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

Author:

Sun Siyu1ORCID,Wu Xiaopeng2ORCID,Xu Tianshu3ORCID

Affiliation:

1. College of Elementary Education, Capital Normal University, Beijing 100048, China

2. Faculty of Education, Northeast Normal University, Changchun 130024, China

3. College of Teacher Education, East China Normal University, Shanghai 200062, China

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.

Funder

Beijing Postdoctoral Research Foundation

Yuanhui Youth Development Program

Teacher Education “JIEBANGLINGTI”

Publisher

MDPI AG

Subject

Behavioral Neuroscience,General Psychology,Genetics,Development,Ecology, Evolution, Behavior and Systematics

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