Using Signals for appropriate feedback: Perceptions and practices

Feedback is a crucial form of information for learners. With the availability of new educational technologies, the manner in which feedback is delivered has changed tremendously. Existing research on the learning outcomes of the content and nature of computer mediated feedback is limited and contradictory. Signals is an educational data-mining technology for student success where instructors can send students elaborate feedback. Hence, this paper examines the content and nature dimensions of feedback in Signals with two studies. Study one identifies how the instructors who used this technology define its feedback function. Study two identifies the types of feedback that were included in the messages sent to students. Both studies employ content analysis method; study one examines the transcripts of interviews with instructors, and study two examines the feedback messages composed by instructors. Results indicate that while instructors perceive Signals as a tool to primarily provide motivational and summative feedback, student success was related to the type, and performance or outcome orientation of both summative and formative feedback students received. The results and implications of both studies are further discussed and future directions are proposed.

► Study 1 examined how instructors define the content and nature of feedback in Signals with content analysis. ► Although formative feedback yields better learning experiences and outcomes, instructors focused on summative feedback. ► Study 2 examined the content and nature of feedback students received via Signals messages and their relation with success. ► Instructors should focus on type of rather than frequency of feedback, and send explicit and instructional feedback. ► Discrepancy between perception and application suggests a feedback message guideline or an inclusive message library.