Making sense of student STEM identity: an ontological approach

Background: Students’ STEM identity has received considerable attention in STEM education in recent years. However, the diversity in how it is operationalized and measured in quantitative studies has led to conceptual confusion and difficulties in comparing findings across studies. This study aims to organize and represent operationalized components of student STEM identity from quantitative measurement studies by applying standards and techniques from ontology engineering, a knowledge modeling approach that systematically represents concepts and their interrelationships in a structured, machine-readable form. We developed the Student STEM Identity Ontology (S-STEMIO), which organizes and integrates empirically derived components of student STEM identity from quantitative measurement studies into a coherent hierarchical framework. Results: S-STEMIO clarifies conceptual boundaries, distinguishes overlaps, and establishes explicit relationships among components of student STEM identity, thereby offering a structured, machine-readable representation of how student STEM identity has been operationalized across the quantitative literature. Within the S-STEMIO, these components cluster into distinct ontological classes, reflecting different assumptions about whether identity is something students possess, enact, and/or develop over time. Three overarching definitional orientations toward identity were identified: trait-based/self-perception, situated/contextualized, and performative/behavioral. Students’ internal perceptions and values were found to be more frequently examined, whereas behavioral and developmental aspects were less explored. Relationships among components were defined by specifying their hierarchical structure and semantic relations, thereby linking dispositional, representational, and enacted aspects of identity within a coherent framework. Conclusions: S-STEMIO provides a unified framework for student STEM identity that brings conceptual clarity, facilitates communication among researchers, and supports measurement instrument development. Serving as a conceptual map of current quantitative STEM identity research, it not only shows where the field stands but also guides future research directions.