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Challenges of Investigating Metacognitive Tool Use and Effects in (Rich) Web-Based Learning Environments

Chapter
Part of the Springer International Handbooks of Education book series (SIHE, volume 28)

Abstract

This chapter summarizes the rationale and findings of several studies using rich open-ended web-based learning environments (Web-LEs) as learning technology in higher education. The purpose of the studies was to examine self-regulated learning activities by tracing university students’ learning activities within a rich open-ended Web-LE by log file data. Hence, the Web-LEs used in these studies provided non-embedded as well as embedded tools supporting cognitive as well as metacognitive learning activities. Students in all studies were free to decide when and how to use these tools. To use them, they had to activate the selected tool explicitly by clicking on the respective button on the Web-LEs’ interface. The rationale for the design of the Web-LEs and for analyzing and interpreting the log file data was derived from psychological task analyses which were based on a multidimensional view of self-regulated learning within Web-LEs (e.g., Narciss et al., 2007; Winter, 2008). This chapter outlines this rationale, describes the resources and tools of the rich Web-LE called Study Desk, and summarizes several studies investigating how students used the tools of the Study Desks. Finally, limitations, challenges and implications of using log file data for investigating self-regulated learning with rich Web-LEs are discussed.

Keywords

Learning Task Online Performance Metacognitive Activity Posttest Performance Study Desk 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Alexander, P. A. (2008). Why this and why now? Introduction to the special issue on metacognition, self-regulation, and self-regulated learning. Educational Psychology Review, 20(4), 369–372.CrossRefGoogle Scholar
  2. Anderson, L. W., & Krathwohl, D. R., (Eds.) (2001). A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives. New York: London Longman.CrossRefGoogle Scholar
  3. Azevedo, R. (2005). Computer environments as metacognitive tools for enhancing learning. Educational Psychologist, 40(4), 193–197.CrossRefGoogle Scholar
  4. 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), 57–65.CrossRefGoogle Scholar
  5. Azevedo, R., & Jacobson, M. (2008). Advances in scaffolding learning with hypertext and hypermedia: A summary and critical analysis. Educational Technology Research & Development, 56(1), 93–100.CrossRefGoogle Scholar
  6. Azevedo, R., Moos, D. C., Johnson, A. M., & Chauncey, A. D. (2010). Measuring cognitive and metacognitive regulatory processes during hypermedia learning: Issues and challenges. Educational Psychologist, 45(4), 210–223.CrossRefGoogle Scholar
  7. Bannert, M., & Mengelkamp, C. (2008). Assessment of metacognitive skills by means of instruction to think aloud and reflect when prompted. Does the verbalisation method affect learning? Metacognition and Learning, 3(1), 39–58.CrossRefGoogle Scholar
  8. Berge, Z. L. (1999). Interaction in post-secondary web-based learning. Educational Technology, 41(1), 5–11.Google Scholar
  9. 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.CrossRefGoogle Scholar
  10. Butler, D. L., & Winne, P. H. (1995). Feedback and self-regulated learning: A theoretical synthesis. Review of Educational Research, 65(3), 245–281.CrossRefGoogle Scholar
  11. Ceddia, J., Sheard, J., & Tibbey, G. (2007). WAT: A tool for classifying learning activities from a log file. In S. Mann & A. Simon (Eds.), Proceedings of the ninth Australasian conference on computing education (Vol. 66, pp. 11–17). Australian Computer Society: Ballarat, Australia.Google Scholar
  12. Chen, C., & Rada, R. (1996). Interacting with hypertext: A meta-analysis of experimental studies. Human-Computer Interaction, 11(2), 125–156.CrossRefGoogle Scholar
  13. Clarebout, G., & Elen, J. (2006). Tool use in computer-based learning environments: Towards a research framework. Computers in Human Behavior, 22(3), 389–411.CrossRefGoogle Scholar
  14. Clarebout, G., & Elen, J. (2008). Tool use in open learning environments: In search of learner-related determinants. Learning Environments Research, 11(2), 163–178.CrossRefGoogle Scholar
