Skip to main content
SpringerLink
Log in

Teachers’ and Students’ Belief Systems About the Self-Regulation of Learning

  • Reflection on the Field
  • Published:
Educational Psychology Review Aims and scope Submit manuscript

Abstract

Contemporary theories of learning and instruction emphasise the importance of students knowing how to effectively regulate their learning. A large body of research indicates that effective regulation of learning is beneficial for achievement. Set against this research are findings showing that the promotion by teachers of strategies for the self-regulation of learning (SRL), and student use of these strategies, is less common than might be expected. We review this research on the promotion and use of SRL strategies and suggest that a range of beliefs about learning and SRL strategies limit the promotion of SRL learning strategies by teachers. This contributes in turn to the lack of knowledge and use of such strategies by students. These beliefs are represented as forming an interrelated system that needs to be made explicit and examined in order to increase the level of SRL strategy promotion and use. Each of the beliefs is described and the paper concludes with discussion of the implications of the review for teacher educators, teachers, students, school leaders, curriculum designers and researchers.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Abelson, R. P. (1979). Differences between belief and knowledge systems. Cognitive Science, 3(4), 355–366. https://doi.org/10.1207/s15516709cog0304_4.

    Google Scholar 

  • Alexander, P. A. (2018). Looking down the road: future directions for research on depth and regulation of strategic processing. British Journal of Educational Psychology, 88(1), 152–166. https://doi.org/10.1111/bjep.12204.

    Google Scholar 

  • Alexander, P. A., Jetton, T. L., & Kulikowich, J. M. (1995). Interrelationship of knowledge, interest, and recall: assessing a model of domain learning. Journal of Educational Psychology, 87(4), 559–575. https://doi.org/10.1037/0022-0663.87.4.559.

    Google Scholar 

  • Amin, T. G., & Levrini, O. (2018). Converging perspectives on conceptual change: Mapping an emerging paradigm in the learning sciences. New York: Routledge/Taylor & Francis Group.

    Google Scholar 

  • Arzi, H. J., & White, R. (2008). Change in teachers’ knowledge of subject matter: a 17-year longitudinal study. Science Education, 92(2), 221–251. https://doi.org/10.1002/sce.20239.

    Google Scholar 

  • Askell-Williams, H., & Lawson, M. J. (2005). Students’ knowledge about the value of discussions for teaching and learning. Social Psychology of Education, 8(1), 83–115. https://doi.org/10.1007/s11218-004-5489-2.

    Google Scholar 

  • Askell-Williams, H., & Lawson, M. (2015). Changes in students’ cognitive and metacognitive strategy use over five years of secondary schooling. In H. Askell-Williams (Ed.), Transforming the future of learning with educational research (pp. 1–19). Hershey: IGI Global.

    Google Scholar 

  • Askell-Williams, H., Lawson, M. J., & Skrzypiec, G. (2012). Scaffolding cognitive and metacognitive strategy instruction in regular class lessons. Instructional Science, 40(2), 413–443. https://doi.org/10.1007/s11251-011-9182-5.

    Google Scholar 

  • Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: a proposed system and its control processes. In K. W. Spence & J. T. Spence (Eds.), The psychology of learning and motivation: II. Oxford: Academic Press. https://doi.org/10.1016/S0079-7421(08)60422-3.

    Google Scholar 

  • Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W.H. Freeman.

    Google Scholar 

  • Bandura, A. (2001). Social cognitive theory: an agentic perspective. Annual Review of Psychology, 52(1), 1–26. https://doi.org/10.1146/annurev.psych.52.1.1.

    Google Scholar 

  • Bereiter, C. (2014). Principled practical knowledge: not a bridge but a ladder. Journal of the Learning Sciences, 23(1), 4–17. https://doi.org/10.1080/10508406.2013.812533.

    Google Scholar 

  • Bereiter, C., & Scardamalia, M. (2012). Theory building and the pursuit of understanding in History, Social Studies, and Literature. In J. R. Kirby & M. J. Lawson (Eds.), Enhancing the quality of learning. New York: Cambridge University Press. https://doi.org/10.1017/CBO9781139048224.011.

    Google Scholar 

  • Berglas-Shapiro, T., Eylon, B.-S., & Scherz, Z. (2017). A technology-enhanced intervention for self-regulated learning in science. Teachers College Record, 119(13), 1–26 ID Number: 21938.

    Google Scholar 

  • Berry, D. C., & Broadbent, D. E. (1984). On the relationship between task knowledge and associated verbalizable knowledge. Quarterly Journal of Experimental Psychology, 36A, 209–231. https://doi.org/10.1080/14640748408402156.

    Google Scholar 

  • Birk, J. L., Rogers, A. H., Shahane, A. D., & Urry, H. L. (2018). The heart of control: proactive cognitive control training limits anxious cardiac arousal under stress. Motivation and Emotion, 42(1), 64–78. https://doi.org/10.1007/s11031-017-9659-x.

    Google Scholar 

  • Bjork, R. A., & Yan, V. X. (2014). The increasing importance of learning how to learn. In M. A. McDaniel, R. F. Frey, S. M. Fitzpatrick, & H. L. Roediger III (Eds.), Integrating cognitive science with innovative teaching in STEM disciplines (pp. 15–36). St Louis: Washington University.

    Google Scholar 

  • Bjork, R. A., Dunlosky, J., & Kornell, N. (2013). Self-regulated learning: beliefs, techniques, and illusions. Annual Review of Psychology, 64(1), 417–444. https://doi.org/10.1146/annurev-psych-113011-143823.

    Google Scholar 

  • Black, L. (2004). Teacher-pupil talk in whole class discussions and processes of social positioning within the primary school classroom. Language and Education, 18(5), 347–360. https://doi.org/10.1080/09500780408666888.

    Google Scholar 

  • Blackwell, L. S., Trzesniewski, K. H., & Dweck, C. S. (2007). Implicit theories of intelligence predict achievement across an adolescent transition: a longitudinal study and an intervention. Child Development, 78(1), 246–263. https://doi.org/10.1111/j.1467-8624.2007.00995.x.

    Google Scholar 

  • Boekaerts, M. (1997). Self-regulated learning: a new concept embraced by researchers, policy makers, educators, teachers, and students. Learning and Instruction, 7(2), 161–186. https://doi.org/10.1016/S0959-4752(96)00015-1.

