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Self-Regulation in Computer-Based Learning Environments: Effects of Learner Characteristics and Instructional Support

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Multidisciplinary Research on Teaching and Learning

Abstract

In the context of fast technological development and the widespread use of learning technologies in education, the need for students to regulate their own learning processes has become increasingly important (Bannert & Reimann, 2012; Winters, Greene, & Costich, 2008). Research in the last decade has revealed that students have to possess specific self-regulated learning (SRL) abilities in order to learn successfully in computer-based learning environments (CBLEs; Azevedo, 2009; Bannert, Hildebrand, & Mengelkamp, 2009). CBLEs contain different kinds of informational resources (e.g., texts, graphics, help tools) and therefore provide various opportunities for students to improve their learning. In addition, many CBLEs provide a high degree of learner control, allowing students to take full responsibility for the entire learning process. In other words, in learner-controlled CBLEs students can choose their own learning activities based on their personal needs and preferences (Williams, 1996).

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References

  • Ainsworth, S. E., Bibby, P. A., & Wood, D. J. (2002). Examining the Effects of Different Multiple Representational Systems in Learning Primary Mathematics. Journal of the Learning Sciences, 11, 25–62.

    Google Scholar 

  • Aleven, V., & Koedinger, K. (2000). Limitations of Student Control: Do Students Know When They Need Help? In G. Gauthier, C. Frasson, & K. VanLehn (Eds), Proceedings of the 5th International Conference on Intelligent Tutoring Systems, ITS 2000 (pp. 292–303). Berlin, Germany: Springer Verlag.

    Book  Google Scholar 

  • Alexander, P. A. (1997). Mapping the Multidimensional Nature of Domain Learning: The Interplay of Cognitive, Motivational, and Strategic Forces. Advances in Motivation and Achievement, 10, 213–250.

    Google Scholar 

  • Azevedo, R. (2005). Using Hypermedia as a Metacognitive Tool for Enhancing Student Learning? The Role of Self-Regulated Learning. Educational Psychologist, 40(4), 199–209.

    Google Scholar 

  • Azevedo, R. (2009). Theoretical, Methodological, and Analytical Challenges in the Research on Metacognition and Self-Regulation: A Commentary. Metacognition & Learning, 4(1), 87–95.

    Google Scholar 

  • Azevedo, R., & Cromley, J. G. (2004). Does Training on Self-Regulated Learning Facilitate Students’ Learning with Hypermedia? Journal of Educational Psychology, 96(3), 523–535.

    Google Scholar 

  • Azevedo, R., & Hadwin, A. F. (2005). Scaffolding Self-Regulated Learning and Metacognition: Implications for the Design of Computer-Based Scaffolds. Instructional Science, 33, 367–379.

    Google Scholar 

  • Azevedo, R, Cromley, J. G., Winters, F. I., Moos, D. C., & Greene, J. A. (2005). Adaptive Human Scaffolding Facilitates Adolescents’ Self-Regulated Learning with Hypermedia. Instructional Science, 33, 381–412.

    Google Scholar 

  • Azevedo, R., Guthrie, J. T., & Seibert, D. (2004). The Role of Self-Regulated Learning in Fostering Students’ Conceptual Understanding of Complex Systems with Hypermedia. Journal of Educational Computing Research, 30, 87–111.

    Google Scholar 

  • Bandura, A. (1993). Perceived Self-Efficacy in Cognitive Development and Functioning. Educational Psychologist, 28, 117–148.

    Google Scholar 

  • Bandura, A. (1997). Self-Efficacy: The Exercise of Control. NY: Freeman/Times Books/Henry Holt & Co.

    Google Scholar 

  • Bannert, M., Hildebrand, M., & Mengelkamp, C. (2009). Effects of Metacognitive Support Device in Learning Environments. Computers in Human Behavior, 25(3), 829–835.

    Google Scholar 

  • Bannert, M., & Mengelkamp, C. (2008). Assessment of Metacognitive Skills by Means of Instruction to Think Aloud and Reflect When Prompted. Does the Verbalization Method Affect Learning? Metacognition Learning, 3, 39–58.

    Google Scholar 

  • Bannert, M., & Reimann, P. (2012). Supporting Self-Regulated Hypermedia Learning through Prompts. Instructional Science, 40, 193–211.

