ABSTRACT VIEW
Abstract NUM 205

UNCOVERING THE DRIVING FORCES BEHIND PRE-SERVICE ELT STUDENTS' INTENTIONS TO EMBRACE CHATGPT IN UZBEKISTAN
N. Köse1, K.M. Kudratovna2
1 Bartın University (TURKEY)
2 Urgench State Pedagogical Institute (UZBEKISTAN)
The integration of AI tools, such as ChatGPT, into language education is growing rapidly and one of the outstanding areas it is integrated is education, particularly language education. As future educators, pre-service English Language Teaching (ELT) students are crucial in shaping the implementation of emerging technologies in classrooms. This study examines their acceptance of ChatGPT through the framework of the Unified Theory of Acceptance and Use of Technology (UTAUT2), which has received a significant number of citations in a short time after it was developed. The predictors of UTAUT2 are Performance Expectancy (PE), Facilitating Conditions (FC), Effort Expectancy (EE); Hedonic Motivation (HM); Social Influence (SI); Habit (HT); Personal Innovativeness (PI). This study explored the determinants of Behavioral Intention (BI); and Use Behavior (UB). Conducted as a cross-sectional survey, data were collected in Uzbekistan in May 2025, from 456 pre-service ELT students from different universities completing an anonymous online questionnaire via Google Forms. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with a weighting path scheme implemented in SmartPLS 4 software. The findings reveal that four predictors that are HT, PE, EE and PI have a positive and significant impact on BI. On the other hand, SI, FC and HM did not have a significant impact on BI. Additionally, FC, HT, and BI did not have an impact on UB. Gender and study year were included as mediating factors in the model and the results indicated that they did not have a significant moderating impact. These results emphasize the important influence of HT, PE, EE and PI on the intention of pre-service ELT students to use ChatGPT, while the other factors from the UTAUT2 framework did not have a significant effect. Notably, this is the first study to recruit participants from Uzbekistan using the UTAUT2 framework. Future research could involve samples from different universities across the country to further understand the acceptance and use behaviors of students in Uzbekistan.

Keywords: AI, ChatGPT, UTAUT2, foreign language learning.

Event: ICERI2025
Session: Emerging Technologies in Education
Session time: Monday, 10th of November from 11:00 to 13:45
Session type: POSTER