    Google Scholar 

  • Bolhuis, S., & Voeten, M. J. M. (2001). Toward self-directed learning in secondary schools: what do teachers do? Teaching and Teacher Education, 17(7), 837–855. https://doi.org/10.1016/S0742-051X(01)00034-8.

    Google Scholar 

  • Botvinick, M., & Braver, T. (2015). Motivation and cognitive control: from behaviour to neural mechanism. Annual Review of Psychology, 66(1), 83–113. https://doi.org/10.1146/annurev-psych-010814-015044.

    Google Scholar 

  • Bråten, I., & Ferguson, L. E. (2015). Beliefs about sources of knowledge predict motivation for learning in teacher education. Teaching and Teacher Education, 50, 13–23. https://doi.org/10.1016/j.tate.2015.04.003.

    Google Scholar 

  • Brown, A. L. (1994). The advancement of learning. Educational Researcher, 23(8), 4–12. https://doi.org/10.3102/0013189X023008004.

    Google Scholar 

  • Brown, A. L., Campione, J. C., & Day, J. D. (1980) Learning to learn: on training students to learn from texts. Technical Report No. 189. University of Illinois at Urbana-Champaign.

  • Bruner, J. B. (1996). The culture of education. Cambridge: Harvard University Press.

    Google Scholar 

  • Bruning, R. H., Schraw, G. J., & Ronning, J. J. (2011). Cognitive psychology and instruction (5th ed.). Upper Saddle River: Pearson.

    Google Scholar 

  • Calderhead, J. (1991). The nature and growth of knowledge in student teaching. Teaching and Teacher Education, 7(5-6), 531–535. https://doi.org/10.1016/0742-051x(91)90047-s.

    Google Scholar 

  • Caprara, G. V., Fida, R., Vecchione, M., Del Bove, G., Vecchio, G. M., Barbaranelli, C., & Bandura, A. (2008). Longitudinal analysis of the role of perceived self-efficacy for self-regulated learning in academic continuance and achievement. Journal of Educational Psychology, 100(3), 525–534. https://doi.org/10.1037/0022-0663.100.3.525.

    Google Scholar 

  • Chatzistamatiou, M., & Dermitzaki, I. (2013). Teaching mathematics with self-regulation and for self-regulation: teachers’ reports. Hellenic Journal of Psychology, 10, 253–274.

    Google Scholar 

  • Chatzistamatiou, M., Dermitzaki, I., & Bagiatis, V. (2014). Self-regulatory teaching in mathematics: relations to teachers’ motivation, affect and professional commitment. European Journal of Psychology of Education, 29(2), 295–310. https://doi.org/10.1007/s10212-013-0199-9.

    Google Scholar 

  • Chein, J. M., & Schneider, W. (2012). The brain’s learning and control architecture. Current Directions in Psychological Science, 21(2), 78–84. https://doi.org/10.1177/0963721411434977.

    Google Scholar 

  • Cheung, C.-N., & Wong, W.-C. (2011). Understanding conceptual development along the implicit–explicit dimension: looking through the lens of the representational redescription model. Child Development, 82(6), 2037–2052. https://doi.org/10.1111/j.1467-8624.2011.01657.x.

    Google Scholar 

  • Churchland, P. S., & Churchland, P. M. (2013). What are beliefs? In F. Krueger & J. Grafman (Eds.), The neural basis of human belief systems (pp. 1–18). New York: Psychology Press.

    Google Scholar 

  • Cleary, T. J., & Kitsantas, A. (2017). Motivation and self-regulated learning influences on middle school mathematics achievement. School Psychology Review, 46(1), 88–107. https://doi.org/10.17105/SPR46-1.88-107.

    Google Scholar 

  • Cleary, T. J., & Zimmerman, B. J. (2004). Self-regulation empowerment program: a school-based program to enhance self-regulated and self-motivated cycles of student learning. Psychology in the Schools, 41(5), 537–550. https://doi.org/10.1002/pits.10177.

    Google Scholar 

  • Coertjens, L. (2018). The relation between cognitive and metacognitive processing: building bridges between the SRL, MDL, and SAL domains. British Journal of Educational Psychology, 88(1), 138–151. https://doi.org/10.1111/bjep.12214.

    Google Scholar 

  • de Bruin, A. B. H., & van Merriënboer, J. J. G. (2017). Bridging cognitive load and self- regulated learning research: a complementary approach to contemporary issues in educational research. Learning and Instruction, 51(1–9), 1–9. https://doi.org/10.1016/j.learninstruc.2017.06.001.

    Google Scholar 

  • Dignath, C., & Büttner, G. (2008). Components of fostering self-regulated learning among students. A meta-analysis on intervention studies at primary and secondary school level. Metacognition and Learning, 3(3), 231–264. https://doi.org/10.1007/s11409-008-9029-x.

    Google Scholar 

  • Dignath, C., & Büttner, G. (2018). Teachers’ direct and indirect promotion of self-regulated learning in primary and secondary school mathematics classes—insights from video-based classroom observations and teacher interviews. Metacognition and Learning, 13(2), 127–157. https://doi.org/10.1007/s11409-018-9181-x.

    Google Scholar 

  • Dignath-van Ewijk, C. (2016). Which components of teacher competence determine whether teachers enhance self-regulated learning? Predicting teachers’ self-reported promotion of self-regulated learning by means of teacher beliefs, knowledge, and self-efficacy. Frontline Learning Research, 4(5), 83–105. https://doi.org/10.14786/flr.v4i5.247.

    Google Scholar 

  • Dignath-van Ewijk, C., & Van der Werf, G. (2012). What teachers think about self-regulated learning: investigating teacher beliefs and teacher behavior of enhancing students’ self-regulation. Education Research International, 2012, 1–10. https://doi.org/10.1155/2012/741713.

    Google Scholar 

  • Dunlosky, J. (2013). Strengthening the student toolbox: study strategies to boost learning. American Educator, 37, 12–21.

    Google Scholar 

  • Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students’ learning with effective learning techniques promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14(1), 4–58. https://doi.org/10.1177/1529100612453266.

    Google Scholar 

  • Durkin, D. (1978). What classroom observations reveal about reading comprehension instruction. Reading Research Quarterly, 14(4), 481–533. https://doi.org/10.1598/RRQ.14.4.2.

    Google Scholar 

  • Dweck, C. S., & Leggett, E. L. (1988). A social-cognitive approach to motivation and personality. Psychological Review, 95(2), 256–273. https://doi.org/10.1037/0033-295X.95.2.256.

