Brown, Neil C. C., Altadmri, Amjad (2017) Novice Java Programming Mistakes: Large-Scale Data vs. Educator Beliefs. ACM Transactions on Computing Education (TOCE), 17 (2). Article Number 7. ISSN 1946-6226. (doi:10.1145/2994154) (KAR id:57219)
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Official URL: http://dx.doi.org/10.1145/2994154 |
Abstract
Teaching is the process of conveying knowledge and skills to learners. It involves preventing misunderstandings or correcting misconceptions that learners have acquired. Thus, effective teaching relies on solid knowledge of the discipline, but also a good grasp of where learners are likely to trip up or misunderstand. In programming, there is much opportunity for misunderstanding, and the penalties are harsh: failing to produce the correct syntax for a program, for example, can completely prevent any progress in learning how to program. Because programming is inherently computer-based, we have an opportunity to automatically observe programming behaviour -- more closely even than an educator in the room at the time. By observing students' programming behaviour, and surveying educators, we can ask: do educators have an accurate understanding of the mistakes that students are likely to make? In this study, we combined two years of the Blackbox dataset (with more than 900 thousand users and almost 100 million compilation events) with a survey of 76 educators to investigate which mistakes students make while learning to program Java, and whether the educators could make an accurate estimate of which mistakes were most common. We find that educators' estimates do not agree with one another or the student data, and discuss the implications of these results.
Item Type: | Article |
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DOI/Identification number: | 10.1145/2994154 |
Subjects: | Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing |
Depositing User: | Neil Brown |
Date Deposited: | 12 Sep 2016 10:16 UTC |
Last Modified: | 05 Nov 2024 10:47 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/57219 (The current URI for this page, for reference purposes) |
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