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Learning Analytics for end-users: from Human Centred Design to Multimodal Data Storytelling

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PDF slides available at https://www.solaresearch.org/wp-content/uploads/2021/10/SoLAR_Webinar13_October_2021.pdf Abstract: The ultimate aim of most Le...

Дата загрузки:2021-10-20T08:50:12+0000

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PDF slides available at https://www.solaresearch.org/wp-content/uploads/2021/10/SoLAR_Webinar13_October_2021.pdf

Abstract: The ultimate aim of most Learning Analytics innovations is to close the human-data loop by providing direct support to “end-users” (e.g., teachers and learners). However, presenting data to non-data savvy stakeholders is not a trivial problem. Trending topics in Learning
Analytics, such as adoption, ethics, privacy, explainability of algorithms, and the intensive promotion of the use of dashboards, emphasise the importance of the human factors and the particularities of educational situations in the successful appropriation of Learning Analytics. Yet, Learning Analytics researchers, designers and practitioners do not need to reinvent methods to deconstruct learner interactions or to create effective user interfaces. The community can more actively consider well established human-computer interaction (HCI) and human-centred design methods to, for example, give students a voice in the design process of data-intensive tools, craft dashboards based on data visualisation principles, and identify authentic needs before creating the next artificial intelligence (AI) solution to be rolled to teachers.

In this webinar, Dr Roberto Martínez-Maldonado provides a high-level overview of the rapidly growing interest in Human-Centred Learning Analytics and potential ways in which the R&D in this area can evolve in the next years. Work in this area is embryonic, with some researchers advocating rapid prototyping with teachers and interviewing students to understand their disciplinary perspectives on data. I will present some examples from our own research in the areas of multimodal learning analytics and data storytelling, emphasising some lessons learnt so far and potential areas of future research.
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