Skip to main content

Self-regulated learning microanalysis as a tool to inform professional development delivery in real-time

An Erratum to this article was published on 30 March 2017

Abstract

Elementary teachers in the United States are tasked with teaching all core subject matter and have training that involves many topics, which may limit the depth of their subject matter knowledge. Since they have low content knowledge, they often feel less confident about teaching technical subject matter, such as science (Bleicher Journal of Science Teacher Education 17:165–187, 2006). The problem of low confidence of elementary teachers for science instruction is exacerbated when they are expected to teach science using inquiry (Hanuscin et al. Science Education 95:145–167, 2010). Self-regulated learning microanalysis, which supports both instruction and assessment, can help teachers reflect on their learning processes. This technique may provide clues for teachers to improve strategies for learning and give information to professional development instructors to inform teacher professional development experiences. The purpose of this study was to examine self-regulatory learning cycles that fourteen elementary teachers experienced while engaged in learning about inquiry during a professional development. Results of this study showed that before the professional development, teachers reported low self-efficacy but high task value and perceived instrumentality for learning about inquiry. As the professional development progressed, teachers improved their goal setting skills, self-monitoring performance, and learning tactics. The self-regulated learning microanalysis revealed information not communicated in the professional development experience, which led to adaptation of the activities in real-time to meet the needs indicated on the self-regulated learning microanalysis reports. Measuring teacher learning processes allowed the professional development instructors to pinpoint difficulties and successes during the learning tasks, which aided in precise adaptation of experiences for teacher needs.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3

References

  1. Ames, C. (1992). Achievement goals and the classroom motivational climate. In D. H. Schunk & J. L. Meece (Eds.), Student perceptions in the classroom (pp. 327–348). New York: Routledge.

    Google Scholar 

  2. Annenberg Learning. (2013). Learning science through inquiry. Retrieved from http://www.learner.org/workshops/inquiry/resources/more.html

  3. Ansberry, K. & Morgan, E. (2007). More picture-perfect science lessons: Using children’s books to guide inquiry. K-4. Arlington, VA: NSTA Press.

  4. Ansberry, K. & Morgan, E. (2011). Picture-perfect science lessons - Expanded 2nd edition: Using children’s books to guide inquiry, 3-6. Arlington, VA: NSTA Press.

  5. Appleton, K. (2003). How do beginning primary school teachers cope with science? Toward an understanding of science teaching practices. Research in Science Education, 33, 1–25.

    Article  Google Scholar 

  6. Author (2015). Book title blinded. Hauppauge: Nova Publishers.

    Google Scholar 

  7. Author & Colleague. (2010). School Science and Mathematics.

  8. Author & Colleague. (2013). Journal of Science Teacher Education.

  9. Author & Colleagues (2015). Book title blinded. New York: APA Press.

    Google Scholar 

  10. Bandura, A. (2002). Social cognitive theory in cultural context. Applied Psychology, 51(2), 269–290.

    Article  Google Scholar 

  11. Bembenutty, H., Clearly, T., & Kitsantas, A. (2013). Self-regulated learning applied across diverse disciplines. A Tribute to Barry J. Zimmerman. New York: Information Age Publishing.

    Google Scholar 

  12. Bleicher, R. E. (2006). Nurturing confidence in preservice elementary science teachers. Journal of. Science Teacher Education, 17, 165–187.

    Article  Google Scholar 

  13. Boekaerts, M., & Corno, L. (2005). Self-regulation in the classroom: A perspective on assessment and intervention. Applied Psychology: An International Review, 54(2), 199–231.

    Article  Google Scholar 

  14. Borman, G. D., Gamoran, A., & Bowdon, J. (2008). A randomized trial of teacher development in elementary science: First-year achievement effects. Journal of Research on Educational Effectiveness, 1, 237–264.

    Article  Google Scholar 

  15. Brundage, D. H., & Mackeracher, D. (1980). Adult learning principles and theirapplicationtoprogram planning. Toronto: Ministry of Education.

    Google Scholar 

  16. Brydges, R., & Butler, D. (2012). A reflective analysis of medical education research on self-regulation in learning and practice. Medical Education, 46, 71–79.

    Article  Google Scholar 

  17. Bybee, R. W. (2004). Scientific inquiry and science teaching. In L. B. Flick & N. G. Lederman (Eds.), Scientific inquiry and nature of science (pp. 1–14). Boston: Kluwer Academic Publishers.

