Student Responses to Computing Exam Questions with Model Answers and Rubrics

A dataset of student responses to structured examination questions for the COS101: Introduction to Computing course at FUHSO, Nigeria, collected for the 2025/2026 academic year. The data, created by TEMIDAYO OMOTEHINWA, was used to develop an AI-driven short-answer grading system that combines semantic similarity with rubric-based evaluation. It includes student answers paired with model answers and mark allocations.

Use Cases

• Training automated grading models based on the described rubric coverage and semantic alignment features.
• Evaluating the performance of NLP models for semantic similarity between student and reference answers.
• Developing interpretable feedback systems based on the identification of covered, partially addressed, and missing concepts.
• Benchmarking computational efficiency and consistency of AI grading systems as mentioned in the description.

Strengths

• Dataset is openly licensed under CC-BY-4.0, facilitating reuse and modification.
• The description details a specific methodological application for AI-driven grading, providing context for the data's intended use.
• Data is stored in a widely accessible XLSX format with a file size of 76.6 KB, indicating a manageable download.

Limitations

• Row count is unknown, which may limit suitability assessment for model training.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is small (76.6 KB), indicating a limited scope of responses.

Provenance

Source

figshare

Collection Method

Collected student responses to structured examination questions and paired with model answers and mark allocations.

Time Range

2025/2026 academic year

Freshness

Last updated 2026-04-28 03:37:51; freshness should be verified.

Geography

FUHSO, Nigeria