Analyzing Preceding Factors Affecting Behavioral Intention on Communicational Artificial Intelligence as an Educational Tool

Research by: Patrick M. Cortez, Ardvin Kester S. Ong , John Francis T. Diaz, Josephine D. German and Singh Jassel Satwant Singh Jagdeep

EXECUTIVE SUMMARY

The research employed a comprehensive approach by integrating the Unified Theory of Acceptance and Use of Technology (UTAUTA2) and Self-Determination Theory (SDT) to evaluate the behavioral intentions of students using communicational artificial intelligence (AI) applications for educational purposes. Utilizing the Structural Equation Model (SEM), the research explored the relationships among various factors like Habit, Perceived relatedness, Perceived Autonomy, Effort Expectancy, Price Value, Perceived Competency, Hedonic Motivation, Facilitating Condition, Performance Expectancy, and Behavioral Intention in influencing the Actual Usage of communicational AI applications in an educational context.

The study revealed that students’ behavioral intentions to use communicational AI tools are significantly influenced by their perceived relatedness. Peer influence and conversations played a crucial role, emphasizing that students tend to adopt these applications when recommended by peers with similar academic goals. Students’ perceptions of autonomy were found to be a significant factor affecting their behavioral intentions. The sense of freedom and control over academic work, coupled with the ability to express opinions and make improvements, contributes to the positive inclination towards using communicational AI tools.

The availability of necessary resources and support emerged as a crucial factor influencing behavioral intentions. Students’ access to CAI applications for free, coupled with provided knowledge and skills, played a pivotal role in shaping their intent to use these tools. Students found communicational AI applications useful in enhancing academic activities, correcting errors, and improving efficiency. The perceived improvement in academic output positively influenced behavioral intentions. The research also emphasized that actual use is a significant factor influencing behavioral intentions. Students believe that the regular utilization of communicational AI tools enhances academic performance, especially during the pandemic, when reliance on these tools increased due to the shift to remote learning.

The integration of UTAUT2 and SDT provided valuable insights into the primary variables influencing students’ behavioral intentions. The study suggests that researchers could further explore the integration of the Theory of Planned Behavior (TPB) to identify additional motivational factors. The SEM analysis was deemed effective in establishing accurate causal relationships among latent variables. Perceived relatedness and perceived autonomy were identified as primary influencers of students’ behavioral intentions. The study recommends educational institutions to encourage cautious use of communicational AI applications, emphasizing the benefits of relatedness and autonomy. Additionally, universities should provide free CAI applications, conduct seminars, and promote real-time interaction features to enhance students’ engagement.

The study acknowledges limitations, such as the exclusive focus on behavioral intention without evaluating the actual effectiveness of CAI tools. Future research is encouraged to explore diverse behavioral intentions and consider advanced analysis methods like machine learning. Evaluating academic output, performance, and development with CAI applications could provide a more comprehensive understanding of their impact. Nonetheless, this study contributes to the understanding of student behavior towards communicational AI applications in education, offering valuable insights for educational institutions, developers, and researchers to optimize the integration of technology in the learning environment.

To cite this article:  Cortez, P. M., Ong, A. K. S., Diaz, J. F. T., German, J. D., & Jagdeep, S. J. S. S. (2024). Analyzing preceding factors affecting behavioral intention on communicational artificial intelligence as an educational tool. Heliyon, 10(3), e25896. https://doi.org/10.1016/j.heliyon.2024.e25896

To access this article: https://doi.org/10.1016/j.heliyon.2024.e25896

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Heliyon is an all-science, open-access journal that is part of the Cell Press family. Any paper reporting scientifically accurate and valuable research, which adheres to accepted ethical and scientific publishing standards, will be considered for publication. As such, the journal also publishes manuscripts reporting negative/null results, incremental advances, and replication studies.

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