  15. 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.CrossRefGoogle Scholar
  16. Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive-developmental inquiry. American Psychologist, 34(10), 906–911.CrossRefGoogle Scholar
  17. Flavell, J. H. (1985). Cognitive development (2nd ed.). Englewood Cliffs, NJ: Prentice Hall.Google Scholar
  18. Greene, J. A., & Azevedo, R. (2010). The measurement of learners’ self-regulated cognitive and metacognitive processes while using computer-based learning environments. Educational Psychologist, 45(4), 203–209.CrossRefGoogle Scholar
  19. Hannafin, M., Land, S., & Oliver, K. (1999). Open learning environments: Foundation, methods, and models. In C. M. Reigeluth (Ed.), Instructional-design theories and models: A new paradigm of instructional theory (Vol. II, pp. 115–140). Mahwah, NJ, USA: Lawrence Erlbaum.Google Scholar
  20. Jonassen, D. H., Tessmer, M., & Hannum, W. H. (1999). Task analysis methods for instructional design. Mahwah, NJ: Lawrence Erlbaum.Google Scholar
  21. Kaplan, A. (2008). Clarifying metacognition, self-regulation, and self-regulated learning: What’s the purpose? Educational Psychology Review, 20(4), 477–484.CrossRefGoogle Scholar
  22. Kapp, F., Narciss, S., Körndle, H., & Proske, A. (2011). Interaktive Lernaufgaben als Erfolgsfaktor für E-Learning (Interactive learning tasks as a success factor for e-learning). Zeitschrift für E-Learning, 6, 21–32.Google Scholar
  23. Klauer, K. J. (1987). Kriteriumsorientierte Tests [Criteria-oriented tests]. Göttingen, Germany: Hogrefe.Google Scholar
  24. Körndle, H., Narciss, S., & Proske, A. (2004). Konstruktion interaktiver Lernaufgaben für die universitäre Lehre [Construction of interactive learning tasks for university instruction]. In D. Carstensen & B. Barrios (Eds.), Campus 2004. Kommen die digitalen Medien an den Hochschulen in die Jahre? (pp. 57–67). Münster, Germany: Waxmann.Google Scholar
  25. Mühlenbrock, M. (2005). Automatic action analysis in an interactive learning environment. In C. Choquet, V. Luengo, & K. Yacef (Eds.), Proceedings of the workshop on usage analysis in learning systems at the 12th international conference on artificial intelligence in education AIED-2005 (pp. 73–80). The Netherlands: Amsterdam.Google Scholar
  26. Narciss, S. (2006). Informatives tutorielles Feedback. Entwicklungs- und Evaluationsprinzipien auf der Basis instruktionspsychologischer Erkenntnisse [Informative tutoring feedback. Design and evaluation principles on the basis of instructional psychology]. Münster: Waxmann.Google Scholar
  27. Narciss, S. (2008). Feedback strategies for interactive learning tasks. In J. M. Spector, M. D. Merrill, J. J. G. van Merriënboer, & M. P. Driscoll (Eds.), Handbook of research on educational communications and technology (3rd ed., pp. 125–144). Mahwah, NJ: Lawrence Erlbaum.Google Scholar
  28. Narciss, S., & Huth, K. (2004). How to design informative tutoring feedback for multi-media learning. In H. M. Niegemann, D. Leutner, & R. Brünken (Eds.), Instructional design for multimedia learning (pp. 181–195). Münster: Waxmann.Google Scholar
  29. Narciss, S., Körndle, H., Reimann, G., & Müller, C. (2004). Feedback-seeking and feedback efficiency in web-based learning – How do they relate to task and learner characteristics? In P. Gerjets, P. A. Kirschner, J. Elen, & R. Joiner (Eds.), Instructional design for effective and enjoyable computer-supported learning. Proceedings of the first joint meeting of the EARLI SIGs Instructional Design and Learning and Instruction with Computers [CD-ROM] (pp. 377–388). Tübingen: Knowledge Media Research Center.Google Scholar
  30. Narciss, S., Peters, S., Körndle, H., Dupeyrat, C., & Huet, N. (2009). Self-evaluation accuracy? How does it relate to learners’ activities and performance in self-regulated web-based learning? Paper presented at the 13th biennal conference of the European Association for Research on Learning and Instruction (EARLI).Google Scholar
