IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i15p8339-d601829.html
   My bibliography  Save this article

Students’ Preference Analysis on Online Learning Attributes in Industrial Engineering Education during the COVID-19 Pandemic: A Conjoint Analysis Approach for Sustainable Industrial Engineers

Author

Listed:
  • Ardvin Kester S. Ong

    (School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines
    School of Graduate Studies, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines)

  • Yogi Tri Prasetyo

    (School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines)

  • Michael Nayat Young

    (School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines)

  • John Francis T. Diaz

    (Department of Finance and Accounting, Asian Institute of Management, 123 Paseo de Roxas, Legazpi Village, Makati, Metro Manila 1229, Philippines)

  • Thanatorn Chuenyindee

    (School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines
    School of Graduate Studies, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines
    Logistics and Supply Chain Management Program, Nakhon Pathom Rajabhat University, Nakhon Pathom 73000, Thailand)

  • Poonyawat Kusonwattana

    (School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines
    School of Graduate Studies, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines)

  • Nattakit Yuduang

    (School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines
    School of Graduate Studies, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines
    Institute of Research and Development, Valaya Alongkorn Rajabhat University, Phahonyothim Rd., Khlong Nueng, Khlong Luang District, Pathum Thani 13180, Thailand)

  • Reny Nadlifatin

    (Department of Information Systems, Institut Teknologi Sepuluh Nopember, Kampus ITS Sukolilo, Surabaya 60111, Indonesia)

  • Anak Agung Ngurah Perwira Redi

    (Industrial Engineering Department, BINUS Graduate Program—Master of Industrial Engineering, Bina Nusantara University, Jakarta 11480, Indonesia)

Abstract

The decline of enrollees for industrial engineering during the COVID-19 pandemic and the increasing demand for professional industrial engineers should be explored. The purpose of this study was to determine the preference of industrial engineering students of different educational levels on online learning during the COVID-19 pandemic. Specifically, this study utilized conjoint analysis with orthogonal design considering seven attributes: delivery type, layout, term style, final requirements, Coursera requirements, seatwork and practice sets, and platforms. Among the attributes, 20 stimuli were created through SPSS and were answered voluntarily by 126 respondents utilizing a 7-point Likert Scale. The respondents were comprised of 79 undergraduate, 30 fully online master’s degree, and 17 master’s and doctorate degree students collected through purposive sampling. One university from the two available universities that offer all educational levels of IE in the Philippines was considered. The results showed that undergraduate students considered the final requirements with multiple-choice as the highest preference, followed by non-modular term style, and no seatwork and practice sets. In addition, fully online master’s degree students considered delivery type with the mix as the highest preference, followed by layout, and no seatwork and practice sets. Finally, master’s and doctorate degree students considered final requirements with publication as the highest preference, followed by no seatwork and practice sets, and mix delivery type. The students are technologically inclined, want to learn at their own pace, know where and how to get additional online learning materials, but still need the guidance of teachers/professors. The results would help contribute to the theoretical foundation for further students’ preference segmentation, specifically on online learning during the COVID-19 pandemic worldwide. Moreover, the design created could be utilized for other courses in measuring students’ preference for online learning even after the COVID-19 pandemic.