    Google Scholar 

  • Bjorkman, M. (1992). Knowledge, Calibration, and Resolution: A Linear Model. Organizational Behavior and Human Decision Processes, 51, 1–21.

    Google Scholar 

  • Boekaerts, M. (1999). Self-Regulated Learning: Where We Are Today. International Journal of Educational Research, 31, 445–457.

    Google Scholar 

  • Boekaerts, M., & Corno, L. (2005). Self-Regulation in the Classroom: A Perspective on Assessment and Intervention. Applied Psychology: An International Review, 54, 199–231.

    Google Scholar 

  • Butler, D. L., & Winne, P. H. (1995). Feedback and Self-Regulated Learning: A Theoretical Synthesis. Review of Educational Research, 65, 245–281.

    Google Scholar 

  • Catrambone, R. (1995). Aiding Sub-goal Learning: Effects on Transfer. Journal of Educational Psychology, 87, 5–17.

    Google Scholar 

  • Chi, M. T. H., Bassok, M., Lewis, M. W., Reimann, P., & Glaser, R. (1989). Self-Explanations: How Students Study and Use Examples in Learning to Solve Problems. Cognitive Science, 13, 145–182.

    Google Scholar 

  • Claparède, E. (1971). Die Entdeckung der Hypothese [The Discovery of the Hypothesis]. In C. F. Graumann (Ed.), Denken (pp. 109–115). Berlin, Germany: Kiepenheuer und Witsch.

    Google Scholar 

  • Dunker, K. (1935). Zur Psychologie des produktiven Denkens [The Psychology of Productive Thinking]. Berlin, Germany: Springer.

    Google Scholar 

  • Dunlosky, J., Hertzog, C., Kennedy, M. R. T., & Thiede, K. W. (2005). The Self-Monitoring Approach for Effective Learning. Cognitive Technology, 9(1), 4–11.

    Google Scholar 

  • Dunning, D., Johnson, K., Ehrlinger, J., & Kruger, J. (2003). Why People Fail to Recognize Their Own Incompetence. Current Directions in Psychological Science, 12(3), 83–87.

    Google Scholar 

  • Eccles, J. S., & Wigfield, A. (2002). Motivational Beliefs, Values, and Goals. Annual Review of Psychology, 53, 109–132.

    Google Scholar 

  • Ehrlinger, J., Johnson, K., Banner, M., Dunning, D., & Kruger, J. (2008). Why the Unskilled Are Unaware: Further Explorations of (Absent) Self-Insight among the Incompetent. Organizational Behavior and Human Decision Processes, 105(1), 98–121.

    Google Scholar 

  • Ericsson, K. A., & Crutcher, R. J. (1991). Introspection and Verbal Reports on Cognitive Processes — Two Approaches to the Study of Thinking: A Response to Howe. New Ideas in Psychology, 9, 57–71.

    Google Scholar 

  • Ericsson, K. A., & Simon, H. A. (1993). Protocol Analysis: Verbal Reports as Data. Cambridge, United Kingdom: MIT.

    Google Scholar 

  • Fox, M. C., Ericsson, K. A., & Best, R. (2011). Do Procedures for Verbal Reporting of Thinking Have to Be Reactive? A Meta-analysis and Recommendations for Best Reporting Methods. Psychological Bulletin, 137, 316–344.

    Google Scholar 

  • Garcia, T., & Pintrich, P. R. (1994). Regulating Motivation and Cognition in the Classroom: The Role of Self-Schemas and Self-Regulatory Strategies. In D. H. Schunk & B. J. Zimmerman (Eds), Self-Regulation of Learning and Performance: Issues and Educational Applications (pp. 127–154). Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Glaser, R., & Chi, M. T. H. (1988). Overview. In M. T. H. Chi, R. Glaser, & M. J. Farr (Eds), The Nature of Expertise (pp. xv-xxvii). Hillsdale, NJ: Lawrence Erlbaum.

    Google Scholar 

  • 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.

    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 and Education, 50, 1069–1083.

    Google Scholar 

  • Hadwin, A. F., Winne, P. H., Stockley, D. B., Nesbit, J., & Woszczyna, C. (2001). Context Moderates Students’ Self-Reports about How They Study. Journal of Educational Psychology, 93, 477–487.

    Google Scholar 

  • 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: Lawrence Erlbaum.

