhill, A. and Joshi, R. (2007). Instruction of metacognitive strategies enhances reading comprehension and vocabulary achievement of third‐grade students. The Reading Teacher, 61(1), 70–77.
  • Bransford, J. D., Brown, A. L. and Cocking, R. R. (1999). How people learn: brain, mind, experience and school. Washington: National Academy Press.
  • Brozo, W. G., Shiel, G. and Topping, K. (2007). Engagement in reading: lessons learned from three PISA countries. Journal of Adolescent and Adult Literacy, 51(4), 304–315.
  • Chapman, E. (2003). Assessing student engagement rates. ERIC Digest, ED482269. Retrieved from
  • Chiu, M. M., Chow, B. W. Y. and Mcbride-Chang, C. (2007). Universals and specifics in learning strategies: explaining adolescent mathematics, science and reading achievement across 34 countries. Learning and Individual Differences, 17(4), 344–365.
  • Conti, G. J. and Fellenz, R. A. (1991). Assessing Adult Learning Strategies. ERIC Digest, ED339847. Retrieved from
  • Czuchry, M. and Dansereau, D. F. (1998). The generation and recall of personally relevant information. The Journal of Experimental Education, 66(4), 293–315.
  • Dansereau, D. F. (1978). The development of a learning strategies curriculum. In H. F. O’Neil, Jr. (ed.), Learning strategies (pp. 1–29). New York: Academic Press.
  • Demir, I. and Kılıç, S. (2010). Using PISA 2003, examining the factors affecting students’ mathematics achievement. Hacettepe Universitesi Egitim Fakultesi Dergisi, 38, 44–54.
  • Diseth, Å. (2013). Personality as an indirect predictor of academic achievement via student course experience and approach to learning. Social Behavior and Personality: an International Journal, 41(8), 1297–1308.
  • Enders, C. K. and Tofighi, D. (2007). Centering predictor variables in cross-sectional multilevel models: a new look at an old issue. Psychological methods, 12(2), 121–138.
  • Featherman, D. L. (1978). Schooling and occupational careers: constancy and change in worldly success. Madison: Center for Demography and Ecology, University of Wisconsin.
  • Flavell, J. H. (1976). Metacognitive aspects of problem solving. In L. B. Resnick (ed.), The nature of intelligence (pp. 231–236). Hillsdale: Erlbaum.
  • Flavell, J. H. (1979). Metacognition and cognitive monitoring: a new area of cognitive–developmental inquiry. American psychologist, 34(10), 906–911.
  • Garson, G. G. D. (ed.). (2012). Hierarchical linear modeling: guide and applications. Los Angeles: Sage Publications.
  • Halpern, D. F. (1998). Teaching critical thinking for transfer across domains: disposition, skills, structure training and metacognitive monitoring. American Psychologist, 53(4), 449–455.
  • Heston, A., Summers, R. and Aten, B. (2009). Penn world table (PWT) 6.3. Center for International Comparisons of Production, Income and Prices at the University of Pennsylvania. Retrieved from
  • Hilberg, R. S. and G Tharp, R. (2002). Theoretical perspectives, research findings and classroom implications of the learning styles of American Indian and Alaska Native students. Retrieved from
  • Hofstede, G., Hofstede, G. J. and Minkov, M. (2010). Cultures and organisations-software of the mind: intercultural cooperation and its importance for survival. New York: McGraw–Hill.
  • Hsiao, T. Y. and Oxford, R. L. (2002). Comparing theories of language learning strategies: a confirmatory factor analysis. The Modern Language Journal, 86(3), 368–383.
  • Isaacson, R. M. and Fujita, F. (2006). Metacognitive Knowledge monitoring and self-regulated learning: academic success and reflections on learning. Journal of Scholarship of Teaching and Learning, 6(1), 39–55.
