Literaturnachweis - Detailanzeige
Autor/inn/en | Corbett, Albert; Kauffman, Linda; Maclaren, Ben; Wagner, Angela; Jones, Elizabeth |
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Titel | A Cognitive Tutor for Genetics Problem Solving: Learning Gains and Student Modeling |
Quelle | In: Journal of Educational Computing Research, 42 (2010) 2, S.219-239 (21 Seiten)Infoseite zur Zeitschrift
PDF als Volltext |
Sprache | englisch |
Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
ISSN | 0735-6331 |
Schlagwörter | Problem Solving; Genetics; Tutors; Evaluation; Postsecondary Education; Pretests Posttests; Academic Achievement; Higher Education; Probability; Thinking Skills |
Abstract | Genetics is a unifying theme of biology that poses a major challenge for students across a wide range of post-secondary institutions, because it entails complex problem solving. This article reports a new intelligent learning environment called the Genetics Cognitive Tutor, which supports genetics problem solving. The tutor presents complex, multi-step problems and is constructed around a "cognitive model" of the knowledge needed to solve the problems. This embedded cognitive model enables the tutor to provide step-by-step assistance, and to maintain a model of the student's problem-solving knowledge. The tutor consists of 16 modules with about 125 total problems, spanning five general topics: Mendelian inheritance, pedigree analysis, genetic mapping, gene regulation, and population genetics. This article reports two evaluations of the tutor. A pretest/posttest evaluation of student learning gains for individual tutor modules across multiple colleges and universities yielded average gains equivalent to almost two letter grades, and the accuracy of student modeling in predicting students' test performance was empirically validated. (Contains 3 tables, 4 figures and 1 footnote.) (As Provided). |
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Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
Update | 2017/4/10 |