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Abstract
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| One of the main lines of research in the field of learning analytics fo-cuses on the identification of adequate data extracted from Learning Management Systems? (LMS) databases that may help predicting different behaviors and out-comes, such as academic achievement or student performance. Prior research has investigated these indicators at an individual level. The situation is more complex in collaborative settings involving teamwork, such as project-based learning, where student assessment considers the group as a single entity, disregard of in-dividual contributions to the team. Furthermore, most often only the final deliv-erable is taken into account when assessing teamwork in collaborative learning, leading to a loss of perspective about the whole process and whether or not team-work is effectively happening. This research aims to provide a comprehensive selection of log-based information from LMS databases that could serve as po-tential indicators to perform learning analytics and assess teamwork in online learning. The proposal of this novel and theory-grounded framework understands the multidimensional nature of teamwork, considers different sets of indicators for each of its dimensions?communication, cooperation, coordination, and mon-itoring and tracking?and incorporates the temporal dimension of activity data. This proposal sets the basis for future software development to effectively trans-form LMS log-based data and provide actionable measures of teamwork using learning analytics. | |
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International
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Si |
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Congress
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Learning Analytics Summer Institute Spain 2017 (LASI-SPAIN 2017) |
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960 |
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Place
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Madrid |
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Reviewers
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Si |
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ISBN/ISSN
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1613-0073 |
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Start Date
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04/07/2017 |
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End Date
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05/07/2017 |
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From page
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78 |
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To page
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92 |
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Proceedings of the Learning Analytics Summer Institute Spain 2017: Advances in Learning Analytics |