    Google Scholar 

  • Eberhardt, K., Esser, S., & Haider, H. (2017). Abstract feature codes: the building blocks of the implicit learning system. Journal of Experimental Psychology: Human Perception and Performance, 43(7), 1275–1290. https://doi.org/10.1037/xhp0000380.

    Google Scholar 

  • Efklides, A. (2006). Metacognition and affect: what can metacognitive experiences tell us about the learning process? Educational Research Review, 1(1), 3–14. https://doi.org/10.1016/j.edurev.2005.11.001.

    Google Scholar 

  • Efklides, A. (2017). Affect, epistemic emotions, metacognition, and self-regulated learning. Teachers College Record, 119(13), 1–22 ID Number: 21913.

    Google Scholar 

  • Efklides, A., Schwartz, B. L., & Brown, V. (2018). Motivation and affect in self-regulated learning: does metacognition play a role? In B. J. Zimmerman & D. H. Schunk (Eds.), Self-regulated learning and academic achievement: Theoretical perspectives (2nd ed., pp. 64–82). Mahwah: Lawrence Erlbaum Associates Publishers.

    Google Scholar 

  • Elen, J., & Lowyck, J. (1999). Metacognitive instructional knowledge: cognitive mediation and instructional design. Journal of Structural Learning and Intelligent Systems, 13, 145–169.

    Google Scholar 

  • Erickson, G., Brandes, G. M., Mitchell, I., & Mitchell, J. (2005). Collaborative teacher learning: findings from two professional development projects. Teaching and Teacher Education, 21(7), 787–798. https://doi.org/10.1016/j.tate.2005.05.018.

    Google Scholar 

  • Ertmer, P. A. (2005). Teacher pedagogical beliefs: the final frontier in our quest for technology integration? Educational Technology Research and Development, 53(4), 25–39. https://doi.org/10.1007/BF02504683.

    Google Scholar 

  • Finley, J. R., & Benjamin, A. S. (2012). Adaptive and qualitative changes in encoding strategy with experience: evidence from the test-expectancy paradigm. Journal of Experimental Psychology: Learning, Memory, and Cognition, 38(3), 632–652. https://doi.org/10.1037/a0026215.

    Google Scholar 

  • Fiorella, L., & Mayer, R. E. (2016). Eight ways to promote generative learning. Educational Psychology Review, 28(4), 717–741. https://doi.org/10.1007/s10648-015-9348-9.

    Google Scholar 

  • Fives, H., & Buehl, M. (2008). What do teachers believe? Developing a framework for examining beliefs about teachers’ knowledge and ability. Contemporary Educational Psychology, 33(2), 134–176. https://doi.org/10.1016/j.cedpsych.2008.01.001.

    Google Scholar 

  • Fives, H., & Buehl, M. M. (2012). Spring cleaning for the “messy” construct of teachers’ beliefs: what are they? Which have been examined? What can they tell us? In K. R. Harris, S. Graham, T. Urdan, S. Graham, J. M. Royer, & M. Zeidner (Eds.), APA educational psychology handbook, Vol 2: Individual differences and cultural and contextual factors (pp. 471–499). Washington, D.C.: American Psychological Association. https://doi.org/10.1037/13274-019.

    Google Scholar 

  • Foster, N. I., Was, C. A., Dunlosky, J., & Isaacson, R. M. (2017). Even after thirteen class exams, students are still overconfident: the role of memory for past exam performance in student predictions. Metacognition and Learning, 12(1), 1–19. https://doi.org/10.1007/s11409-016-9158-6.

    Google Scholar 

  • Fryer, L. K., & Vermunt, J. D. (2018). Regulating approaches to learning: testing learning strategy convergences across a year at university. British Journal of Educational Psychology, 88(1), 21–41. https://doi.org/10.1111/bjep.12169.

    Google Scholar 

  • Galton, M., & Pell, T. (2012). Do class size reductions make a difference to classroom practice? The case of Hong Kong primary schools. International Journal of Educational Research, 53, 22–31. https://doi.org/10.1016/j.ijer.2011.12.004.

    Google Scholar 

  • Geary, D. C. (2008). An evolutionarily informed education science. Educational Psychologist, 43(4), 179–195. https://doi.org/10.1080/00461520802392133.

    Google Scholar 

  • Geary, D. C. (2012). Evolutionary educational psychology. In K. Harris, S. Graham, & T. Urdan (Eds.), APA educational psychology handbook (Vol. 1, pp. 597–621). Washington, D.C.: American Psychological Association. https://doi.org/10.1037/13273-020.

    Google Scholar 

  • Geary, D. C., & Berch, D. B. (2016). Evolution and children's cognitive and academic development. In D. C. Geary & D. E. Berch (Eds.), Evolutionary perspectives on child development and education (pp. 217–249). Cham, Switzerland: Springer International Publishing. https://doi.org/10.1007/978-3-319-29986-0_9.

    Google Scholar 

  • Glogger-Frey, I., Ampatziadis, Y., Ohst, A., & Renkl, A. (2018). Future teachers’ knowledge about learning strategies: misconcepts and knowledge-in-pieces. Thinking Skills and Creativity, 28, 41–45. https://doi.org/10.1016/j.tsc.2018.02.001.

    Google Scholar 

  • Gore, J. M. (2014). Towards quality and equity: the case for Quality Teaching Rounds. Proceedings of the Australian Council for Educational Research (ACER) Research Conference, Adelaide, Australia. Retrieved 2/2/2015 from http://research.acer.edu.au/research_conference/RC2014/5august/4/.

  • Gratton, G., Cooper, P., Fabiani, M., Carter, C. S., & Karayanidis, F. (2018). Dynamics of cognitive control: theoretical bases, paradigms, and a view for the future. Psychophysiology, 55(3), 1–28. https://doi.org/10.1111/psyp.13016.

    Google Scholar 

  • Greene, J. A., Moos, D. C., Azevedo, R., & Winters, F. I. (2008). Exploring differences between gifted and grade-level students’ use of self-regulatory learning processes with hypermedia. Computers & Education, 50(3), 1069–1083. https://doi.org/10.1016/j.compedu.2006.10.004.

