Artificial Intelligence-Assisted Community Needs Assessment and Extension Planning: Evidence from Wesleyan University-Philippines Partner Communities

This study conducted an Artificial Intelligence-assisted community needs assessment of partner-community respondents of Wesleyan University-Philippines, with emphasis on the Tricycle Operators and Drivers Association. Using a descriptive-quantitative design, five objectives were addressed: to describe the socioeconomic profile of the respondents; to determine livelihood and income conditions; to identify health, educational, and public-service needs; to rank priority community needs; and to develop a transparent, data-driven Artificial Intelligence-assisted framework. A cleaned dataset of 151 respondents was analyzed, of whom 46 were formally affiliated with tricycle operator and driver associations. Frequency, percentage, mean, and a proportion-based priority score summarized the data, while an Artificial Intelligence-assisted workflow supported response coding, respondent clustering, pattern detection, and need-to-intervention matching. Results showed that the transport subgroup consisted entirely of male drivers with lower average income, stronger income-expenditure pressure, greater reliance on borrowing and relatives, and recurring health concerns, including respiratory illness, hypertension, dental problems, and diabetes. Educational needs centered on books and learning materials. Ranked priorities were transport-oriented support, public-service linkage, health and wellness, educational assistance, livelihood and financial stability, skills training, and environmental support. The study concludes that pairing descriptive statistics with a reproducible Artificial Intelligence-assisted procedure produces more targeted, equitable, and responsive extension planning, and offers a practical template for other higher-education institutions.

@article{Ayro2026,
  title     = {Artificial Intelligence-Assisted Community Needs Assessment and Extension Planning: Evidence from Wesleyan University-Philippines Partner Communities},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {17},
  number    = {6},
  year      = {2026},
  publisher = {The Science and Information Organization},
  author    = {Eufemia Ayro and Karl Leugim Bernarte and Hazel May Babiera and Evangeline Agpoon and Jhon Carlo Villa and Maureen Bondoc and Jennyfer Villalon and Jose Arsenio Adriano and Christian Navarro},
  doi       = {10.14569/IJACSA.2026.0170641},
  url       = {https://doi.org/10.14569/IJACSA.2026.0170641}
}