Abstract
We collected think-aloud, pre-test, post-test, and motivation data from 43 undergraduates to examine the impact of conceptual scaffolds on the fluctuation of certain motivation constructs and use of self-regulatory processes during learning with hypermedia. Participants were randomly assigned to either the No Scaffolding (NS) or Conceptual Scaffolding (CS) condition. During the experimental session, each participant individually completed a pre-test on the circulatory system, a pre-task motivation questionnaire, one 30-min hypermedia learning task during which they learned about the circulatory system, a motivation questionnaire at three regular intervals during this learning task, a post-test on the circulatory system, and a post-task motivation questionnaire. Results indicated that while participants in both conditions gained declarative knowledge, participants who received conceptual scaffolds during learning demonstrated deeper understanding of the circulatory system on the post-test. In terms of self-regulatory processes, the results indicated that participants in the CS condition used significantly more planning processes during learning than participants in the NS condition. Additionally, participants in both conditions significantly decreased their use of strategies as they progressed through the learning task. Regarding motivation while learning with hypermedia, results indicated that participants in both conditions reported significantly increased levels of interest as they progressed through the learning task. Furthermore, participants in the CS condition reported the task as being easier and putting forth less effort than participants in the NS condition.
Similar content being viewed by others
Notes
Data from six participants was not included in the SRL data analysis due to incomplete measures (CS = 19; NS = 18)
As a validity check of the post-test measures, a one-way ANOVA was used, with post-test mental models (low, intermediate, and high) as the between-subjects factor and post-test matching scores as a within subjects factor. Significant differences were found, F (2, 36) = 9.701, p < .001. A post-hoc Scheffé test showed that the participants who had a high mental model at post-test had a significantly higher post-test matching score (M matching score = 11.43) than both participants who had an intermediate mental model at post-test (M matching score = 8.70; p = .018), and participants who had a low mental model at post-test (M matching score = 6.50; p = .003).
References
Anderson, J. R., Corbett, A. T., & Koedinger, K. R. (1995). Cognitive tutors: Lessons learned. Journal of the Learning Sciences, 4(2), 167–207.
Azevedo, R. (2005). Computer environment as metacogntive tools for enhancing learning. Educational Psychologist, 40(4), 193–197.
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.
Azevedo, R., Cromley, J. G., & Seibert, D. (2004a). Does adaptive scaffolding facilitate students’ ability to regulate their learning with hypermedia. Contemporary Educational Psychology, 29, 344–370.
Azevedo, R., Guthrie, J. T., & Seibert, D. (2004b). The role of self-regulated learning in fostering students’ conceptual understanding of complex systems with hypermedia. Journal of Educational Computing Research, 30(1), 87–111.
Azevedo, R., Winters, F. I., & Moos, D. C. (2004c). Can students collaboratively use hypermedia to lean about science? The dynamics of self- and other-regulatory processes in an ecology classroom. Journal of Educational Computing Research, 31(3), 215–245.
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.
Bandura, A. (1994). Regulative function of perceived self-efficacy. In M. G. Rumsey, C. B. Walker, & J. H. Harris (Eds.) Personnel selection and classification (pp. 261–271). Mahwah, NJ: Erlbaum.
Bergin, D. A., Ford, M. E., & Hess, R. D. (1993). Patterns of motivation and social behavior associated with microcomputer use of young children. Journal of Educational Psychology, 84(3), 272–281.
Boekaerts, M. (2002). The on-line motivation questionnaire: A self-report instrument to assess students’ context sensitivity. New Directions in Measures and Methods, 12, 77–120.
Boekaerts, M., Pintrich, P. R., & Zeidner, M. (Eds.) (2000). Handbook of self-regulation. San Diego, CA: Academic Press.
Chi, M. T. H. (2000). Self-explaining: The dual processes of generating inference and repairing mental models. In R. Glaser (Ed.), Advances in instructional psychology: Educational design and cognitive science (Vol. 5, pp. 161–238). Mahwah, NJ: Erlbaum.
