A study of keystroke data in two contexts: written language and programming language influence predictability of learning outcomes
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Conference article in proceedings
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Date
2020-02-26
Major/Subject
Mcode
Degree programme
Language
en
Pages
7
413-419
413-419
Series
SIGCSE 2020 - Proceedings of the 51st ACM Technical Symposium on Computer Science Education, Annual Conference on Innovation and Technology in Computer Science Education
Abstract
We study programming process data from two introductory programming courses. Between the course contexts, the programming languages differ, the teaching approaches differ, and the spoken languages differ. In both courses, students' keystroke data timestamps and the pressed keys are recorded as students work on programming assignments.We study how the keystroke data differs between the contexts, and whether research on predicting course outcomes using keystroke latencies generalizes to other contexts. Our results show that there are differences between the contexts in terms of frequently used keys, which can be partially explained by the differences between the spoken languages and the programming languages. Further, our results suggest that programming process data that can be collected non-intrusive in-situ can be used for predicting course outcomes in multiple contexts. The predictive power, however, varies between contexts possibly because the frequently used keys differ between programming languages and spoken languages. Thus, context-specific fine-tuning of predictive models may be needed.Description
Keywords
Digraphs, Educational data mining, Keystroke analysis, Keystroke data, Predicting performance, Programming process data
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Citation
Edwards , J , Leinonen , J & Hellas , A 2020 , A study of keystroke data in two contexts: written language and programming language influence predictability of learning outcomes . in SIGCSE 2020 - Proceedings of the 51st ACM Technical Symposium on Computer Science Education . Annual Conference on Innovation and Technology in Computer Science Education , ACM , pp. 413-419 , ACM Technical Symposium on Computer Science Education , Portland , Oregon , United States , 11/03/2020 . https://doi.org/10.1145/3328778.3366863
