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ERIC Number: EJ1323876
Record Type: Journal
Publication Date: 2021
Pages: 11
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1049-4820
EISSN: N/A
Available Date: N/A
CS-BKT: Introducing Item Relationship to the Bayesian Knowledge Tracing Model
Meng, Lingling; Zhang, Mingxin; Zhang, Wanxue; Chu, Yu
Interactive Learning Environments, v29 n8 p1393-1403 2021
Bayesian knowledge tracing model (BKT) is a typical student knowledge assessment method. It is widely used in intelligent tutoring systems. In the standard BKT model, all knowledge and skills are independent of each other. However, in the process of student learning, they have a very close relation. A student may understand knowledge B better when he masters knowledge A. Therefore, this work introduces a new student model based on BKT. It takes the relationship between knowledge into account. By doing this, the new model proves higher prediction accuracy and performs better. Then this paper uses the new model to make a cognitive diagnosis according to students' test scores. The diagnostic results can help teachers provide personalized guidance to students and improve teaching efficiency.
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A
Author Affiliations: N/A