Towards a Bayesian Student Model for Detecting Decimal Misconceptions

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Authors

This paper describes the development and evaluation of a Bayesian network model of student misconceptions in the domain of decimals. The Bayesian model supports a remote adaptation service for an intelligent tutoring system within a project focused on adaptively presenting erroneous examples to students. We have evaluated the accuracy of the student model by comparing its predictions to the outcomes of the interactions of 255 students with the software. Students' logs were used for retrospective training of the Bayesian network parameters. The accuracy of the student model was evaluated from three different perspectives: its ability to predict the outcome of an individual student's answer, the correctness of the answer, and the presence of a particular misconception. The results show that the model is capable of producing predictions of high accuracy (up to 87%).

OriginalspracheEnglisch
TitelProceedings of the 19th International Conference on Computers in Education, ICCE 2011 : ICCE 2011
HerausgeberFu-Yun Yu, Tsukasa Hirashima, Thepchai Supnithi, Gautum Biswas
Anzahl der Seiten8
ErscheinungsortChiang Mai
VerlagAsia-Pacific Society for Computers in Education
Erscheinungsdatum2011
Seiten34-41
ISBN (Print)978-616-12-0188-3
PublikationsstatusErschienen - 2011
Extern publiziertJa
Veranstaltung19th International Conference on Computers in Education - ICCE 2011 - Chiang Mai, Thailand
Dauer: 28.11.201102.12.2011
Konferenznummer: 19