Automating the Detection of Reflection-on-Action

Abstract

Learning to solve complex problems — problems whose solutions require the application of more than basic facts and skills — is critical to meaningful participation in the economic, social, and cultural life of the digital age. In this paper, we use a theoretical understanding of how professionals use reflection-in-action to solve complex problems to investigate how students learn this critical 21st-century skill and how we can develop and automate learning analytic techniques to assess that learning. We present a preliminary study examining the automated detection of reflective discourse during collaborative, complex problem solving. We analyze student reflection-on-action in a virtual learning environment, focusing on both reflection in individual discourse and collaborative reflection among students. Our results suggest that it is possible to detect student reflection on complex problems in virtual learning environments, but that different models may be appropriate depending on students’ prior domain experience.