Suggested Citation

  • Ardvin Kester S. Ong & Yogi Tri Prasetyo & Michael Nayat Young & John Francis T. Diaz & Thanatorn Chuenyindee & Poonyawat Kusonwattana & Nattakit Yuduang & Reny Nadlifatin & Anak Agung Ngurah Perwira , 2021. "Students’ Preference Analysis on Online Learning Attributes in Industrial Engineering Education during the COVID-19 Pandemic: A Conjoint Analysis Approach for Sustainable Industrial Engineers," Sustainability, MDPI, vol. 13(15), pages 1-20, July.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:15:p:8339-:d:601829
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/15/8339/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/15/8339/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Schultze, Thomas & Mojzisch, Andreas & Schulz-Hardt, Stefan, 2012. "Why groups perform better than individuals at quantitative judgment tasks: Group-to-individual transfer as an alternative to differential weighting," Organizational Behavior and Human Decision Processes, Elsevier, vol. 118(1), pages 24-36.
    2. Pal, Debajyoti & Vanijja, Vajirasak, 2020. "Perceived usability evaluation of Microsoft Teams as an online learning platform during COVID-19 using system usability scale and technology acceptance model in India," Children and Youth Services Review, Elsevier, vol. 119(C).
    3. Sethuraman, Raj & Kerin, Roger A. & Cron, William L., 2005. "A field study comparing online and offline data collection methods for identifying product attribute preferences using conjoint analysis," Journal of Business Research, Elsevier, vol. 58(5), pages 602-610, May.
    4. Mok, Min Seok & Sohn, So Young & Ju, Yong Han, 2010. "Conjoint analysis for intellectual property education," World Patent Information, Elsevier, vol. 32(2), pages 129-134, June.
    5. Shailendra Palvia & Prageet Aeron & Parul Gupta & Diptiranjan Mahapatra & Ratri Parida & Rebecca Rosner & Sumita Sindhi, 2018. "Online Education: Worldwide Status, Challenges, Trends, and Implications," Journal of Global Information Technology Management, Taylor & Francis Journals, vol. 21(4), pages 233-241, October.
    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. Ardvin Kester S. Ong & Jelline C. Cuales & Jose Pablo F. Custodio & Eisley Yuanne J. Gumasing & Paula Norlene A. Pascual & Ma. Janice J. Gumasing, 2023. "Investigating Preceding Determinants Affecting Primary School Students Online Learning Experience Utilizing Deep Learning Neural Network," Sustainability, MDPI, vol. 15(4), pages 1-24, February.
    2. Ma. Janice J. Gumasing & Ardvin Kester S. Ong & Maria Angelica D. Bare, 2022. "User Preference Analysis of a Sustainable Workstation Design for Online Classes: A Conjoint Analysis Approach," Sustainability, MDPI, vol. 14(19), pages 1-23, September.
    3. Ardvin Kester S. Ong & Yogi Tri Prasetyo & Kerr Lorenzo Picazo & Kim Aaron Salvador & Bobby Ardiansyah Miraja & Yoshiki B. Kurata & Thanatorn Chuenyindee & Reny Nadlifatin & Anak Agung Ngurah Perwira , 2021. "Gym-Goers Preference Analysis of Fitness Centers during the COVID-19 Pandemic: A Conjoint Analysis Approach for Business Sustainability," Sustainability, MDPI, vol. 13(18), pages 1-17, September.
    4. Jenalyn Shigella G. Yandug & Erika Mae D. Costales & Ardvin Kester S. Ong, 2023. "A Conjoint Analysis Approach, Implications, and Mitigation Plans in Analyzing Students’ Preferences for Online Learning Delivery Types during the COVID-19 Pandemic for Engineering Students: A Case Stu," Sustainability, MDPI, vol. 15(6), pages 1-15, March.
    5. Jeya Amantha Kumar & Sharifah Osman & Mageswaran Sanmugam & Rasammal Rasappan, 2022. "Mobile Learning Acceptance Post Pandemic: A Behavioural Shift among Engineering Undergraduates," Sustainability, MDPI, vol. 14(6), pages 1-13, March.
    6. S. Ong, Ardvin Kester & Prasetyo, Yogi Tri & Chuenyindee, Thanatorn & Young, Michael Nayat & Doma, Bonifacio T. & Caballes, Dennis G. & Centeno, Raffy S. & Morfe, Anthony S. & Bautista, Christine S., 2022. "Preference analysis on the online learning attributes among senior high school students during the COVID-19 pandemic: A conjoint analysis approach," Evaluation and Program Planning, Elsevier, vol. 92(C).

