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Prediction versus Production for Teaching Computer Programming

Abstract

Learning to program is increasingly important. Yet, it is becoming clear that most students struggle when learning to program (McCracken et al., 2001). This is leading to a divide where some people can program but many others can’t. Prior research has traced poor student outcomes to their early experiences learning programming. Still, little is known about how different programming tasks might impact the processes involved in learning programming. In this dissertation, I extend prior research on students’ experiences when learning computer programming and build on this research by testing the causal influences of different learning tasks on students’ emotions, motivation, and learning. In a randomized experiment, I manipulated the instructional tasks used to introduce programming and investigated students’ emotional trajectories, motivation, and learning outcomes. Participants randomly assigned to predict the outcome of pre-provided code showed more positive emotional trajectories, increased motivation, and greater learning compared to students randomly assigned to modify or produce their own code.

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