RT info:eu-repo/semantics/article
T1 e-FeeD4Mi: human-centred design of personalised and contextualised feedback in MOOCs
A1 Topali, Paraskevi
A1 Ortega-Arranz, Alejandro
A1 Asensio Pérez, Juan Ignacio
A1 Villagrá Sobrino, Sara Lorena
A1 Martínez Monés, Alejandra
A1 Dimitriadis Damoulis, Ioannis
K1 Human-centred learning analytics
K1 personalised feedback
K1 teacher-led interventions
K1 MOOCs
AB Personalised feedback in MOOCs is often prevented by the non-scalability of traditional approaches and the lack of pedagogical grounding of the current learning analytics (LA) solutions. One way to tackle such limitations is the adoption of a participatory approach through the active positioning of MOOC instructors in the design and development of LA solutions. Nonetheless, there is a scarcity of empirical proposals supporting these approaches in MOOCs. To that end, the current paper presents e-FeeD4Mi, a web-based tool, incorporating a set of catalogues, recommendations and a process, that aim to support instructors in the design of human-centred LA-informed feedback. We conducted an evaluative study with 6 MOOC instructors who employed the tool into their course designs to assess e-FeeD4Mi usefulness, usability and associated workload. The evidence gathered permitted us to understand how e-FeeD4Mi support the design of human-centred LA-based feedback in MOOCs. Altogether, the results showed a good usability and participants' satisfaction regarding the use of the tool for shaping personalised feedback. At the same time, participants offered ideas for further tool enrichment. This study expands upon the current body of empirical research on the human-centred approaches in the design of LA-driven interventions in MOOCs.
PB Taylor & Francis
SN 1362-3001
YR 2024
FD 2024
LK https://uvadoc.uva.es/handle/10324/74152
UL https://uvadoc.uva.es/handle/10324/74152
LA eng
NO Behaviour & Information Technology, Julio 2024, p. 1-18
NO Producción Científica
DS UVaDOC
RD 22-ene-2025