Mixed-Methods Study on Digital STEM Education in Kazakhstani Schools

A mixed-methods study in Kazakhstan explores digital STEM approaches to improve school-university continuity in mathematics education. The research includes an experimental study with two 10th-grade classes and a survey of 33 university participants. It reports a 15-16% improvement in student academic performance and an average positive attitude score of 3.85 from university respondents.

Use Cases

• Analyze the reported 15-16% academic performance improvement linked to the use of digital tools like GeoGebra and Desmos.
• Examine university survey responses with an average score of 3.85 regarding attitudes toward integrating STEM with digital technologies.
• Study the proposed cyclic model connecting schools, students, and universities for teacher professional development.
• Review findings on student gains in modeling, data interpretation, and interdisciplinary thinking from the quasi-experimental design.

Strengths

• Reports statistically significant (p < 0.05) quantitative results, including a 15-16% improvement in student performance.
• Includes qualitative survey data from 33 university participants, providing multiple perspectives.
• Details specific digital tools (GeoGebra, Desmos, PhET, Excel) and pedagogical approaches (inquiry-based, project-oriented learning) used in the study.

Limitations

• The dataset is a 442.0 KB DOCX document, not a structured data table, limiting direct computational analysis.
• Sample sizes are small, with only two experimental classes and 33 survey respondents, reducing generalizability.
• The data is specific to a particular educational context in Kazakhstan, which may limit direct applicability to other regions.

Provenance

Source

figshare, authored by Alma Abylkassymova.

Collection Method

Mixed-method, quasi-experimental design involving an experimental study in two 10th-grade classes and a survey.

Freshness

Last updated March 25, 2026.

Geography

Kazakhstan (implied by author's name and study context).