6 resultados para online courses

em Open University Netherlands


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Abstract The number of students engaged in Massive Open Online Courses (MOOCs) is increasing rapidly. Due to the autonomy of students in this type of education, students in MOOCs are required to regulate their learning to a greater extent than students in traditional, face-to-face education. However, there is no questionnaire available suited for this online context that measures all aspects of self-regulated learning (SRL). In this study, such a questionnaire is developed based on existing SRL questionnaires. This is the self-regulated online learning ques- tionnaire. Exploratory factor analysis (EFA) on the first dataset led to a set of scales differing from those theoretically defined beforehand. Confirmatory factor analysis (CFA) was conducted on a second dataset to compare the fit of the theoretical model and the exploratively obtained model. The exploratively obtained model provided much better fit to the data than the theoretical model. All models under investigation provided better fit when excluding the task strategies scale and when merging the scales measuring metacognitive activities. From the results of the EFA and the CFA it can be concluded that further development of the questionnaire is necessary.

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Wat is kenmerkend voor het design van Massive Open Online Courses (MOOCs)? Wat maakt ontwerpen van MOOCs bijzonder uitdagend maar ook bijzonder interessant? In de workshop over MOOC Ontwerp gaat u actief op zoek naar antwoorden aan de hand van ervaringen met het ontwerpen en uitleveren van MOOCs in twee Europese projecten: EMMA en ECO.

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The purpose of this article is to gain an insight into the effects of practicing short, frequent,and structured reflection breaks interspersed with the learning material in a computer-based course. To that end, the study sets up a standardized control trial with two groups of secondary school pupils. The study shows that while performance is not affected by these embedded “reflection rituals,” they significantly impact time on task and perceived learning. The study also suggests that the exposure to such built-in opportunities for reflection modifies the engagement with the content and fosters the claimed readiness for application of a similar reflective approach to learning in other occasions.

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Article is available at: http://www.tandfonline.com/doi/full/10.1080/17439884.2015.1064953.

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Nistor, N., Dascalu, M., Stavarache, L.L., Serafin, Y., & Trausan-Matu, S. (2015). Informal Learning in Online Knowledge Communities: Predicting Community Response to Visitor Inquiries. In G. Conole, T. Klobucar, C. Rensing, J. Konert & É. Lavoué (Eds.), 10th European Conf. on Technology Enhanced Learning (pp. 447–452). Toledo, Spain: Springer.

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Nistor, N., Dascalu, M., Stavarache, L.L., Tarnai, C., & Trausan-Matu, S. (2015). Predicting Newcomer Integration in Online Knowledge Communities by Automated Dialog Analysis. In Y. Li, M. Chang, M. Kravcik, E. Popescu, R. Huang, Kinshuk & N.-S. Chen (Eds.), State-of-the-Art and Future Directions of Smart Learning (Vol. Lecture Notes in Educational Technology, pp. 13–17). Berlin, Germany: Springer-Verlag Singapur