    Google Scholar 

  • Greene, J. A., Bolick, C. M., Caprino, A. M., Deekens, V. M., McVea, M., Yu, S., & Jackson, W. P. (2015). Fostering high-school students’ self-regulated learning online and across academic domains. The High School Journal, 99(1), 88–106. https://doi.org/10.1353/hsj.2015.0019.

    Google Scholar 

  • Griffin, P., Care, E., Crigan, J., Robertson, P., Zhang, Z. H., & Arratia-Martinez, A. (2012). The influence of evidence-based decisions by collaborative teacher teams on student achievement. In S. Billett, C. Harteis, & H. Gruber (Eds.), International handbook of research in professional and practice-based learning (pp. 1299–1331). Dordrecht: Springer.

    Google Scholar 

  • Grigal, M., Neubart, D. A., Moon, S. M., & Graham, S. (2003). Self-determination for students with disabilities: views of parents and teachers. Exceptional Children, 70(1), 97–112. https://doi.org/10.1177/001440290307000106.

    Google Scholar 

  • Hacking, I. (2001). Aristotelian categories and cognitive domains. Synthese, 126(3), 473–515. https://doi.org/10.1023/A:1005221431872.

    Google Scholar 

  • Hadwin, A., Järvelä, S., & Miller, M. (2018). Self-regulation, co-regulation, and shared regulation in collaborative learning environments. In D. H. Schunk & J. A. Greene (Eds.), Handbook of self-regulation of learning and performance (2nd ed., pp. 83–106). New York: Routledge/Taylor & Francis.

    Google Scholar 

  • Hamman, D. (1998). Preservice teachers’ value for learning-strategy instruction. The Journal of Experimental Education, 66(3), 209–221. https://doi.org/10.1080/00220979809604405.

    Google Scholar 

  • Hamman, D., Berthelot, J., Saia, J., & Crowley, E. (2000). Teachers’ coaching of learning and its relation to students’ strategic learning. Journal of Educational Psychology, 92(2), 342–348. https://doi.org/10.1037//0022-0663.92.2.342.

    Google Scholar 

  • Harris, K. R., & Graham, S. (2009). Self-regulated strategy development in writing: premises, evolution, and the future. British Journal of Educational Psychology, 11(6), 113–135. https://doi.org/10.1348/978185409X422542.

    Google Scholar 

  • Hartwig, M. K., & Dunlosky, J. (2012). Study strategies of college students: are self-testing and scheduling related to achievement? Psychonomic Bulletin & Review, 19(1), 126–134. https://doi.org/10.3758/s13423-011-0181-y.

    Google Scholar 

  • Hatano, G., & Inagaki, K. (2003). When is conceptual change intended? A cognitive-sociocultural view. In G. M. Sinatra & P. R. Pintrich (Eds.), Intentional conceptual change (pp. 407–427). Mahwah: Lawrence Erlbaum Associates.

    Google Scholar 

  • Hattie, J. (2009). Visible learning. Oxon: Routledge.

    Google Scholar 

  • Hattie, J., & Yates, G. C. R. (2014). Visible learning and the science of how we learn. New York: Routledge.

    Google Scholar 

  • Hattie, J., Masters, D., & Birch, K. (2016). Visible learning into action. Oxon: Routledge.

    Google Scholar 

  • Hayes, D., Mills, M., Christie, P., & Lingard, B. (2005). Teachers and schooling making a difference: Productive pedagogies, assessment, and performance. Sydney: Allen and Unwin.

    Google Scholar 

  • Hermans, van Braak, J., & Van Keer, H. (2008). Development of the beliefs about primary education scale: distinguishing a developmental and transmissive dimension. Teaching and Teacher Education, 24(1), 127–139. https://doi.org/10.1016/j.tate.2006.11.007.

    Google Scholar 

  • Herzog, C. (2016). Aging and metacognitive control. In J. Dunlosky & S. K. Tauber (Eds.), The Oxford handbook of metamemory (pp. 537–558). New York: Oxford University Press.

    Google Scholar 

  • Hirschfeld, L. A., & Gelman, S. A. (1994). Toward a topography of mind: an introduction to domain specificity. In L. A. Hirschfeld & S. A. Gelman (Eds.), Mapping the mind: domain specificity in cognition and culture (pp. 3–36). New York: Cambridge University Press. https://doi.org/10.1017/CBO9780511752902.002.

    Google Scholar 

  • Hofer, B. K. (2002). Epistemological world views of teachers: from beliefs to practice. Issues in Education: Contributions from Educational Psychology, 8, 166–173.

    Google Scholar 

  • Hofer, B. K., & Pintrich, P. R. (1997). The development of epistemological theories: beliefs about knowledge and knowing and their relation to learning. Review of Educational Research, 67(1), 88–140. https://doi.org/10.3102/00346543067001088.

    Google Scholar 

  • Hora, M. T. (2014). Exploring faculty beliefs about student learning and their role in instructional decision-making. The Review of Higher Education, 38(1), 37–70. https://doi.org/10.1353/rhe.2014.0047.

    Google Scholar 

  • Hussey, E. K., Harbison, J. I., Teubner-Rhodes, S. E., Mishler, A., Velnoskey, K., & Novick, J. M. (2017). Memory and language improvements following cognitive control training. Journal of Experimental Psychology: Learning, Memory, and Cognition, 43, 23–58. https://doi.org/10.1037/xlm0000283.

    Google Scholar 

  • Ioannidou-Koutselini, M., & Patsalidou, F. (2015). Engaging school teachers and school principals in an action research in-service development as a means of pedagogical self-awareness. Educational Action Research, 23(2), 124–139. https://doi.org/10.1080/09650792.2014.960531.

    Google Scholar 

  • Karlen, Y., Merki, K. M., & Ramseier, E. (2014). The effect of individual differences in the development of metacognitive strategy knowledge. Instructional Science, 42(5), 777–794. https://doi.org/10.1007/s11251-014-9314-9.

    Google Scholar 

  • Karmiloff-Smith, A. (1986). From meta-processes to conscious access: evidence from children’s metalinguistic and repair data. Cognition, 23(2), 95–147. https://doi.org/10.1016/0010-0277(86)90040-5.

    Google Scholar 

  • Karmiloff-Smith, A. (1992). Beyond modularity: A developmental perspective on cognitive science. Cambridge: MIT Press.

    Google Scholar 

  • Karmiloff-Smith, A. (1994). Precis of beyond modularity: a developmental perspective on cognitive science. Behavioral and Brain Sciences, 17(04), 693–745. https://doi.org/10.1017/S0140525X00036621.

