Assessing Self-Learning Attitude Toward Usages of YouTube for Learning Purpose

• Published in: 2024 International Conference on Advances in Computing, Communication, Electrical, and Smart Systems (iCACCESS) pp. 01 - 05
• Main Authors: Md. Nurullah Rabbani, Golam Mustafa, Hassan, Farheen, Nahid, Mehzabul Hoque, Anwar, Md. Aftab
• Format: Conference Proceeding
• Language: English
• Published: IEEE 08-03-2024
• Subjects: Analytical models; Education; Manifolds; Mathematical models; Numerical analysis; Predictive models; Self-learning; Surveys; Task-Technology-Fit; Technology-Acceptance-Model; Video on demand; YouTube
• DOI: 10.1109/iCACCESS61735.2024.10499614

This research integrates the Task-Technology-Fit (TTF) and Technology-Acceptance-Model (TAM) components to create a novel conceptual framework for predicting university students' satisfaction levels in Bangladesh about self-directed learning using YouTube. The research includes four external variables- "Perceived Ease of Use", "Task-Technology Fit", "YouTube Self efficacy", and "Content Richness"-to forecast the endogenous variable known as User Satisfaction. 138 responses have been collected using an online questionnaire survey. This investigation adopted structural equation modeling (SEM) using PLS software to analyse and explain the prediction performance of this new model to understand the validity and feasibility for future implications. the results show that, in Bangladesh, perceived ease of use, task-technology-fit and YouTube self-efficacy have significant effect on the User Satisfaction, whereas content richness has no significant effect on the user Satisfaction of using YouTube as a self-learning tool. This research provides important information on the satisfaction levels of students participating in YouTube-based learning. It recommends that educators improve their instructional content and tools and help students develop self-efficacy to improve the effectiveness and pleasure of learning.