Predictors of Students’ Satisfaction in Online Learning

Dr Priscilla Njoki Gachigi, Dr Susan Ngunu, Emily Okoth and Lily Alulu
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Dr Priscilla Njoki Gachigi: KCA University
Dr Susan Ngunu: Kenyatta University
Emily Okoth: KCA University
Lily Alulu: KCA University

International Journal of Research and Innovation in Social Science, 2023, vol. 7, issue 8, 1657-1669

Abstract: The entire globe is recovering from the Covid-19 pandemic. The pandemic resulted in the closure of all learning institutions across the world leading to an emphasis of e- learning in order to keep the students engaged and to mediate the effects of the pandemic on the education sector. This brought considerable changes in the pedagogy of teaching and learning as conventional face-to-face classes were converted to online learning. This paradigm shift saw significant changes in education with the use of e-learning where learning took place remotely or through the use of various digital online platforms like zoom, Google meet, Microsoft teams among others. This type of learning has benefits like added flexibility, better time management, improved virtual communication etc. This shift could also have impacted on the students learning. The aim of this study is to interrogate the predictors of students’ satisfaction in online learning. The study was guided by the following objectives; to determine the relationship between course delivery and student’s satisfaction, to establish the relationship between modes of assessments and students’ satisfaction, to assess the relationship between sense of belongingness and students’ satisfaction and to evaluate the technological quality and students’ satisfaction. The study was grounded on the constructivism theory of learning. The study adopted a correlational study design. The target population were university students but the sample was specifically drawn from 2 private universities. The study sample was 400 students (200 males and 200 females). Data was collected using an online questionnaire. The data was analyzed quantitatively using both descriptive and inferential statistics. Presentations were done through graphs, tables and frequency distributions. The results indicated a statistically significant relationship (F = 72.618, Sig.

Date: 2023
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