Analyzing Students’ Attitudes and Behavior Toward Artificial Intelligence Technologies in Higher Education

Abstract

In this study, we aim to contribute to the existing literature on the implementation of artificial intelligence (AI) in education. We explore the factors that impact the behavior and attitude of students toward the use of AI in higher education. We employed a quantitative approach using a wide range of adoption theories and models, including the unified theory of acceptance and use of technology model. We formulated hypotheses and verified the conceptual model. A questionnaire was used to collect data from 350 students. The structural equation model (SEM) was applied to estimate the relationship between dependent and independent variables. Based on SEM results, we found that despite perceived risk negatively impacting students’ attitudes, the factors of performance expectancy and facilitating conditions significantly influenced students’ attitudes and their behavioral intention to use AI in education. The results also show that effort expectancy does not significantly influence attitudes toward AI use in higher education. Research limitations are discussed at the end of this study.

Determinants of Humanities and Social Sciences Students’ Intentions to Use Artificial Intelligence Applications for Academic Purposes

“…Despite the burgeoning interest in AI in recent years, there remains a need for more research studies on students' utilization of AI worldwide [39]. Recently, however, a handful of studies employing the UTAUT model across various countries have shed light on a consistent set of factors influencing students' behavioural intentions and acceptance of AI in general [19,25], as well as specifically in chatbot technologies [23,24,26]. Some studies have focused solely on explicating the factors underlying students' behavioural intentions towards using AI applications [19,24], with only one study exploring the moderating effect (specifically, the influence of study years and gender) [40].…”

“…Recently, however, a handful of studies employing the UTAUT model across various countries have shed light on a consistent set of factors influencing students' behavioural intentions and acceptance of AI in general [19,25], as well as specifically in chatbot technologies [23,24,26]. Some studies have focused solely on explicating the factors underlying students' behavioural intentions towards using AI applications [19,24], with only one study exploring the moderating effect (specifically, the influence of study years and gender) [40]. Moreover, three studies have examined these factors within the context of the European Union, specifically in England [23], Spain [26], and Poland [40].…”

“…Table 1 provides an overview of recent studies concerning higher education students' behavioural intention to utilize AI applications for academic purposes. Notably, Alzahrani [19], employing a combination of TAM and UTAUT models with a sample of 350 students from universities in Saudi Arabia, investigated the factors influencing students' behavioural intention to use AI applications in general. Their findings revealed that performance expectancy, effort expectancy, and facilitating conditions significantly impacted behavioural intention.…”

“…In order to effectively use specific applications, it is essential to understand the experiences of students who have used them in the past [8] and to identify the factors that influence their intention to use them in the future [19]. However, limited studies have been conducted on this topic in the European Union, with only a few studies conducted in Greece [20].…”

“…However, limited studies have been conducted on this topic in the European Union, with only a few studies conducted in Greece [20]. Previous studies have primarily used the technology acceptance model (TAM), e.g., [21,22] and, to a lesser degree, the Unified Theory of Acceptance and Use of Technology (UTAUT), e.g., [19,[23][24][25][26]. However, these studies have investigated the factors influencing the intention to use these applications with participants from various scientific disciplines without specifying any particular field of study.…”