Skip to main content
SpringerLink
Log in

Mine the process: investigating the cyclical nature of upper primary school students’ self-regulated learning

  • Original Research
  • Published:
Instructional Science Aims and scope Submit manuscript

Abstract

The present study investigates primary school students’ self-regulated learning (SRL) process by exploring the sequence in which SRL activities are conducted during learning. The aims of this study are twofold: investigating the presence of the theoretically hypothesized cyclical nature in students’ SRL process, as well as potential differences herein for high, average, and low achievers. Think-aloud data of 104 upper primary school students were analysed by means of process mining analysis. The results indicate that students commonly adopt a cyclical approach to learning by implementing preparatory, performance, and appraisal activities during learning. However, the results indicate clear differences in the quality of students’ SRL process. High achievers, compared to low and average achievers, show a more strategic and adaptive approach to learning during all phases of their learning process. They more strategically and effectively orient on and plan assignments, combine different cognitive strategies, and adopt self-evaluation to regulate their learning process.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Notes

  1. Since no national measures of academic standards are available in Flanders and in line with prior research (e.g., Merchie and Van Keer 2014b; Perry and VandeKamp 2000; Wijsman et al. 2016) teacher judgements on students’ general ability level were used to select participants and assure a cross-section of abilities in the sample. In this respect, prior research indicates that using teacher judgements is a reliable technique to estimate students’ ability level since their strong congruence with students’ actual scores (e.g. Südkamp et al. 2012).

  2. Note that elaboration strategies are conducted by only 18 of the 32 high achieving students, while the SRL activities included in high achievers’ process map are adopted by 20 or more students.

  3. Solid and dashed lines do not represent substantive differences. They are included to enhance the figures’ readability.

References

  • Alexander, P. A. (1998). The nature of disciplinary and domain learning: The knowledge, interest, and strategic dimensions of learning from subject matter text. In C. R. Hynd (Ed.), Learning from texts across conceptual domains (pp. 263–287). New York: Routledge.

    Google Scholar 

  • Azevedo, R. (2007). Understanding the complex nature of self-regulatory processes in learning with computer-based learning environments: An introduction. Metacognition and Learning, 2(2–3), 57–65. https://doi.org/10.1007/s11409-007-9018-5.

    Article  Google Scholar 

  • Bannert, M., Reimann, P., & Sonnenberg, C. (2014). Process mining techniques for analysing patterns and strategies in students’ self-regulated learning. Metacognition and Learning, 9(2), 161–185. https://doi.org/10.1007/s11409-013-9107-6.

    Article  Google Scholar 

  • Boekaerts, M. (1999). Self-regulated learning: Where we are today. International Journal of Educational Research, 1(31), 445–457.

    Article  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.

    Article  Google Scholar 

  • Boekaerts, M., & Corno, L. (2005). Self regulation in the classroom: A perspective on assessment and intervention. Applied Psychology, 54(2), 199–231. https://doi.org/10.1111/j.1464-0597.2005.00205.x.

    Article  Google Scholar 

  • Chi, M. T. H. (1997). Quantifying qualitative analyses of verbal data: A practical guide. The Journal of the Learning Sciences, 6(3), 271–315. https://doi.org/10.1207/s15327809jls0603_1.

    Article  Google Scholar 

  • Cleary, T. J., & Chen, P. P. (2009). Self-regulation, motivation, and math achievement in middle school: Variations across grade level and math context. Journal of School Psychology, 47(5), 291–314. https://doi.org/10.1016/j.jsp.2009.04.002.

    Article  Google Scholar 

  • DiFrancesca, D., Nietfeld, J. L., & Cao, L. (2016). A comparison of high and low achieving students on self-regulated learning variables. Learning and Individual Differences. https://doi.org/10.1016/j.lindif.2015.11.010.

