Identification of undergraduate student learning attribute preferences using the conjoint analysis approach in the post-pandemic era
The COVID-19 pandemic triggered a rapid transition from traditional in-person education to fully online learning environments. Consequently, understanding students’ preferences for online learning attributes in the post-pandemic era has become essential, especially as blended and hybrid models gain...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-08-01
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| Series: | Cogent Education |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/2331186X.2025.2543037 |
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| Summary: | The COVID-19 pandemic triggered a rapid transition from traditional in-person education to fully online learning environments. Consequently, understanding students’ preferences for online learning attributes in the post-pandemic era has become essential, especially as blended and hybrid models gain prominence. This study investigated undergraduate students’ preferences regarding various aspects of online learning using conjoint analysis. Eight key attributes were examined: delivery type, evaluation type, feedback mechanism, communication media, supplementary videos, company visits, study guides and material flexibility. An orthogonal design enabled simultaneous analysis of these attributes. A total of 235 undergraduate students in Indonesia participated through proportionate stratified random sampling, completing a survey with 16 stimuli. Findings revealed that feedback type was the most influential attribute, followed by evaluation type, company visits and study guides. Students preferred direct, constructive feedback; flexible evaluation methods; company visits for experiential learning; and supplementary study guides for pre-class preparation. This study is among the first to employ conjoint analysis to explore online learning preferences in higher education during the post-pandemic transition. The results highlight the method’s effectiveness and adaptability in evaluating learning preferences across diverse contexts, providing a foundation for future research. |
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| ISSN: | 2331-186X |