Automatic feedback, self-regulated learning and social comparison: a case study

Formative assessment is one of the main challenges facing MOOC research and practice. Providing timely and personalised feedback to large cohorts of learners poses issues in terms of scalability and sustainability. This paper puts forward a proposal for automated feedback well suited for assessing non-declarative knowledge. The proposed feedback strategy consists in displaying a comparison of responses and behaviors of individual participants with descriptive statistics reflecting the same data for the entire cohort. To investigate the self-reported usefulness and potential of this feedback strategy, quali-quantitative data were collected during a MOOC on learning design. While usefulness was statistically above the mid-point of the scale, no significant difference was found when considering the nature of the data (answers to surveys vs actions carried out) as an independent variable. Suggestions on how to improve this feedback strategy were also drawn from subjects' responses.