Work

Big Data Research on Personalized Learning in Computer Education: A Thematic Evolution Analysis

Year: 2026

Type: article

Abstract: ABSTRACT This paper presents a systematic review of the literature on personalized learning in computer education from 2014 to 2024, using a thematic evolution analysis to uncover the origins and emerging hotspots in this field. The review shows that the research hotspots in personalized learning present an apparent trend from early interventions focusing on academic warning systems and performance prediction, to technology‐enabled intelligent tutoring and resource recommendation, and then to the development of a range of competencies for computational thinking. Furthermore, the emerging application of novel technologies, such as generative AI, is advancing personalized learning toward an even more intelligent and human‐AI collaborative stage. Finally, the paper summarizes the existing challenges in methodological transparency, integration of educational praxis, and ethical balance, and highlights potential avenues for future research and practice.

Source: Computer Applications in Engineering Education

DOI: 10.1002/cae.70159

Authors: Youyin Mo, Jie Zhang, Yan Mou

Institution: Chongqing Preschool Education College

Language: English

Topic: Intelligent Tutoring Systems and Adaptive Learning

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: hybrid

Estimated APC paid: $4,150