    Article  Google Scholar 

  • Dinsmore, D. L., Alexander, P. A., & Loughlin, S. M. (2008). Focusing the conceptual lens on metacognition, self-regulation, and self-regulated learning. Educational Psychology Review, 20(4), 391–409. https://doi.org/10.1007/s10648-008-9083-6.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Eveland, W. P., & Dunwoody, S. (2000). Examining information processing on the world wide web using think aloud protocols. Media Psychology, 2(3), 219–244. https://doi.org/10.1207/S1532785XMEP0203_2.

    Article  Google Scholar 

  • Fluxicon. (2019). Disco user’s guide. Retrieved January 7, 2019, from https://fluxicon.com/disco/files/Disco-User-Guide.pdf

  • Fox, E. (2009). The role of reader characteristics in processing and learning from informational text. Review of Educational Research. https://doi.org/10.3102/0034654308324654.

    Article  Google Scholar 

  • Greene, J. A., Dellinger, K. R., Binba, B., & Costa, L. (2013). A two-tiered approach to analyzing self-regulated learning data to inform the design of hypermedia learning environments. In R. Azevedo & V. Aleven (Eds.), International handbook of metacognition and learning technologies (pp. 117–128). New York: Springer.

    Chapter  Google Scholar 

  • Greene, J. A., Robertson, J., & Croker Costa, L. J. (2011). Assessing self-regulated learning using think-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 

  • Günther, C. W., & van der Aalst, W. M. P. (2007). Fuzzy mining—adaptive process simplification based on multi-perspective metrics. In G. Alonso, P. Dadam, & M. Rosemann (Eds.), Proceedings of the 5th international conference on business process management (BPM 2007) 24–28 September 2007 (pp. 328–343). Brisbane, Australia

  • Hadwin, A. F., Järvelä, S., & Miller, M. (2011). Self-regulated, co-regulated, and socially shared regulation of learning. In D. H. S. Barry & J. Zimmerman (Eds.), Handbook of self-regulation of learning and performance (pp. 65–84). New York: Routledge.

    Google Scholar 

  • Heirweg, S., De Smul, M., Devos, G., & Van Keer, H. (2019). Profiling upper primary school students’ self-regulated learning through self-report questionnaires and think-aloud protocol analysis. Learning and Individual Differences, 70, 155–168. https://doi.org/10.1016/j.lindif.2019.02.001.

    Article  Google Scholar 

  • Kistner, S., Rakoczy, K., Otto, B., Dignath-van Ewijk, C., Büttner, G., & Klieme, E. (2010). Promotion of self-regulated learning in classrooms: Investigating frequency, quality, and consequences for student performance. Metacognition and Learning, 5(2), 157–171. https://doi.org/10.1007/s11409-010-9055-3.

    Article  Google Scholar 

  • Klug, J., Ogrin, S., & Keller, S. (2011). A plea for self-regulated learning as a process. Psychological Test and Assessment Modeling, 53(1), 51–72.

    Google Scholar 

  • Lawson, M. J., Vosniadou, S., Van Deur, P., Wyra, M., & Jeffries, D. (2019). Teachers’ and students’ belief systems about the self-regulation of learning. Educational Psychology Review. https://doi.org/10.1007/s10648-018-9453-7.

    Article  Google Scholar 

  • Liu, W. C., Wang, C. K. J., Kee, Y. H., Koh, C., Lim, B. S. C., & Chua, L. (2014). College students’ motivation and learning strategies profiles and academic achievement: A self-determination theory approach. Educational Psychology, 34(3), 338–353. https://doi.org/10.1080/01443410.2013.785067.

    Article  Google Scholar 

  • Malmberg, J., Järvenoja, H., & Järvelä, S. (2010). Tracing elementary school students’ study tactic use in gStudy by examining a strategic and self-regulated learning. Computers in Human Behavior, 26(5), 1034–1042. https://doi.org/10.1016/j.chb.2010.03.004.

    Article  Google Scholar 

  • Malmberg, J., Järvenoja, H., & Järvelä, S. (2013). Patterns in elementary school students′ strategic actions in varying learning situations. Instructional Science, 41(5), 933–954. https://doi.org/10.1007/s11251-012-9262-1.