    Google Scholar 

  • Karpicke, J. D. (2009). Metacognitive control and strategy selection: deciding to practice retrieval during learning. Journal of Experimental Psychology: General, 38(4), 469–486. https://doi.org/10.1037/a0017341.

    Google Scholar 

  • Karpicke, J. D., Butler, A. C., Roediger, I. I. I., & L, H. (2009). Metacognitive strategies in student learning: do students practise retrieval when they study on their own? Memory, 17(4), 471–479. https://doi.org/10.1080/09658210802647009.

    Google Scholar 

  • Kornell, N., & Bjork, R. A. (2007). The promise and perils of self-regulated study. Psychonomic Bulletin & Review, 14, 219–224. https://doi.org/10.3758/BF03194055.

    Google Scholar 

  • Kuhn, D. (1999). Metacognitive development. In L. Balter & C. S. Tamis-LeMonda (Eds.), Child psychology: A handbook of contemporary issues (pp. 259–286). New York: Psychology Press.

    Google Scholar 

  • Lane, R. (2015). Experienced geography teachers’ PCK of students’ ideas and beliefs about learning and teaching. International Research in Geographical and Environmental Education, 24(1), 43–57. https://doi.org/10.1080/10382046.2014.967113.

    Google Scholar 

  • Lane, D. M., & Chang, Y.-H. A. (2018). Chess knowledge predicts chess memory even after controlling for chess experience: evidence for the role of high-level processes. Memory and Cognition, 46(3), 337–348. https://doi.org/10.3758/s13421-017-0768-2.

    Google Scholar 

  • Lawson, M. J., & Askell-Williams, H. (2001). What facilitates learning in my university classes? The students’ account. Paper presented at the Annual Conference of the Higher Education Research and Development Society of Australasia, Newcastle.

  • Lawson, M. J., & Askell-Williams, H. (2012). Framing the features of good quality knowledge for teachers and students. In J. R. Kirby & M. J. Lawson (Eds.), Enhancing the quality of learning (pp. 137–159). New York: Cambridge University Press. https://doi.org/10.1017/CBO9781139048224.010.

    Google Scholar 

  • Lawson, M. J., & Chinnappan, M. (1994). Generative activity during geometry problem solving: comparison of the performance of high-achieving and low-achieving students. Cognition and Instruction, 12(1), 61–93. https://doi.org/10.1207/s1532690xci1201_3.

    Google Scholar 

  • Lichtman, K. (2013). Developmental comparisons of implicit and explicit language learning. Language Acquisition, 20, 93–108. https://doi.org/10.1080/10489223.2013.766740.

    Google Scholar 

  • Lipsey, M. W., Nesbitt, K. T., Farran, D. C., Dong, N., Fuhs, M. W., & Wilson, S. J. (2017). Learning-related cognitive self-regulation measures for prekindergarten children: a comparative evaluation of the educational relevance of selected measures. Journal of Educational Psychology, 109(8), 1084–1102. https://doi.org/10.1037/edu0000203.

    Google Scholar 

  • Logan, G. D. (2017). Taking control of cognition: an instance perspective on acts of control. American Psychologist, 72, 875–884. https://doi.org/10.1037/amp0000226.

    Google Scholar 

  • Lombaerts, K., De Backer, F., Engels, N., van Braak, J., & Athanasou, J. (2009). Development of the self-regulated learning teacher belief scale. European Journal of Psychology of Education, 24(1), 79–96. https://doi.org/10.1007/BF03173476.

    Google Scholar 

  • Lopez, E. J., Nandagopal, K., Shavelson, R. J., Szu, E., & Penn, J. (2013). Self-regulated learning study strategies and academic performance in undergraduate organic chemistry: an investigation examining ethnically diverse students. Journal of Research in Science Teaching, 50(6), 660–676. https://doi.org/10.1002/tea.21095.

    Google Scholar 

  • MacArthur, C. A. (2012). Strategies instruction. In K. R. Harris, S. Graham, T. Urdan, A. G. Bus, S. Major, & H. L. Swanson (Eds.), APA educational psychology handbook, Vol 3: Application to learning and teaching (pp. 379–401). Washington, DC: American Psychological Association.

    Google Scholar 

  • Maggioni, L., & Parkinson, M. M. (2008). The role of teacher epistemic cognition, epistemic beliefs, and calibration in instruction. Educational Psychology Review, 20(4), 445–461. https://doi.org/10.1007/s10648-008-9081-8.

    Google Scholar 

  • Mayer, R. E. (2008). Learning and instruction (2nd ed.). Upper Saddle River: Pearson.

    Google Scholar 

  • Mayer, R. E. (2017). Educational psychology’s past and future contributions to the science of learning, science of instruction, and science of assessment. Journal of Educational Psychology, 110, 174–179. https://doi.org/10.1037/edu0000195.

    Google Scholar 

  • McCabe, J. (2011). Metacognitive awareness of learning strategies in undergraduates. Memory and Cognition, 39(3), 462–476. https://doi.org/10.3758/s13421-010-0035-2.

    Google Scholar 

  • McCabe, J. A. (2018). What learning strategies do academic support centers recommend to undergraduates? Journal of Applied Research in Memory and Cognition, 7(1), 143–153. https://doi.org/10.1016/j.jarmac.2017.10.002.

    Google Scholar 

  • Meijer, J., Veenman, M. V. J., & van Hout-Wolters, B. H. A. M. (2006). Metacognitive activities in text-studying and problem-solving: development of a taxonomy. Educational Research and Evaluation, 12(3), 209–237. https://doi.org/10.1080/13803610500479991.

    Google Scholar 

  • Midford, R., & Kirsner, K. (2005). Implicit and explicit learning in aged and young adults. Aging, Neuropsychology, and Cognition, 12, 359–387. https://doi.org/10.1080/13825580500246894.

    Google Scholar 

  • Mitchell, I., & Mitchell, J. (2008). The program for enhancing effective learning (PEEL): 22 years of praxis. In A. P. Samaras, A. R. Freese, C. Kosnick, & C. Beck (Eds.), Learning communities in practice (pp. 7–18). New York: Springer.

    Google Scholar 

  • Moely, B., Hart, S., Leal, L., Santulli, K., Rao, N., Johnson, T., & Hamilton, E. B. (1992). The teacher’s role in facilitating memory and study strategy development in the elementary school classroom. Child Development., 63(3), 653–672. https://doi.org/10.2307/1131353.

