Self-inductance Learning Strategies Predict Learner Behavior and Goal Attainment in Massive Open Online Courses
| Autor: | Jorge J. Maldonado, Mar Pérez-Sanagustín, René F. Kizilcec |
|---|---|
| Přispěvatelé: | Stanford University, Service IntEgration and netwoRk Administration (IRIT-SIERA), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Pontificia Universidad Católica de Chile (UC), Universidad de Cuenca (UCUENCA) |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Knowledge management
General Computer Science Process (engineering) Computer science MOOCs Control (management) Massive open online course Learning analytics 050109 social psychology Education Self-regulated learning Mathematics education ComputingMilieux_COMPUTERSANDEDUCATION 0501 psychology and cognitive sciences [INFO]Computer Science [cs] Goal setting Strategic planning Individual Differences business.industry 05 social sciences 050301 education Help-seeking Learning Analytics Massive Open Online Course Online Learning Online learning business 0503 education Self-Regulated Learning |
| Zdroj: | Computers and Education Computers and Education, Elsevier, 2017, 104, pp.18--33. ⟨10.1016/j.compedu.2016.10.001⟩ Repositorio Universidad de Cuenca Universidad de Cuenca instacron:UCUENCA |
| ISSN: | 0360-1315 |
| DOI: | 10.1016/j.compedu.2016.10.001⟩ |
| Popis: | Individuals with strong self-regulated learning (SRL) skills, characterized by the ability to plan, manage and control their learning process, can learn faster and outperform those with weaker SRL skills. SRL is critical in learning environments that provide low levels of support and guidance, as is commonly the case in Massive Open Online Courses (MOOCs). Learners can be trained to engage in SRL and actively supported with prompts and activities. However, effective implementation of learner support systems in MOOCs requires an understanding of which SRL strategies are most effective and how these strategies manifest in online behavior. Moreover, identifying learner characteristics that are predictive of weaker SRL skills can advance efforts to provide targeted support without obtrusive survey instruments. We investigated SRL in a sample of 4,831 learners across six MOOCs based on individual records of overall course achievement, interactions with course content, and survey responses. We found that goal setting and strategic planning predicted attainment of personal course goals, while help seeking was associated with lower goal attainment. Learners with stronger SRL skills were more likely to revisit previously studied course materials, especially course assessments. Several learner characteristics, including demographics and motivation, predicted learners' SRL skills. We discuss implications for theory and the development of learning environments that provide adaptive support. Goal setting and strategic planning positively predict goal attainment in MOOCs.Help seeking negatively predicts goal attainment, e.g., earning a certificate.Self-reported SRL strategies manifest behaviorally in revisiting course content.Learner characteristics (demographics, motivation, etc.) predict self-reported SRL. |
| Databáze: | OpenAIRE |
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