  • Kang, D. H. (1997). Assessing Korean Middle school students’ language learning strategies in input-poor environments. ERIC Digest, ED413778. Retrieved from
  • Kaur, B. and Areepattamannil, S. (2012). Influences of metacognitive and self-regulated learning strategies for reading on mathematical literacy of adolescents in Australia and Singapore. Paper presented at the 35th Annual Conference of the Mathematics Education Research Group of Australasia Incorporated (MERGA 2012) on “Mathematics education: Expanding horizons”, Singapore, 2–6 July 2012. Retrieved from
  • Kilic, S., Cene, E. and Demir, I. (2012). Comparison of learning strategies for mathematics achievement in Turkey with eight countries. Educational Sciences: Theory and Practice, 12(4), 2594–2598.
  • Kuensting, J., Kempf, J. and Wirth, J. (2013). Enhancing scientific discovery learning through metacognitive support. Contemporary Educational Psychology, 38(4), 349–360.
  • Laskey, M. L. and Hetzel, C. J. (2010). Self-regulated learning, metacognition and soft skills: the 21st century learner. Retrieved from
  • Lau, K. L. and Chan, D. W. (2001). Motivational characteristics of under-achievers in Hong Kong. Educational Psychology, 21(4), 417–430.
  • Law, Y. K., Chan, C. K. and Sachs, J. (2008). Beliefs about learning, self‐regulated strategies and text comprehension among Chinese children. British Journal of Educational Psychology, 78(1), 51–73.
  • Lee, I. S. (2002). Gender differences in self-regulated on-line learning strategies within Korea’s university context. Educational Technology Research and Development, 50(1), 101–111.
  • Lewalter, D. (2003). Cognitive strategies for learning from static and dynamic visuals. Learning and Instruction, 13(2), 177–189.
  • Martin, M. A. (2012). Family structure and the intergenerational transmission of educational advantage. Social Science Research, 41(1), 33–47
  • McInerney, D. M., Cheng, R. W. Y., Mok, M. M. C. and Lam, A. K. H. (2012). Academic self-concept and learning strategies direction of effect on student academic achievement. Journal of Advanced Academics, 23(3), 249–269.
  • Nodoushan, M. A. S. (2012). Self-regulated learning (SRL): emergence of the RSRLM model. International Journal of Language Studies, 6(3)1–16.
  • O’Malley, J. M. and Chamot, A. U. (1990). Learning strategies in second language acquisition. Cambridge: Cambridge University Press.
  • OECD (2009a). PISA Assessment framework – key competencies in reading, mathematics and science. Paris: OECD Publishing.
  • OECD (2009b). PISA data analysis manual: SPSS second edition. Paris: OECD Publishing.
  • OECD (2010a). PISA 2009 results: learning to learn – student engagement, strategies and practices (vol. 3). Paris: OECD Publishing.
  • OECD (2010b). PISA 2009 results: what students know and can do – student performance in reading, mathematics and science (vol. I). Paris: OECD Publishing.
  • OECD (2012a). Grade expectations: how marks and education policies shape students’ ambitions. Paris: OECD Publishing.
  • OECD (2012b). PISA 2009 technical report. Paris: OECD Publishing.
  • Oxford, R. L. (1990). Language learning strategies: what every teacher should know. New York: Newbury House.
  • Ozsoy, G., Memis, A. and Temur, T. (2009). Metacognition, study habits and attitudes. International Electronic Journal of Elementary Education, 2(1), 154–166. Retrieved from
  • Paris, S. G. and Paris, A. H. (2001). Classroom applications of research on self-regulated learning. Educational psychologist, 36(2), 89–101.
  • Peng, S., Siriyothin, P. and Lian, A. P. (2014). Reading strategy use and reading proficiency of chinese undergraduate students majoring in english. International Journal of Academic Research, 6(2), 69–74.
  • Pintrich, P. R. (2002). The role of metacognitive knowledge in learning, teaching and assessing. Theory into practice, 41(4), 219–225.
  • Pintrich, P. R. and De Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of educational psychology, 82(1), 33–44.
  • Raudenbush, S. W., Bryk, A. S. and Congdon, R. (2005). HLM 6: hierarchical linear and nonlinear modeling (ver. 6.06). [Computer software]. Lincolnwood: Scientific Software International.