    Google Scholar 

  • Hattie, J., Biggs, J., & Purdie, N. (1996). Effects of Learning Skills Interventions on Student Learning: A Meta-analysis. Review of Educational Research, 66, 99–136.

    Google Scholar 

  • Jacobson, M. J., & Archodidou, A. (2000). The Design of Hypermedia Tools for Learning: Fostering Conceptual Change and Transfer of Complex Scientific Knowledge. Journal of the Learning Sciences, 9(2), 145–199.

    Google Scholar 

  • Kalyuga, S. Ayres, P., Chandler, P., & Sweller, J. (2003). The Expertise Reversal Effect. Educational Psychologist, 38(1), 23–31.

    Google Scholar 

  • Kramarski, B., & Gutman, M. (2005). How Can Self-Regulated Learning Be Supported in Mathematical E-learning Environments? Journal of Computer Assisted Learning, 22(1), 24–33.

    Google Scholar 

  • Kulik, C. C., & Kulik, J. A. (1991). Effectiveness of Computer-Based Instruction: An Updated Analysis. Computers in Human Behavior, 7(1–2), 75–94.

    Google Scholar 

  • Kulik, J. A. (1994). Meta-analytic Studies of Findings on Computer-Based Instruction. In E. L. Baker & H. F. O’Neil Jr. (Eds), Technology Assessment in Education and Training (pp. 9–34). Hillsdale, NJ: Lawrence Erlbaum.

    Google Scholar 

  • Lajoie, S. P., & Azevedo, R. (2006). Teaching and Learning in Technology-rich Environments. In P. A. Alexander & P. H. Winne (Eds), Handbook of Educational Psychology (2nd ed., pp. 803–821). Mahwah, NJ: Erlbaum.

    Google Scholar 

  • Lodewyk, K. R., Winne, P. H., & Jamieson-Noel, D. L. (2009). Implications of Task Structure on Self-Regulated Learning and Achievement. Educational Psychology: An International Journal of Experimental Educational Psychology, 29(1), 1–25.

    Google Scholar 

  • Loo, R. (1996). Construct Validity and Classification Stability of the Revised Learning Style Inventory (LSI-1985). Educational and Psychological Measurement, 56, 529–536.

    Google Scholar 

  • Loyens, S. M. M., Magda, J., & Rikers, R. M. J. P. (2008). Self-Directed Learning in Problem-Based Learning and Its Relationships with Self-Regulated Learning. Educational Psychology Review, 20, 411–427.

    Google Scholar 

  • MacGregor, S. K. (1999). Hypermedia Navigation Profiles: Cognitive Characteristics and Information Processing Strategies. Journal of Educational Computing Research, 20(2), 189–206.

    Google Scholar 

  • Metcalfe, J. (2002). Is Study Time Allocated Selectively to a Region of Proximal Learning? Journal of Experimental Psychology: General, 131, 349–363.

    Google Scholar 

  • Metcalfe, J., & Kornell, N. (2005). A Region of Proximal Learning Model of Study Time Allocation. Journal of Memory and Language, 52, 463–477.

    Google Scholar 

  • Moos, D. C., & Azevedo, R. (2006). The Role of Goal Structure in Undergraduates’ Use of Self-Regulatory Processes in Two Hypermedia Learning Tasks. Journal of Educational Multimedia and Hypermedia, 15(2), 49–86.

    Google Scholar 

  • Moos, D. C., & Azevedo, R. (2008). Monitoring, Planning, and Self-Efficacy during Learning with Hypermedia: The Impact of Conceptual Scaffolds. Computers in Human Behavior, 24(4), 1686–1706.

    Google Scholar 

  • Moos, D. C., & Azevedo, R. (2009). Learning with Computer-Based Learning Environments: A Literature Review of Computer Self-Efficacy. Review of Educational Research, 79(2), 576–600.

    Google Scholar 

  • Narciss, S. (2008). Feedback Strategies for Interactive Learning Task. In J. Spector, D. M. Merril, J. van Merriënboer, & M. P. Driscoll (Eds), Handbook of Research on Educational Communications and Technologies (3rd ed.). New York, NY: Taylor & Francis Group.

    Google Scholar 

  • Nelson, T. O., Dunlosky, J., Graf, A., & Narens, L. (1994). Utilization of Metacognitive Judgments in the Allocation of Study during Multitrial Learning. Psychological Science, 5(4), 207–213.

