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A Theoretical Framework for a Mathematical Cognitive Model for Adaptive Learning Systems

Authors :
Siyu Sun
Xiaopeng Wu
Tianshu Xu
Source :
Behavioral Sciences, Vol 13, Iss 5, p 406 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

The emergence of artificial intelligence has made adaptive learning possible, but building an adaptive system requires a comprehensive understanding of students’ cognition. The cognitive model provides a crucial theoretical framework to explore students’ cognitive attributes, making it vital for learning assessment and adaptive learning. This study investigates 52 experts, including primary and secondary school teachers, mathematics education experts, and graduate students, based on the 16 cognitive attributes in the TIMSS 2015 assessment framework. Through an analysis of their attribute questionnaires, the Interpretive structural modeling (ISM) method is used to construct a five-level mathematical cognitive model. The model is then revised through oral reports and expert interviews, resulting in a final cognitive model ranging from “memorize” to “justify”. The cognitive model describes the relationship between different attributes in detail, enabling the development of adaptive systems and aiding in the diagnosis of students’ cognitive development and learning paths in mathematics.

Details

Language :
English
ISSN :
2076328X
Volume :
13
Issue :
5
Database :
Directory of Open Access Journals
Journal :
Behavioral Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.32f658f50e7a4ec2ba21b1c40c0fc635
Document Type :
article
Full Text :
https://doi.org/10.3390/bs13050406