IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i23p15775-d985545.html
   My bibliography  Save this article

Analysis of MOOC Quality Requirements for Landscape Architecture Based on the KANO Model in the Context of the COVID-19 Epidemic

Author

Listed:
  • Lifang Qiao

    (School of Horticulture and Landscape Architecture, Henan Institute of Science and Technology, Xinxiang 453003, China
    Henan Province Engineering Center of Horticultural Plant Resource Utilization and Germplasm Enhancement, Xinxiang 453003, China)

  • Yichuan Zhang

    (School of Horticulture and Landscape Architecture, Henan Institute of Science and Technology, Xinxiang 453003, China
    Henan Province Engineering Center of Horticultural Plant Resource Utilization and Germplasm Enhancement, Xinxiang 453003, China)

Abstract

COVID-19 has had a severe impact on higher education worldwide, and Massive Open Online Courses (MOOCs) have become the best solution to reduce the impact of the COVID-19 on student learning. In order to improve the quality of MOOCs for Landscape Architecture, it is essential to fully understand the psychological needs of students learning online. A total of 119 undergraduates and postgraduates majoring in landscape architecture were selected as the research subjects, and 18 indicators falling into 5 functions, including course organization, course resources, learning environment, learning experience, and learning support were screened. Questionnaires based on the KANO model were prepared at wjx.cn for investigation through WeChat. Attributes were classified according to the traditional KANO model and the KANO model based on Better-Worse coefficients. The research showed that based on the classification results of the traditional KANO model, 17 of the 18 indicators were of the attractive quality factor and the rest were of the must-be quality factor. After reclassification using the KANO model based on Better-Worse coefficients, 4 of the 18 indicators were must-be quality factors, 6 were one-dimensional quality factors, 4 were attractive quality factors, and the rest 4 were indifferent quality factors. Compared to the traditional KANO model, the KANO model based on Better-Worse coefficients has better quality element classification discrimination. According to the KANO-based analysis, appropriate strategies for indicators shall be adopted for MOOC development according to the four types of quality requirements. The research can provide a basis for the development and optimization of MOOCs for landscape architecture so as to better meet the learning needs of students and achieve better learning effects.

Suggested Citation

  • Lifang Qiao & Yichuan Zhang, 2022. "Analysis of MOOC Quality Requirements for Landscape Architecture Based on the KANO Model in the Context of the COVID-19 Epidemic," Sustainability, MDPI, vol. 14(23), pages 1-17, November.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:23:p:15775-:d:985545
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/23/15775/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/23/15775/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Björn Stöcker & Daniel Baier & Benedikt M. Brand, 2021. "New insights in online fashion retail returns from a customers’ perspective and their dynamics," Journal of Business Economics, Springer, vol. 91(8), pages 1149-1187, October.
    2. Martin Beer & Frances Slack & Gillian Armitt, 2005. "Collaboration and Teamwork: Immersion and Presence in an Online Learning Environment," Information Systems Frontiers, Springer, vol. 7(1), pages 27-37, February.
    3. Han, Haipeng & Lien, Donald & Lien, Jaimie W. & Zheng, Jie, 2022. "Online or face-to-face? Competition among MOOC and regular education providers," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 857-881.
    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. Huiya Xu & Ha-young Song, 2024. "Key Factors Influencing Chinese Consumers’ Demand for Naturally Dyed Garments: Data Analysis through KJ Method and KANO Model," Sustainability, MDPI, vol. 16(3), pages 1-28, January.
    2. Zhi Qiu & Yue Wang & Jie Wang & Zhu Wang & Yi Zhou, 2023. "Needs Hierarchy for Public Service Facilities and Guidance-Control Programming in Small Chinese Towns Influenced by Complex Urbanization of Residents: The Evidence from Zhejiang," Land, MDPI, vol. 12(6), pages 1-27, June.

    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. Miroslava Raspopovic & Aleksandar Jankulovic, 0. "Performance measurement of e-learning using student satisfaction analysis," Information Systems Frontiers, Springer, vol. 0, pages 1-12.
    2. Miroslava Raspopovic & Aleksandar Jankulovic, 2017. "Performance measurement of e-learning using student satisfaction analysis," Information Systems Frontiers, Springer, vol. 19(4), pages 869-880, August.
    3. Stefan Stieglitz & Milad Mirbabaie & Nicholas R. J. Möllmann & Jannik Rzyski, 2022. "Collaborating with Virtual Assistants in Organizations: Analyzing Social Loafing Tendencies and Responsibility Attribution," Information Systems Frontiers, Springer, vol. 24(3), pages 745-770, June.
    4. Wolfgang Breuer & Jannis Bischof & Christian Hofmann & Jochen Hundsdoerfer & Hans-Ulrich Küpper & Marko Sarstedt & Philipp Schreck & Tim Weitzel & Peter Witt, 2023. "Recent developments in Business Economics," Journal of Business Economics, Springer, vol. 93(6), pages 989-1013, August.
    5. Nizar Abdelkafi & Jinou Xu & Margherita Pero & Federica Ciccullo & Antonio Masi, 2023. "Does the combination of sustainable business model patterns lead to truly sustainable business models? Critical analysis of existing frameworks and extensions," Journal of Business Economics, Springer, vol. 93(4), pages 597-634, May.
    6. He, Wei & Li, Mingzhi & Zheng, Jie, 2023. "Switching cost, network externality and platform competition," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 428-443.
    7. Chulhwan Chris Bang, 2015. "Information systems frontiers: Keyword analysis and classification," Information Systems Frontiers, Springer, vol. 17(1), pages 217-237, February.
    8. Huang, Naqun & Lien, Jaimie W. & Zheng, Jie, 2023. "To acquire or compete? Government intervention in transportation under different route structures," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 172(C).
    9. Wenan Tan & Senbo Chen & Jingxian Li & Lingxia Li & Tong Wang & Xiaoming Hu, 2014. "A Trust Evaluation Model for E‐Learning Systems," Systems Research and Behavioral Science, Wiley Blackwell, vol. 31(3), pages 353-365, May.

    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:14:y:2022:i:23:p:15775-:d:985545. 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.