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International Journal of Education and Digital Learning (IJEDL)
Published by CV. LAFADZ JAYA
ISSN : -     EISSN : 2962052X     DOI : https://doi.org/10.47353/ijedl
Core Subject : Education, Social,
Education Languange, Linguistic, Communication & Media Mathematics Social Sciences Other
International Journal of Education and Digital Learning (IJEDL) | ISSN (e): 2962-052X is an international peer-reviewed Open Access journal that publishes original and relevant articles in all fields of education research. It publishes both theoretical as well as empirical and methodological contributions to education research. Its coverage encompasses all forms of teaching and learning at all levels, from early childhood development to lifelong learning. The journal provides the readers with free and permanent access to all content worldwide; and the authors with article promotion, long-time preservation, language assistance, no space constraints and immediate publication.
Arjuna Subject : Ilmu Sosial - Pendidikan
Articles 182 Documents
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Information Overload in Digital Learning Environments and Academic Achievement among Libyan University Students: A Structural Equation Modeling Approach Abubaker Kashada; Khalid J Bisher; Abubaker Sasi; Riyadh M. Suwayd
International Journal of Education and Digital Learning (IJEDL) Vol. 4 No. 1 (2025)
Publisher : Lafadz Jaya Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47353/ijedl.v4i1.356

Abstract

This study examines the complex role of information overload in shaping academic achievement within digital learning environments, with a specific focus on Libyan higher education. Drawing on data from 205 undergraduate students and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), the study investigates both the direct and indirect effects of information overload through cognitive load and self-regulated learning (SRL). The findings reveal a dual and nuanced effect. Information overload exerts a significant negative direct impact on academic achievement by increasing cognitive load and disrupting attentional processes. At the same time, it demonstrates a positive indirect effect by stimulating self-regulated learning, which partially offsets its adverse cognitive consequences. Cognitive load emerges as a key mediator that amplifies the negative pathway, while self-regulated learning functions as an adaptive mechanism that enhances academic performance. These results contribute to the literature by integrating Cognitive Load Theory and self-regulated learning within a unified empirical framework, highlighting the conditional nature of information overload in educational settings. Rather than being purely detrimental, information overload operates as a double-edged phenomenon, with its impact depending on students’ capacity to regulate their learning processes. Practically, the study underscores the need for higher education institutions—particularly in resource-constrained contexts—to move beyond information provision toward developing students’ digital literacy and self-regulation skills. Such interventions are essential for mitigating cognitive overload and fostering sustainable academic achievement in increasingly complex digital environments.
Reconceptualizing Digital Pedagogy: Integrating Artificial Intelligence and Learning Analytics for Adaptive Education Systems Daniel Thompson; Maria Fernandes
International Journal of Education and Digital Learning (IJEDL) Vol. 4 No. 1 (2025)
Publisher : Lafadz Jaya Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47353/ijedl.v4i1.373

Abstract

This study reconceptualizes digital pedagogy by integrating artificial intelligence (AI) and learning analytics as core drivers of adaptive education systems. While existing research has largely positioned digital technologies as supplementary instructional tools, this study argues that AI and data-driven systems fundamentally reshape pedagogical structures, learner engagement, and educational outcomes. Using a systematic literature review approach, this study synthesizes recent developments in artificial intelligence in education and learning analytics to identify key patterns and conceptual relationships. The findings reveal that effective digital pedagogy is characterized by the integration of AI-driven personalization, learning analytics, pedagogical alignment, and continuous feedback mechanisms. Based on these findings, this study proposes an Adaptive Digital Pedagogy Framework that conceptualizes digital learning as a dynamic and multidimensional system. This framework highlights the importance of aligning technological capabilities with instructional design to support adaptive and data-informed learning environments. This study contributes to the literature by offering a unified theoretical framework that bridges previously fragmented domains of AI in education and learning analytics. It also provides practical implications for educators and policymakers in designing scalable, adaptive, and inclusive education systems in the digital era.

Page 19 of 19 | Total Record : 182

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