The Role of Prompting and Feedback in Facilitating Students' Learning about Science with MetaTutor.

An experiment was conducted to test the efficacy of a new intelligent hypermedia system, MetaTutor, which is intended to prompt and scaffold the use of self-regulated learning (SRL) processes during learning about a human body system. Sixtyeight (N=68) undergraduate students learned about the human circulatory system under one of three conditions: prompt and feedback (PF), prompt-only (PO), and control (C) condition. The PF condition received timely prompts from animated pedagogical agents to engage in planning processes, monitoring processes, and learning strategies and also received immediate directive feedback from the agents concerning the deployment of the processes. The PO condition received the same timely prompts, but did not receive any feedback following the deployment of the processes. Finally, the control condition learned without any assistance from the agents during the learning session. All participants had two hours to learn using a 41-page hypermedia environment which included texts describing and static diagrams depicting various topics concerning the human circulatory system. Results indicate that the PF condition had significantly higher learning efficiency scores, when compared to the control condition. There were no significant differences between the PF and PO conditions. These results are discussed in the context of development of a fully-adaptive hypermedia learning system intended to scaffold self-regulated learning. Objectives and Theoretical Framework When learning about complex science topics such as the human circulatory system, research indicates that individuals can gain deep conceptual understanding through effective use of self-regulated learning (SRL). The successful use of cognitive and metacognitive SR processes involves setting meaningful goals for one’s learning, planning a course of action for attaining these goals, deploying a diverse set of effective learning strategies in pursuit of the goals, continuously monitoring one’s own understanding of the material and the appropriateness of the current information, and making adaptations to one’s goals, strategies, and navigational patterns, based on the results of such monitoring processes and their resulting judgments (Azevedo, 2005; Azevedo & Witherspoon, 2009; Opfermann, Azevedo, & Leutner, in press; Pintrich, 2000; Winne, 2001; Winne & Hadwin, 2008; Zimmerman, 2001; Zimmerman & Schunk, in press). Although learners should attempt to follow these guidelines when attempting difficult topics, exploration of typical learning has demonstrated that few learners, in fact, engage in effective self-regulated learning. We assume that, while motivation and affect play a role in determining learners’ willingness to self-regulate, a lack of selfregulatory skills is the main obstacle to adequate regulation and therefore deficient learning gains and conceptual understanding (Azevedo & Jacobson, 2008; Shapiro, 2008; Schwartz et al., 2009; White, Frederiksen, & Collins, 2009). Therefore, our current research is directed toward scaffolding learners’ use of self-regulation using artificial pedagogical agents (PAs) during learning with MetaTutor, a multi-agent adaptive hypermedia learning environments that models, scaffolds, and fosters learners’ use of cognitive and metacognitive SRL processes during learning about human biology. Learners attempting to self-regulate often face limitations in their own metacognitive skills, which, when compounded with lack of domain knowledge, can result in cognitive overload in open-ended learning environments like hypermedia (Azevedo, Johnson, Chauncey, & Graesser, in press; Leelawong & Biswas, 2008; McQuiggan, Robinson, & Lester, 2010). One method of relieving the cognitive burden placed on learners in this situation is to provide assistance in the form of adaptive scaffolding. Previous experiments conducted by Azevedo and colleagues (e.g., Azevedo, Cromley, Winters, Moos, & Greene, 2005; Azevedo, Moos, Greene, Winters, & Cromley, 2008) established that adaptive scaffolding 11 Cognitive and Metacognitive Educational Systems: Papers from the AAAI Fall Symposium (FS-10-01)

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.