What influences college students using AI for academic writing? - A quantitative analysis based on HISAM and TRI theory

Artificial intelligence (AI) technologies have been widely adopted as tools for academic writing, sparking interest in the factors that influence their adoption. However, existing research has predominantly focused on cognitive factors, such as perceived usefulness and ease of use, while giving insufficient attention to emotional motivations (e.g., perceived enjoyment, emotional engagement) in students' use of AI tools. This gap has led to a somewhat oversimplified or incomplete understanding of the factors influencing students' adoption of AI technologies. This study constructs a theoretical framework based on the Hedonic Information System Acceptance Model (HISAM) and the Technology Readiness Index (TRI), and employs Structural Equation Modeling (SEM) to analyze survey data from 148 university students. The study finds that students' intention to use AI tools is influenced not only by cognitive evaluations, such as perceived usefulness and ease of use, but also by emotional factors, including technological optimism and perceived enjoyment. Perceived enjoyment, as a positive emotional factor in the interaction process, significantly promotes students' usage intention. Additionally, technological optimism, as a positive aspect of technology readiness, has a direct positive effect on perceived enjoyment. Furthermore, although negative experiences such as technical discomfort and insecurity have a minor impact on the evaluation of AI tool functionality, they still affect students' emotional experiences, thereby influencing their usage intention. The study suggests that future AI tool designs should prioritize enhancing students' emotional experiences by providing personalized feedback and optimizing user interfaces to improve ease of use. Moreover, increasing the tool’s interpretability and transparency can help reduce the risks of misuse, such as academic dishonesty or a decline in learning ability, which may arise from negative emotional experiences.

Authors

Institutions

Publication Details

Journal
Computers and Education Artificial Intelligence
Published
2025-03-08
DOI
https://doi.org/10.1016/j.caeai.2025.100391
Citations
16
Primary Topic
Education and Learning Interventions
Type
article
Field-Weighted Citation Impact
51.94

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

What influences college students using AI for academic writing? - A quantitative analysis based on HISAM and TRI theory

Yulu Cui
16 citations
Computers and Education Artificial Intelligence
Education and Learning Interventions
51.94
article

What influences college students using AI for academic writing? - A quantitative analysis based on HISAM and TRI theory

Yulu Cui
article en
16 citations

Abstract

Artificial intelligence (AI) technologies have been widely adopted as tools for academic writing, sparking interest in the factors that influence their adoption. However, existing research has predominantly focused on cognitive factors, such as perceived usefulness and ease of use, while giving insufficient attention to emotional motivations (e.g., perceived enjoyment, emotional engagement) in students' use of AI tools. This gap has led to a somewhat oversimplified or incomplete understanding of the factors influencing students' adoption of AI technologies. This study constructs a theoretical framework based on the Hedonic Information System Acceptance Model (HISAM) and the Technology Readiness Index (TRI), and employs Structural Equation Modeling (SEM) to analyze survey data from 148 university students. The study finds that students' intention to use AI tools is influenced not only by cognitive evaluations, such as perceived usefulness and ease of use, but also by emotional factors, including technological optimism and perceived enjoyment. Perceived enjoyment, as a positive emotional factor in the interaction process, significantly promotes students' usage intention. Additionally, technological optimism, as a positive aspect of technology readiness, has a direct positive effect on perceived enjoyment. Furthermore, although negative experiences such as technical discomfort and insecurity have a minor impact on the evaluation of AI tool functionality, they still affect students' emotional experiences, thereby influencing their usage intention. The study suggests that future AI tool designs should prioritize enhancing students' emotional experiences by providing personalized feedback and optimizing user interfaces to improve ease of use. Moreover, increasing the tool’s interpretability and transparency can help reduce the risks of misuse, such as academic dishonesty or a decline in learning ability, which may arise from negative emotional experiences.

Computers and Education Artificial IntelligenceVol. 8
Xinyang Normal University (CN)
Ministry of Education
Quality Education
Openalex Percentile: Top 0%
Education and Learning Interventions
51.94
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

What influences college students using AI for academic writing? - A quantitative analysis based on HISAM and TRI theory — Yulu Cui · Computers and Education Artificial Intelligence (2025) | TGRS Research Map | TGRS