Towards Attention-Based Automatic Misconception Identification in Introductory Programming Courses
Author:
Affiliation:
1. North Carolina State University, Raleigh, NC, USA
2. University of California Berkeley, Berkeley, CA, USA
Funder
NSF (National Science Foundation)
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3626253.3635575
Reference8 articles.
1. Bita Akram, Wookhe Min, Eric Wiebe, Anam Navied, Bradford Mott, Kristy Elizabeth Boyer, and James Lester. 2020. Automated assessment of computer science competencies from student programs with gaussian process regression. In EDM'20.
2. Sometimes It's Just Sloppiness - Studying Students' Programming Errors and Misconceptions
3. Myse Elmadani Moffat Mathews and Antonija Mitrovic. 2012. Data-driven misconception discovery in constraint-based intelligent tutoring systems. (2012).
4. Common logic errors made by novice programmers
5. A Data-Driven Technique for Misconception Elicitation
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