    Article  Google Scholar 

  • Mayer, R. E. (1996). Learning strategies for making sense out of expository text: The SOI model for guiding three cognitive processes in knowledge construction. Educational Psychology Review, 8(4), 357–371. https://doi.org/10.1007/BF01463939.

    Article  Google Scholar 

  • Mega, C., Ronconi, L., & De Beni, R. (2014). What makes a good student? How emotions, self-regulated learning, and motivation contribute to academic achievement. Journal of Educational Psychology, 106(1), 121–131. https://doi.org/10.1037/a0033546.

    Article  Google Scholar 

  • Meneghetti, C., De Beni, R., & Cornoldi, C. (2007). Strategic knowledge and consistency in students with good and poor study skills. European Journal of Cognitive Psychology, 19(4–5), 628–649. https://doi.org/10.1080/09541440701325990.

    Article  Google Scholar 

  • Merchie, E., & Van Keer, H. (2014a). Learning from text in late elementary education. Comparing think-aloud protocols with self-reports. Procedia Social and Behavioral Sciences. https://doi.org/10.1016/j.sbspro.2014.01.1193.

    Article  Google Scholar 

  • Merchie, E., & Van Keer, H. (2014b). Using on-line and off-line measures to explore fifth and sixth graders’ text-learning strategies and schematizing skills. Learning and Individual Differences, 32, 193–203. https://doi.org/10.1016/j.lindif.2014.03.012.

    Article  Google Scholar 

  • Nandagopal, K., & Ericsson, K. A. (2012). An expert performance approach to the study of individual differences in self-regulated learning activities in upper-level college students. Learning and Individual Differences. https://doi.org/10.1016/j.lindif.2011.11.018.

    Article  Google Scholar 

  • Paloş, R., Munteanu, A., Costea, I., & Macsinga, I. (2011). Motivational and cognitive variables with impact on academic performance—Preliminary study. Procedia Social and Behavioral Sciences, 15, 138–142. https://doi.org/10.1016/j.sbspro.2011.03.063.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Panadero, E., Klug, J., & Järvelä, S. (2016). Third wave of measurement in the self-regulated learning field: When measurement and intervention come hand in hand. Scandinavian Journal of Educational Research, 60(6), 723–735. https://doi.org/10.1080/00313831.2015.1066436.

    Article  Google Scholar 

  • Pekrun, R., Goetz, T., Titz, W., & Perry, R. P. (2002). Academic emotions in students’ self-regulated learning and achievement: A program of qualitative and quantitative research. Educational Psychologist, 37(2), 91–106.

    Article  Google Scholar 

  • Perry, N. E., & VandeKamp, K. J. O. (2000). Creating classroom contexts that support young children’s development of self-regulated learning. International Journal of Educational Research, 33(7–8), 821–843. https://doi.org/10.1016/S0883-0355(00)00052-5.

    Article  Google Scholar 

  • 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. 451–502). San Diego, CA: Acadamic Press.

    Chapter  Google Scholar 

  • Pintrich, P. R. (2004). A conceptual framework for assessing motivation and self-regulated learning in college students. Educational Psychology Review, 16(4), 385–407. https://doi.org/10.1007/s10648-004-0006-x.

    Article  Google Scholar 

  • Pintrich, P. R., & De Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82(1), 33–40. https://doi.org/10.1037/0022-0663.82.1.33.

    Article  Google Scholar 

  • Pressley, M., Borkowski, J. G., & Schneider, W. (1985). Cognitive strategies: Good strategy users coordinate metacognition and knowledge. Annals of Child Development, 4, 89–129.

    Google Scholar 

  • Puustinen, M., & Pulkkinen, L. (2001). Models of self-regulated learning: A review. Scandinavian Journal of Educational Research, 45(3), 269–286. https://doi.org/10.1080/00313830120074206.

    Article  Google Scholar 

  • Scheiter, K., Schubert, C., & Schüler, A. (2018). Self-regulated learning from illustrated text: Eye movement modelling to support use and regulation of cognitive processes during learning from multimedia. British Journal of Educational Psychology, 88(1), 80–94. https://doi.org/10.1111/bjep.12175.