    Google Scholar 

  • Nelson, T. O., & Narens, L. (1994). Why Investigate Metacognition? In J. Metcalfe & A. Shimamura (Eds), Metacognition: Knowing about Knowing (pp. 1–25). Cambridge, United Kingdom: Bradford Books.

    Google Scholar 

  • Nietfeld, J. L., & Schraw, G. (2002). The Effect of Knowledge and Strategy Training on Monitoring Accuracy. Journal of Educational Research, 95(3), 131–142.

    Google Scholar 

  • Pintrich, P. R. (2000). Multiple Goals, Multiple Pathways: The Role of Goal Orientation in Learning and Achievement. Journal of Educational Psychology, 92, 544–555.

    Google Scholar 

  • Pintrich, P. R. (2004). A Conceptual Framework for Assessing Motivation and Self-Regulated Learning in College Students. Educational Psychology Review, 16, 385–407.

    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, 33–40.

    Google Scholar 

  • Pintrich, P. R., & Schunk, D. H. (1996). Motivation in Education: Theory, Research, and Applications. Englewood Cliffs, NJ: Prentice Hall.

    Google Scholar 

  • Reed, S. R. (2006). Cognitive Architectures for Multimedia Learning. Educational Psychologist, 41, 87–98.

    Google Scholar 

  • Renkl, A. (1997). Learning from Worked-out Examples: A Study on Individual Differences. Cognitive Science, 21, 1–29.

    Google Scholar 

  • Renkl, A. (2002). Worked-out Examples: Instructional Explanations Support Learning by Self-Explanations. Learning and Instruction, 12, 529–556.

    Google Scholar 

  • Renkl, A. (2005). The Worked-out Example Principle in Multimedia Learning. In R. E. Mayer (Ed.), Cambridge Handbook of Multimedia Learning (pp. 229–247). Cambridge, United Kingdom: Cambridge University Press.

    Book  Google Scholar 

  • Renkl, A., & Atkinson, R. K. (2003). Structuring the Transition from Example Study to Problem Solving in Cognitive Skill Acquisition: A Cognitive Load Perspective. Educational Psychologist, 38, 15–22.

    Google Scholar 

  • Russo, E. J., Johnson, E. J., & Stephens, D. L. (1989). The Validity of Verbal Protocols. Memory and Cognition, 17, 759–769.

    Google Scholar 

  • Samuelstuen, M. S., & BrÃ¥ten, I. (2007). Examining the Validity of Self-Reports on Scales Measuring Students’ Strategic Processing. British Journal of Educational Psychology, 77(2), 351–378.

    Google Scholar 

  • Schellings, G. L. M., van Hout-Wolters, B. H. A. M., Veenman, M. V. J., & Meijer, J. (2012). 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.

    Google Scholar 

  • Schlagmüller, M., & Schneider, W. (2007). Würzburger Lesestrategie-Wissenstest für die Klassen 7–12 (WLST 7–12). Ein Verfahren zur Erfassung metakognitiver Kompetenzen bei der Verarbeitung von Texten [The Würzburg Reading Strategy Knowledge Test for Grades 7–12 (WLST 7–12)]. Göttingen, Germany: Hogrefe.

    Google Scholar 

  • Schmeck, R. R. (1983). Learning Styles of College Students. In R. F. Dillon & R. R. Schmeck (Eds), Individual Differences in Cognition (Vol. 1, pp. 233–278). New York, NY: Academic Press.

    Google Scholar 

  • Schraw, G. (2007). The Use of Computer-Based Environments for Understanding and Improving Self-Regulation. Metacognition and Learning, 2, 169–176.

    Google Scholar 

  • Schraw, G. (2010). Measuring Self-Regulation in Computer-Based Learning Environments. Educational Psychologist, 45, 258–266.

    Google Scholar 

  • Schraw, G., & Dennison, R. S. (1994). Assessing Metacognitive Awareness. Contemporary Educational Psychology, 19, 460–475.

    Google Scholar 

  • Schunk, D. H. (1991). Self-Efficacy and Academic Motivation. Educational Psychologist, 26, 207–231.

    Google Scholar 

  • Schunk, D. H., & Pajares, F. (2002). The Development of Academic Self-Efficacy. In A. Wigfield & J. Eccles (Eds), Development of Achievement Motivation (pp. 15–31). San Diego, CA: Academic Press.

