Universiti Teknologi Malaysia Institutional Repository

An evaluation of the Online Social Learning Environment Instrument (OSLEI) using Rasch Model Analysis

Che Lah, Noor Hidayah and Tasir, Zaidatun and Jumaat, Nurul Farhana (2022) An evaluation of the Online Social Learning Environment Instrument (OSLEI) using Rasch Model Analysis. SAGE Open, 12 (2). pp. 1-16. ISSN 2158-2440

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Official URL: http://dx.doi.org/10.1177/21582440221104083

Abstract

One of the questionnaires that will be used to evaluate social learning environments such as Facebook is the Online Social Learning Environment Instrument (OSLEI). The aim of this study was to evaluate the OSLEI using alternative method of analysis via Rasch model toward 49 undergraduate students in Malaysia. To date, no study has evaluated the OSLEI through the lens of Rasch model analysis among Malaysian samples. Firstly, the OSLEI underwent content validation by three experts. The results of the overall percent agreement on eight constructs (perceived usefulness, usage of learning groups, learning outcomes, affective outcomes, self-efficacy, trust, privacy, and teaching member presence) of the OSLEI was 86% for 48 items. Next, 10 measurement properties of Rasch model analysis were employed with the OSLEI. The results revealed that 23 respondents needed to be dropped. Subsequently, the data from the remaining 26 respondents proceeded to Rasch Model analysis of the 43 items in the OSLEI. The results of the item analysis revealed that 13 items and the construct of privacy needed to be dropped. The findings demonstrated that 35 items were robust, valid, and reliable, and could be used to measure online social learning environments.

Item Type:Article
Uncontrolled Keywords:evaluation, questionnaire, Rasch, reliability, social learning, validity
Subjects:L Education > L Education (General)
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computing
ID Code:103943
Deposited By: Yanti Mohd Shah
Deposited On:07 Dec 2023 08:31
Last Modified:07 Dec 2023 08:31

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