STEM Education Study Data on School-University Continuity

Alma Abylkassymova's mixed-methods study data explores digitalized STEM approaches for mathematics education continuity. The dataset contains results from an experimental study in two 10th-grade classes and a survey of 33 university participants, measuring academic performance gains and attitudes. Findings include a 15-16% student performance improvement and an average survey score of 3.85 on STEM-digital integration.

Use Cases

• Analyze the reported 15-16% academic performance gain from the experimental study to validate the impact of digital STEM tools.
• Examine university participant survey responses, including the average score of 3.85, to assess attitudes towards school-university continuity.
• Study the implementation details of inquiry-based learning using specific digital tools like GeoGebra, Desmos, PhET, and Excel mentioned in the research.

Strengths

• Includes quantitative results from a quasi-experimental design with a reported 15-16% student performance improvement (p<0.05).
• Combines data from two distinct sources: an experimental study in two school classes and a survey of 33 university participants.
• Dataset is openly shared under a CC BY 4.0 license, facilitating reuse and analysis.

Limitations

• The dataset is very small at 10.5 KB, indicating limited raw data or summary statistics rather than a large, granular dataset.
• Sample sizes are limited to two school classes and 33 university survey participants, restricting generalizability.
• Specific data columns and sample rows are unknown, making it difficult to assess the dataset's structure and scope prior to download.

Provenance

Source

Alma Abylkassymova via figshare.

Collection Method

Mixed-method, quasi-experimental design involving an experimental study in school classes and a university participant survey.

Freshness

Last updated on 2026-03-25.