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Why is externally-facilitated regulated learning more effective than self-regulated learning with hypermedia?

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Abstract

We examined how self-regulated learning (SRL) and externally-facilitated self-regulated learning (ERL) differentially affected adolescents’ learning about the circulatory system while using hypermedia. A total of 128 middle-school and high school students with little prior knowledge of the topic were randomly assigned to either the SRL or ERL condition. Learners in the SRL condition regulated their own learning, while learners in the ERL condition had access to a human tutor who facilitated their self-regulated learning. We converged product (pretest-posttest shifts in students’ mental models and declarative knowledge measures) with process (think-aloud protocols) data to examine the effectiveness of self- versus externally-facilitated regulated learning. Findings revealed that learners in the ERL condition gained statistically significantly more declarative knowledge and that a greater number of participants in this condition displayed a more advanced mental model on the posttest. Verbal protocol data indicated that learners in the ERL condition regulated their learning by activating prior knowledge, engaging in several monitoring activities, deploying several effective strategies, and engaging in adaptive help-seeking. By contrast, learners in the SRL condition used ineffective strategies and engaged in fewer monitoring activities. Based on these findings, we present design principles for adaptive hypermedia learning environments, engineered to foster students’ self-regulated learning about complex and challenging science topics.

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Notes

  1. We conducted a series of chi-square tests to examine how learners’ use of self-regulatory variables differed across conditions. We first converted the raw counts to percentages for each person’s use of each strategy. We then conducted a median split across all conditions for the proportion of use for each variable. We were then able to identify, for each variable, which participants used that variable at a proportion above or below the median. For example, participant 1029 used feeling of knowing (FOK) 3 times out of 87 utterances, or 3% of her moves. Across all participants, the median proportion for FOK was 14%, placing participant 1029 below the median proportion for FOK. By contrast, participant 1050 used FOK 20 times out of 95 moves, or 21% of her moves, placing her above the median proportion for FOK. We then conducted a 2 × 2 chi-square analysis for each self-regulatory variable to determine whether the distribution of participants above and below the median across the treatments was significantly different from the null.

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Acknowledgment

This research was supported by funding from the National Science Foundation (Early Career Grant ROLE#0133346, ROLE#0731828, and REESE#0633918) awarded to the first author. The authors would like to thank Megan Clark and Jessica Vick for assistance with data collection, and Angie Lucier, Ingrid Ulander, Jonny Meritt, Neil Hofman, Evan Olson, and Pragati Godbole for transcribing the audio data. The authors would like to thank Michael Jacobson, Steven Ross, Amy Witherspoon and Jeremiah Sullins for comments and feedback on earlier versions of this manuscript.

Author information

Authors and Affiliations

  1. Department of Psychology and Institute for Intelligent Systems, University of Memphis, 400 Innovation Drive, Memphis, TN, 38152, USA

    Roger Azevedo

  2. Gustavus Adolphus College, Saint Peter, USA

    Daniel C. Moos

  3. University of North Carolina, Chapel Hill, USA

    Jeffrey A. Greene

  4. University of Maryland, College Park, USA

    Fielding I. Winters

  5. Temple University, Philadelphia, USA

    Jennifer G. Cromley

Authors
  1. Roger Azevedo
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  2. Daniel C. Moos
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  3. Jeffrey A. Greene
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  4. Fielding I. Winters
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  5. Jennifer G. Cromley
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Corresponding author

Correspondence to Roger Azevedo.

Additional information

An earlier version of this paper was presented at the international conference of Artificial Intelligence in Education (AI-Ed 2005), Amsterdam, The Netherlands (August, 2005).

Appendices

Appendix A

Necessary features for each type of mental model (based on Azevedo and Cromley 2004)

  • Low mental model category

    • a. No understanding

    • b. Basic global concepts

      • blood circulates

    • c. Global concepts with purpose

      • blood circulates

      • describes “purpose”—oxygen/nutrient transport

    • d. Single loop—basic

      • blood circulates

      • heart as pump

      • vessels (arteries/veins) transport

    • e. Single loop with purpose

      • blood circulates

      • heart as pump

      • vessels (arteries/veins) transport

      • describe “purpose”—oxygen/nutrient transport

    • f. Single loop—advanced

      • blood circulates

      • heart as pump

      • vessels (arteries/veins) transport

      • describe “purpose”—oxygen/nutrient transport

      • mentions one of the following: electrical system, transport functions of blood, details of blood cells

  • Intermediate mental model category

    • g. Single loop with lungs

      • blood circulates

      • heart as pump

      • vessels (arteries/veins) transport

      • mentions lungs as a “stop” along the way

      • describe “purpose”—oxygen/nutrient transport

    • h. Single loop with lungs—advanced

      • blood circulates

      • heart as pump

      • vessels (arteries/veins) transport

      • mentions lungs as a “stop” along the way describe “purpose”—oxygen/nutrient transport mentions one of the following: electrical system, transport functions of blood, details of blood cells

  • High mental model category

    • i. Double loop concept

      • blood circulates

      • heart as pump

      • vessels (arteries/veins) transport

      • describes “purpose”—oxygen/nutrient transport

      • mentions separate pulmonary and systemic systems

      • mentions importance of lungs

    • j. Double loop—basic

      • blood circulates

      • heart as pump

      • vessels (arteries/veins) transport

      • describe “purpose”—oxygen/nutrient transport

      • describes loop: heart–body-heart-lungs-heart

    • k. Double loop—detailed

      • blood circulates

      • heart as pump

      • vessels (arteries/veins) transport

      • describe “purpose”—oxygen/nutrient transport

      • describes loop: heart–body–heart–lungs–heart

      • structural details described: names vessels, describes flow through valves

    • l. Double loop—advanced

      • blood circulates

      • heart as pump

      • vessels (arteries/veins) transport

      • describe “purpose”—oxygen/nutrient transport

      • describes loop: heart–body–heart–lungs–heart

      • structural details described: names vessels, describes flow through valves

      • mentions one of the following: electrical system, transport functions of blood, details of blood cell

Appendix B

Classes, descriptions and examples of the variables used to code students’ regulatory behavior (based on Azevedo and Cromley 2004)

   
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Azevedo, R., Moos, D.C., Greene, J.A. et al. Why is externally-facilitated regulated learning more effective than self-regulated learning with hypermedia?. Education Tech Research Dev 56, 45–72 (2008). https://doi.org/10.1007/s11423-007-9067-0

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