    Google Scholar 

  • Morehead, K., Rhodes, M. G., & DeLozier, S. (2016). Instructor and student knowledge of study strategies. Memory, 24(2), 257–271. https://doi.org/10.1080/09658211.2014.1001992.

    Google Scholar 

  • Mueller, M. L., & Dunlosky, J. (2017). How beliefs can impact judgments of learning: evaluating analytic processing theory with beliefs about fluency. Journal of Memory and Language, 93, 245–258. https://doi.org/10.1016/j.jml.2016.10.008.

    Google Scholar 

  • National Council for the Accreditation of Teacher Education. (2008). Professional standards for the accreditation of teacher preparation institutions. Washington, D. C.: Author.

    Google Scholar 

  • Nesdale, D. (2007). The development of ethnic prejudice in early childhood: theories and research. In O. Saracho & B. Spodek (Eds.), Contemporary perspectives on social learning in early childhood education (pp. 213–240). Charlotte: Information Age Publishing.

    Google Scholar 

  • Nibali, N. (2017). Teaching self-regulated learning: teacher perspective on the opportunities and challenges. Paper presented at the Annual Conference of the Australian Association for Research in Education. Canberra, Australia.

  • Norman, D. A. (1980). Cognitive engineering and education. In D. T. Tuma & F. Reif (Eds.), Problem solving and education. Hillsdale: Erlbaum.

    Google Scholar 

  • Novak, J. D., & Gowin, D. B. (1984). Learning how to learn. Cambridge: Cambridge University Press. https://doi.org/10.1017/CBO9781139173469.

    Google Scholar 

  • Ohlsson, S. (2009). Resubsumption: a possible mechanism for conceptual change and belief revision. Educational Psychologist, 44, 20–40. https://doi.org/10.1080/00461520802616267.

    Google Scholar 

  • Ohst, A., Glogger, I., Nuckles, M., & Renkl, A. (2015). Helping preservice teachers with inaccurate and fragmentary prior knowledge to acquire conceptual understanding of psychological principles. Psychology Learning & Teaching, 14, 5–25. https://doi.org/10.1177/1475725714564925.

    Google Scholar 

  • Pajares, M. F. (1992). Teachers’ beliefs and educational research. Review of Educational Research, 62, 307–332. https://doi.org/10.3102/00346543062003307.

    Google Scholar 

  • Pajares, F. (1993). Preservice teachers’ beliefs: a focus for teacher education. Action in Teacher Education, 15, 45–54. https://doi.org/10.1080/01626620.1993.10734409.

    Google Scholar 

  • Panadero, E. (2017). A review of self-regulated learning: six models and four directions for research. Frontiers in Psychology, 8(422), 1–28. https://doi.org/10.3389/fpsyg.2017.00422.

    Google Scholar 

  • Patrick, H., & Pintrich, P. R. (2001). Conceptual change in teachers’ intuitive conceptions of learning, motivation, and instruction: the role of motivational and epistemological beliefs. In B. Torff & R. J. Sternberg (Eds.), Understanding and teaching the intuitive mind: Student and teacher learning (pp. 117–143). Mahwah: Lawrence Erlbaum Associates.

    Google Scholar 

  • Peeters, J., De Backer, F., Kindekens, A., Triquet, K., & Lombaerts, K. (2016). Teacher differences in promoting students’ self-regulated learning: exploring the role of student characteristics. Learning and Individual Differences, 52, 88–96. https://doi.org/10.1016/j.lindif.2016.10.014.

    Google Scholar 

  • Perry, N. E., Hutchinson, L., & Thauberger, C. (2008). Talking about teaching self-regulated learning: scaffolding student teachers’ development and use of practices that promote self-regulated learning. International Journal of Educational Research, 47, 97–108. https://doi.org/10.1016/j.ijer.2007.11.010.

    Google Scholar 

  • Perry, N. E., Brenner, C. A., & Macpherson, N. (2015a). Using teacher learning teams as a framework for bridging theory and practice in self-regulated learning. In T. J. Cleary (Ed.), Self-regulated learning interventions with at-risk youth: Enhancing adaptability, performance, and well-being (pp. 229–250). Washington, DC: American Psychological Association. https://doi.org/10.1037/14641-011.

    Google Scholar 

  • Perry, N. E., Brenner, C. A., & MacPherson, N. (2015b). Using teacher learning teams as a framework for bridging theory and practice in self-regulated learning. In T. J. Cleary (Ed.), Self-regulated learning interventions with at-risk youth. Washington, DC: American Psychological Association. https://doi.org/10.1037/14641-011.

    Google Scholar 

  • Pintrich, P. R. (1999). The role of motivation in promoting and sustaining self-regulated learning. International Journal of Educational Research, 31, 459–470. https://doi.org/10.1016/S0883-0355(99)00015-4.

    Google Scholar 

  • Pintrich, P. R. (2002). The role of metacognitive knowledge in learning, teaching, and assessing. Theory Into Practice, 41, 219–225. https://doi.org/10.1207/s15430421tip4104_3.

    Google Scholar 

  • Pintrich, P. R., McKeachie, W. J., & Lin, Y. (1987). Teaching a course in learning to learn. Teaching of Psychology, 14, 81–86. https://doi.org/10.1207/s15328023top1402_3.

    Google Scholar 

  • Posner, G. J., Strike, K. A., Hewson, P. W., & Gertzog, W. A. (1982). Accommodation of a scientific conception: toward a theory of conceptual change. Science Education, 66, 211–227. https://doi.org/10.1002/sce.3730660207.

    Google Scholar 

  • Pressley, M. (1986). The relevance of the good strategy user model to the teaching of mathematics. Educational Psychologist, 21, 139–161. https://doi.org/10.1080/00461520.1986.9653028.

    Google Scholar 

  • Pressley, M., & Afflerbach, P. (1995). Verbal protocols of reading: The nature of constructively responsive reading. Hillsdale: Lawrence Erlbaum Associates, Inc..

    Google Scholar 

  • Pressley, M., Borkowski, J., & Schneider, W. (1989). Good information processing: what is it and what education can do to promote it. Journal of Experimental Child Psychology, 43, 194–211. https://doi.org/10.1016/0883-0355(89)90069-4.

