Convergent validity

Physics

Construct (python library)

Online learning

Mathematics

Confirmatory factor analysis

Construct validity

Multimedia

Distance education

Statistics

Mathematics education

Developmental psychology

Psychology

Power (physics)

Psychometrics

Programming language

Item analysis

Scale (ratio)

Computer science

Quantum mechanics

Internal consistency

Reliability (semiconductor)

Validity

Structural equation modeling

Social psychology

Distance Education

The purpose of this study was to examine the psychometric properties of the Self-Efficacy Questionnaire for Online Learning (SeQoL; Shen et al., 2013). Using two samples of college students, this study examined evidence of construct validity, concurrent validity, convergent validity, and reliability for the SeQoL. Confirmatory factor analysis and latent profiles analysis were conducted to provide different aspects of construct validity evidence. Our results suggest the SeQoL consistently measures the five dimensions of online learning self-efficacy found in Shen et al.’s original study. We flagged five items from the original scale for further examination. In the current study, strong construct validity and reliability evidence were observed across two different samples, analytical approaches, and related measures. Online learners with higher online learning self-efficacy were found to have higher learning satisfaction and expect better grades. Interpretations and implications of the findings are discussed.

The Self-Efficacy Questionnaire for Online Learning (SeQoL)