Gendered Confidence Gaps and Empowering Future STEM Careers: Insights from Expectancy-Value Theory

Abstract High school is a formative stage in which students make pivotal decisions about pursuing careers in science, technology, engineering, and mathematics (STEM). Guided by Situated Expectancy-Value Theory (SEVT), this study investigated how social support and motivational beliefs shape STEM aspirations among 332 grade XI and XII students in a developing country. Structural equation modeling and path analysis revealed that teacher support significantly predicted both STEM interest ( β = .627) and Confidence in STEM Knowledge ( β = .489). Interest was the strongest predictor of STEM knowledge ( β = .492), mediating the relationship between teacher support and students’ perceived competence. Deviating from prior research, parental support was not a significant predictor, suggesting that its influence may be contingent on cultural and contextual factors. Gender differences did not emerge in perceived support or interest but were evident in Confidence in STEM Knowledge, with boys reporting significantly higher confidence than girls. These findings extend SEVT by underscoring the variability of motivational influences across contexts and demonstrating the role of teacher support in post-conflict and resource-constrained environments. The study enhances SEVT’s explanatory scope, providing evidence for policymakers that targeted professional development and STEM initiatives can foster equitable participation and guide STEM pathways in comparable settings.

Authors

Institutions

Publication Details

Journal
Journal for STEM Education Research
Published
2025-11-06
DOI
https://doi.org/10.1007/s41979-025-00168-x
Primary Topic
Education, Achievement, and Giftedness
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Gendered Confidence Gaps and Empowering Future STEM Careers: Insights from Expectancy-Value Theory

Fatlume Berisha, Elma Berisha, Julie Kolgjini, Yllza Kolloni
Journal for STEM Education Research
Education, Achievement, and Giftedness
article

Gendered Confidence Gaps and Empowering Future STEM Careers: Insights from Expectancy-Value Theory

Fatlume Berisha, Elma Berisha, Julie Kolgjini, Yllza Kolloni
article en

Abstract

Abstract High school is a formative stage in which students make pivotal decisions about pursuing careers in science, technology, engineering, and mathematics (STEM). Guided by Situated Expectancy-Value Theory (SEVT), this study investigated how social support and motivational beliefs shape STEM aspirations among 332 grade XI and XII students in a developing country. Structural equation modeling and path analysis revealed that teacher support significantly predicted both STEM interest ( β = .627) and Confidence in STEM Knowledge ( β = .489). Interest was the strongest predictor of STEM knowledge ( β = .492), mediating the relationship between teacher support and students’ perceived competence. Deviating from prior research, parental support was not a significant predictor, suggesting that its influence may be contingent on cultural and contextual factors. Gender differences did not emerge in perceived support or interest but were evident in Confidence in STEM Knowledge, with boys reporting significantly higher confidence than girls. These findings extend SEVT by underscoring the variability of motivational influences across contexts and demonstrating the role of teacher support in post-conflict and resource-constrained environments. The study enhances SEVT’s explanatory scope, providing evidence for policymakers that targeted professional development and STEM initiatives can foster equitable participation and guide STEM pathways in comparable settings.

Journal for STEM Education Research
Rochester Institute of Technology (US), Ibn Haldun University (TR), University of Prishtina (XK)
Openalex Percentile: Top 66%
Education, Achievement, and Giftedness
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.