The success in computer courses is influenced by the levels of students' beliefs in their computer abilities (computer self-efficacy). Low level of computer self-efficacy (CSE) may affect to student's attention, engagement, and achievement in computer courses. Teacher feedback is one of the important factors helping students boost their CSE. The interaction with teachers influences students' intrinsic motivation and computer abilities. This study was to explore the influence of teachers' feedback in the computer classroom environment. The different types of teachers' feedback affect the different levels of students' CSE. An individual computer project was given to students. Data collection with pre-test and post-test design was used to capture students' changing perceptions of learning at the beginning and end of the computer course. The final sample was 105 high-school students in Thailand. A survey measured 8 items of abilities feedback, 5 items for general praise, 9 items for negative feedback, 5 items for CSE, and 24 items for SE Sources. Results from regression analysis revealed that SE source of social persuasions influenced by the ability feedback, along with general praise, and negative feedback respectively was the strongest predictor to predict students' CSE. The result highlighted not only teacher feedback can help students strengthen their CSE but also link with students' psychological Index Terms-Computer classroom, computer self-efficacy, needs in a computer classroom. feedback, self-efficacy source.
The Internet of Things (IoT) concept is one of the most popular concepts that can be applied from simple things to the smart appliances of today. IoT also helps human life to be more convenient and easier. IoT for learning and teaching in higher education is so important to help students gain their knowledge and experience before graduation and industrial work. An Introduction of IoT course for undergraduate students mostly focuses on the IoT concepts and fundamentals which may affect learners to understand well about the concepts. To apply those concepts into practice is still quite difficult for learners. This article proposes the development of a learning kit for the Smart Transformer Detection System using IoT as teaching material. The capability of this tool can help learners automatically detect and notify events using online tools. Moreover, it helps students monitor the transformer system with IoT concepts more clearly, practically, and understandingly. The study volunteered a sample group of students who used this kit in their learning and practices. Then, the sample did a survey on learning satisfaction. The results show that students were very satisfied with both accuracy of the work system and the quality of the learning kit.
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