Motivations Matter: Predicting Entrepreneurship Education MOOC Course Completion with a Decision Tree Approach.
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| Title: | Motivations Matter: Predicting Entrepreneurship Education MOOC Course Completion with a Decision Tree Approach. |
|---|---|
| Authors: | Wei, Chin Jia1, Shahmi, Abdullah Muhammad Farhan1, Qing, Wah Yue1, Melati, Nungsari2 |
| Source: | Online Learning. Mar2026, Vol. 30 Issue 1, p294-322. 29p. |
| Subject Terms: | *COVID-19 pandemic, *Retention of college students, *Online education, Entrepreneurship education, Decision trees, Sociodemographic factors, Psychological factors |
| Abstract: | Online entrepreneurship education (EE) courses experienced a sharp 66% spike in demand around March 2020, attributed to the COVID-19 pandemic and the subsequent surge in digital entrepreneurship uptake. Completion rates serve as a key indicator of online MOOC efficacy, with students’ psychological attributes and contextual factors often examined as explanatory variables in assessing online course completion. This mixed-methods study explores influential factors in student retention in an EE Massive Open Online Course (MOOC) by using survey responses from 222 Malaysian youths who voluntarily registered for an EE MOOC, which was active from February to October 2021. A Decision Tree approach was chosen to predict the course completion likelihood based on sociodemographic and psychological factors, while qualitative content analysis was conducted to explore participant course enrollment motivations from their textual responses. The results indicated that entrepreneurial intention (EI) does not necessarily translate into EE MOOC completion. Instead, internal locus of control and socioeconomic factors held more priority in predicting completion status. These results were reflected in the students’ thematic narratives from their textual responses. Both completed (CP) and dropout participants (DP) expressed similar entrepreneurial interests and, indeed, in the transferability of entrepreneurial skills and knowledge beyond entrepreneurial settings. However, there was a distinction in clarity; most CPs had well-defined and detailed enrolment goals, whereas the narratives from DPs were mainly ambiguous. Overall, the study contributes to the methodological discussion of using decision tree modelling, expands the application of Social Cognitive Career Theory (SCCT) and informs practical implications in online EE context. [ABSTRACT FROM AUTHOR] |
| Copyright of Online Learning is the property of Online Learning Consortium and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 192942695 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Motivations Matter: Predicting Entrepreneurship Education MOOC Course Completion with a Decision Tree Approach. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Wei%2C+Chin+Jia%22">Wei, Chin Jia</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Shahmi%2C+Abdullah+Muhammad+Farhan%22">Shahmi, Abdullah Muhammad Farhan</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Qing%2C+Wah+Yue%22">Qing, Wah Yue</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Melati%2C+Nungsari%22">Melati, Nungsari</searchLink><relatesTo>2</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Online+Learning%22">Online Learning</searchLink>. Mar2026, Vol. 30 Issue 1, p294-322. 29p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22COVID-19+pandemic%22">COVID-19 pandemic</searchLink><br />*<searchLink fieldCode="DE" term="%22Retention+of+college+students%22">Retention of college students</searchLink><br />*<searchLink fieldCode="DE" term="%22Online+education%22">Online education</searchLink><br /><searchLink fieldCode="DE" term="%22Entrepreneurship+education%22">Entrepreneurship education</searchLink><br /><searchLink fieldCode="DE" term="%22Decision+trees%22">Decision trees</searchLink><br /><searchLink fieldCode="DE" term="%22Sociodemographic+factors%22">Sociodemographic factors</searchLink><br /><searchLink fieldCode="DE" term="%22Psychological+factors%22">Psychological factors</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Online entrepreneurship education (EE) courses experienced a sharp 66% spike in demand around March 2020, attributed to the COVID-19 pandemic and the subsequent surge in digital entrepreneurship uptake. Completion rates serve as a key indicator of online MOOC efficacy, with students’ psychological attributes and contextual factors often examined as explanatory variables in assessing online course completion. This mixed-methods study explores influential factors in student retention in an EE Massive Open Online Course (MOOC) by using survey responses from 222 Malaysian youths who voluntarily registered for an EE MOOC, which was active from February to October 2021. A Decision Tree approach was chosen to predict the course completion likelihood based on sociodemographic and psychological factors, while qualitative content analysis was conducted to explore participant course enrollment motivations from their textual responses. The results indicated that entrepreneurial intention (EI) does not necessarily translate into EE MOOC completion. Instead, internal locus of control and socioeconomic factors held more priority in predicting completion status. These results were reflected in the students’ thematic narratives from their textual responses. Both completed (CP) and dropout participants (DP) expressed similar entrepreneurial interests and, indeed, in the transferability of entrepreneurial skills and knowledge beyond entrepreneurial settings. However, there was a distinction in clarity; most CPs had well-defined and detailed enrolment goals, whereas the narratives from DPs were mainly ambiguous. Overall, the study contributes to the methodological discussion of using decision tree modelling, expands the application of Social Cognitive Career Theory (SCCT) and informs practical implications in online EE context. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Online Learning is the property of Online Learning Consortium and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.24059/olj.v30i1.4517 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 29 StartPage: 294 Subjects: – SubjectFull: COVID-19 pandemic Type: general – SubjectFull: Retention of college students Type: general – SubjectFull: Online education Type: general – SubjectFull: Entrepreneurship education Type: general – SubjectFull: Decision trees Type: general – SubjectFull: Sociodemographic factors Type: general – SubjectFull: Psychological factors Type: general Titles: – TitleFull: Motivations Matter: Predicting Entrepreneurship Education MOOC Course Completion with a Decision Tree Approach. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Wei, Chin Jia – PersonEntity: Name: NameFull: Shahmi, Abdullah Muhammad Farhan – PersonEntity: Name: NameFull: Qing, Wah Yue – PersonEntity: Name: NameFull: Melati, Nungsari IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 24725749 Numbering: – Type: volume Value: 30 – Type: issue Value: 1 Titles: – TitleFull: Online Learning Type: main |
| ResultId | 1 |