    Google Scholar 

  18. Bybee, R., Taylor, J., Gardner, A., Van Scotter, P., Carlson, J., Westbrook, A., & Landes, N. (2006). The BSCE 5E instructional model: Origins and effectiveness. A report for Office of Science Education National Institutes of Health. Retrieved online at http://science.education.nih.gov/houseofreps.nsf/b82d55fa138783c2852572c9004f5566/$FILE/Appendix?D.pdf.

  19. Cheema, J., & Kitsantas, A. (2013). Influences of disciplinary classroom climate on high school student self-efficacy and mathematics achievement. A look at gender and racial-ethnic differences. International Journal of Science and Mathematics Education, advance online publication. doi:10.1007/s10763-013-9454-4.

    Google Scholar 

  20. Chen, C., & Whitesel, J. (2012). The validity and reliability study of a revised motivated strategy for learning questionnaire (MSLQ) for assessing computer software learning strategies. International Journal of E-Adoption, 4(2), 28–51.

    Article  Google Scholar 

  21. Cho, K., & Cho, M.-H. (2013). Training of self-regulated learning skills on a social network system. Social Psychology of Education, 16, 617–634.

    Article  Google Scholar 

  22. Cho, K., & MacArthur, C. (2011). Learning by reviewing. Journal of Educational Psychology, 103(1), 73–84.

    Article  Google Scholar 

  23. Cleary, T. J. (2011). Shifting towards self-regulation microanalytic assessment: Historical overview, essential features, and implications for research and practice. In B. J. Zimmerman & D. H. Schunk (Eds.), Handbook of Self-Regulation of Learning and Performance (pp. 329–345). Abingdon: Routledge.

    Google Scholar 

  24. Cleary, T. J., & Zimmerman, B. J. (2006). Teachers’ perceived usefulness of strategy microanalyic assessment information. Psychology in the Schools, 43, 149–155.

  25. Cleary, T. J. & Platten, P. (2013). Examining the correspondence between self-regulated learning and academic achievement: A case study analysis. Education Research International. Early online publication doi:10.1155/2013/272560.

  26. 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, 537–550.

    Article  Google Scholar 

  27. Cleary, T. J., Zimmerman, B. J., & Keating, T. (2006). Training physical education students to self-regulate during basketball free-throw practice. Research Quarterly for Exercise and Sport, 77, 251–262.

    Article  Google Scholar 

  28. Cleary, T. J., Platten, P., & Nelson, A. (2008). Effectiveness of the self-regulation empowerment program with urban high school students. Journal of Advanced Academics, 20, 70–107.

    Google Scholar 

  29. Corno, L. (1993). The best-laid plans: modern conceptions of volition and educational research. Educational Researcher, 22(2), 14–22.

    Article  Google Scholar 

  30. Corno, L., & Mandinach, E. (1983). The role of cognitive engagement in classroom learning and motivation. Educational Psychologist, 18, 88–108.

    Article  Google Scholar 

  31. Council of Chief State School Officers (2009). Effects of teacher professional development on gains in student achievement. Washington, DC: Council of Chief State School Officers.

    Google Scholar 

  32. Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed method approaches (4th ed.). Thousand Oaks: SAGE Publications, Inc..

    Google Scholar 

  33. Davis, E. A., Petish, D., & Smithey, J. (2006). Challenges new science teachers face. Review of Educational Research, 76, 607–651.

    Article  Google Scholar 

  34. Deci, E. L. (1975). Intrinsic motivation. New York: Plenum Press.

    Book  Google Scholar 

  35. Dempsey, N. P. (2010). Stimulated recall interviews in ethnography. Qualitative Sociology, 33, 349–367.

    Article  Google Scholar 

  36. DiBenedetto, M. K., & Zimmerman, B. J. (2010). Differences in self-regulatory processes among students studying science: A microanalytic investigation. The International Journal of Educational and Psychological Assessment, 5, 2–24.

    Google Scholar 

  37. DiBenedetto, M. K., & Zimmerman, B. J. (2013). Construct and predictive validity of microanalytic measures of students’ self-regulation of science learning. Learning and Individual Differences, 26, 30–41.

    Article  Google Scholar 

  38. Dickson, T. K. (2002). Assessing the effect of inquiry-based professional development on science achievement tests scores. (Doctoral Dissertation, University of North Texas, (2002). (UMI No. 3076239).

  39. Durning, S., Cleary, T., Sandars, J., Hemmer, P. A., Kokotailo, P., & Artino, A. R. (2011). Perspective: viewing ‘strugglers’ through a different lens: how a self-regulated learning perspective can help medical educators with assessment and remediation. Academic Medicine, 86, 488–495.

