Brian Lukoff

Catalyzing learner engagement using cutting-edge classroom response systems in higher education

In this chapter, we introduce a new technology for facilitating and measuring learner engagement. The system creates a learning experience for students based on frequent feedback, which is critical to learning. We open by problematizing traditional approaches to learner engagement that do not maximize the potential of feedback and offer a research-based solution in a new classroom response system (CRS) two of the authors developed at Harvard University – Learning Catalytics. The chapter includes an overview of cognitive science principles linked to student learning and how those principles are tied to Learning Catalytics. We then provide an overview of the limitations of existing CRSs and describe how Learning Catalytics addresses those limitations. Finally, we describe how we used Learning Catalytics to facilitate and measure learner engagement in novel ways, through a pilot implementation in an undergraduate physics classroom at Harvard University. This pilot was guided by two questions: How can we use Learning Catalytics to help students engage with subject matter in ways that will help them learn? And how can we measure student engagement in new ways using the analytics built into the system? The objective of this chapter is to introduce Learning Catalytics as a new instructional tool and respond to these questions.

Use of a Social Annotation Platform for Pre-Class Reading Assignments in a Flipped Introductory Physics Class

In this paper, we illustrate the successful implementation of pre-class reading assignments through a social learning platform that allows students to discuss the reading online with their classmates. We show how the platform can be used to understand how students are reading before class. We find that, with this platform, students spend an above average amount of time reading (compared to that reported in the literature) and that most students complete their reading assignments before class. We identify specific reading behaviors that are predictive of in-class exam performance. We also demonstrate ways that the platform promotes active reading strategies and produces high-quality learning interactions between students outside class. Finally, we compare the exam performance of two cohorts of students, where the only difference between them is the use of the platform; we show that students do significantly better on exams when using the platform.