    Google Scholar 

  • Rawson, K. A., Vaughn, K. E., Walsh, M., & Dunlosky, J. (2018). Investigating and explaining the effects of successive relearning on long-term retention. Journal of Experimental Psychology: Applied. https://doi.org/10.1037/xap0000146.

  • Reber, A. S. (1989). Implicit learning and tacit knowledge. Journal of Experimental Psychology: General, 118, 219–235. https://doi.org/10.1037/0096-3445.118.3.219.

    Google Scholar 

  • Richardson, V., & Placier, P. (2001). Teacher change. In V. Richardson (Ed.), Handbook of research on teaching (4th ed., pp. 905–947). Washington, DC: American Educational Research Association.

    Google Scholar 

  • Rieser, S., Naumann, A., Decristan, J., Fauth, B., Klieme, E., & Buttner, G. (2016). The connection between teaching and learning: linking teaching quality and metacognitive strategy use in primary school. British Journal of Educational Psychology, 86, 526–545. https://doi.org/10.1111/bjep.12121.

    Google Scholar 

  • Schneider, W., Lingel, K., Artelt, C., & Neuenhaus, N. (2017). Metacognitive knowledge in secondary school students: assessment, structure, and developmental change. In D. Leutner, J. Fleischer, J. Grunkorn, & E. Klieme (Eds.), Competence assessment in education: Research, models and instruments (pp. 285–302). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-50030-0_17.

    Google Scholar 

  • Schunk, D. A., & Greene, J. A. (Eds.). (2018). Handbook of self-regulation of learning and performance (2nd ed.). New York: Routledge.

    Google Scholar 

  • Schunk, D. H., & Zimmerman, B. J. (2013). Self-regulation and learning. In W. M. Reynolds, G. E. Miller, & I. B. Weiner (Eds.), Handbook of psychology: Educational psychology (Vol. 7, 2nd ed., pp. 45–68). Hoboken: Wiley.

    Google Scholar 

  • Servant, M., Cassey, P., Woodman, G. F., & Logan, G. D. (2018). Neural bases of automaticity. Journal of Experimental Psychology: Learning, Memory, and Cognition, 44, 440–464. https://doi.org/10.1037/xlm0000454.

    Google Scholar 

  • Sinatra, G. M., & Taasoobshirazi, G. (2018). The self-regulation of learning and conceptual change in science: research, theory, and educational applications. In D. H. Schunk & J. A. Greene (Eds.), Handbook of self-regulation of learning and performance (2nd ed., pp. 153–165). New York: Routledge/Taylor & Francis Group.

    Google Scholar 

  • Sitzman, T., & Ely, K. (2011). A meta-analysis of self-regulated learning in work-related training and educational attainment: what we know and where we need to go. Psychological Bulletin, 137, 421–442. https://doi.org/10.1037/a0022777.

    Google Scholar 

  • Smith, J. P., diSessa, A. A., & Roschelle, J. (1993-1994). Misconceptions reconceived: a constructivist analysis of knowledge in transition. Journal of the Learning Sciences, 3, 115–163. https://doi.org/10.1207/s15327809jls0302_1.

    Google Scholar 

  • Spörer, N., & Brunstein, J. C. (2009). Fostering the reading comprehension of secondary school students through peer-assisted learning: effects on strategy knowledge, strategy use, and task performance. Contemporary Educational Psychology, 34, 289–297. https://doi.org/10.1016/j.cedpsych.2009.06.004.

    Google Scholar 

  • Spoth, R., Rohrbach, L. A., Greenberg, M., Leaf, P., Brown, C. H., Fagan, A., Catalano, R. F., Pentz, M. A., Sloboda, J., & Hawkins, J. D. (2013). Addressing core challenges for the next generation of type 2 translation research and systems: the translation science to population impact (TSCI impact) framework. Prevention Science, 14, 319–351. https://doi.org/10.1007/s11121-012-0362-6.

    Google Scholar 

  • Spruce, R., & Bol, L. (2015). Teacher beliefs, knowledge, and practice of self-regulated learning. Metacognition and Learning, 10, 245–277. https://doi.org/10.1007/s11409-014-9124-0.

    Google Scholar 

  • Stathopoulou, C., & Vosniadou, S. (2007). Conceptual change in physics and physics related epistemological beliefs: a relationship under scrutiny. In S. Vosniadou, A. Baltas, & X. Vamvakoussi (Eds.), Reframing the conceptual change approach in learning and instruction (pp. 145–165). Amsterdam: Elsevier.

    Google Scholar 

  • Staub, F., & Stern, E. (2002). The nature of teachers’ pedagogical content beliefs matters of student achievement gains: quasi-experimental evidence from elementary mathematics. Journal of Educational Psychology, 94, 344–355. https://doi.org/10.1037/0022-0663.94.2.344.

    Google Scholar 

  • Sweller, J., & Paas, F. (2017). Should self-regulated learning be integrated with cognitive load theory? A commentary. Learning and Instruction, 51, 85–89. https://doi.org/10.1016/j.learninstruc.2017.05.005.

    Google Scholar 

  • Thadani, V., Breland, W., & Dewar, J. (2015). Implicit theories about teaching skills predict university faculty members’ interest in professional learning. Learning and Individual Differences, 40, 163–169. https://doi.org/10.1016/j.lindif.2015.03.026.

    Google Scholar 

  • Tricot, A., & Sweller, J. (2014). Domain-specific knowledge and why teaching generic skills does not work. Educational Psychology Review, 26, 265–283. https://doi.org/10.1007/s10648-013-9243-1.

    Google Scholar 

  • Tuckman, B. W., & Kennedy, G. J. (2011). Teaching learning strategies to increase success of first-term college students. The Journal of Experimental Education, 79, 478–504. https://doi.org/10.1080/00220973.2010.512318.

    Google Scholar 

  • Usher, E. L., & Schunk, D. H. (2018). Social cognitive theoretical perspective of self-regulation. In D. H. Schunk & J. A. Greene (Eds.), Handbook of self-regulation of learning and performance (2nd ed., pp. 19–35). New York: Routledge/Taylor & Francis.

    Google Scholar 

  • Usó-Doménech, J. L., & Nescolarde-Selva, L. (2016). What are belief systems? Foundations of Science, 21, 147–152. https://doi.org/10.1007/s10699-015-9409-z.

