Analyzing productive learning behaviors for students using immediate corrective feedback in a blended learning environment

Abstract

Undergraduate classes in many science and engineering courses are utilizing asynchronous computer platforms to host educational materials such as lecture videos or discussion forums. These platforms also have the ability to provide immediate feedback to students on formative assessment tasks such as homework problems, reading questions, or weekly quizzes. Although there have been a number of studies on computer-based feedback, there is more we need to know about how students interact with immediate feedback, and how those interactions influence their learning. In this study, we characterize introductory physics students' interactions with one computer-based immediate simple corrective feedback tool, the “checkable answer feature” (CAF), powered by the institutional version of the edX platform. We investigate how much students interact with the CAF, the patterns of interaction, and, ultimately, how these patterns are associated with course performance. We utilize rich quantitative data, including a large volume of server tracking logs that show students’ use the CAF, as well as performance metrics. Our findings show certain patterns of engagement with feedback reflect productive study strategies and significantly predict higher performance. The findings provide guidance for instructional practice and the continued development of online feedback tools in introductory STEM courses.