Web-based technologies have influenced programming education, yet many courses still rely on static materials and delayed feedback, making it difficult for students to test ideas during problem-solving. This limitation is especially evident in Internet of Things (IoT) programming, where code must interact with physical devices. This study examined an LMS-based learning module combining live coding, remote IoT device access, and AI-supported formative feedback. The module was implemented with 97 undergraduate students in an IoT-based web programming course, using a single-group pre-test and post-test design. Results showed a significant improvement from pre-test (M = 63.05, SD = 6.86) to post-test (M = 80.23, SD = 7.21), with a mean gain of 17.18 points (t(96) = 19.441, p < 0.001, d = 1.97). LMS activity logs showed that students revised their code multiple times before submission, with a task completion rate of 93.7%. Gains were comparable across sex and platform access time. Interviews suggested that immediate feedback and real-device interaction helped students persist through challenging tasks. These findings support integrating live coding, automated feedback, and IoT interaction within a single LMS environment. Further research is needed beyond a single institutional setting.
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Purbohadi et al. (2026) studied this question.
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