Artificial Intelligence In Social Sciences: Behavioral Intention and Use Among Students in a State University in Central Luzon, Philippines
Year: 2025
Type: dissertation
Abstract: This study assessed the views and usage of AI among social sciences students in a state university in Luzon, Philippines using the Unified Theory of Acceptance of Technology (UTAUT) theory. A total of 311 students were chosen through stratified proportional sampling and surveyed using Google forms for 8 days. Data underwent statistical tests such as T-test and correlations (Point-Biserial, Spearman's rank, and Phi Coefficient). The behavioral intentions and actual use of AI among students was quite high. They actively utilize AI such as chatbots (e.g., ChatGPT) and writing assistance tools (e.g., Grammarly and QuillBot) to enhance their learning and assist with academic tasks. They hold a positive perception of AI, particularly in terms of performance expectancy and effort expectancy. They believe that AI enhances their academic performance and is easy to use. However, students remain neutral regarding social influence and facilitating conditions, suggesting that they feel neither strongly encouraged nor discouraged by their peers to use AI. Additionally, they perceive external support for AI as neutral, indicating a perceived lack of encouragement from academic institutions regarding its use. Students' attitudes toward AI are also neutral, probably due to the absence of standardized guidelines and implementation strategies from academic institutions. This seems to have created uncertainty, as students are unsure whether they are encouraged or discouraged from using AI. As a result, they approach the ethical use of AI with caution. Despite these uncertainties, the students still intend to use AI to enhance their creativity and ideas, innovate their academic methods, and improve the quality of their work.
Author: Soliven, Paolo Carl
Institution: University of the Philippines Open University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W7092367653
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