Factors of learning towards creating blended learning curriculum using learning management system in higher education during Covid-19

• Main Authors: Razali, Fazilah, Sulaiman, Tajularipin, Mohd Ayub, Ahmad Fauzi
• Format: Article
• Published: International Journal of Instruction 2022
• Online Access: http://psasir.upm.edu.my/id/eprint/101491/; https://www.e-iji.net/volumes/371-october-2022,-volume-15,-number-4

Blended learning is a mix of online and face-to-face instruction. It refers to a variety of possibilities made available by integrating the internet and streaming media with traditional educational formats that necessitate the physical co-presence of teachers and students. While the Covid-19 pandemic is being referred to as the greatest challenge facing education systems around the world, it has prompted authorities to issue a drastic order requiring institutions to switch from face-to-face teaching to online teaching and virtual education for students. This present study aims to determine the model of integration between learning style and active learning towards enhancing blended learning curriculums among higher education students. A total of 208 students at a selected Malaysian higher education institution were selected randomly in this study. For data collection, this study used the quantitative approach and random sampling technique. The instrument was developed based on the literature review, and expert validation was obtained from various universities. The survey forms were distributed using an online medium (Google forms). Pearson Coefficient correlation (r) was employed to examine the relationship between variables, while Structural Equation Modelling (SEM) was utilized to examine the effect of the mediator variable. By dopting a two-stage method, the measurement model was first tested, followed by the structural model. Confirmatory Factor Analysis (CFA) is to test whether the data is compatible with the hypothesized measurement model as well as for the purpose of validation and construct reliability. The results show that the measurement model was a good fit for the data, and that the constructs were reliable and valid for testing the hypotheses based on the results. The assessment of the structural model, on the other hand, involved testing the hypothesized relationships about the direct effects. Four hypothesized direct paths were found to be statistically significant.