    Article  Google Scholar 

  40. Duschl, R. A., & Grandy, R. (2013). Two views about explicitly teaching nature of science. Science & Education, 22, 2109–2139.

    Article  Google Scholar 

  41. Duschl, R. A., Schweingruber, H. A., & Shouse, A. W. (Eds.) (2007). Taking science to school: Learning and teaching science in grades K-8. Washington, DC: National Academies Press.

    Google Scholar 

  42. Efklides, A. (2011). Interactions of metacognition with motivation and affect in self-regulated learning: the MASRL model. Educational Psychologist, 46(1), 6–25. doi:10.1080/00461520.2011.538645.

    Article  Google Scholar 

  43. English, M., & Kitsantas, A. (2013). Self-regulated learning in project based settings. Interdisciplinary Journal of Problem Based Learning, 7(2), 128–150.

    Article  Google Scholar 

  44. Gerard, L. F., Spitulnik, M., & Linn, M. C. (2010). Teacher use of evidence to customize inquiry science instruction, Journal of Research in Science Teaching, 47(9), 1037–1063.

  45. Gerard, L. F., Varma, D., Corliss, S. B., & Linn, M. C. (2011). Professional development for technology-enhanced inquiry science. Review of Educational Research, 81, 408–448.

    Article  Google Scholar 

  46. Gergen, K. J., Josselson, R., & Freeman, M. (2015). The promises of qualitative inquiry. American Psychologist, 70(1), 1–9.

    Article  Google Scholar 

  47. Ghatala, E. S. (1986). Strategy monitoring training enables young learners to select effective strategies. Educational Psychologist, 21, 434–454.

    Article  Google Scholar 

  48. Greene, J. A., & Azevedo, R. (2007). A theoretical review of Winne and Hadwin’s model of self-regulated learning: New perspectives and directions. Review of Educational Research, 77, 334–372.

    Article  Google Scholar 

  49. Greene, J. A., Robertson, J., & Croker Costa, L. J. (2011). Assessing self-regulated learning using thinking-aloud methods. In B. J. Zimmerman & D. H. Schunk (Eds.), Handbook of self-regulation of learning and performance (pp. 313–328). New York: Routledge.

    Google Scholar 

  50. Handelsman, J., Miller, S., & Pfund, C. (2007). Scientific teaching: The Wisconsin program for scientific teaching. New York: W.H. Freeman.

    Google Scholar 

  51. Hanuscin, D. L., Lee, M. H., & Akerson, V. L. (2010). Elementary teachers’ pedagogical content knowledge for teaching the nature of science. Science Education, 95, 145–167.

    Article  Google Scholar 

  52. Heller, J. L., Shinohara, M., Miratrix, L., and Hesketh, S. R., Daehler, K. R. (2010). Learning science for teaching: Effects of professional development on elementary teachers, classrooms, and students. Proceedings from Society for Research on Educational Effectiveness. Washington, D.C.

  53. Hiller, S., & Kitsantas, A. (2014). The effect of a horseshoe crab citizen science Program on student science performance and STEM career motivation. School Science and Mathematics Journal, 114(6), 302–311. doi:10.1111/ssm.12082.

    Article  Google Scholar 

  54. Hogan, K. (2000). Exploring a process view of students’ knowledge about the nature of science. Science Education, 84, 51–70.

    Article  Google Scholar 

  55. Hogan, K., & Maglienti, M. (2001). Comparing the epistemological underpinnings of students’ and scientists’ reasoning about conclusions. Journal of Research in Science Teaching, 38, 663–687.

    Article  Google Scholar 

  56. Kartika, A. (2007). Study skills training: is it an answer to the lack of college study skills? The International Journal of Learning, 14(9), 35–44.

    Google Scholar 

  57. Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry based teaching. Educational Psychologist, 41, 7586.

    Article  Google Scholar 

  58. Kitsantas, A., & Dabbagh, N. (2010). Learning to learn with integrative learning technologies (ILT): A practical guide for academic success. New York: Information Age Publishing.

    Google Scholar 

  59. Kitsantas, A., & Zimmerman, B. J. (2002). Comparing self-regulatory processes among novice, non-expert, and expert volleyball players: A microanalytic study. Journal of Applied Sports Psychology, 14, 91–2015.

    Article  Google Scholar 

  60. Kitsantas, A., Zimmerman, B. J., & Cleary, T. (2000). The role of observation and emulation in the development of athletic self-regulation. Journal of Educational Psychology, 92(4), 811–817.

