Modeling the sustainability perspectives on personalized digital games for digital citizenship education: A PLS-SEM approach

As digital citizenship becomes an essential educational priority in the digital age, there is a growing need for sustainable and engaging instructional designs that foster students' ethical and responsible use of technology. Addressing this gap, this study modeled the sustainability perspectives underlying personalized digital game-based learning through a partial least squares structural equation modeling (PLS-SEM) approach. A longitudinal repeated-measures design was conducted with 372 lower secondary students in Thailand, using fuzzy logic and decision tree algorithms to personalize ethical digital scenarios. The proposed model examined how pedagogical design, content quality, usability, behavioral decisions, and motivation shape students' perceptions of sustainability. Results indicated that sustained motivation at later learning stages was the strongest predictor of perceived sustainability, while pedagogical and experiential factors exerted significant indirect effects through motivational engagement. The analysis also confirmed the longitudinal influence of early motivational experiences on later engagement, emphasizing the importance of adaptive feedback and reflective learning processes. These findings advance understanding of how AI-driven personalization can promote sustainable digital citizenship learning by integrating adaptive pathways, culturally relevant content, and motivational scaffolds to support long-term behavioral change. Implications for educational design, pedagogy, and policy are discussed to guide the development of scalable AI-supported learning environments. • Longitudinal study on AI-personalized games for digital citizenship education. • Motivation is the strongest predictor of perceived sustainability. • Pedagogy, content, and usability indirectly support sustained motivation. • Personalized feedback enhances engagement with digital behavior scenarios. • Supports policy for scalable, sustainable, AI-enhanced learning in Thailand.

Authors

Institutions

Publication Details

Journal
Computers and Education Artificial Intelligence
Published
2025-11-20
DOI
https://doi.org/10.1016/j.caeai.2025.100498
Primary Topic
Sustainability in Higher Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Modeling the sustainability perspectives on personalized digital games for digital citizenship education: A PLS-SEM approach

Patcharin Panjaburee, Gwo‐Jen Hwang, Niwat Srisawasdi, Ungsinun Intarakamhang
Computers and Education Artificial Intelligence
Sustainability in Higher Education
article

Modeling the sustainability perspectives on personalized digital games for digital citizenship education: A PLS-SEM approach

Patcharin Panjaburee, Gwo‐Jen Hwang, Niwat Srisawasdi, Ungsinun Intarakamhang
article en

Abstract

As digital citizenship becomes an essential educational priority in the digital age, there is a growing need for sustainable and engaging instructional designs that foster students' ethical and responsible use of technology. Addressing this gap, this study modeled the sustainability perspectives underlying personalized digital game-based learning through a partial least squares structural equation modeling (PLS-SEM) approach. A longitudinal repeated-measures design was conducted with 372 lower secondary students in Thailand, using fuzzy logic and decision tree algorithms to personalize ethical digital scenarios. The proposed model examined how pedagogical design, content quality, usability, behavioral decisions, and motivation shape students' perceptions of sustainability. Results indicated that sustained motivation at later learning stages was the strongest predictor of perceived sustainability, while pedagogical and experiential factors exerted significant indirect effects through motivational engagement. The analysis also confirmed the longitudinal influence of early motivational experiences on later engagement, emphasizing the importance of adaptive feedback and reflective learning processes. These findings advance understanding of how AI-driven personalization can promote sustainable digital citizenship learning by integrating adaptive pathways, culturally relevant content, and motivational scaffolds to support long-term behavioral change. Implications for educational design, pedagogy, and policy are discussed to guide the development of scalable AI-supported learning environments. • Longitudinal study on AI-personalized games for digital citizenship education. • Motivation is the strongest predictor of perceived sustainability. • Pedagogy, content, and usability indirectly support sustained motivation. • Personalized feedback enhances engagement with digital behavior scenarios. • Supports policy for scalable, sustainable, AI-enhanced learning in Thailand.

Computers and Education Artificial IntelligenceVol. 9
National Taiwan University of Science and Technology (TW), Khon Kaen University (TH), National Taichung University of Education (TW), Srinakharinwirot University (TH), Yuan Ze University (TW)
Openalex Percentile: Top 63%
Sustainability in Higher Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.