Chi, M. T. H. (2005). Commonsense conceptions of emergent processes: Why some misconceptions are robust. Journal of the Learning Sciences, 14(2), 161–199.
Chi, M. T. H., de Leeuw, N., Chiu, M. H., & LaVancher, C. (1994). Eliciting self-explanation improves understanding. Cognitive Science, 18, 439–477.
Derry S., & Lajoie S. (Eds.) (1993). Computers as cognitive tools. Mahwah, NJ: Erlbaum.
Ericsson, K. A. (2006). Protocol analysis and expert thought: Concurrent verbalizations of thinking during experts’ performance on representative tasks. In K. A. Ericsson, N. Charness, R. R. Hoffman, & P. J. Feltovich (Eds.), The Cambridge handbook of expertise and expert performance (pp. 223–242). Cambridge, MA: Cambridge University Press.
Ericsson, K. A., & Simon, H. A. (1994). Protocol analysis: Verbal reports as data. Cambridge, MA: MIT Press.
Gerjets, P., & Scheiter, K. (2003). Goal configurations and processing strategies as moderators between instructional design and cognitive load: Evidence from hypertext-based instruction. Edcuational Psychologist, 38(1), 33–41.
Graesser, A. C., McNamara, D. S., & VanLehn, K. (2005). Scaffolding deep comprehension strategies through Point&Query, AutoTutor, and iStart. Educational Psychologist, 40(4), 225–234.
Greene, S., & Ackerman, J. M. (1995). Expanding the constructivist metaphor: A rhetorical perspective on literacy research and practice. Review of Educational Research, 65, 383–420.
Greene, B., & Land, S. (2000). A qualitative analysis of scaffolding use in resource-based learning environments involving the world wide web. Journal of Educational Computing Research, 23(2), 151–179.
Hadwin, A. F., Boutara, L., & Knoetze, T. (2004). Cross-case study of self-regulated learning as a series of events. Educational Research and Evaluation, 10(4–6), 365–417.
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: Erlbaum.
Hartley, J., & Sydes, M. (1997). Are structured abstracts easier to read than traditional ones? Journal of Research in Reading, 20(2), 122–136.
Hill, J. R., & Hannafin, M. (2001). Teaching and learning in digital environments: The resurgence of resource-based learning. Educational Technology Research and Development, 49(3), 37–52.
Holladay, C. L., & Quiñones, M. A. (2003). Practice variability and transfer of training: The role of self-efficacy generality. Journal of Applied Psychology, 88(6), 1094–1103.
Jacobson, M., & 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.
Jonassen, D., Hartley, J., & Trueman, M. (1986). The effects of learner-generated versus text-provided headings on immediate and delayed recall and comprehension: An exploratory study. Human Learning: Journal of Practical Research & Application, 5(3), 139–150.
Jonassen, D., & Reeves, T. (1996). Learning with Technology: Using computers as cognitive tools. In D. Jonassen (Ed.), Handbook of research for educational communications and technology (pp. 694–719). NY: Macmillan.
Kester, L., Kirschner, P. A., & van Merriënboer, J. G. (2005). The management of cognitive load during complex cognitive skill acquisition by means of computer-simulated problem solving. British Journal of Educational Psychology, 75(1), 71–85.
Koedinger, K. R. (2001). Cognitive tutors as modeling tools and instructional models. In K. D.Forbus, & P. J. Feltovich (Eds.). Smart machines in education: The coming revolution in educational technology (pp. 145–167). Cambridge, MA: MIT.
Lajoie S. P. (Ed.) (2000). Computers as cognitive tools: No more walls, Vol. II. Mahwah, NJ: Erlbaum.
Lajoie, S. P. (2005). Cognitive tools for the mind: The promises of technology-cognitive amplifiers or bionic prosthetics? In R. Sternberg, & D. D. Preiss (Eds.), Intelligence and technology: The impact of tools on the nature and development of human abilities. Mahwah, NJ: Erlbaum.