  31. Narciss, S., Proske, A., & Körndle, H. (2004). Interaktive Aufgaben für das computergestützte Lernen. Vom ersten Entwurf bis zur technischen Realisierung [Interactive learning tasks for computer-supported learning. From first draft to technical realisation]. In U. Schmitz (Ed.), Linguistik lernen im Internet. Tübingen, Germany: Gunter Narr.Google Scholar
  32. Narciss, S., Proske, A., & Körndle, H. (2007). Promoting self-regulated learning in web-based learning environments. Computers in Human Behavior, 23(3), 1126–1144.CrossRefGoogle Scholar
  33. Niederhauser, D. (2008). Educational hypertext research. In J. M. Spector, M. D. Merrill, J. J. G. van Merriënboer, & M. P. Driscoll (Eds.), Handbook of research on educational communications and technology (3rd ed., pp. 199–210). Mahwah, NJ: Lawrence Erlbaum.Google Scholar
  34. Peters, S. (2010). Fähigkeitskonzepte beim selbstregulierten Lernen mit Multimedia [The role of task-specific self-concepts in self-regulated multimedia learning]. Hamburg: Dr. Kovač.Google Scholar
  35. Pressley, M., Borkwski, J. G., & Schneider, W. (1989). Good information processing: What it is and how education can promote it. International Journal of Educational Research, 13(8), 857–867.CrossRefGoogle Scholar
  36. Proske, A., Körndle, H., & Narciss, S. (2004a). The Exercise Format Editor: A multimedia tool for the design of multiple learning tasks. In H. M. Niegemann, D. Leutner, & R. Brünken (Eds.), Instructional design for multimedia learning (pp. 149–164). Münster, Germany: Waxmann.Google Scholar
  37. Proske, A., Körndle, H., & Narciss, S. (2004b). How the Exercise Format-Editor supports the design of interactive learning tasks. In G. Richards (Ed.), Proceedings of the world conference on e-learning in corporate, government, healthcare, and higher education 2004 (pp. 2881–2887). Washington, DC, USA: AACE.Google Scholar
  38. Proske, A., Körndle, H., & Narciss, S. (2005). The exercise format editor – Supporting the systematic construction of interactive learning tasks. In K. P. Jantke, K. P. Fähnrich, & W. S. Wittig (Eds.), Marktplatz Internet: Von e-Learning bis e-Payment: Tagungsband der 13 Leipziger Informatik-Tage (pp. 429–435). Bonn, Germany: Gesellschaft für Informatik.Google Scholar
  39. Proske, A., Narciss, S., & Körndle, H. (2007). Interactivity and learners’ achievement in web-based learning. Journal of Interactive Learning Research, 18(4), 511–531.Google Scholar
  40. Scheiter, K., & Gerjets, P. (2007). Learner control in hypermedia environments. Educational Psychology Review, 19(3), 285–307.CrossRefGoogle Scholar
  41. Scheuer, O., Mühlenbrock, M., & Melis, E. (2007). Results from action analysis in an interactive learning environment. Journal of Interactive Learning Research, 18(2), 185–205.Google Scholar
  42. Wade, S. E., Trathen, W., & Schraw, G. (1990). An analysis of spontaneous study strategies. Reading Research Quarterly, 25(2), 147–166.CrossRefGoogle Scholar
  43. Wagner, E. D. (1997). Interactivity: From agents to outcomes. New Directions for Teaching and Learning, 71, 19–26.CrossRefGoogle Scholar
  44. 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, NJ, USA: Lawrence Erlbaum.Google Scholar
  45. Winne, P. H. (2010). Improving measurements of self-reglated learning. Educational Psychologist, 45(4), 267–276.CrossRefGoogle Scholar
  46. Winne, P. H., & Hadwin, A. F. (1998). Studying as self-regulated learning. In D. J. Hacker, J. Dunlosky, & A. C. Graesser (Eds.), Metacognition in educational theory and practice (pp. 277–304). Mahwah, NJ, USA: Lawrence Erlbaum.Google Scholar
  47. Winne, P. H., & Hadwin, A. F. (2008). The weave of motivation and self-regulated learning. In D. H. Schunk & B. J. Zimmerman (Eds.), Motivation and self-regulated learning: Theory, research, and applications (pp. 297–314). Mahwah, NJ, USA: Lawrence Erlbaum.Google Scholar
  48. Winters, F., Greene, J., & Costich, C. (2008). Self-regulation of learning within computer-based learning environments: A critical analysis. Educational Psychology Review, 20(4), 429–444.CrossRefGoogle Scholar
  49. 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: Academic.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Susanne Narciss
    • 1
  • Hermann Koerndle
    • 1
  • Antje Proske
    • 1
  1. 1.Psychology of Learning and InstructionTechnische Universität DresdenDresdenGermany

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