    Book  Google Scholar 

  • Schunk, D. H., & Zimmerman, B. J. (2006). Competence and Control Beliefs: Distinguishing the Means and the Ends. In P. Alexander & P. Winne (Eds), Handbook of Educational Psychology (2nd ed., pp. 349–367). San Diego, CA: Academic Press.

    Google Scholar 

  • Schwonke, R., Ertelt, A., Otieno, C., Renkl, A., Aleven, V., & Salden, R. J. C. M. (2013). Metacognitive Support Promotes an Effective Use of Instructional Resources in Intelligent Tutoring. Learning and Instruction, 23, 136–150.

    Google Scholar 

  • Son, L. K., & Kornell, N. (2008). Metacognition in Education: A Focus on Calibration. In J. Dunlosky & R. A. Bjork (Eds), Handbook of Metamemory and Memory (pp. 333–351). New York, NY: Psychology Press.

    Google Scholar 

  • Stone, N. J. (2000). Exploring the Relationship between Calibration and Self-Regulated Learning. Educational Psychology Review, 12, 437–475.

    Google Scholar 

  • Sweller, J., Van Merriënboer, J. J. G., & Paas, F. (1998). Cognitive Architecture and Instructional Design. Educational Psychology Review, 10, 251–296.

    Google Scholar 

  • Thiede, K. W., Anderson, M. C. M., & Therriault, D. (2003). Accuracy of Metacognitive Monitoring Affects Learning of Texts. Journal of Educational Psychology, 95(1), 66–73.

    Google Scholar 

  • Van Gog, T., Kester, L., & Paas, F. (2011). Effects of Worked Examples, Example-Problem, and Problem-Example Pairs on Novices’ Learning. Contemporary Educational Psychology, 36(3), 212–218.

    Google Scholar 

  • Van Gog, T., Paas, F., & Van Merriënboer, J. J. G. (2005). Uncovering Expertise-Related Differences in Troubleshooting Performance: Combining Eye Movement and Concurrent Verbal Protocol Data. Applied Cognitive Psychology, 19, 205–221.

    Google Scholar 

  • Van Merriënboer, J. J. G., Kirschner, P. A., & Kester, L. (2003). Taking the Load Off a Learner’s Mind: Instructional Design for Complex Learning. Educational Psychologist, 38, 5–14.

    Google Scholar 

  • Van Merriënboer, J. J. G., & Paas, F. (1989). Automation and Schema Acquisition in Learning Elementary Computer Programming: Implications for the Design of Practice. Computers in Human Behavior, 6, 273–289.

    Google Scholar 

  • Veenman, M. V. J. (2005). The Assessment of Metacognitive Skills: What Can Be Learned from Multi-method Designs? In C. Artelt & B. Moschner (Eds), Lernstrategien und Metakognition: Implikationen für Forschung und Praxis (pp. 77–99). Münster, Germany: Waxmann.

    Google Scholar 

  • Veenman, M. (2007). The Assessment and Instruction of Self-Regulation in Computer-Based Environments: A Discussion. Metacognition and Learning, 2, 177–183.

    Google Scholar 

  • Veenman, M. V. J., Elshout, J. J., & Busato, V. V. (1994). Metacognitive Mediation in Learning with Computer-Based Simulations. Computers in Human Behavior, 10, 93–106.

    Google Scholar 

  • Veenman, M. V. J., Kerseboom, L, & Imthorn, C. (2000). Test Anxiety and Metacognitive Skillfulness: Availability versus Production Deficiencies. Anxiety, Stress, and Coping, 13, 391–412.

    Google Scholar 

  • Veenman, M. V. J., Van Hout-Wolters, B., & Afflerbach, P. (2006). Metacognition and Learning: Conceptual and Methodological Considerations. Metacognition Learning, 1, 3–14.

    Google Scholar 

  • Veenman, M. V. J., Wilhelm, P., & Beishuizen, J. J. (2004). The Relation between Intellectual and Metacognitive Skills from a Developmental Perspective. Learning and Instruction, 14, 89–109.

    Google Scholar 

  • Vermunt, J. D. (1996). Metacognitive, Cognitive and Affective Aspects of Learning Styles and Strategies: A Phenomenographic Analysis. Higher Education, 31, 25–50.

    Google Scholar 

  • Whipp, J., & Chiarelli, S. (2004). Self-Regulation in a Web-Based Course: A Case Study. Educational Technology Research and Development, 52(4), 5–22.

