RT info:eu-repo/semantics/article
T1 Delving into instructor‐led feedback interventions informed by learning analytics in massive open online courses
A1 Topali, Paraskevi
A1 Chounta, Irene Angelica
A1 Martínez Monés, Alejandra
A1 Dimitriadis Damoulis, Ioannis
K1 Distance education
K1 Online learning
K1 Feedback interventions
K1 Learning analytics
K1 MOOCs
K1 58 Pedagogía
K1 33 Ciencias Tecnológicas
K1 1203.17 Informática
AB Background:Providing feedback in massive open online courses (MOOCs) is chal-lenging due to the massiveness and heterogeneity of learners' population. Learninganalytics (LA) solutions aim at scaling up feedback interventions and supportinginstructors in this endeavour.Paper Objectives:This paper focuses on instructor-led feedback mediated by LAtools in MOOCs. Our goal is to answer how, to what extent data-driven feedback isprovided to learners, and what its impact is.Methods:We conducted a systematic literature review on the state-of-the-art LA-informed instructor-led feedback in MOOCs. From a pool of 227 publications, weselected 38 articles that address the topic of LA-informed feedback in MOOCs medi-ated by instructors. We applied etic content analysis to the collected data.Results and Conclusions:The results revealed a lack of empirical studies exploring LA todeliver feedback, and limited attention on pedagogy to inform feedback practices. Our find-ings suggest the need for systematization and evaluation of feedback. Additionally, there isa need for conceptual tools to guide instructors' in the design of LA-based feedback.Takeaways:We point out the need for systematization and evaluation of feedback. Weenvision that this research can support the design of LA-based feedback, thus contribut-ing to bridge the gap between pedagogy and data-driven practice in MOOCs.
PB Wiley
SN 0266-4909
YR 2023
FD 2023
LK https://uvadoc.uva.es/handle/10324/59003
UL https://uvadoc.uva.es/handle/10324/59003
LA eng
NO Journal of Computer Assisted Learning, 2023.
NO Producción Científica
DS UVaDOC
RD 18-nov-2024