    Article  Google Scholar 

  • Schellings, G. L. M., Van Hout-Wolters, B. H. A. M., Veenman, M. V. J., & Meijer, J. (2013). Assessing metacognitive activities: The in-depth comparison of a task-specific questionnaire with think-aloud protocols. European Journal of Psychology of Education, 28(3), 963–990. https://doi.org/10.1007/s10212-012-0149-y.

    Article  Google Scholar 

  • Schoor, C., & Bannert, M. (2012). Exploring regulatory processes during a computer-supported collaborative learning task using process mining. Computers in Human Behavior, 28(4), 1321–1331. https://doi.org/10.1016/j.chb.2012.02.016.

    Article  Google Scholar 

  • Schunk, D. H., & Zimmerman, B. J. (1998). Self-regulated learning: From teaching to self-reflective practice. New York: Guilford Press.

    Google Scholar 

  • Stoeger, H., Fleischmann, S., & Obergriesser, S. (2015). Self-regulated learning (SRL) and the gifted learner in primary school: The theoretical basis and empirical findings on a research program dedicated to ensuring that all students learn to regulate their own learning. Asia Pacific Education Review, 16, 257–267. https://doi.org/10.1007/s12564-015-9376-7.

    Article  Google Scholar 

  • Südkamp, A., Kaiser, J., & Möller, J. (2012). Accuracy of teachers’ judgments of students’ academic achievement: A meta-analysis. Journal of Educational Psychology, 104(3), 743–762. https://doi.org/10.1037/a0027627.

    Article  Google Scholar 

  • Taub, M., Mudrick, N. V., Azevedo, R., Millar, G. C., Rowe, J., & Lester, J. (2016). Using multi-level modeling with eye-tracking data to predict metacognitive monitoring and self-regulated learning with crystal island. In A. Micarelli, J. Stamper, & K. Panourgia (Eds.), International conference on intelligent tutoring systems (pp. 240–246). Dordrecht, The Netherlands: Springer.

    Chapter  Google Scholar 

  • van der Aalst, W. (2011). Process mining: Discovery, conformance and enhancement of business processes. New York: Springer.

    Book  Google Scholar 

  • van der Aalst, W., Adriansyah, A., De Medeiros, A., Arcieri, F., Baier, T., Blickle, T., et al. (2011). Process mining manifesto. In F. Daniel, K. Barkaoui, & S. Dustdar (Eds.), Business process management workshops (pp. 169–194). Berlin: Springer-Verlag.

    Google Scholar 

  • van Someren, M. W., Barnard, Y. F., & Sandberg, J. A. (1994). The think aloud method: A practical guide to modelling cognitive processes. Department of Social Science Informatics, University of Amsterdam. https://doi.org/10.1016/0306-4573(95)90031-4

  • Vanderstoep, S., Pintrich, P., & Fagerlin, A. (1996). Disciplinary differences in self-regulated learning in college students. Contemporary Educational Psychology, 21(4), 345–362. https://doi.org/10.1006/ceps.1996.0026.

    Article  Google Scholar 

  • Vandevelde, S., Van Keer, H., Schellings, G., & Van Hout-Wolters, B. (2015). Using think-aloud protocol analysis to gain in-depth insights into upper primary school children’s self-regulated learning. Learning and Individual Differences, 43, 11–30. https://doi.org/10.1016/j.lindif.2015.08.027.

    Article  Google Scholar 

  • Vandevelde, S., Van Keer, H., & Merchie, E. (2017). The challenge of promoting self-regulated learning among primary school children with a low socioeconomic and immigrant background. Journal of Educational Research. https://doi.org/10.1080/00220671.2014.999363.

    Article  Google Scholar 

  • Vansteenkiste, M., Sierens, E., Soenens, B., Luyckx, K., & Lens, W. (2009). Motivational profiles from a self-determination perspective: The quality of motivation matters. Journal of Educational Psychology, 101(3), 671–688. https://doi.org/10.1037/a0015083.

