Learning analytics of CS0 students programming errors
Author:
Affiliation:
1. National Research University, Russia
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3377290.3377319
Reference19 articles.
1. Phillip Ackerman Ruth Kanfer and Charles Calderwood. 2013. High School Advanced Placement and Student Performance in College: STEM Majors Non-STEM Majors and Gender Differences. Teachers College Record 115 (10 2013). Phillip Ackerman Ruth Kanfer and Charles Calderwood. 2013. High School Advanced Placement and Student Performance in College: STEM Majors Non-STEM Majors and Gender Differences. Teachers College Record 115 (10 2013).
2. Norazlina Ahmad Zaidatun Tasir Jamri Kasim and Harun Sahat. 2013. Automatic Detection of Learning Styles in Learning Management Systems by Using Literature-based Method. Procedia - Social and Behavioral Sciences 103 (Nov. 2013) 181--189. 10.1016/j.sbspro.2013.10.324 Norazlina Ahmad Zaidatun Tasir Jamri Kasim and Harun Sahat. 2013. Automatic Detection of Learning Styles in Learning Management Systems by Using Literature-based Method. Procedia - Social and Behavioral Sciences 103 (Nov. 2013) 181--189. 10.1016/j.sbspro.2013.10.324
3. An Effective Approach to Enhancing Compiler Error Messages
4. Exploring online students’ self-regulated learning with self-reported surveys and log files: a data mining approach
5. Finding traces of self-regulated learning in activity streams
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