    Google Scholar 

  • Van Deur, P., Napier, R., & Lawson, M. J. (2016). Teachers’ and pre-service teachers’ knowledge about learning and teaching. Paper presented at the Annual Conference of the Australian Association for Research in Education, Melbourne, Australia.

  • Vanderlinde, R., & van Braak, J. (2010). The gap between educational research and practice: views of teachers, school leaders, intermediaries and researchers. British Educational Research Journal, 36, 299–316. https://doi.org/10.1080/01411920902919257.

    Google Scholar 

  • Veenman, M. V. J. (2017). Assessing metacognitive deficiencies and effectively instructing metacognitive skills. Teachers College Record, 119(13), 1–20 ID Number: 21923.

    Google Scholar 

  • Verneau, M., van der Kamp, J., Savelsbergh, G. J., & de Looze, M. P. (2014). Age and time effects on implicit and explicit learning. Experimental Aging Research, 40, 477–511. https://doi.org/10.1080/0361073X.2014.926778.

    Google Scholar 

  • Vosniadou, S. (Ed.). (2013). International handbook of research on conceptual change (2nd ed.). New York: Routledge.

    Google Scholar 

  • Vosniadou, S., & Skopeliti, I. (2014). Conceptual change from the framework theory side of the fence. Science and Education, 23, 1427–1445. https://doi.org/10.1007/s11191-013-9640-3.

    Google Scholar 

  • Vosniadou, S., Lawson, M. J., Wyra, M., Van Deur, P., Napier, R., & Jeffries, D. (2017). Pre-service teachers’ beliefs about learning and teaching and their influence on self-reported SRL practices and achievement. Paper presented at the Annual Conference of the Australian Association for Research in Education, Canberra, Australia.

  • Waeytens, K., Lens, W., & Vandenberghe, R. (2002). ‘Learning to learn’: teachers’ conceptions of their supporting role. Learning and Instruction, 12, 305–322. https://doi.org/10.1016/S0959-4752(01)00024-X.

    Google Scholar 

  • Warfield, J., Wood, T., & Lehman, J. D. (2005). Autonomy, beliefs and the learning of elementary mathematics teachers. Teaching and Teacher Education, 21, 439–456. https://doi.org/10.1016/j.tate.2005.01.011.

    Google Scholar 

  • Wehmeyer, M. L., Agran, M., & Hughes, C. A. (2000). National survey of teachers’ promotion of self-determination and student-directed learning. The Journal of Special Education, 34, 58–68. https://doi.org/10.1177/002246690003400201.

    Google Scholar 

  • Weinstein, C. E., & Mayer, R. E. (1986). The teaching of learning strategies. In M. C. Wittrock (Ed.), Handbook of research on teaching (3rd ed., pp. 315–327). New York: Macmillan.

    Google Scholar 

  • Winne, P. H. (1991). Motivation and teaching. In H. C. Waxman & H. J. Walberg (Eds.), Effective teaching: Current research (pp. 295–314). Berkeley: McCutchan Publishing.

    Google Scholar 

  • Winne, P. H. (2001). Self-regulated learning viewed from models of information processing. In B. J. Zimmerman & D. H. Schunk (Eds.), Self-regulated learning and academic achievement: Theoretical perspectives (2nd ed., pp. 153–189). Mahwah: Lawrence Erlbaum Associates Publishers.

    Google Scholar 

  • Winne, P. H. (2014). Issues in researching self-regulated learning as patterns of events. Metacognition and Learning, 9, 229–237. https://doi.org/10.1007/s11409-014-9113-3.

    Google Scholar 

  • Winne, P. H. (2018). Cognition and metacognition within self-regulated learning. In D. H. Schunk & J. A. Greene (Eds.), Handbook of self-regulation of learning and performance (2nd ed., pp. 36–48). New York: Routledge/Taylor & Francis.

    Google Scholar 

  • Wittrock, M. C. (1974). Learning as a generative process. Educational Psychologist, 11, 87–95. https://doi.org/10.1080/0046152740952912.

    Google Scholar 

  • Woolfolk-Hoy, A., & Murphy, P. K. (2001). Teaching educational psychology to the implicit mind. In B. Torff & R. J. Sternberg (Eds.), Understanding and teaching the intuitive mind: Student and teacher learning (pp. 145–185). Mahwah: Lawrence Erlbaum.

    Google Scholar 

  • Woolfolk-Hoy, A., & Tschannen-Moran, M. (1999). Implications of cognitive approaches to peer learning for teacher education. In A. King & A. M. O’Donnell (Eds.), Cognitive perspectives on peer learning (pp. 257–283). Mahwah: Erlbaum.

    Google Scholar 

  • Yang, C., Potts, R., & Shanks, D. R. (2017). Metacognitive unawareness of the errorful generation benefit and its effects on self-regulated learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 43, 1073–1092. https://doi.org/10.1037/xlm0000363.

    Google Scholar 

  • Ziegler, E., Edelsbrunner, P. A., & Stern, E. (2018). The relative merits of explicit and implicit learning of contrasted algebra principles. Educational Psychology Review. https://doi.org/10.1007/s10648-017-9424-4.

  • Zimmerman, B. J. (2002). Becoming a self-regulated learner: an overview. Theory into Practice, 41, 64–70. https://doi.org/10.1207/s15430421tip4102_2.

    Google Scholar 

  • Ziori, E., & Dienes, Z. (2012). The time course of implicit and explicit concept learning. Consciousness and Cognition, 21, 204–216. https://doi.org/10.1016/j.concog.2011.12.008.

    Google Scholar 

Download references

Funding

This research was supported by a grant from the Office of Research, Flinders University.

Author information

Authors and Affiliations

  1. College of Education, Psychology and Social Work, Flinders University, Adelaide, Australia

    Michael J. Lawson, Stella Vosniadou, Penny Van Deur, Mirella Wyra & David Jeffries

Authors
  1. Michael J. Lawson
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Stella Vosniadou
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Penny Van Deur
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mirella Wyra
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. David Jeffries
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Michael J. Lawson.

Ethics declarations

Conflict of Interest

The authors declare that they have no conflicts of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lawson, M.J., Vosniadou, S., Van Deur, P. et al. Teachers’ and Students’ Belief Systems About the Self-Regulation of Learning. Educ Psychol Rev 31, 223–251 (2019). https://doi.org/10.1007/s10648-018-9453-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10648-018-9453-7

Keywords

Search

Navigation