The effects of open self-explanation prompting during source code comprehension


This paper reports the findings of an empirical study on the effects and nature of self explanation during source code comprehension learning activities in the context of learning computer programming language Java. Our study shows that self explanation helps learning and there is a strong positive correlation between the volume of self-explanation students produce and how much they learn. Furthermore, selfexplanations as an instructional strategy has no discrepancy based on student's prior knowledge. We found that participants explain target code examples using a combination of language, code references, and mathematical expressions. This is not surprising given the nature of the target item, a computer program, but this indicates that automatically evaluating such self-explanations may require novel techniques compared to self-explanations of narrative or scientific texts.

Publication Title

Proceedings of the 33rd International Florida Artificial Intelligence Research Society Conference, FLAIRS 2020

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