IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i18p10149-d632980.html
   My bibliography  Save this article

Learning Analytics for Diagnosing Cognitive Load in E-Learning Using Bayesian Network Analysis

Author

Listed:
  • Younyoung Choi

    (Department of Adolescent Coaching Counseling, Hanyang Cyber University, Seoul 04763, Korea)

  • Jigeun Kim

    (Institute of Psychological Innovation, Yonsei University, Seoul 03722, Korea)

Abstract

A learner’s cognitive load is highly associated with their academic achievement within learning systems. Diagnostic information about a learner’s cognitive load is useful for achieving optimal learning, by enabling the learner to manage and control their cognitive load in the e-learning environment. However, little empirical research has been conducted to obtain diagnostic information about the cognitive load in e-learning systems. The purpose of this study was to analyze a personalized diagnostic evaluation for a learner’s cognitive load in an e-learning system, using the Bayesian Network (BN) as a learning analytic method. Data from 700 learners were collected from Cyber University. A learner’s cognitive load level was measured in terms of three components: extraneous cognitive load, intrinsic cognitive load, and germane cognitive load. The BN was built by representing the relationship among the extraneous cognitive load, intrinsic cognitive load, germane cognitive load, and academic achievement. The conditional and marginal probabilities in the BN were estimated. This study found that the BN provided diagnostic information about a learner’s level of cognitive load in the e-learning system. In addition, the BN predicted the learner’s academic achievement in terms of their different cognitive load patterns. This study’s results imply that diagnostic information related to cognitive load helps learners to improve academic achievement by managing and controlling their cognitive loads in the e-learning environment. In addition, instructional designers are able to offer more appropriately customized instructional methods by considering learners’ cognitive loads in online learning.