    Article  Google Scholar 

  61. Knowles, M. (1980). The modern practice of adult education: Andragogy versus pedagogy. Englewood Cliffs: Cambridge Adult Education.

    Google Scholar 

  62. Lincoln, Y. S., & Guba, E. G. (2000). Paradigmatic controversies, contradictions, and emerging confluences. In N. K. Denzin & Y. S. Lincoln (Eds.), Handbook of qualitative research (pp. 163–188). Thousand Oaks: SAGE Publications, Inc..

    Google Scholar 

  63. Locke, E. A., & Latham, G. P. (1990). A theory of goal setting and task performance. Englewood Cliffs: Prentice Hall.

    Google Scholar 

  64. Loucks-Horsley, S., Love, N., Stiles, K., Mundry, S., & Hewson, P. (2003). Designing professional development for teachers of science and mathematics (2nd ed.) Thousand Oaks, CA: Corwin Press.

  65. Loucks-Horsley, S., Stiles, K., Mundry, S., Love, N., & Hewson, P. W. (2010). Designing professional development for teachers of science and mathematics. Thousand Oaks: Corwin Press.

    Google Scholar 

  66. Lucangeli, D., & Cabrele, S. (2006). Mathematical difficulties in ADHD. Exceptionality., 14(1), 53–62. doi:10.1207/s15327035ex1401.

    Article  Google Scholar 

  67. Maxwell, J. A. (2003). Qualitative research design: an interactive approach. New York: Sage Publications, Inc..

    Google Scholar 

  68. Minner, D. D., Levy, A. J., & Century, J. R. (2010). Inquiry-based science instruction - what is it and does it matter? Results from a research synthesis years 1984 to 2002. Journal of Research in Science Teaching, 47, 474–496.

    Article  Google Scholar 

  69. National Center for Educational Statistics (NCES) (2012). Science in action: Hands-on and interactive computer tasks from the 2009 science assessment. Washington, DC: U.S. Department of Education.

    Google Scholar 

  70. National Research Council (1996). National science education standards. Washington, DC: National Academy Press.

    Google Scholar 

  71. Panadero, E., Klug, J., & Järvelä, S. (2015). Third wave of measurement in the self-regulated learning field: When measurement and intervention come hand in hand. Scandinavian Journal of Educational Research (online first). doi:10.1080/00313831.2015.1066436.

    Google Scholar 

  72. Paris, S. G., Cross, D. R., & Lipson, M. Y. (1984). Informed strategies for learning: A program to improve children’s reading awareness and comprehension. Journal of Educational Psychology, 76, 1239–1252.

    Article  Google Scholar 

  73. Perry, N. E., & Rahim, A. (2011). Studying self-regulated learning in classrooms. In B. J. Zimmerman & D. H. Schunk (Eds.), Handbook of self-regulation of learning and performance (pp. 122–136). New York: Routledge.

    Google Scholar 

  74. Pintrich, P. R. (2000). The role of goal orientation in self-regulated learning. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 452–502). San Diego: Academic Press.

    Google Scholar 

  75. Pintrich, P. R., & Smith, D. A. (1993). Reliability and predictive validity of the motivated strategies for learning questionnaire (MSLQ). Educational and Psychological Measurement, 53, 801–813. doi:10.1177/0013164493053003024.

    Article  Google Scholar 

  76. Rohrkemper, M. (1989). Self-regulated learning and academic achievement: A Vygotskian view. In B. J. Zimmerman & D. H. Schunk (Eds.), Self-regulated learning and academic achievement: Theory, research and practice (pp. 143–167). New York: Springer.

    Chapter  Google Scholar 

  77. Rubin, R. L., & Norman, J. T. (1992). Systematic modeling versus the learning cycle: Comparative effects of integrated science process skill achievement. Journal of Research in Science Teaching, 29, 715–727.

    Article  Google Scholar 

  78. Ryan, R. M., Connell, J. P., & Deci, E. L. (1984). A motivational analysis of self-determination and self-regulation in education. In C. Ames & R. Ames (Eds.), Research on Motivation in Education (Vol. 2, pp. 13–52). New York: Academic Press.

    Google Scholar 

  79. Schmitz, B., & Perels, F. (2011). Self-monitoring of self-regulation during math homework behaviour using standardized diaries. Metacognition and Learning, 6(3), 255–273. doi:10.1007/s11409-011-9076-6.

    Article  Google Scholar 

  80. Schraw, G., Crippen, K., & Hartley, K. (2006). Promoting self-regulation in science education: Metacognition as part of a broader perspective on learning. Research in Science Education, 36, 111139.

