Programming: predicting student success early in CS1. a re-validation and replication study

Author:

Quille Keith1,Bergin Susan2

Affiliation:

1. Institute of Technology Tallaght, Ireland / Maynooth University, Ireland

2. Maynooth University, Ireland

Publisher

ACM

Reference43 articles.

1. Exploring Machine Learning Methods to Automatically Identify Students in Need of Assistance

2. A predictor for success in an introductory programming class based upon abstract reasoning development

3. Using machine learning techniques to predict introductory programming performance;Bergin S.;International Journal of Computer Science and Software Engineering,2015

4. Programming

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1. From Visual Arts to Programming: Exploring the Impact on Achievement in Constructionist College CS1 Classes;Proceedings of the 2024 on Innovation and Technology in Computer Science Education V. 1;2024-07-03

2. Assessment of a Predictive Model for Academic Performance in a Small-Sized Programming Course;2024 International Symposium on Computers in Education (SIIE);2024-06-19

3. Computer programmers show distinct, expertise-dependent brain responses to violations in form and meaning when reading code;Scientific Reports;2024-03-05

4. Reproducing Predictive Learning Analytics in CS1;Journal of Learning Analytics;2024-01-26

5. Multi-Institutional Multi-National Studies of Parsons Problems;Proceedings of the 2023 Working Group Reports on Innovation and Technology in Computer Science Education;2023-12-22

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