Behavior and Satisfaction with Ai-Developed Online Lessons of Communication Faculty of Management Science Students at Udon Thani Rajabhat University
DOI:
https://doi.org/10.14456/rc-sdj.2026.6Keywords:
Online Lessons, Artificial Intelligence, Satisfaction, Self-Directed Learning, Journalism EducationAbstract
Background and Objective: In the contemporary digital education landscape, Artificial Intelligence (AI) has emerged as a transformative force in higher education instruction. This research aimed to: 1) study the usage behaviors of Communication Arts students, Faculty of Management Science, Udon Thani Rajabhat University regarding AI-developed online lessons, 2) examine their level of satisfaction with these instructional tools, and 3) compare student opinions between AI-developed online lessons and traditional instructional methods.
Methodology: The research sample consisted of 63 Communication Arts students at Udon Thani Rajabhat University enrolled in the News Reporting course during Semester 2, Academic Year 2025, selected using purposive sampling (students who had engaged with all AI-developed online lesson activities, at least 80% of all activities, throughout the semester). The research instrument was an online questionnaire administered via Google Forms, yielding a high reliability coefficient (Cronbach's Alpha = 0.93). Data were analyzed using descriptive statistics—frequency, percentage, mean, and standard deviation—along with a One-Sample t-test for comparative analysis (reference value μ₀ = 3.00).
Results: The majority of participants were female (60.32%), aged 19 years (53.97%), and primarily utilized smartphones as their main device (84.13%), typically 2–3 times per week with peak usage occurring near examination periods and before class sessions. Overall satisfaction was rated at a high level (μ = 4.08, σ = 0.69), with Google Classroom usability receiving the highest score (μ = 4.15), followed by lesson content quality (μ = 4.12). Regarding the comparative analysis, students perceived AI-developed lessons as significantly superior to traditional methods across all measured dimensions (μ = 3.81, σ = 0.79, t(566) = 24.245, p < 0.001), with the highest scores attributed to ease of use and timely assessment feedback (μ = 3.92).
Discussion and/or Suggestion: The findings reflect the digital learning behaviors of Communication students at Udon Thani Rajabhat University, who prioritize convenience and mobile accessibility. It is recommended that instructors adopt a Mobile-First Design approach and selectively integrate AI into appropriate courses to support Self-Directed Learning alongside classroom instruction. Future research should employ quasi-experimental designs with control groups to more rigorously validate these comparative findings.
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