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- Publisher Website: 10.1111/jcal.12427
- Scopus: eid_2-s2.0-85080142582
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Article: Computational thinking and assignment resubmission predict persistence in a computer science MOOC
Title | Computational thinking and assignment resubmission predict persistence in a computer science MOOC |
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Authors | |
Issue Date | 2020 |
Citation | Journal of Computer Assisted Learning, 2020, v. 36, n. 5, p. 581-594 How to Cite? |
Abstract | Massive open online course (MOOC) studies have shown that precourse skills (such as precomputational thinking) and course engagement measures (such as making multiple submission attempts with assignments when the initial submission is incorrect) predict students' grade performance, yet little is known about whether these factors predict students' course retention. In applying survival analysis to a sample of more than 20,000 participants from one popular computer science MOOC, we found that students' precomputational thinking skills and their perseverance in assignment submission strongly predict their persistence in the MOOC. Moreover, we discovered that precomputational thinking skills, programming experience, and gender, which were previously considered to be constant predictors of students' retention, have effects that attenuate over the course milestones. This finding suggests that MOOC educators should take a growth perspective towards students' persistence: As students overcome the initial hurdles, their resilience grows stronger. |
Persistent Identifier | http://hdl.handle.net/10722/316539 |
ISSN | 2023 Impact Factor: 5.1 2023 SCImago Journal Rankings: 1.842 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Chen, Chen | - |
dc.contributor.author | Sonnert, Gerhard | - |
dc.contributor.author | Sadler, Philip M. | - |
dc.contributor.author | Malan, David J. | - |
dc.date.accessioned | 2022-09-14T11:40:42Z | - |
dc.date.available | 2022-09-14T11:40:42Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Journal of Computer Assisted Learning, 2020, v. 36, n. 5, p. 581-594 | - |
dc.identifier.issn | 0266-4909 | - |
dc.identifier.uri | http://hdl.handle.net/10722/316539 | - |
dc.description.abstract | Massive open online course (MOOC) studies have shown that precourse skills (such as precomputational thinking) and course engagement measures (such as making multiple submission attempts with assignments when the initial submission is incorrect) predict students' grade performance, yet little is known about whether these factors predict students' course retention. In applying survival analysis to a sample of more than 20,000 participants from one popular computer science MOOC, we found that students' precomputational thinking skills and their perseverance in assignment submission strongly predict their persistence in the MOOC. Moreover, we discovered that precomputational thinking skills, programming experience, and gender, which were previously considered to be constant predictors of students' retention, have effects that attenuate over the course milestones. This finding suggests that MOOC educators should take a growth perspective towards students' persistence: As students overcome the initial hurdles, their resilience grows stronger. | - |
dc.language | eng | - |
dc.relation.ispartof | Journal of Computer Assisted Learning | - |
dc.title | Computational thinking and assignment resubmission predict persistence in a computer science MOOC | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1111/jcal.12427 | - |
dc.identifier.scopus | eid_2-s2.0-85080142582 | - |
dc.identifier.volume | 36 | - |
dc.identifier.issue | 5 | - |
dc.identifier.spage | 581 | - |
dc.identifier.epage | 594 | - |
dc.identifier.eissn | 1365-2729 | - |
dc.identifier.isi | WOS:000516762600001 | - |