| Title: |
An Investigation of College Students' Acceptance of AI-Assisted Reading Tools: An Expansion of the TAM and SDT |
| Language: |
English |
| Authors: |
Tiansheng Xia (ORCID 0000-0002-6943-2958); Xinyi Pan; Meitao Cao; Jiayue Guo |
| Source: |
Education and Information Technologies. 2025 30(13):18031-18058. |
| Availability: |
Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/ |
| Peer Reviewed: |
Y |
| Page Count: |
28 |
| Publication Date: |
2025 |
| Document Type: |
Journal Articles; Reports - Research |
| Education Level: |
Higher Education; Postsecondary Education |
| Descriptors: |
College Students; Student Attitudes; Adoption (Ideas); Artificial Intelligence; Computer Assisted Instruction; Reading Instruction; Trust (Psychology); Reading Attitudes; Anxiety; Usability; Reading Skills; Competence; Personal Autonomy |
| DOI: |
10.1007/s10639-025-13491-y |
| ISSN: |
1360-2357; 1573-7608 |
| Abstract: |
Reading provides college students with vital assistance in their efforts to expand their knowledge base. Artificial intelligence (AI)-assisted reading tools have been developed with the aim of improving students' reading efficiency and reading experience. However, the acceptance of such tools and relevant influencing factors remain unknown. This study investigated the factors influencing college students' acceptance of AI-assisted reading tools. An integrative framework consisting of eight variables--perceived social presence (PSE), trust (TR), reading anxiety (RA), perceived usefulness (PU), perceived ease of use (PEOU), perceived competence (PC), perceived autonomy (PA), and behavioral intention (BI)--was constructed with the aim of exploring the effects of these factors on intention to use in this context. The relationships among these variables were analyzed via structural equation modeling (SEM; n = 303). The results indicated that PEOU significantly enhanced college students' behavioral intentions to use AI-assisted reading tools, whereas RA had a significant negative effect on BI. Additionally, an investigation of the relevant mediating paths verified the indirect effects of PSE, TR, PC, and PA on BI. Level of education (undergraduate vs. graduate) had moderating effects on some of these variables. This study provides practical guidance for efforts to use artificial intelligence to facilitate learning among college students; furthermore, this guidance can be generalized by optimizing tool design on the basis of key factors such as RA. The analysis of the variability of these affects across different levels of education can also be extended and applied to other educational fields. |
| Abstractor: |
As Provided |
| Entry Date: |
2025 |
| Accession Number: |
EJ1480874 |
| Database: |
ERIC |