    Article  Google Scholar 

  81. Schunk, D. H. (1982). Verbal self-regulation as a facilitator of children’s achievement and self-efficacy. Human Learning, 1¸ 265–277.

  82. Stake, R. E. (2006). Multiple case study analysis. London: The Guilford Press.

    Google Scholar 

  83. Thomas, J. W., & Rohwer Jr., W. D. (1986). Academic studying: The role of learning strategies. Educational Psychologist, 21, 19–41.

    Article  Google Scholar 

  84. Trautmann, N. M., & MaKinster, J. G. (2010). Flexibly adaptive professional development in support of teaching science with geospatial technology. Journal of Science Teacher Education, 21, 351–370.

    Article  Google Scholar 

  85. Veenman, M. V. J. (2011). Learning to self-monitor and self-regulate. In R. Mayer & P. Alexander (Eds.), Handbook of research on learning and instruction (pp. 197–218). New York: Routledge.

  86. Wang, M. C., & Peverly, S. T. (1986). The self-instructive process in classroom learning contexts. Contemporary Educational Psychology, 11, 370–404.

    Article  Google Scholar 

  87. Weinstein, C. E., Schulte, A. C., & Palmer, D. R. (1987). Learning And Study Strategies Inventory. Clearwater: H & H Publishing.

    Google Scholar 

  88. Wingate, U. (2006). Doing away with study skills. Teaching in Higher Education, 11(4), 457–469.

    Article  Google Scholar 

  89. Winne, P. H., & Jamieson-Noel, D. L. (2002). Exploring students’ calibration of self-reports about study tactics and achievement. Contemporary Educational Psychology, 28, 259–276.

    Article  Google Scholar 

  90. Winne, P., & Perry, N. (2000). Measuring self-regulated learning. In M. Boekaerts, P. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 531–566). San Diego: Academic Press.

    Chapter  Google Scholar 

  91. Yoon, K. S., Duncan, T., Lee, S. W., Scarloss, B., & Shapley, K. L. (2007). Reviewing the evidence on how teacher professional development affects student achievement. National Center for Educational Evaluation and Regional Assistance.

  92. Zimmerman, B. J. (1986). Development of self-regulated learning: which are the key subprocesses? Contemporary Educational Psychology, 11, 307–313.

    Article  Google Scholar 

  93. Zimmerman, B. J. (1990). Self-regulating academic learning and achievement: the emergence of a social cognitive perspective. Educational Psychology Review, 2, 173–201.

    Article  Google Scholar 

  94. Zimmerman, B. J. (2000). Attaining self-regulation: A social-cognitive perspective. In M. Boekaerts, P. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 13–39). San Diego: Academic Press.

    Chapter  Google Scholar 

  95. Zimmerman, B. J. (2008). Investigating self-regulation and motivation: historical background, methodological developments, and future prospects. American Educational Research Journal, 45(1), 166–183.

    Article  Google Scholar 

  96. Zimmerman, B. J., & Kitsantas, A. (1997). Developmental phases in self-regulation: Shifting from process goals to outcome goals. Journal of Educational Psychology, 89, 29–36.

    Article  Google Scholar 

  97. Zimmerman, B., & Kitsantas, A. (2002). Acquiring writing revision and self-regulatory skill through observation and emulation. Journal of Educational Psychology, 94(4), 660–668.

    Article  Google Scholar 

  98. Zimmerman, B. J., & Kitsantas, A. (2007). Reliability and validity of self-efficacy for learning form (SELF) scores of college students. Journal of Psychology, 215(3), 157–163.

    Google Scholar 

  99. Zimmerman, B. J., & Martinez-Pons, M. (1986). Development of a structured interview for assessing student use of self-regulated learning-strategies. American Educational Research Journal, 23(4), 614–628.

    Article  Google Scholar 

Download references

Acknowledgment

We would like to acknowledge Dr. Timothy Cleary for his helpful comments on the draft versions of this manuscript.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Erin E. Peters-Burton.

Ethics declarations

Funding

This study was not funded by a grant source.

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

An erratum to this article is available at http://dx.doi.org/10.1007/s11409-017-9169-y.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Peters-Burton, E.E., Botov, I.S. Self-regulated learning microanalysis as a tool to inform professional development delivery in real-time. Metacognition Learning 12, 45–78 (2017). https://doi.org/10.1007/s11409-016-9160-z

Download citation

Keywords

  • Self-regulated learning
  • SRL microanalysis
  • Inquiry-based instruction
  • Science education
  • Teacher professional development