PICA: A Data-driven Synthesis of Peer Instruction and Continuous Assessment
Steve Geinitz

TL;DR
This paper introduces PICA, a novel data-driven method combining Peer Instruction and Continuous Assessment to enhance student engagement, communication, and collaborative learning, with promising but mixed quantitative and qualitative results.
Contribution
It presents a new approach to pairing students for collaborative learning based on recent assessment data, aiming to improve engagement and communication.
Findings
Improved assessment scores on PI CA tasks.
High student engagement and positive perceptions.
Broader peer interactions observed.
Abstract
Peer Instruction (PI) and Continuous Assessment(CA) are two distinct educational techniques with extensive research demonstrating their effectiveness. The work herein combines PI and CA in a deliberate and novel manner to pair students together for a PI session in which they collaborate on a CA task. The data used to inform the pairing method is restricted to the most previous CA task students completed independently. The motivation for this data-driven collaborative learning is to improve student learning, communication, and engagement. Quantitative results from an investigation of the method show improved assessment scores on the PI CA tasks, although evidence of a positive effect on subsequent individual CA tasks was not statistically significant as anticipated. However, student perceptions were positive, engagement was high, and students interacted with a broader set of peers than…
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Taxonomy
TopicsEducational Assessment and Pedagogy · Intelligent Tutoring Systems and Adaptive Learning · Online Learning and Analytics
