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Part of the book series: Studies in Computational Intelligence ((SCI,volume 408))

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Abstract

Teachers often use flow design patterns of particular learning strategies in order to define the type of the learning and supportive tasks, their duration, their orchestration as well as the use of learning objects, tool and services needed to support the execution of these tasks. It is quite easy for teachers (even novice learning designers) to create a learning script by applying a flow design pattern. However, they often need to mix and match learning strategies in order to create customized learning scripts that are more appropriate to the learners’ preferences and the learning context in general. This task is even more challenging when such adaptations need to be made on-the-fly, i.e. during the learning process and in response to the learner’ online behavior. The aim of this paper is to discuss how the learners’ interaction data that is collected during an online learning process and analyzed using interaction analysis indicators can be used by a teacher to alter the learning script on the fly. It is shown that with the aid of a learning interaction analysis tool, which is called CoSyLMSAnalytics, a teacher can modify a learning script that is based on a typical Think-Pair-Share strategy in order to offer scaffolds to the learners during the learning process. Also, an example will be shown that will depict how a learning designer can create a variation of a learning scenario that is based on a typical Think-Pair-Share strategy by using the tool referred above.

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Correspondence to Ourania Petropoulou .

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Petropoulou, O., Lazakidou, G., Georgiakakis, P., Retalis, S. (2012). Making Adaptations of CSCL Scripts by Analyzing Learners’ Online Behavior. In: Daradoumis, T., Demetriadis, S., Xhafa, F. (eds) Intelligent Adaptation and Personalization Techniques in Computer-Supported Collaborative Learning. Studies in Computational Intelligence, vol 408. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28586-8_8

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  • DOI: https://doi.org/10.1007/978-3-642-28586-8_8

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