Combining latent profile analysis and programming traces to understand novices’ differences in debugging
Combining latent profile analysis and programming traces to understand novices’ differences in debugging
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结合潜在的配置文件分析和编程跟踪来了解新手在调试中的差异
DOI:
10.1007/s10639-022-11343-7
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发表时间:
2022
影响因子:
5.5
通讯作者:
Fan, Aysa Xuemo
中科院分区:
文献类型:
--
作者:
Zhang, Yingbin;Paquette, Luc;Pinto, Juan D.;Liu, Qianhui;Fan, Aysa Xuemo
It is widely recognized that debugging is challenging for novice programmers and, as such, computing educators and researchers have called for explicit debugging instruction. Debugging requires various knowledge and skills, and different students may show different strengths and weaknesses. An understanding of such individual differences is important as it may guide personalized instruction. The current study investigated individual differences in debugging in an undergraduate introductory computer science course. We extracted variables related to debugging from students’ submission traces to programming problems in the first month of the course. We applied latent profile analysis to these variables and identified three distinctive profiles. Profile A showed higher debugging accuracy and speed. Profile B showed lower debugging performance in runtime and logic errors, while profile C had lower performance in syntactic errors and tended to make large code edit every submission. Students’ gender and self-rated programming ability predicted profile membership. Moreover, profile A got higher scores than the others in the first exam, and this difference persisted in the second and third exam, even controlling for background variables and score on the first exam. We investigated how students transitioned across debugging profiles over the duration of the course. From the beginning to the end of the course, a large part of students stayed in lower performance profiles. Overall, these findings support the call that debugging should be taught at an early stage and suggest that different groups may need different debugging instructions or support.
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影响因子:
22.7
作者:
D. Spinellis
通讯作者:
D. Spinellis
DOI:
10.1007/978-3-319-26633-6_12
发表时间:
2016-01-01
期刊:
MODERN STATISTICAL METHODS FOR HCI
影响因子:
--
作者:
Oberski, Daniel
通讯作者:
Oberski, Daniel
DOI:
--
发表时间:
2017
期刊:
Education and Information Technologies : Official Journal of the IFIP technical committee on Education
影响因子:
--
作者:
S. I. Malik;Jo Coldwell
通讯作者:
Jo Coldwell
DOI:
--
发表时间:
2005
期刊:
Advances in the designing of classroom teaching : Bridging theories and practice (Mayumi Takagaki (ed.))(Kyoto : Kitaohjishobo)
影响因子:
--
作者:
Maruno;Shunichi
通讯作者:
Shunichi
影响因子:
2.6
作者:
Lin, Yu-Tzu;Wu, Cheng-Chih;Chang, Chia-Hu
通讯作者:
Chang, Chia-Hu