Suggested Citation

  • Younyoung Choi & Jigeun Kim, 2021. "Learning Analytics for Diagnosing Cognitive Load in E-Learning Using Bayesian Network Analysis," Sustainability, MDPI, vol. 13(18), pages 1-13, September.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:18:p:10149-:d:632980
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/18/10149/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/18/10149/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. May Portuguez Castro & Marcela Georgina Gómez Zermeño, 2020. "Challenge Based Learning: Innovative Pedagogy for Sustainability through e-Learning in Higher Education," Sustainability, MDPI, vol. 12(10), pages 1-15, May.
    2. Wahab Ali, 2020. "Online and Remote Learning in Higher Education Institutes: A Necessity in light of COVID-19 Pandemic," Higher Education Studies, Canadian Center of Science and Education, vol. 10(3), pages 1-16, September.
    3. Jeongju Lee & Hae-Deok Song & Ah Jeong Hong, 2019. "Exploring Factors, and Indicators for Measuring Students’ Sustainable Engagement in e-Learning," Sustainability, MDPI, vol. 11(4), pages 1-12, February.
    4. Younyoung Choi & Young Il Cho, 2020. "Learning Analytics Using Social Network Analysis and Bayesian Network Analysis in Sustainable Computer-Based Formative Assessment System," Sustainability, MDPI, vol. 12(19), pages 1-13, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sébastien Jacques & Abdeldjalil Ouahabi & Zoe Kanetaki, 2023. "Post-COVID-19 Education for a Sustainable Future: Challenges, Emerging Technologies and Trends," Sustainability, MDPI, vol. 15(8), pages 1-4, April.
    2. Zeinab Shahbazi & Yung-Cheol Byun, 2022. "Agent-Based Recommendation in E-Learning Environment Using Knowledge Discovery and Machine Learning Approaches," Mathematics, MDPI, vol. 10(7), pages 1-19, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. William Villegas-Ch & Xavier Palacios-Pacheco & Sergio Luján-Mora, 2019. "Application of a Smart City Model to a Traditional University Campus with a Big Data Architecture: A Sustainable Smart Campus," Sustainability, MDPI, vol. 11(10), pages 1-28, May.
    2. Marta Medina-García & Lina Higueras-Rodríguez & Mª del Mar García-Vita & Luis Doña-Toledo, 2021. "ICT, Disability, and Motivation: Validation of a Measurement Scale and Consequence Model for Inclusive Digital Knowledge," IJERPH, MDPI, vol. 18(13), pages 1-17, June.
    3. Luis Miguel Moctezuma Teresa & José Luis Aparicio López & Columba Rodríguez Alviso & Herlinda Gervacio Jiménez & Rosa María Brito Carmona, 2022. "Environmental Competencies for Sustainability: A Training Experience with High School Teachers in a Rural Community," Sustainability, MDPI, vol. 14(9), pages 1-17, April.
    4. Al Lily, Abdulrahman Essa & Ismail, Abdelrahim Fathy & Abunasser, Fathi Mohammed & Alhajhoj Alqahtani, Rafdan Hassan, 2020. "Distance education as a response to pandemics: Coronavirus and Arab culture," Technology in Society, Elsevier, vol. 63(C).
    5. Rozina Afroz & Nurul Islam & Sajedur Rahman & Nusrat Zerin Anny, 2021. "Students’ and teachers’ attitude towards online classes during Covid-19 pandemic: A study on three Bangladeshi government colleges," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 10(3), pages 462-476, April.
    6. Mine Halis & Duygu Yildirim, 2022. "The effect of perceived social support and life orientation on anxiety caused by online education in Covid 19 conditions," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 11(4), pages 310-322, June.
    7. William Villegas-Ch. & Milton Roman-Cañizares & Santiago Sánchez-Viteri & Joselin García-Ortiz & Walter Gaibor-Naranjo, 2021. "Analysis of the State of Learning in University Students with the Use of a Hadoop Framework," Future Internet, MDPI, vol. 13(6), pages 1-25, May.
    8. Jagoda Mrzyglocka-Chojnacka & Radoslaw Rynca, 2021. "Lessons from Covid‑19: Toward the Conceptual Model of University Management During Pandemic," European Research Studies Journal, European Research Studies Journal, vol. 0(2B), pages 383-393.
    9. Bijoya Saha & Shah Md Atiqul Haq & Khandaker Jafor Ahmed, 2023. "How does the COVID-19 pandemic influence students’ academic activities? An explorative study in a public university in Bangladesh," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-10, December.
    10. Bumho Lee & Jinwoo Kim, 2023. "Managing Social Presence in Collaborative Learning with Agent Facilitation," Sustainability, MDPI, vol. 15(7), pages 1-26, April.
    11. O’Connor, Jane & Ludgate, Shannon & Le, Quang-Vuong & Le, Huy Thanh & Huynh, Pham Dung Phat, 2023. "Lessons from the pandemic: Teacher educators’ use of digital technologies and pedagogies in Vietnam before, during and after the Covid-19 lockdown," International Journal of Educational Development, Elsevier, vol. 103(C).
    12. Sunha Kim & Suzanne Rosenblith & Yunjeong Chang & Shira Pollack, 2020. "Will ICMT Access and Use Support URM Students’ Online Learning in the (Post) COVID-19 Era?," Sustainability, MDPI, vol. 12(20), pages 1-14, October.
    13. Shafi AlDousari, 2023. "Capacities and Obstacles of Kuwait Medical Educational Sector in Transitioning Education System to Online Form: A Paradigm Shift," International Journal of Business and Management, Canadian Center of Science and Education, vol. 16(12), pages 1-88, February.
    14. Tidarat Luangrungruang & Urachart Kokaew, 2022. "E-Learning Model to Identify the Learning Styles of Hearing-Impaired Students," Sustainability, MDPI, vol. 14(20), pages 1-19, October.
    15. Cunying Fan & Juan Wang, 2023. "Undergraduates’ behavioral intention to use indigenous Chinese Web 2.0 tools in informal English learning: Combining language learning motivation with technology acceptance model," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-9, December.
    16. Kenneth Nwanua Ohei & Sam Lubbe, 2022. "Taking Full Advantage of the COVID-19 Era to Intensify the Use of Information and Communication Technology Tools in Higher Education Institutes," International Review of Management and Marketing, Econjournals, vol. 12(5), pages 21-32, September.
    17. Valentin Kuleto & Milena P. Ilić & Nevenka Popović Šević & Marko Ranković & Dušan Stojaković & Milutin Dobrilović, 2021. "Factors Affecting the Efficiency of Teaching Process in Higher Education in the Republic of Serbia during COVID-19," Sustainability, MDPI, vol. 13(23), pages 1-20, November.
    18. Annchen Mielmann, 2021. "Being Innovative in Running an Online Food Research Project in Consumer Sciences during the COVID-19 Pandemic," Sustainability, MDPI, vol. 13(24), pages 1-22, December.
    19. Noé Abraham González-Nieto & Caridad García-Hernández & Margarita Espinosa-Meneses, 2021. "School Culture and Digital Technologies: Educational Practices at Universities within the Context of the COVID-19 Pandemic," Future Internet, MDPI, vol. 13(10), pages 1-22, September.
    20. Lixuan Sun, 2024. "Translanguaging pedagogy on the digital stage: exploring Chinese undergraduates’ English grammar learning through DingTalk platform," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:18:p:10149-:d:632980. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.