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Learning Management System-Based Evaluation to Determine Academic Efficiency Performance

Author

Listed:
  • Brenda Juárez Santiago

    (Facultad de Ingeniería, Universidad Internacional Iberoamericana, Campeche 24560, Mexico
    Ingeniería, Universidad Tecnológica de San Juan del Río, Querétaro 76800, Mexico
    These authors contributed equally to this work.)

  • Juan Manuel Olivares Ramírez

    (Ingeniería, Universidad Tecnológica de San Juan del Río, Querétaro 76800, Mexico
    These authors contributed equally to this work.)

  • Juvenal Rodríguez-Reséndiz

    (Facultad de Ingeniería, Universidad Autónoma de Querétaro, Querétaro 76010, Mexico
    These authors contributed equally to this work.)

  • Andrés Dector

    (CONACYT–Universidad Tecnológica de San Juan del Río, Querétaro 76800, Mexico
    These authors contributed equally to this work.)

  • Raúl García García

    (Ingeniería, Universidad Tecnológica de San Juan del Río, Querétaro 76800, Mexico
    These authors contributed equally to this work.)

  • José Eli Eduardo González-Durán

    (Instituto Tecnológico Superior del Sur de Guanajuato, Guanajuato 38980, Mexico
    These authors contributed equally to this work.)

  • Fermín Ferriol Sánchez

    (Facultad de Ingeniería, Universidad Internacional Iberoamericana, Campeche 24560, Mexico
    These authors contributed equally to this work.)

Abstract

At present, supporting e-learning with interactive virtual campuses is a future goal in education. Models that measure the levels of acceptance, performance, and academic efficiency have been recently developed. In light of the above, we carried out a study to evaluate a model for which architecture design, configuration, metadata, and statistical coefficients were obtained using four Learning Management Systems (LMSs). That allowed us to determine reliability, accuracy, and correlation, using and integrating the factors that other researchers have previously used, only using isolated models, such as Anxiety–Innovation (AI), Utility and Use (UU), Tools Learning (TL), System Factors (SF), Access Strategies (AS), Virtual Library (VL), and Mobile Use (MU). The research was conducted over one year in nine groups. The results from an LMS Classroom, architecturally and configuration-wise, had the highest level of performance, with an average of 73% when evaluated using statistical coefficients. The LMS Classroom had a good acceptance and a greater impact: SF, 82%, AI, 80%, and VL, 43%, while out of the seven factors, those with the most significant impact on academic efficiency were TL, 80%, VL, 82%, and MU, 85%.

Suggested Citation

  • Brenda Juárez Santiago & Juan Manuel Olivares Ramírez & Juvenal Rodríguez-Reséndiz & Andrés Dector & Raúl García García & José Eli Eduardo González-Durán & Fermín Ferriol Sánchez, 2020. "Learning Management System-Based Evaluation to Determine Academic Efficiency Performance," Sustainability, MDPI, vol. 12(10), pages 1-17, May.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:10:p:4256-:d:361618
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    References listed on IDEAS

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    Cited by:

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    3. Aljawharah M. Aldosari & Hala F. Eid & Yi-Ping Phoebe Chen, 2022. "A Proposed Strategy Based on Instructional Design Models through an LMS to Develop Online Learning in Higher Education Considering the Lockdown Period of the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(13), pages 1-14, June.
    4. Eduard Edelhauser & Lucian Lupu-Dima, 2020. "Is Romania Prepared for eLearning during the COVID-19 Pandemic?," Sustainability, MDPI, vol. 12(13), pages 1-30, July.
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    7. Sálvora Feliz & María-Carmen Ricoy & Juan-Andrés Buedo & Tiberio Feliz-Murias, 2022. "Students’ E-Learning Domestic Space in Higher Education in the New Normal," Sustainability, MDPI, vol. 14(13), pages 1-15, June.
    8. Seren Başaran & Kowther Abdikarin Hussein, 2023. "Determinants of University Students’ Intention to Use Video Conferencing Tools during COVID-19 Pandemic: Case of Somalia," Sustainability, MDPI, vol. 15(3), pages 1-22, January.
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