    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. S. Ong, Ardvin Kester & Prasetyo, Yogi Tri & Chuenyindee, Thanatorn & Young, Michael Nayat & Doma, Bonifacio T. & Caballes, Dennis G. & Centeno, Raffy S. & Morfe, Anthony S. & Bautista, Christine S., 2022. "Preference analysis on the online learning attributes among senior high school students during the COVID-19 pandemic: A conjoint analysis approach," Evaluation and Program Planning, Elsevier, vol. 92(C).
    2. Ardvin Kester S. Ong & Yogi Tri Prasetyo & Kerr Lorenzo Picazo & Kim Aaron Salvador & Bobby Ardiansyah Miraja & Yoshiki B. Kurata & Thanatorn Chuenyindee & Reny Nadlifatin & Anak Agung Ngurah Perwira , 2021. "Gym-Goers Preference Analysis of Fitness Centers during the COVID-19 Pandemic: A Conjoint Analysis Approach for Business Sustainability," Sustainability, MDPI, vol. 13(18), pages 1-17, September.
    3. Cliff R. Kikawa & Charity Kiconco & Moses Agaba & Dimas Ntirampeba & Amos Ssematimba & Billy M. Kalema, 2022. "Social Media Marketing for Small and Medium Enterprise Performance in Uganda: A Structural Equation Model," Sustainability, MDPI, vol. 14(21), pages 1-20, November.
    4. Rita Takács & Szabolcs Takács & Judit T. Kárász & Attila Oláh & Zoltán Horváth, 2023. "The impact of the first wave of COVID-19 on students’ attainment, analysed by IRT modelling method," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 10(1), pages 1-10, December.
    5. Jiří Hnilica & Lorraine M. Uhlaner & Ondřej Machek & Ales Kubíček & Martin Lukeš & Martin Jurek & Petra Štamfestová, 2019. "The Role of Responsible Ownership and Family in Privately Held Firms with Multiple Owners: Preliminary Findings from the Czech Republic," Central European Business Review, Prague University of Economics and Business, vol. 2019(5), pages 1-17.
    6. Hanea, A.M. & McBride, M.F. & Burgman, M.A. & Wintle, B.C. & Fidler, F. & Flander, L. & Twardy, C.R. & Manning, B. & Mascaro, S., 2017. "I nvestigate D iscuss E stimate A ggregate for structured expert judgement," International Journal of Forecasting, Elsevier, vol. 33(1), pages 267-279.
    7. Julia A. Minson & Jennifer S. Mueller & Richard P. Larrick, 2018. "The Contingent Wisdom of Dyads: When Discussion Enhances vs. Undermines the Accuracy of Collaborative Judgments," Management Science, INFORMS, vol. 64(9), pages 4177-4192, September.
    8. Huang, Duen-Huang & Chueh, Hao-En, 2022. "Behavioral intention to continuously use learning apps: A comparative study from Taiwan universities," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    9. Maricar M. Navarro & Yogi Tri Prasetyo & Michael Nayat Young & Reny Nadlifatin & Anak Agung Ngurah Perwira Redi, 2021. "The Perceived Satisfaction in Utilizing Learning Management System among Engineering Students during the COVID-19 Pandemic: Integrating Task Technology Fit and Extended Technology Acceptance Model," Sustainability, MDPI, vol. 13(19), pages 1-18, September.
    10. Oh, Hyunjoo & Weitz, Barton & Lim, Jeremy, 2016. "Retail career attractiveness to college students: Connecting individual characteristics to the trade-off of job attributes," Journal of Retailing and Consumer Services, Elsevier, vol. 31(C), pages 345-354.
    11. Md Irteja Islam & Shah Saif Jahan & Mohammad Tawfique Hossain Chowdhury & Samia Naz Isha & Arup Kumar Saha & Sujan Kanti Nath & Mohammed Shahed Jahan & Md. Humayun Kabir & Ehsanul Hoque Apu & Russell , 2022. "Experience of Bangladeshi Dental Students towards Online Learning during the COVID-19 Pandemic: A Web-Based Cross-Sectional Study," IJERPH, MDPI, vol. 19(13), pages 1-13, June.
    12. repec:cup:judgdm:v:14:y:2019:i:3:p:349-363 is not listed on IDEAS
    13. Mohammed Arshad Khan & Vivek & Mohammed Kamalun Nabi & Maysoon Khojah & Muhammad Tahir, 2020. "Students’ Perception towards E-Learning during COVID-19 Pandemic in India: An Empirical Study," Sustainability, MDPI, vol. 13(1), pages 1-14, December.
    14. Józef Ober & Anna Kochmańska, 2022. "Remote Learning in Higher Education: Evidence from Poland," IJERPH, MDPI, vol. 19(21), pages 1-35, November.
    15. Ueno, Akiko & Dennis, Charles & Dafoulas, Georgios A., 2023. "Digital exclusion and relative digital deprivation: Exploring factors and moderators of internet non-use in the UK," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    16. Laura Ihm & Han Zhang & Alexandra van Vijfeijken & Mark G. Waugh, 2021. "Impacts of the Covid‐19 pandemic on the health of university students," International Journal of Health Planning and Management, Wiley Blackwell, vol. 36(3), pages 618-627, May.
    17. Saud Altaf & Rimsha Asad & Shafiq Ahmad & Iftikhar Ahmed & Mali Abdollahian & Mazen Zaindin, 2023. "A Hybrid Framework of Deep Learning Techniques to Predict Online Performance of Learners during COVID-19 Pandemic," Sustainability, MDPI, vol. 15(15), pages 1-24, July.
    18. Thanatorn Chuenyindee & Ardvin Kester S. Ong & Yogi Tri Prasetyo & Satria Fadil Persada & Reny Nadlifatin & Thaninrat Sittiwatethanasiri, 2022. "Factors Affecting the Perceived Usability of the COVID-19 Contact-Tracing Application “Thai Chana” during the Early COVID-19 Omicron Period," IJERPH, MDPI, vol. 19(7), pages 1-16, April.
    19. Walid Mahmoud Khalilia & Abdallatif Abuowda & Stylianos Mystakidis & Maria Fragkaki, 2023. "A Mediation Model of the Usability and Intergroup Relation for Online Project Management Community Effectiveness with Microsoft Teams," Societies, MDPI, vol. 13(12), pages 1-15, December.
    20. Nadezhda Radina & Yulia Balakina, 2021. "Challenges for Education during the Pandemic: An Overview of Literature," Voprosy obrazovaniya / Educational Studies Moscow, National Research University Higher School of Economics, issue 1, pages 178-194.
    21. Liao, Shu-Chun & Chou, Tzu-Chuan & Huang, Chen-Hao, 2022. "Revisiting the development trajectory of the digital divide: A main path analysis approach," Technological Forecasting and Social Change, Elsevier, vol. 179(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:15:p:8339-:d:601829. 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.