Student performance knowledge tracking model integrating forgetting behavior

Yuan Yang; Tong Li

doi:10.1117/12.3004114

11 October 2023 Student performance knowledge tracking model integrating forgetting behavior

Yuan Yang, Tong Li

Proceedings Volume 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023); 128004N (2023) https://doi.org/10.1117/12.3004114
Event: 6th International Conference on Computer Information Science and Application Technology (CISAT 2023), 2023, Hangzhou, China

Abstract

The main task of knowledge tracking is to predict the change of students' mastery of knowledge points over time according to their historical learning records, so as to provide students with personalized tutorship. Previous deep learning models often did not take into account the influence of different students' abilities on their learning absorption and forgetting, in this paper, we propose a model called F-SPKT, which integrates forgetting behavior into the student's performance knowledge tracking. The Rasch model was used to extract the information of students' learning ability and difficulty, and then the full-connection network was used to calculate the students' forgetting degree vector. Then, the multi-attention mechanism was used to predict the probability of answers. Compared with the traditional methods, F-SPKT has better prediction ability in experimental verification.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yuan Yang and Tong Li "Student performance knowledge tracking model integrating forgetting behavior", Proc. SPIE 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023), 128004N (11 October 2023); https://doi.org/10.1117/12.3004114

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available