  • Rockoff, J. E. (2004). The impact of individual teachers on student achievement: evidence from panel data. American Economic Review, 94(2), 247–252.
  • Sadler‐Smith, E. and Tsang, F. (1998). A comparative study of approaches to studying in Hong Kong and the United Kingdom. British Journal of Educational Psychology, 68(1), 81–93.
  • Sanders, W. L., Wright, S. P. and Horn, S. P. (1997). Teacher and classroom context effects on student achievement: implications for teacher evaluation. Journal of personnel evaluation in education, 11(1), 57–67.
  • Schunk, D. H. and Zimmerman, B. J. (2003). Self-regulation and learning. In W. M. Reynolds, G. E. Miller and I. B. Weiner (eds.), Handbook of psychology (vol. 7: Educational Psychology, pp. 59–78). Hoboken: John Wiley & Sons.
  • Shawer, S. F. (2012). Interdisciplinary and intercultural differences in learning strategy use: implications for language processing, curriculum and instruction. Asia Pacific Education Review, 13(3), 529–540.
  • Sheorey, R. A. and Mokhtari, K. (2001). Differences in the metacognitive awareness of reading strategies among native and non-native readers. System, 29(4), 431–449
  • Smith, M. C., Mikulecky, L., Kibby, M. W., Dreher, M. J. and Dole, J. A. (2000). What will be the demands of literacy in the workplace in the next millennium? Reading Research Quarterly, 35(3), 378–383.
  • Somuncuoglu, Y. and Yildirim, A. (1999). Relationship between achievement goal orientations and use of learning strategies. The Journal of Educational Research, 92(5), 267–277.
  • Stefanou, C. R. and Salisbury-Glennon, J. D. (2002). Developing motivation and cognitive learning strategies through an undergraduate learning community. Learning Environments Research, 5(1), 77–97.
  • Sywelem, M., Al-Harbi, Q., Fathema, N. and Witte, J. E. (2012). Learning style preferences of student teachers: a cross-cultural perspective. Institute for Learning Styles Journal, 1, 10–24.
  • Tang, M. and Neber, H. (2008). Motivation and self‐regulated science learning in high‐achieving students: differences related to nation, gender and grade‐level. High ability studies, 19(2), 103–116.
  • Valentine, J. C., DuBois, D. L. and Cooper, H. (2004). The relation between self-beliefs and academic achievement: a meta-analytic review. Educational Psychologist, 39(2), 111–133.
  • Weinstein, C. E. and Mayer, R. E. (1986). The teaching of learning strategies. In M. C. Wittrock (ed.), Handbook of research on teaching (pp. 315–327). New York: Collier Macmillan.
  • Wong, J. K. K. (2004). Are the Learning Styles of Asian International students culturally or contextually based? International Education Journal, 4(4), 154–166.
  • Wong, S. L., Ibrahim, N. and Ayub, A. F. M. (2012). Learning strategies as correlates of computer attitudes: a case study among Malaysian secondary school students. International Journal of Social Science and Humanity, 2(2), 123–126.
  • World Bank (2014). GDP per capita, GINI Atlas method. [Data file]. Retrieved from
  • Zimmerman, B. J. (1989). A social cognitive view of self-regulated academic learning. Journal of Educational Psychology, 81(3), 329.
  • Zimmerman, B. J. and Kitsantas, A. (2014). Comparing students’ self-discipline and self-regulation measures and their prediction of academic achievement. Contemporary Educational Psychology, 39(2), 145–155.
  • Zimmerman, B. J. and Martinez Pons, M. (1990). Student differences in SRL: relating grade, sex and giftedness to self-efficacy and strategy use. Journal of Educational Psychology, 82, 51–59.
  • Zimmerman, B. J. and Martinez Pons, M. M. (1986). Development of a structured interview for assessing student use of self-regulated learning strategies. American Educational Research Journal, 23(4), 614–628.
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