Lajoie, S. P., & Azevedo, R. (2006). Teaching and learning in technology-rich environments. In P. Alexander, & P. Winne (Eds.), Handbook of educational psychology. Mahwah, NJ: Erlbaum.
Land, S., & Greene, B. (2000). Project-based learning with the World Wide Web: A qualitative study of resource integration. Educational Technology Research & Development, 48(3), 61–78.
Lepper, M. R., Woolverton, M., Mumme, D. L., & Gutner, J. L. (1993). Motivational techniques of expert human tutors: Lessons for the design of computer-based tutors. In S. P. Lajoie, & S. J. Derry (Eds.), Computers as cognitive tools (pp. 75–105). Hillsdale, NJ: Erlbaum.
Lepper, M., & Wolverton, M. (2004). The wisdom of practice: Lessons learned from the study of highly effective tutors. In J. Aranson (Ed.), Improving academic achievement: Impact of psychological factors on education (pp. 135–158). New York, NY: Academic Press.
Markman, A. B., & Gentner, D. (2000). Structure mapping in the comparison process. American Journal of Psychology, 113(4), 501–538.
Martin, V. L., & Pressley, M. (1991). Elaborative-interrogation effects depend on nature of question. Journal of Educational Psychology, 83(1), 113–119.
Mayer, R. E. (1994). Visual aids to knowledge construction: Building mental representations from pictures and words. In W. Schnotz, & R. W. Kulhavy (Eds.), Comprehension of graphics (pp. 125–138). Amsterdam, Netherlands: Elsevier.
Mayer, R. E. (2003). Learning environments: The case for evidence-based practice and issue-driven research. Educational Psychologist, 40, 257–265.
Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38(1), 43–52.
McCrudden, M. T., Schraw, G., & Kambe, G. (2005). The effect of relevance instructions on reading time and learning. Journal of Educational Psychology, 97(1), 88–102.
McDaniel, M. A., & Donnelly, C. M. (1996). Learning with analogy and elaborative interrogation. Journal of Educational Psychology, 88(3), 508–519.
Moos, D. C., & Azevedo, R. (2006). The role of goal structure in undergraduates’ use of self-regulatory variables in two hypermedia learning tasks. Journal of Educational Multimedia and Hypermedia, 15(1), 49–86.
Murphy, K. P., & Alexander, P. A. (2000). A motivated exploration of motivation terminology. Contemporary Educational Psychology, 25, 3–53.
Ozgungor, S., & Guthrie, J. T. (2004). Interactions among elaborative interrogation, knowledge, and interest in the process of constructing knowledge form text. Journal of Educational Psychology, 96(3), 437–443.
Pajares, F. (1996). Self-efficacy beliefs in academic domains. Review of Educational Research, 66(4), 543–578.
Pea, R. D. (2004). The social and technological dimensions of scaffolding and related theoretical concepts for learning, education, and human activity. Journal of the Learning Sciences, 13, 423–451.
Perry, N. E. (1998). Young children’s self-regulated learning and contexts that support it. Journal of Educational Psychology, 90(4), 715–729.
Perry, N. E., VandeKamp, K. O., & Mercer, L. K. (2000). Investigating teacher-student interactions that foster self-regulated learning. Educational Psychologist, 37(1), 5–15.
Pintrich, P. (2000). The role of goal orientation in self-regulated learning. In M. Boekaerts, P. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 452–502). San Diego, CA: Academic Press.
Pintrich, P. (2003). A motivational science perspective on the role of student motivation in learning and teaching contexts. Journal of Educational Psychology, 95(4), 667–686.
Puntambekar, S., & Hubscher, R. (2005). Tools for scaffolding students in a complex learning environment: What have we gained and what have we missed? Educational Psychologist, 40(1), 1–12.
Seifert, T. L. (1993). Characteristics of ego- and task-orientated students: A comparison of two methodologies. British Journal of Educational Psychology, 65, 125–138.
