Abstract
The purpose of this study is to determine contributory factors to students' self-efficacy and barriers in online learning during the COVID-19 pandemic. This research used a quantitative-cross sectional with the 202 student nurses of the College of Nursing, University of Hail. These students were chosen through convenience sampling. Data gathering was between November and December 2021. The frequency and percentage were used to analyze the demographic characteristics and the identified barriers. The results show a significant difference between gender and online environment (t=-3.807; p<.001), time management (t=-2.651; p<.009), and technology (t=-2.902; p<.004) was established. The age was not significant difference with online environment (F=.103; p>.902), time management (F=1.408; p>.247), and technology (F=.750; p>.474). In addition, the level of proficiency was found no significant difference in the online environment (F=1.986; p>.098), time management (F=1.026; p>.395), and technology (F=2.231; p>.067). Lastly, the grade point average (GPA) was also found no significant difference with the online environment (F=.923; p>.490), time management (F=.743; p>.636), and technology (F.449; p>.870). The weak internet connection has the highest percentage (43.6%) followed by poor presentation materials of instructors (34.2%) as the identified barriers to self-efficacy in online learning education. In conclusion, educational institutions need to understand the factors that influence student attraction and motivation to continue taking online studies in the future.
Publisher
International Journal of Advanced and Applied Sciences
Reference22 articles.
1. Almaiah M, Al-Khasawneh A, Althunibat A, and Khawatreh S (2020). Mobile government adoption model based on combining GAM and UTAUT to explain factors according to adoption of mobile government services. International Journal of Interactive Mobile Technologies, 14: 199-225.
2. Alqurashi E (2016). Self-efficacy in online learning environments: A literature review. Contemporary Issues in Education Research, 9(1): 45-52.
3. Aronoff SC, Evans B, Fleece D, Lyons P, Kaplan L, and Rojas R (2010). Integrating evidence based medicine into undergraduate medical education: Combining online instruction with clinical clerkships. Teaching and Learning in Medicine, 22(3): 219-223.
4. Aung TN and Khaing SS (2015). Challenges of implementing e-learning in developing countries: A review. In: Zin T, Lin JW, Pan JS, Tin P, and Yokota M (Eds.) Genetic and evolutionary computing (GEC 2015): Advances in intelligent systems and computing: 405-411. Volume 388, Springer, Cham, Switzerland.
5. Bandura A (2016). The power of observational learning through social modeling. In: Sternberg RJ, Fiske ST, and Foss DJ (Eds.), Scientists making a difference: 235-239. Cambridge University Press, Cambridge, UK.
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