Student Assessment Data for Problem-Based Learning Curriculum Evaluation

A real-life case study involving 24 students evaluated by multiple stakeholder groups, including peer teams, instructors, and industry experts. The data-driven framework integrates Multi-Criteria Group Decision Making and Z-number theory to capture uncertainty in expert evaluations. Authored by Limin Yu and last updated on 2026-05-18, this 5.5 KB Excel file is shared under a CC-BY-4.0 license.

Use Cases

• Benchmarking student performance based on multi-stakeholder evaluations described in the study
• Testing the robustness of ranking algorithms using the described Z-number modeling for uncertainty
• Developing weighting schemes for evaluation criteria based on the hybrid Entropy-CRITIC method mentioned
• Comparing assessment outcomes across different stakeholder groups (peers, instructors, experts) as outlined in the framework

Strengths

• Includes data from a real-life case study with 24 students, providing a concrete application context
• Applies a novel framework integrating Z-number theory and the MABAC method, as detailed in the description
• Employs a multi-stage assessment process (Pass check, Score determination, Grading) aligned with PBL pedagogical principles

Limitations

• Row count is unknown, which may limit suitability assessment for large-scale modeling
• Column-level documentation is absent; field semantics must be inferred after download
• The dataset's 5.5 KB size indicates a very limited scope, likely containing only summary or example data

Provenance

Source

figshare

Collection Method

Applied as a case study within a proposed educational assessment framework, involving evaluations from peer teams, instructors, and industry experts.

Freshness

Last updated 2026-05-18 17:41:01; freshness should be verified