An empirical study from 2026 analyzes first-year student adaptation in Kazakhstani universities under mass higher education conditions. The dataset likely contains validated assessments of academic, social, and psychological adaptation, transversal skills, and an Adaptation Quotient (AQ). The analysis draws on several independent samples from linguistically and culturally diverse student populations.
Use Cases
- Modeling the relationship between organizational constraints and student adaptation outcomes based on cohort overcrowding and bureaucratic density variables.
- Identifying vulnerable student groups based on heterogeneous adaptation profiles captured by the Adaptation Quotient.
- Analyzing moderating effects on adaptation patterns based on language of instruction, cultural background, and gender.
- Investigating transversal skills as compensatory resources in navigating massified educational environments.
Strengths
- Psychometric analyses demonstrated satisfactory reliability and factorial validity across measurement models.
- The analytical strategy relied on cross-sample triangulation combined with moderation analyses and multi-group modeling.
- The dataset is licensed under CC-BY-4.0, allowing for open reuse.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- The dataset is 30.4 KB, indicating a very small scale.
Provenance
- Source
- G. K. Baimuldinova via figshare.
- Collection Method
- Data collected from several independent samples in public universities in Kazakhstan using validated instruments.
- Freshness
- Last updated 2026-04-10 06:04:01; freshness should be verified.
- Geography
- Kazakhstan.