| Project/Area Number |
22K02874
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 09070:Educational technology-related
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| Research Institution | Kyoto University of Advanced Science (2023)
Ritsumeikan University (2022) |
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Principal Investigator |
マルチュケ モリツ 京都先端科学大学, 経済経営学部, 准教授 (80738584)
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| Co-Investigator(Kenkyū-buntansha) |
林 勇吾 立命館大学, 総合心理学部, 教授 (60437085)
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| Project Period (FY) |
2022-04-01 – 2025-03-31
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| Project Status |
Granted (Fiscal Year 2023)
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| Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2024: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2023: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2022: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
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| Keywords | E-Learning / Online Course / Kano model / E-learning / Educational technology / Machine Learning / Kano Model |
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| Outline of Research at the Start |
This research aims to address the comprehension of e-learning online course features by using the Kano model in combination with statistical and machine learning methods.
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| Outline of Annual Research Achievements |
I have (co-)authored six papers and two books (editor of IEEE and Springer conferences), five of them as first author, including a high-impact journal (Disasters, accepted for publishing). The knowledge gained form this research has ignited another collaborative research project with an international community of practice.
The research system setup was updated (dynamic CMS website with necessary functionality and questionnaire updates). Because of a job change, course data could not be collected as planned. One online course (Introduction to Algorithms and Programming) was continued and analyzed. Re-designed questionnaires were implemented. While the job change resulted in a delay of the research conduct, an effort was made instead to disseminate the research findings and analyze existing results. As a Program Committee Chair for three international conferences (Springer, IEEE, and ACM), research ideas could be shared with wider audiences.
A word-embedding language model (based on Word2Vec) was developed to support the Kano model findings. Students' expectation vs consumption experience were compared via ex-ante and ex-post Kano questionnaires. The language model was used to explain some of the shifts that occurred in students' perception of online course feature from before to after taking the course. The findings were published in an ACM conference and lead to a separate paper accepted for publication in the journal Disasters.
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| Current Status of Research Progress |
Current Status of Research Progress
3: Progress in research has been slightly delayed.
Reason
Due to a job change to a different university, class data could not be collected as planned. For each class that data is gathered from, an online course has to be designed, implemented, and tested. This lead to a delay in the planned research conduct.
A workshop and research discussions planned for AY2023 in Germany were also delayed for AY2024. A focus was given to research result dissemination and planning (working as a PC Chair for three international conferences, IEEE, Springer, and ACM).
The research is therefore panned to be extended for one year.
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| Strategy for Future Research Activity |
Data from further courses is planned to be implemented and evaluated. In addition to undergraduate classes, graduate classes will also be taken into account.
Results from additional classes will be consolidated with previous findings. Advanced language models (transformer based, e.g., BERT), including Topic Modeling, will be used to evaluate freeform text comments and create a hybrid model with the Kano method. New and updated results will be published in top international conferences. A workshop in Germany is planned to expand the educational community of practice.
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