    Article  Google Scholar 

  • Vauras, M., Kinnunen, R., & Kuusela, L. (1994). Development of text-processing skills in high-, average- and low-achieving primary school children. Journal of Reading Behaviour, 26(4), 361–389.

    Article  Google Scholar 

  • Veenman, M. V. J. (2011). Alternative assessment of strategy use with self-report instruments: A discussion. Metacognition and Learning, 6(2), 205–211. https://doi.org/10.1007/s11409-011-9080-x.

    Article  Google Scholar 

  • Veenman, M. V. J., Van Hout-Wolters, B. H. A. M., & Afflerbach, P. (2006). Metacognition and learning: Conceptual and methodological considerations. Metacognition and Learning, 1(1), 3–14. https://doi.org/10.1007/s11409-006-6893-0.

    Article  Google Scholar 

  • Weinstein, C. E., Jung, J., & Acee, T. W. (2011). Learning strategies. In V. G. Aukrust (Ed.), Learning and cognition in education (pp. 137–143). Oxford: Elsevier Limited.

    Google Scholar 

  • Wijsman, L. A., Warrens, M. J., Saab, N., van Driel, J. H., & Westenberg, P. M. (2016). Declining trends in student performance in lower secondary education. European Journal of Psychology of Education, 31(4), 595–612. https://doi.org/10.1007/s10212-015-0277-2.

    Article  Google Scholar 

  • Winne, P. H. (2011). A cognitive and metacognitive analysis of self-regulated learning. In B. J. Zimmerman & D. H. Schunk (Eds.), Handbook of self-regulation of learning and performance (pp. 15–32). New York: Routledge.

    Google Scholar 

  • Winne, P. H., & Hadwin, A. F. (1998). Studying as self-regulated engagement in learning. In D. Hacker, J. Dunlosky, & A. Graesser (Eds.), Metacognition in educational theory and practice (pp. 277–304). Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Winne, P. H., & Perry, N. E. (2000). Measuring self-regulated learning. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 532–566). San Diego, CA: Academic Press.

    Google Scholar 

  • Zeidner, M., Boekaerts, M., & Pintrich, P. R. (2000). Self-regulation: Directions and challenges for future research. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 749–768). San Diego, CA: Acadamic Press.

    Chapter  Google Scholar 

  • Zimmerman, B. J. (1986). Becoming a self-regulated learner: Which are the key subprocesses? Contemporary Educational Psychology, 11(4), 307–313. https://doi.org/10.1016/0361-476X(86)90027-5.

    Article  Google Scholar 

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

    Chapter  Google Scholar 

  • Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory into Practice, 41(2), 64–71.

    Article  Google Scholar 

  • 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 

Download references

Funding

This work was supported by Grant G.0198.15N of the Research Foundation Flanders (FWO).

Author information

Authors and Affiliations

  1. Department of Educational Studies, Ghent University, Henri Dunantlaan 2, 9000, Ghent, Belgium

    Sofie Heirweg, Mona De Smul, Emmelien Merchie, Geert Devos & Hilde Van Keer

Authors
  1. Sofie Heirweg
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mona De Smul
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Emmelien Merchie
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Geert Devos
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hilde Van Keer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Emmelien Merchie.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

See Tables 2 , 3 , 4 and 5 .

Table 2 Coding scheme for analysing the use of metacognitive and motivational strategies during respectively all assignments (i.e., game, mathematics, French) and during the study text (based on Vandevelde et al. 2015)
Full size table
Table 3 Coding scheme for analysing the use of cognitive strategies during informative text studying (based on Vandevelde et al. 2015)
Full size table
Table 4 Excerpt from a think-aloud protocol: transcript and coding
Full size table
Table 5 Cued recall test questions and detailed answer key
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Heirweg, S., De Smul, M., Merchie, E. et al. Mine the process: investigating the cyclical nature of upper primary school students’ self-regulated learning. Instr Sci 48, 337–369 (2020). https://doi.org/10.1007/s11251-020-09519-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11251-020-09519-0

Keywords

Search

Navigation