Original scientific paper
https://doi.org/10.15516/cje.v28i3.41262
Development and Validation of a Scale for Assessing Students’ Perceptions of Artificial Intelligence in E-Learning
Marko Marković
; University Business Academy in Novi Sad, Faculty of Applied Management, Economics and Finance
*
Dragan Soleša
; University Business Academy in Novi Sad, Faculty of Economics and Engineering Management
Petar Ciganović
; University Business Academy in Novi Sad, Faculty of Applied Management, Economics and Finance
* Corresponding author.
Abstract
Abstract
The increasing integration of artificial intelligence (AI) in higher education highlights the need for valid instruments to assess students’ perceptions of its use in e-learning environments. The aim of this study was to develop and validate a psychometric scale for measuring students’ perceptions of artificial intelligence in e-learning. A scale development research design was employed on a sample of 225 higher education students. The development process included four phases: item generation based on the technology acceptance model (TAM) and relevant literature, content validation through expert evaluation, pilot testing, and empirical validation. Exploratory factor analysis (EFA) identified a stable three-factor structure consisting of perceived usefulness, efficiency and optimization, and support in teaching. The Kaiser-Meyer-Olkin value (.812) and Bartlett’s test of sphericity (p < .001) confirmed data adequacy. The scale demonstrated satisfactory reliability, with Cronbach’s alpha coefficients of .889, .823, and .767. Discriminant validity was confirmed using an independent samples t-test, while inter-factor correlations supported construct validity. The findings indicate that the developed instrument is a reliable and valid tool for assessing students’ perceptions of artificial intelligence in e-learning environments.
Keywords: artificial intelligence; e-learning; scale development; psychometric validation; factor analysis; student attitudes
Keywords
artificial intelligence; e-learning; scale development; psychometric validation; factor analysis; student attitudes
Hrčak ID:
351234
URI
Publication date:
21.9.2026.
Visits: 0 *