Research Article
Valentine Joseph Owan, Ibrahim Abba Mohammed, Ahmed Bello, Tajudeen Ahmed Shittu
CONT ED TECHNOLOGY, Volume 17, Issue 4, Article No: ep592
ABSTRACT
Despite the increasing interest in artificial intelligence technologies in education, there is a gap in understanding the factors influencing the adoption of ChatGPT among Nigerian higher education students. Research has not comprehensively explored these factors in the Nigerian context, leaving a significant gap in understanding technology adoption in this setting. This study addressed this gap by investigating the predictors of students’ behavioral intentions (BIs) and actual use behavior of ChatGPT through the lens of the unified theory of acceptance and use of technology 2 (UTAUT2) framework. A cross-sectional correlational research design was used to examine the relationships between extended UTAUT variables, BIs, and ChatGPT use behavior. A sample of 8,496 higher education students from diverse institutions in Nigeria participated in the study. The data were collected using the higher education students’ ChatGPT utilization questionnaire, which assessed various factors, such as performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FCs), hedonic motivation (HM), habit (HB), BI, and ChatGPT use behavior. The findings reveal several significant predictors of students’ BIs and actual usage of ChatGPT. PE, SI, HM, and HB were found to be significant positive predictors of BI, while EE and FCs were significant negative predictors. For ChatGPT use behavior, FCs, HM, HB, and BI were significant positive predictors, whereas PE and SI were significant negative predictors. BI mediated the relationships between several factors and ChatGPT usage behavior: positively for some (PE, SI, HM, and HB) and negatively for others (EE and FC). This study contributes to understanding the adoption of ChatGPT in higher education contexts. The findings highlight the importance of addressing usability issues, providing adequate support and resources, promoting a positive user experience, fostering habitual usage, and leveraging social networks to encourage adoption.
Keywords: artificial intelligence, chatbots, GenAI, large language models, technology use
Research Article
Carmen Köhler, Johannes Hartig
CONT ED TECHNOLOGY, Volume 16, Issue 4, Article No: ep528
ABSTRACT
Since ChatGPT-3.5 has been available to the public, the potentials and challenges regarding chatbot usage in education have been widely discussed. However, little evidence exists whether and for which purposes students even apply generative AI tools. The first main purpose of the present study was to develop and test scales that assess students’ (1) knowledge about ChatGPT, (2) actual ChatGPT usage and perceived value of use, and (3) attitude towards ChatGPT. Our second aim was to examine the intercorrelations between these scales, and to investigate differences (a) across five academic fields (i.e., human sciences, social sciences, teaching profession, health sciences, and law and economics) and (b) between stages of education (i.e., number of semesters). N = 693 students from various German universities participated in our online survey. Quality checks (Cronbach’s alpha, MacDonald’s omega, and confirmatory factor analyses) show satisfactory results for all scales. The scales all positively relate to each other, except for the knowledge and attitude scales. This means that more knowledge about ChatGPT is connected to a less favorable attitude regarding the generative AI tool. Lastly, MANOVA and subsequent Bonferroni corrected ANOVA tests show that ChatGPT is mostly used by law and economics students, and most frequently by students in the third year of higher education.
Keywords: ChatGPT in higher education, student knowledge, student use, student attitude, scale development, assessment, large language models (LLMs)