The lifetime of a cast-resin transformer mainly depends on the condition of insulation material. Partial discharge (PD) is an important reason for insulation deterioration in cast-resin transformers. Identifying the position of PD is very necessary for damage assessment while the transformer is still operating, and the transformer is covered by housing. This paper proposes the investigation of a cast-resin transformer using an AE sensor and HFCT sensor to specify the precise source of PD. In this study, four AE sensors were used to find PD sources, and the high-frequency current transducer (HFCT) technique was used to identify the PD source and the criteria level. The experiment, in the first two parts, identified the possibility of PD, which includes the position of PD. The final part of the experiment verified the position of the PD source of a cast-resin transformer and confirmed the inspection results. AE and HFCT sensors can be used to detect the location of PD sources, confirming the position of the PD source by sensor detection. In addition, the evident partial discharge picture on the insulator surface of high voltage side. The process successfully and accurately identifies and locates the PD source.

The COVID-19 pandemic has heightened the need for 21st century skills, particularly computer and ICT literacy (CICT) in Thailand. This study aimed to develop a TPACK (Technological Pedagogical and Content Knowledge)-based blended learning model (BLM) to enhance CICT skills and academic performance among 179 Business Administration (BA) undergraduates in the 2022 academic year Computer and Information Applications course. Research instruments were designed and evaluated by experts. Over 18 weeks, qualitative and quantitative data were collected, with the qualitative data undergoing content analysis. Descriptive statistics were used to analyze quantitative data, comparing pretests, post-tests, and 2-week retests using a repeated measure ANOVA. One-sample t-tests were used to assess the model’s impact on CICT skills. The results showed a significant score improvement between tests, with the highest mean being seen in the 2-week retest. The BA-TPACK model significantly enhanced CICT skills, exceeding 80%. The students expressed high satisfaction, with the BA-TPACK model effectively enhancing CICT skills and academic achievement, recommending its integration into future computer and information courses. This study’s contribution lies in addressing the pressing need for CICT skills in the ‘new normal’. By developing and implementing a BLM grounded in the TPACK framework, this study not only enhances students’ CICT proficiency but also fills a crucial gap in the literature regarding effective pedagogical approaches to foster 21st century skills.

This study aimed to develop and evaluate a flipped, microlearning, and augmented reality model to enhance undergraduate engineering students’ conceptual understanding and problem‑solving skills in an electrical circuit laboratory course. The participants consisted of 43 first‑year engi‑ neering students, divided into an experimental group (n = 21) and a control group (n = 22). The experimental group was instructed using the integrated model, while the control group received traditional instruction. Research instruments included a learning achievement test, a problem‑solving skills rubric, and a satisfaction questionnaire, all of which demonstrated acceptable validity and reliability. Data were analyzed using multivariate analysis of variance (MANOVA) and mixed ANOVA. The findings indicated that students in the experimental group significantly outperformed those in the control group in both learning achievement (p < .05) and problem‑solving skills (p < .01). In addition, the experimental group demonstrated greater learn‑ ing retention at two weeks after instruction. These results suggest that integrating augmented reality and microlearning within a flipped classroom framework effectively supports conceptual understanding and enhances problem‑solving skills in engineering education. The integrated model provides a practical instructional approach for improving laboratory‑based learning in science and engineering contexts. This study extends existing research by providing an instruc‑ tional framework that supports both cognitive and experiential learning in higher education.