Learning programming online: Influences of various types of feedback on programming performances

Abstract

This article draws on a one-semester online programming course to determine the relationships between the types of feedback that students received and their programming performances. An explorative study was designed including both quantitative and qualitative data. Participants were 15 second-year students enrolled at an Information Technology department of a public university who received weekly programming problems as projects. The instructor provided various types of feedback (corrective, confirmatory, explanatory, diagnostic and expanded feedback) to the students via Github. The results showed that; when the students who received corrective and explanatory feedback more, the programming performance scores were high. A strong positive relationship existed between a total amount of feedback with programming performance scores, also a number of times that students received explanatory feedback and programming performance scores. In addition, while the positive correlations existed between programming performance scores and the amount of all types of feedback, there was a weak correlation between the number of times that students received expanded feedback and programming performance scores. The difficulty of the programming projects, the needs of the participants and the affordances of the online learning environment played key role in the students’ preference for receiving feedback type. Recommendations for future research and practice are included.