Software Engineering Teamwork Assessment Data for Education

UCI Machine Learning Repository provides a dataset for assessing software engineering teamwork in an educational context. The dataset's specific size and creation date are not provided. It is categorized under Student Performance, Software Engineering, and Education Research tags.

Use Cases

• Predict final team performance scores from individual contribution metrics and peer assessment data.
• Analyze correlations between specific teamwork behaviors, like communication frequency, and project completion grades.
• Cluster student teams based on feature sets like task distribution, meeting attendance, or code commit patterns to identify common collaboration styles.
• Train classifiers to identify at-risk teams early in a semester using features from initial project milestones and peer reviews.

Strengths

• Sourced from the UCI Machine Learning Repository, a recognized source for benchmark datasets.
• Focuses on a specific, high-value domain for educational data mining and learning analytics.

Limitations

• Unknown row count and column count prevent assessment of statistical power.
• Unknown temporal coverage and lack of recency information limit analysis of trends over time.

Provenance

Source

UCI Machine Learning Repository