Cebu Technological University

The integration of artificial intelligence (AI) tools into educational settings is reshaping how students learn, create, and engage with digital technologies, particularly in fields such as technology and design education where virtual simulations and AI-assisted workflows are increasingly prevalent. Despite this momentum, student adoption of AI tools remains inconsistent, especially in developing regions where technological readiness and trust in emerging technologies vary widely. This study investigates factors influencing AI tool acceptance among 493 industrial technology students from a public university in Central Visayas, Philippines. Using structural equation modeling (SEM), the research examined the relationships among perceived usefulness, perceived ease of use, perceived risk, and behavioral intention to adopt AI-driven virtual simulation applications. Findings confirm that perceived usefulness and ease of use remain strong drivers of adoption intention, aligning with the Technology Acceptance Model (TAM). However, perceived risk demonstrated a significant negative influence on both perceptions and intentions, highlighting the impact of concerns related to data privacy, algorithmic transparency, and ethical implications of AI in design-oriented learning environments. Integrating perceived risk into TAM expands the explanatory power of the model in technical drafting and design education, offering a more comprehensive picture of how students evaluate and adopt AI-driven virtual simulation apps. This enriched perspective highlights the necessity for institutional strategies that build AI literacy, reinforce data governance mechanisms, and foster responsible engagement with emerging technologies. The results provide valuable insights for educators, curriculum designers, and policymakers working to advance AI-supported learning, particularly within resource-constrained and rapidly developing educational contexts.

This systematic literature review examines how higher education institutions govern and implement generative artificial intelligence and what outcomes are reported for institutional efficiency and student learning. The review adheres to the PRISMA 2020 protocol. Searches across seven academic databases [i.e., Scopus, Web of Science, Google Scholar, ERIC (Education Resources Information Center), IEEE Xplore, ScienceDirect, and ACM Digital Library] covering 2020 to 2026 identified 239 records, with 18 duplicates removed. A total of 221 records were screened, yielding 101 exclusions. Subsequently, 120 full text reports were assessed, of which 70 were excluded with documented reasons. The final qualitative synthesis included 50 studies. Thematic findings indicate that effective adoption depends on governance maturity, characterized by coherent multi-unit oversight, clearly defined academic integrity and disclosure standards, and risk based data governance frameworks. The evidence demonstrates operational gains through automation and analytics, alongside improved student engagement and learning when implementation is supported by appropriate pedagogical scaffolding. However, persistent challenges remain, including risks of academic misconduct, inequitable access, privacy and bias concerns, and pronounced regional disparities, particularly in Global South contexts. Accordingly, institutions should prioritize embedded governance structures, equity safeguards, sustained faculty development, and continuous monitoring to ensure responsible, legitimate, and educationally meaningful deployment.

This research examined the levels of professional competence, institutional support, and instructional practices of special education and receiving teachers in selected public schools under the Cebu City Division during the School Year 2025-2026, and examined the relationships among these variables as bases for an intervention plan. A descriptive-correlational research design was employed, and data were gathered from 42 teacher respondents using adapted survey questionnaires that measured teachers’ competence across seven professional domains, the extent of institutional support, and instructional practices in special needs education settings. The findings revealed very high levels of professional competence and instructional practices across all measured dimensions, while institutional support was perceived to range from moderate to high in terms of administrative support, working conditions, professional development opportunities, and collaboration and support networks. Statistical analysis showed a strong positive relationship between teachers’ professional competence and their instructional practices, whereas no significant relationship was found between institutional support and instructional practices. Based on these results, the study concludes that teachers’ professional competence plays a vital role in ensuring effective instructional practices in special needs education settings, providing a sound basis for the proposed intervention plan aimed at strengthening teacher competence, reinforcing institutional support, and sustaining effective inclusive classroom practices.

Noise pollution negatively affects comfort, productivity, and health. This study develops and evaluates a coconut husk sound absorber panel as a sustainable, low-cost alternative to synthetic acoustic materials. Coconut husks, an abundant agricultural by-product, offer a porous and fibrous structure that can trap sound waves. The panel was made from 500 g ground coconut husk and 1 kg sodium silicate shaped into a 20 × 20 × 2 cm mold. Tests were conducted in a residential room using a mobile sound meter to compare noise levels before and after panel installation. Results showed an average noise reduction of 6.7 dB. The panel was also observed to be lightweight, eco-friendly, aesthetically natural, and more affordable than commercial acoustic products. This study supports the potential of coconut husk as an environmentally responsible material for noise reduction in indoor spaces.

This research design aims to investigate the influence of self-regulation as the mediating variable on the relationship between self-efficacy and mathematics achievement of the participants who are Grade Nine students at the selected public high schools in the Philippines for the school year 2024 – 2025. The study seeks to enhance the theoretical and empirical understanding of psychological processes that contribute to effective student performance in mathematics, where planning, monitoring, adjusting, and reflecting are critical for academic success. A quantitative descriptive correlational research design was used to collect the data through two adopted survey questionnaires administered using a simple random sampling technique. The survey measured key constructs, including self-efficacy and self-regulation, while mathematics achievement was evaluated using first quarter mathematics grades. The study included a total of 845 valid responses from Grade Nine students. The data collected were treated using frequency count, percentage, weighted mean, standard deviation, Pearson’s r, and multiple regression analysis. The analysis of the findings revealed moderate levels of students’ self-efficacy and self-regulation in planning and monitoring, while levels of adjusting and reflecting were high. Moreover, there was a significant weak positive correlation between self-efficacy and mathematics achievement, a weak positive for self-efficacy and self-regulation, and a weak positive for self-regulation and mathematics achievement. It is determined that the students’ self-regulation partially mediates the relationship between students’ self-efficacy and mathematics achievement, indicating that self-efficacy enhances mathematics performance not only directly but also indirectly by fostering self-regulatory behaviors. Thus, teaching staff and administrators must put into practice methods that strengthen self-efficacy and self-regulation to boost mathematics achievement.