Conference Paper

A Metacognitive ACT-R Model of Students' Learning Strategies in Intelligent Tutoring Systems.

DOI: 10.1007/978-3-540-30139-4_98 Conference: Intelligent Tutoring Systems, 7th International Conference, ITS 2004, Maceiò, Alagoas, Brazil, August 30 - September 3, 2004, Proceedings
Source: DBLP

ABSTRACT Research has shown that students' problem-solving actions vary in type and duration. Among other causes, this behavior is a result of strategies that are driven by different goals. We describe a first version of a computational cognitive model that explains the origin of these strategies and identifies the tendencies of students towards different learning goals. Our model takes into account (i) interpersonal differences, (ii) an estimation of the student's knowledge level, and (iii) current feedback from the tutor, in order to predict the next action of the student - a solution, a guess or a help request. Our long-term goal is to use identification of the students' strategies and their efficiency in order to better understand the learning process and to improve the metacognitive learning skills of the students.

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    ABSTRACT: Intelligent Tutoring Systems (ITS) are computer programs that model learners’ psychological states to provide individualized instruction. They have been developed for diverse subject areas (e.g., algebra, medicine, law, reading) to help learners acquire domain-specific, cognitive and metacognitive knowledge. A meta-analysis was conducted on research that compared the outcomes from students learning from ITS to those learning from non-ITS learning environments. The meta-analysis examined how effect sizes varied with type of ITS, type of comparison treatment received by learners, type of learning outcome, whether knowledge to be learned was procedural or declarative, and other factors. After a search of major bibliographic databases, 107 effect sizes involving 14,321 participants were extracted and analyzed. The use of ITS was associated with greater achievement in comparison with teacher-led, large-group instruction (g = .42), non-ITS computer-based instruction (g = .57), and textbooks or workbooks (g = .35). There was no significant difference between learning from ITS and learning from individualized human tutoring (g = –.11) or small-group instruction (g = .05). Significant, positive mean effect sizes were found regardless of whether the ITS was used as the principal means of instruction, a supplement to teacher-led instruction, an integral component of teacher-led instruction, or an aid to homework. Significant, positive effect sizes were found at all levels of education, in almost all subject domains evaluated, and whether or not the ITS provided feedback or modeled student misconceptions. The claim that ITS are relatively effective tools for learning is consistent with our analysis of potential publication bias.
    Journal of Educational Psychology 06/2014; 106(4). DOI:10.1037/a0037123 · 3.08 Impact Factor

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