Name
Title | ||
|---|---|---|
Deciphering the complex nature of log-file data collected during self-regulated learning with MetaTutor |
Abstract | ||
|---|---|---|
MetaTutor is a multi-agent, adaptive hypermedia learning environment that trains and fosters high school and college students' use of self-regulatory processes in the context of learning about science topics such as human body systems. The purpose of the MetaTutor environment is to examine the effectiveness of pedagogical agents (PAs) as external regulatory agents used to detect, trace, model, and foster students' self-regulatory processes during science learning with multiple representations of information. The multi-agent system provides adaptive tutoring based on students' evolving conceptual understanding of the topic and their strategic use of cognitive and metacognitive processes. Each of the four agents is responsible for specific aspects of SRL, including task definition, planning, metacognitive processes, and learning strategies. Based on their specialized roles, each PA has been designed to detect a specific set of SRL processes. For example, Mary the Monitor is in charge of detecting when students deploy metacognitive processes and make metacognitive judgments such as expressing a judgment of learning (JOL; e.g., used in relation to judging one's understanding of the current content) and also in determining the valence (e.g., JOL - or JOL +) associated with the metacognitive judgment. The presupposition of an accurate detection method (by each agent) leads the agent to model the temporal dynamics associated with each SRL process, across all SRL processes, and how they relate to several learning outcomes such as declarative, procedural, and inferential knowledge and mental models of the science topic. This evolving model is then used to foster SRL and content understanding by providing several levels of scaffolding. Instructional scaffolding involves the coordination of other architectural modules of MetaTutor that coordinate and manage the dialogue system between agents and the learner. Instructional scaffolding is provided based on current research on human and computerized tutoring research (Chi et al., 2004; Graesser, D'Mello & Person, in press; VanLehn et al., 2007; Wolff, 2009) and recent studies comparing SRL with ERL (externally-regulated learning; Azevedo et al., 2007, 2008). The types of scaffolding range from having the learner vicariously watch as the agent models the SRL process to having the student use a specific SRL process while being provided with elaborate feedback regarding the effective use of the process (based on Zimmerman & Moylan, in press). |
Year | Venue | Keywords |
|---|---|---|
2010 | ICLS | complex nature,log-file data,learning outcome,metacognitive process,instructional scaffolding,self-regulated learning,SRL process,science topic,metacognitive judgment,externally-regulated learning,specific SRL process,self-regulatory process,effective use |
Field | DocType | Citations |
Self-regulated learning,Cognitive science,Adaptive hypermedia,Presupposition,Psychology,Metacognition,Learning environment,Mathematics education,Science learning,Cognition,Instructional scaffolding | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Roger Azevedo | 1 | 127 | 24.65 |
| Amy Witherspoon | 2 | 162 | 13.11 |
| Amber Chauncey | 3 | 36 | 4.25 |
| Mihai Lintean | 4 | 98 | 7.73 |
| zhiqiang cai | 5 | 344 | 78.81 |
| Vasile Rus | 6 | 973 | 134.69 |
| Arthur Greesser | 7 | 0 | 0.34 |