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.

Higher education institutions (HEIs) catalyze community development through extension programs that promote economic empowerment, skill development, social inclusion, environmental sustainability, and leadership capacity. Despite numerous community extension initiatives in Philippine higher education, a comprehensive synthesis of beneficiary experiences remains absent. This qualitative meta-synthesis systematically reviewed qualitative studies (2021–2024) examining beneficiaries’ lived experiences in Philippine HEI extension programs. Following PRISMA 2020 guidelines, 13 studies meeting Critical Appraisal Skills Program criteria were analyzed using Braun and Clarke’s thematic analysis. Five interconnected themes emerged: (1) Economic Empowerment and Livelihood Enhancement, (2) Skill Development and Capacity Building, (3) Social Inclusion and Community Engagement, (4) Sustainability and Long-Term Impact, and (5) Leadership and Empowerment. These coalesced into an overarching meta-theme: Transformative Community Empowerment through Higher Education Extension Programs. Building upon empowerment theory, community development frameworks, and capability approach, this study proposes the Transformative Community Empowerment Theory (TCET), positing that effective extension programs operate through five interdependent pillars that transform beneficiaries from passive recipients to active change agents. Findings illuminate HEIs’ transformative role in cultivating empowered, self-sustaining communities while strengthening reciprocal HEI-community relationships.

The conventional method for producing pervious concrete (PC) involves balancing permeability and compressive strength, which can be complicated due to variability in voids. This study investigates combinations of two aggregate sizes (3/8″ and 3/4″) and four water-to-cement (W/C) ratios (0.30–0.39) with a constant aggregate-to-binder ratio to achieve a uniform cement paste distribution. Results showed a cement paste thickness ratio varying between 0.7 to around 1.0 across mixes. Compressive strength peaked at a W/C ratio of 0.36 for the mix with equal 3/8″ and 3/4″ aggregate, while higher strength was reached with a higher W/C ratio of 0.39 for mix with higher 3/8″ aggregate content due to better packing density. Permeability generally decreased with higher W/C ratios, while a balanced aggregate mix (50