Utilizing the Constrained K-Means Algorithm and Pre-Class GitHub Contribution Statistics for Forming Student Teams-Reference-Cited by-同舟云学术

Utilizing the Constrained K-Means Algorithm and Pre-Class GitHub Contribution Statistics for Forming Student Teams

Published:2024-07-03 Issue: Volume:19 Page:569-575
ISSN:
Container-title:Proceedings of the 2024 on Innovation and Technology in Computer Science Education V. 1
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Author:

Cui Jialin¹^ORCID,Zhou Fangtong¹^ORCID,Liu Chengyuan¹^ORCID,Jia Qinjin¹^ORCID,Song Yang²^ORCID,Gehringer Edward¹^ORCID

Affiliation:

1. North Carolina State University, Raleigh, NC, USA

2. University of North Carolina Wilmington, Wilmington, NC, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3649217.3653634

Reference43 articles.

1. Mahreen Ahmad Wasi Haider Butt and Abrar Ahmad. 2019. Advance Recommendation System for the Formation of More Prolific and Dynamic Software Project Teams. In 2019 IEEE 10th International Conference on Software Engineering and Service Science (ICSESS). 161--165. https://doi.org/10.1109/ICSESS47205.2019.9040791

2. Improving formation of student teams

3. Formal model for assigning human resources to teams in software projects

4. K.P. Bennett, P.S. Bradley, and A. Demiriz. 2000. Constrained K-Means Clustering. Technical Report MSR-TR-2000--65. 8 pages. https://www.microsoft.com/enus/ research/publication/constrained-k-means-clustering/

5. Picking the right project: Assigning student teams in a GSD course

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