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Analyzing Preceding factors affecting behavioral intention on communicational artificial intelligence as an
Patrick M Cortez1, Ardvin Kester S Ong1,2, John Francis T Diaz3
1School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila, 1002, Philippines.
Heliyon
|February 15, 2024
Summary
Students increasingly use communicational AI (CAI) for academic tasks, driven by perceived relatedness and autonomy. Their intention to use CAI is linked to productivity gains and specific technology acceptance factors.
Area of Science:
- Educational Technology
- Human-Computer Interaction
- Psychology of Technology Use
Background:
- The global pandemic accelerated AI adoption in education.
- Student behavior evolved with the return to in-person instruction.
- Understanding AI's role in academic settings is crucial.
Purpose of the Study:
- To analyze students' behavioral intention and actual academic use of communicational AI (CAI).
- To investigate factors influencing CAI adoption in education.
- To integrate technology acceptance and self-determination theories.
Main Methods:
- An integrated framework combining UTAUT2 and self-determination theory was used.
- Online survey data from 533 students were collected and analyzed.
- Structural Equation Modeling (SEM) was employed for data analysis.
Main Results:
- Perceived relatedness and perceived autonomy significantly influenced behavioral intention to use CAI.
- Facilitating conditions, habit, and performance expectancy directly affected behavioral intention.
- Students primarily used CAI to enhance productivity and achieve objectives.
Conclusions:
- Social and psychological factors are key drivers for CAI adoption in education.
- Technology acceptance models need to incorporate self-determination principles for educational contexts.
- Findings offer insights for developing and implementing educational AI tools.
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