Shapiro, A. (1999). The relevance of hierarchies to learning biology from hypertext. Journal of the Learning Sciences, 8(2), 215–243.
Shapiro, A. (2000). The effects of interactive overviews on the development of conceptual structure in novices learning from hypermedia. Journal of Educational Multimedia and Hypermedia, 9(1), 57–78.
Sharp, J. G., Kuerbis, P., & Kelley, G. J. (2006). Children’s ideas about the solar system and the chaos in learning sciences. Science Education, 90(1), 124–147.
Shute, V., & Psotka, J. (1996). Intelligent tutoring systems: Past, present, and future. In D. Jonassen (Ed.), Handbook of research for educational communications and technology (pp. 570–600). NY: Macmillan.
Taylor, R. (1980). The computer in the school: Tutor, tool, tutee. NY: Teachers College Press.
White, B., & Frederiksen, J. (2005). A theoretical framework and approach for fostering metacognitive development. Educational Psychologist, 40(4), 211–223.
Williams, M. (1996). Student control and instructional technologies. In D. Jonassen (Ed.), Handbook of research on educational communications and technology (pp. 957–983). NY: Macmillan.
Willoughby, T., & Wood, E. (1994). Elaborative interrogation examined at encoding and retrieval. Learning and Instruction, 4(2), 139–149.
Winne, P. H. (2001). Self-regulated learning viewed from models of information processing. In B. Zimmerman, & D. Schunk. (Eds.), Self-regulated learning and academic achievement: Theoretical perspectives (pp. 153–189). Mahwah, NJ: Erlbaum.
Winne, P. H. (2005). Key issues in modeling and applying research on self-regulated learning. Applied Psychology: An International Review, 54(2), 232–238.
Winne, P. H., & Hadwin, A. F. (1998). Studying self-regulated learning. In D. J. Hacker, J. Dunlosky, & A. Graesser (Eds.), Metacognition in educational theory and practice (pp. 277–304). Hillsdale, NJ: Erlbaum.
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). Orlando, FL: Academic Press.
Winne, P. H., & Jamieson-Noel, D. (2003). Self-regulating studying by objectives for learning: Students’ reports compared to a model. Contemporary Educational Psychology, 28(3), 259–276.
Wood, D., & Middleton, D. (1975). A study of assisted problem-solving. British Journal of Psychology, 66(2), 181–191.
Wood, D., Bruner, J., & Ross, G. (1976). The role of tutoring in problem solving. Journal of Child Psychology & Psychiatry & Allied Disciplines, 17(2), 89–102.
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. 1–37). San Diego, CA: Academic Press.
Zimmerman, B. J. (2001). Theories of self-regulated learning and academic achievement: An overview and analysis. In B. Zimmerman, & D. Schunk (Eds.), Self-regulated learning and academic achievement: Theoretical perspectives (pp. 1–37). Mahwah, NJ: Erlbaum.
Zimmerman, B., & Tsikalas, K. (2005). Computer-based learning environments (CBLEs) be used as self-regulatory tools to enhance learning? Educational Psychologist, 40(4), 267–271.
Acknowledgements
This study was partially supported by a departmental doctoral fellowship from the University of Maryland awarded to the first author and by funding from the National Science Foundation (Early Career Grant REC#0133346 and REC#0633918) awarded to the second author. The authors wish to acknowledge and thank Jeffery Greene, Fielding Winters, and Jennifer Cromley for their feedback on the data analysis and assistance with the construction of the learning task questions. We also thank the anonymous reviewers for their thoughtful and critical feedback.
Author information
Authors and Affiliations
Corresponding author
Appendix
Appendix
Rights and permissions
About this article
Cite this article
Moos, D.C., Azevedo, R. Exploring the fluctuation of motivation and use of self-regulatory processes during learning with hypermedia. Instr Sci 36, 203–231 (2008). https://doi.org/10.1007/s11251-007-9028-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11251-007-9028-3