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Please use this identifier to cite or link to this item: http://hdl.handle.net/1820/5459
Title: Where is my time? Identifying productive time of lifelong learners for effective feedback services
Authors: Tabuenca, Bernardo
Kalz, Marco
Börner, Dirk
Ternier, Stefaan
Specht, Marcus
Keywords: lifelong learning
experience sampling method
mobile learning
self-regulated learning
reflection
Issue Date: 30-Jul-2014
Citation: Tabuenca, B., Kalz, M., Börner, D., Ternier, S., & Specht, M. (2014). Where is my time? Identifying productive time of lifelong learners for effective feedback services. In M. Kalz & E. Ras (Eds.), Computer Assisted Assessment -- Research into E-Assessment. Proceedings of the 17th International Conference on Computer Assisted Assessment. Vol. 439 (pp. 149–161). Zeist, The Netherlands: Springer.
Abstract: Lifelong learners are confronted with a broad range of activities they have to manage every day. In most cases they have to combine learning, working, family life and leisure activities throughout the day. Hence, learning activities from lifelong learners are disrupted. The difficulty to find a suitable time slot to learn during the day has been identified as the most frequent cause. In this scenario mobile technologies play an important role since they can keep track of the most suitable moments to accomplish specific learning activities in context. Sampling of learning preferences on mobile devices are key benchmarks for lifelong learners to become aware on which learning task suits in which context, set realistic goals and set aside time to learn on a regular basis. The contribution of this manuscript is twofold: first, a classification framework for modelling lifelong learners’ preferences is presented based on a literature review; second, a mobile application for experience sampling is piloted aiming to identify which are the preferences from lifelong learners regarding when, how and where learning activities can be integrated. Both framework and pilot provide an important scaffold for lifelong learners to identify productive times during the day with mobile technologies.
URI: http://hdl.handle.net/1820/5459
ISBN: 978-3-319-08656-9
ISSN: 1865-0929
Appears in Collections:1. TELI Publications, books and conference papers

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