Supplementary material for the article "Comparing a LEGO® Serious Play Activity With a Tra

Data from 227 software engineering students, with 110 in a control group and 117 in an experimental group, collected for a study comparing a LEGO Serious Play activity to a traditional lecture. The dataset contains pre-test and post-test scores, calculated learning gain for each student, and results from a 9-item perceptions questionnaire. Daniel López Fernández authored the dataset, which was last updated on October 14, 2025.

Use Cases

• Compare learning outcomes between experimental and control teaching methods based on pre-test and post-test scores.
• Analyze student perceptions of an innovative teaching activity based on the 9-item questionnaire results.
• Calculate and model learning gain for individual students based on the provided scores.
• Investigate correlations between student perceptions and measured learning gains.

Strengths

• Contains data from 227 participants, providing a substantial sample size for analysis.
• Includes both quantitative learning gain scores and qualitative perception data from a 9-item questionnaire.
• Data is fully anonymized to protect participant identity.
• Clearly defines two groups (110 control, 117 experimental) for comparative analysis.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Daniel López Fernández, associated with e-cienciaDatos Harvested Dataverse.

Collection Method

Likely collected via educational experiments and surveys in a software engineering course.

Time Range

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Freshness

Last updated 2025-10-14 21:37:14; freshness should be verified.

Geography

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