Development and Validation of an Instrument to Measure the Effects of Self-regulated Learning Strategies on Online Learning Performance

Lilian Anthonysamy, Koo Ah Choo and Hew Soon Hin

The objective of this study is to develop and validate a scale that would evaluate self-regulated learning strategies used by students in blended online learning in relation to learning performance. Self-regulated learning strategies are characterized by four domains, i.e., cognitive engagement, metacognitive knowledge, resource management and motivational beliefs. Based on the Future of Jobs Survey Report 2018 published by the World Economic Forum, active learning and learning strategies are among the trending skills of 2022. Current studies show that students have difficulties with online learning because they lack in self-regulation. This paper describes the psychometric properties of the measured scale for future use. It provides results of the developed instrument from 107 computer science students enrolled in at least one blended learning course in a private university in Malaysia. The development of the instrument addressed face and content validity. In order to meaningfully interpret the results, SPSS (v25) and SmartPLS 3.0 were utilized. Reliability and validity assessments were carried out. Internal consistency reliability was analysed using Cronbach’s alpha and composite reliability. Two types of construct validity were examined, convergent reliability and discriminant reliability. The results of the instrument validation study are positive, thus suggesting that the instrument may be useful to researchers or educators interested in measuring self-regulated learning strategies among university students who learn through digital media.

Volume 11 | 10-Special Issue

Pages: 1093-1099

DOI: 10.5373/JARDCS/V11SP10/20192910