Paraskevi Topali, Ruth Cobos, Unai Agirre-Uribarren, Alejandra Martínez-Monés, Sara Villagrá-Sobrino
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引用次数: 0
Abstract
Background
Personalised and timely feedback in massive open online courses (MOOCs) is hindered due to the large scale and diverse needs of learners. Learning analytics (LA) can support scalable interventions, however they often lack pedagogical and contextual grounding. Previous research claimed that a human-centred approach in the design of LA solutions can be beneficial. Yet, there is a scarcity of empirical studies discussing participatory approaches addressing LA for feedback in MOOCs.
Paper Objectives
We report a human-centred design, where an instructor and a tool developer employed a conceptual framework, named FeeD4Mi, to shape personalised LA-informed feedback in a MOOC.
Methods
The current study follows a qualitative interpretative approach to understand how the proposed conceptual framework FeeD4Mi served the MOOC instructor and the tool developer to design feedback interventions and re-design an existing LA tool, respectively.
Results and Conclusions
The results showed that FeeD4Mi helped the tool developer to create a contextualised LA tool, named edX-LIMS+. edX-LIMS+ allowed the instructor to monitor and assist struggling MOOC learners in a timely manner. Additionally, FeeD4Mi successfully guided the course instructor in designing and delivering personalised interventions. Yet, the feedback design process was perceived as time-demanding, an issue we plan to address in our future work.
Takeaways
The current study extends the existing empirical research about employing human-centred approaches for the design of LA-driven interventions. Moreover, this study advances the theory of scalable feedback tactics, through a conceptual framework that aims to guide MOOC instructors during the definition of feedback interventions. We envision that this research contributes to promoting participatory approaches for designing, delivering, and evaluating LA-informed feedback interventions in authentic contexts.
期刊介绍:
The Journal of Computer Assisted Learning is an international peer-reviewed journal which covers the whole range of uses of information and communication technology to support learning and knowledge exchange. It aims to provide a medium for communication among researchers as well as a channel linking researchers, practitioners, and policy makers. JCAL is also a rich source of material for master and PhD students in areas such as educational psychology, the learning sciences, instructional technology, instructional design, collaborative learning, intelligent learning systems, learning analytics, open, distance and networked learning, and educational evaluation and assessment. This is the case for formal (e.g., schools), non-formal (e.g., workplace learning) and informal learning (e.g., museums and libraries) situations and environments. Volumes often include one Special Issue which these provides readers with a broad and in-depth perspective on a specific topic. First published in 1985, JCAL continues to have the aim of making the outcomes of contemporary research and experience accessible. During this period there have been major technological advances offering new opportunities and approaches in the use of a wide range of technologies to support learning and knowledge transfer more generally. There is currently much emphasis on the use of network functionality and the challenges its appropriate uses pose to teachers/tutors working with students locally and at a distance. JCAL welcomes: -Empirical reports, single studies or programmatic series of studies on the use of computers and information technologies in learning and assessment -Critical and original meta-reviews of literature on the use of computers for learning -Empirical studies on the design and development of innovative technology-based systems for learning -Conceptual articles on issues relating to the Aims and Scope