Latent classes of students' ICT engagement behaviors
Predictive role of psychological factors based on Pisa 2022 data
Bibliographic Data
| ID | 21283125 |
|---|---|
| Authors | Qing Guo (0009-0007-0292-6930, Ningbo University, corresponding author) |
| Year | 2026 |
| Volume | 267 |
| Pages | 107171 |
| Publication date | 2026-07-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Acta Psychologica (JOURNAL) |
| Journal identifiers | ISSN: 0001-6918 • E-ISSN: 1873-6297 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.actpsy.2026.107171 |
| PMID | 42241847 |
| OpenAlex | W7163506602 |
| Language | EN |
| References cited | 54 |
OBJECTIVES: This study aims to investigate the latent structure of ICT engagement behaviors among secondary school students in Hong Kong (China), Japan, Korea, and Singapore, and to examine the predictive roles of demographic and psychological factors in determining engagement types. METHODS: Data from 21,004 students were analyzed using Latent Class Analysis (LCA) to identify underlying ICT engagement profiles. Multinomial logistic regression was employed to evaluate the influence of demographic variables and ICT-related psychological factors on class membership. RESULTS: Four distinct ICT engagement profiles emerged: Comprehensive, Routine, Selective, and Limited. Hong Kong (China) students were predominantly Selective or Limited, Japanese students were evenly distributed, Korean students leaned toward Routine and Limited types, and Singaporean students were mainly Comprehensive or Routine participants. Differences were most pronounced in higher-order ICT engagement, while basic ICT engagement was similar across countries/regions. For applied ICT engagement, cognitive and collaborative tasks were more prominent than operational tasks, with Japanese and Korean students favoring higher cognitive and collaborative engagement, and Hong Kong (China) and Singaporean students exhibiting a more balanced profile. High-order ICT tasks highlighted Japanese students' strengths in digital simulation and programming. Regression analyses indicated that ICT-related psychological factors were the strongest predictors, whereas gender and grade exerted partial effects, and ESCS had limited influence. CONCLUSIONS: Students across the four countries/regions exhibited convergence in basic ICT engagement but divergence in applied and higher-order ICT engagement. These findings provide empirical guidance for designing targeted educational interventions
Class (philosophy) · Cognition · Convergence (economics) · Cross-cultural · Information and Communications Technology · Latent class model · Logistic regression · Multinomial logistic regression · Education, Achievement, and Giftedness · Gender and Technology in Education · Teaching and Learning Programming
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| Citation velocity | historical |
|---|---|
| Highly cited | No |