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Adaptation of the Social Presence Scale into Turkish: A Validity and Reliability Study

Year 2025, Volume: 6 Issue: 1, 31 - 42, 30.06.2025

Abstract

This study aims to adapt the Social Presence Scale (SPS), developed by Kizilcec et al. (2015), into Turkish to measure perceptions of social presence in online learning environments. Social presence refers to individuals' ability to perceive the physical or psychological presence of others in a digital environment, which plays a significant role in fostering interaction, motivation, and engagement in learning processes. The study evaluates the validity and reliability of the Turkish version of the scale and its applicability in the Turkish context.The research was conducted with 221 associate degree students enrolled in a distance education program at a public university. The validity of the scale was tested using confirmatory factor analysis (CFA), confirming its single-factor structure. Fit indices (χ²/df = 2.33, RMSEA = 0.065, CFI = 1.0) indicate a high level of model fit. Reliability analysis revealed a Cronbach’s alpha value of 0.918, demonstrating a high level of internal consistency.The findings indicate that the Turkish version of the SPS is a valid and reliable instrument for measuring social presence in online learning contexts. This scale will serve as a valuable tool for evaluating social presence perceptions and their impact on learning processes.

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There are 16 citations in total.

Details

Primary Language English
Subjects Social and Humanities Education (Excluding Economics, Business and Management)
Journal Section Research Articles
Authors

Yalın Kılıç Türel 0000-0002-0021-0484

Mustafa Alpsülün 0000-0003-2928-218X

Early Pub Date June 28, 2025
Publication Date June 30, 2025
Submission Date December 21, 2024
Acceptance Date May 13, 2025
Published in Issue Year 2025 Volume: 6 Issue: 1

Cite

APA Türel, Y. K., & Alpsülün, M. (2025). Adaptation of the Social Presence Scale into Turkish: A Validity and Reliability Study. Instructional Technology and Lifelong Learning, 6(1), 31-42. https://doi.org/10.52911/itall.1605036

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