Recommendations for Orchestration of Formative Assessment Sequences: A Data-Driven Approach

Formative assessment aims to improve teaching and learning by providing teachers students with feedback designed help them adapt their behavior. To face the increasing number of in higher education support this kind activity, technology-enhanced formative tools emerged. These generate data that can serve as a basis for improving processes services they provide. Based on literature using dataset gathered from use tool whose process, inspired Mazur’s Peer Instruction, consists asking learners answer question before after confrontation peers, we analytics provide evidence-based knowledge about practices. Our results suggest that: (1) Benefits sequences increase when proportion correct answers is close 50% during first vote; (2) learners’ rationales are better rated than incorrect ones; (3) ratings consistent more confident (4) Self-rating inconsistent peer rating context; (5) The amount makes no significant difference terms benefits. these results, recommendations discussed data-informed process inferred.