Understanding and Supporting Peer Feedback at Massive Learning Scale
BACKGROUND AND RESEARCH GOALS
Not every individual accessing MOOCs equally benefits from them. In particular, learners, who have limited or no background on a topic that they are enthusiastic to learn about, often struggle to master the concepts, submit assignments, and complete the course. The dropout of such students is inevitable particularly given the limited instructor guidance. In MOOCs, it is not feasible for instructors to monitor every student and provide formative feedback tailored to their unique needs. As a result, many MOOC learners who are at risk of dropping out miss the opportunity of receiving feedback on their work to improve their learning and performance. Thus, feedback, which is imperative to learning, is troublesome in MOOCs, and it needs to be addressed so that every learner can maximally benefit from MOOC education.
Attending to this gap, this project aims to advance the understanding of feedback phenomenon at massive learning scale and improve the current MOOC practice in this regard by enabling the provision of timely, constructive, personalized peer feedback. This research aims to:
- generate design guidelines for effective feedback exchange among MOOC learners, and
- use these guidelines to build an adaptive, crowdsourced peer-feedback system called WeLearn@Scale (WL@S).
This project is funding by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 793317. The research fellow in this project is Erkan Er, who is supervised by Yannis Dimitriadis (Universidad de Valladolid) and co-supervised by Dragan Gasevic (Monash University). Senior researchers of GSIC-EMIC (Eduardo Gómez Sánchez, Miguel Luis Bote Lorenzo, and Juan Ignacio Asensio Pérez) are also involved in the project.