    Google Scholar 

  • Wigfield, A., Eccles, J. S., Schiefele, U., Roesner, R., & Davis-Kean (2006). Development of Achievement Motivation. In W. Damon & R. M. Lerner (Eds), Handbook of Child Psychology (pp. 933–1002). Hoboken, NJ: John Wiley.

    Google Scholar 

  • Wild, K.-P., & Schiefele, U. (1994). Lernstrategien im Studium: Ergebnisse zur Faktorenstruktur und Reliabilität eines neuen Fragebogens [Learning Strategies during Further Education: Results on the Factor Structure and Reliability of a New Questionnaire]. Zeitschrift für Differentielle und Diagnostische Psychologie, 15, 185–200.

    Google Scholar 

  • Williams, M. D. (1996). Learner-Control and Instructional Technologies. In D. H. Jonassen (Ed.), Handbook of Research of Educational Communications and Technology (pp. 957–983). New York, NY: Macmillan.

    Google Scholar 

  • Winne, P. H. (1996). A Metacognitive View of Individual Differences in Self-Regulated Learning. Learning and Individual Differences, 8, 327–353.

    Google Scholar 

  • Winne, P. H. (1997). Experimenting to Bootstrap Self-Regulated Learning. Journal of Educational Psychology, 89, 397–410.

    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, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • 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). Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Winne, P. H., & Jamieson-Noel, D. (2002). Exploring Students’ Calibration of Self-Reports about Study Tactics and Achievement. Contemporary Educational Psychology, 27, 551–572.

    Google Scholar 

  • Winne, P. H., & Marx, R. W. (1982). Students’ and Teachers’ Views of Thinking Processes for Classroom Learning. Elementary School Journal, 82, 493–518.

    Google Scholar 

  • Winne, P. H., & Perry, N. E. (2000). Measuring Self-Regulated Learning. In M. Boekaerts, P. Pintrich, & M. Zeidner (Eds), Handbook of Self-Regulation (pp. 531–566). San Diego, CA: Academic Press.

    Book  Google Scholar 

  • Winters, F. I., Greene, J. A., & Costich, C. M. (2008). Self-Regulation of Learning within Computer-Based Learning Environments: A Critical Analysis. Educational Psychology Review, 20, 429–444.

    Google Scholar 

  • Wittwer, J., & Renkl, A. (2010). How Effective Are Instructional Explanations in Example-Based Learning? A Meta-analytic Review. Educational Psychology Review, 22, 393–409.

    Google Scholar 

  • Zimmerman, B. J. (1989). A Social Cognitive View of Self-Regulated Academic lLearning. Journal of Educational Psychology, 81, 329–339.

    Google Scholar 

  • Zimmerman, B. J. (1990). Self-Regulated Learning and Academic Achievement: An Overview. Educational Psychologist, 25, Resolution: Global3–17.

    Google Scholar 

  • Zimmerman, B. J. (2001). Theories of Self-Regulated Learning and Academic Achievement: An Overview and Analysis. In B. J. Zimmerman & D. E. Schunk (Eds), Self-Regulated Learning and Academic Achievement: Theoretical Perspectives (pp. 1–37). Mahwah, NJ: Erlbaum.

    Google Scholar 

  • Zimmerman, B. (2008). Investigating Self-Regulation and Motivation: Historical Background, Methodological Developments, and Future Prospects. American Educational Research Journal, 45(1), 166–183.

    Google Scholar 

  • Zimmerman, B. J., & Martinez-Pons, M. (1992). Perceptions of Efficacy and Strategy Use in the Self-Regulation of Learning. In D. H. Schunk & J. Meese (Eds), Student Perceptions in the Classroom: Causes and Consequences. Hillsdale, NJ: Erlbaum.

    Google Scholar 

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© 2015 Loredana Mihalca, Wolfgang Schnotz and Christoph Mengelkamp

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Mihalca, L., Schnotz, W., Mengelkamp, C. (2015). Self-Regulation in Computer-Based Learning Environments: Effects of Learner Characteristics and Instructional Support. In: Schnotz, W., Kauertz, A., Ludwig, H., Müller, A., Pretsch, J. (eds) Multidisciplinary Research on Teaching and Learning. Palgrave Macmillan, London. https://doi.org/10.1057/9781137467744_3

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