AI Assistance Usage and Programming Performance: A Data Analytics–Driven Correlational Study of First-Year IT Students

Eric B. Bulala, Mark Angelou A. Balonga, Alvin M. Boncales, Emelyn Shaira B. Felisilda, Raymund Castañares, Maria Shina Jane A. Melendres, Serafin C. Palmares and Kristine T. Soberano
Additional contact information
Eric B. Bulala: State University of Northern Negros, Sagay, Negros Occidental
Mark Angelou A. Balonga: State University of Northern Negros, Sagay, Negros Occidental
Alvin M. Boncales: State University of Northern Negros, Sagay, Negros Occidental
Emelyn Shaira B. Felisilda: State University of Northern Negros, Sagay, Negros Occidental
Raymund Castañares: State University of Northern Negros, Sagay, Negros Occidental
Maria Shina Jane A. Melendres: State University of Northern Negros, Sagay, Negros Occidental
Serafin C. Palmares: State University of Northern Negros, Sagay, Negros Occidental
Kristine T. Soberano: State University of Northern Negros, Sagay, Negros Occidental

International Journal of Research and Scientific Innovation, 2026, vol. 13, issue 5, 1651-1663

Abstract: This research examined the AI assistance usage and programming performance among first-year Information Technology (IT) students at three municipal colleges in the Philippines. The study's objectives were to evaluate students' utilization of AI tools, identify usage patterns, and analyze the correlation between AI assistance usage and programming performance. A descriptive-correlational quantitative research design was used. Data were collected from 250 first-year IT students using a structured questionnaire. The results indicate that, although students demonstrated considerable confidence in the perceived usefulness of AI (mean 3.63), their actual dependency on these tools remained relatively low (mean 2.79). Many respondents reported limited study habits, with 82% (n=205) spending only 1–3 hours per week practicing programming. The findings indicated that a significant percentage of students commenced the IT program without any prior programming knowledge or experience (79.2%), and 84% (n=210) recognized ChatGPT as their principal AI resource. Statistical analysis showed no significant differences in AI assistance usage and programming performance between male and female students (p > 0.05). Furthermore, Pearson correlation analysis revealed a statistically significant but weak positive relationship between AI assistance usage and programming performance (r = 0.1096, p = 0.001). Multiple regression analysis further revealed that AI assistance usage alone was not a significant predictor (p = 0.182); rather, performance was primarily driven by weekly study hours (p = 0.001) and prior programming experience (p = 0.032). Crucially, a significant interaction effect (p = 0.008) confirmed that AI assistance usage effectively served as a "cognitive scaffold" for students with higher study hours, whereas high AI reliance did not yield significant gains for those with minimal practice.

Date: 2026
References: Add references at CitEc
Citations:

Downloads: (external link)
https://rsisinternational.org/journals/ijrsi/uploa ... -1663-202606_pdf.pdf (application/pdf)
https://rsisinternational.org/journals/ijrsi/view/ ... st-year-it-students/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bjc:journl:v:13:y:2026:i:5:p:1651-1663

Access Statistics for this article

International Journal of Research and Scientific Innovation is currently edited by Dr. Renu Malsaria

More articles in International Journal of Research and Scientific Innovation from International Journal of Research and Scientific Innovation (IJRSI)
Bibliographic data for series maintained by Dr. Renu Malsaria ().