Metacognition and Learning

, Volume 2, Issue 2–3, pp 67–87 | Cite as

The effect of a human agent’s external regulation upon college students’ hypermedia learning

  • Roger AzevedoEmail author
  • Jeffrey A. Greene
  • Daniel C. Moos


In this study we examined the effectiveness of self-regulated learning (SRL) and externally regulated learning (ERL) on college students’ learning about a science topic with hypermedia during a 40-min session. A total of 82 college students with little knowledge of the topic were randomly assigned either to the SRL or ERL condition. Students in the SRL condition regulated their own learning, while students in the ERL condition had access to a human tutor who facilitated their self-regulated learning. We converged product (pretest–posttest declarative knowledge and qualitative shifts in participants’ mental models) with process (think-aloud) data to examine the effectiveness of SRL versus ERL. Analysis of the declarative knowledge measures showed that the ERL condition group mean was statistically significantly higher than the group mean for the SRL condition on the labeling and flow diagram tasks. There were no statistically significant differences between groups on the matching task, but both groups showed statistically significant increases in performance. Further analyses showed that the odds of being in a higher mental model posttest group were decreased by 65% for the SRL group as compared to the ERL group. In terms of SRL behavior, participants in the SRL condition engaged in more use of selecting new information sources, re-reading, summarizing, free searching, and enacting control over the context of their learning. In comparison, the ERL participants engaged in more activation of prior knowledge, utilization of feeling of knowing and judgment of learning, monitoring their progress toward goals, drawing, hypothesizing, coordination of information sources, and expressing task difficulty.


Self-regulated learning Externally-regulated learning Science Hypermedia Tutoring Learning Mixed-methods Think-aloud protocols 



This research was supported by funding from the National Science Foundation (Early Career Grant ROLE#0133346, REESE #0633918, and ROLE#0731828) awarded to the first author. The authors would like to thank Fielding Winters, Dr. Jennifer Cromley, Angie Lucier, and Neil Hofman, for transcribing the audio data. The authors would like to thank three reviewers for comments and feedback on an earlier version of this manuscript.


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Copyright information

© Springer Science + Business Media, LLC 2007

Authors and Affiliations

  • Roger Azevedo
    • 1
    Email author
  • Jeffrey A. Greene
    • 2
  • Daniel C. Moos
    • 3
  1. 1.Department of Psychology and Institute for Intelligent SystemsUniversity of MemphisMemphisUSA
  2. 2.University of North Carolina, Chapel HillChapel HillUSA
  3. 3.Gustavus Adolphus CollegeSaint PeterUSA

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