DEVELOPING ACTIVE LEARNING MANAGEMENT THROUGH VIRTUAL CLASSROOMS INTEGRATED WITH AI FOR GRADUATE DIPLOMA IN TEACHING PROFESSION STUDENTS
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Abstract
This research study aimed to (1) develop an active learning model through a virtual classroom integrated with artificial intelligence (AI) for graduate diploma in teaching profession students, (2) examine students' active learning management competencies before and after implementing the developed model, and (3) evaluate student satisfaction with the developed model. A mixed-methods approach was employed using a research and development (R&D) design. The population consisted of 154 graduate diploma students enrolled in the 2025 academic year. The sample comprised 30 students selected through simple random sampling, along with a panel of 5 experts who evaluated the model. Research instruments included the AIVA-PBL active learning model, a five-dimension active learning management competency assessment, and a five-point Likert scale satisfaction questionnaire. Data were analyzed using means, standard deviations, and a paired-samples t-test.
The findings were as follows. (1) The developed AIVA-PBL Model consisted of five continuously integrated components. Experts rated the overall appropriateness at the highest level (x̄ = 4.72, S.D. = 0.38), with active assessment using AI receiving the highest score (x̄ = 4.85) and virtual classroom interaction receiving the lowest score, though still at a high level (x̄ = 4.60). (2) Students' (n = 30) active learning management competencies after implementing the AIVA-PBL model were significantly higher than before implementation at the .05 level (t = 16.83, df = 29, p < .001), with the overall mean increasing from 3.22 to 4.50. (3) Students expressed the highest level of overall satisfaction with the active learning model delivered through the virtual classroom integrated with AI (x̄ = 4.59, S.D. = 0.46), with the dimension of professional development benefits recording the highest mean score (x̄ = 4.74).
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References
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