Technology-Mediated Learning and Knowledge Retention among Students

  • Authors

    • Niklaus Emil Wirth Professor, ETH Zurich, Switzerland. Author

    DOI:

    https://doi.org/10.67228/3071561X/IJIRHT-2025PII7A8N

    Published 10-05-2025

  • Blockchain, Financial Transactions, Distributed Ledger Technology, Cryptocurrency, Smart Contracts, Cybersecurity, Consensus Mechanism, Decentralized Finance

    Issue

    Vol. 8 No. 2 (2025)

    Section

    Articles

    How to Cite

    [1]
    N. E. Wirth, “Technology-Mediated Learning and Knowledge Retention among Students”, IJIRHT, vol. 8, no. 2, pp. 01–15, Oct. 2025, doi: 10.67228/3071561X/IJIRHT-2025PII7A8N.

  • Abstract

    Technology-mediated learning has transformed education by improving knowledge acquisition and retention through digital technologies such as Learning Management Systems (LMS), Artificial Intelligence (AI), Virtual Reality (VR), Augmented Reality (AR), adaptive learning platforms, and mobile learning applications. These technologies support personalized learning, collaboration, interactive content, and timely feedback, enhancing student learning experiences. This study investigates the relationship between technology-mediated learning and student knowledge retention using a quantitative research framework. A structured questionnaire was administered to undergraduate and postgraduate students who regularly use digital learning tools. Statistical techniques, including descriptive statistics, reliability testing, correlation analysis, and comparative performance evaluation, were employed to identify key factors influencing knowledge retention. The proposed Technology-Mediated Knowledge Retention Framework (TMKRF) integrates instructional design with adaptive digital technologies to improve learning outcomes through continuous assessment, personalized feedback, spaced repetition, and collaborative learning. The findings indicate that technology-mediated learning significantly enhances knowledge retention, conceptual understanding, motivation, and academic performance compared with traditional teaching methods. Although challenges such as digital inequality, cognitive overload, technological competency, internet connectivity, and data privacy persist, the study offers practical recommendations for educators, institutions, technology developers, and policymakers. The proposed framework contributes to the development of effective digital learning environments that support long-term knowledge retention and lifelong learning.

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