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This study investigated how pre-service teachers perceive and plan to use a virtual reality classroom for science teaching during microteaching practices. The UTAUT 2 model was adopted as the conceptual framework for this study. Data were collected through an online survey from eighty-three pre-service science teachers from a large metropolitan uni...
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... Understanding teachers' attitudes is essential for encouraging the effective use of mobile apps, particularly in providing personalized education tailored to students' needs. Preservice teachers' intentions to integrate mobile apps into classrooms are affected by various factors, including prior experience, institutional support, and training [28]. By understanding these factors, it becomes possible to foster positive attitudes toward technology integration in education, potentially leading to improved outcomes for SWLD. ...
Grounded in the Theory of Reasoned Action, this study aims to examine how technology self-efficacy and attitudes toward AI-based mobile applications predict preservice special education teachers’ (SETs) intentions to integrate these applications into teaching students with learning disabilities (SWLD). A stepwise multiple regression analysis assessed the impact of these variables on preservice teachers’ intentions. Data were collected from 173 preservice SETs. The results revealed that preservice teachers exhibited moderate levels of technology self-efficacy, intentions to integrate AI-based mobile applications, and attitudes toward these applications. Furthermore, attitudes toward AI-based mobile applications emerged as the strongest predictor of teachers’ intentions to integrate these technologies (r = 0.878, p < 0.05), while technology self-efficacy also had a significant effect (r = 0.698, p < 0.05). Together, these variables accounted for 76% of the variance in intentions (R2 = 0.77). These findings underscore the important role of technology self-efficacy and positive attitudes in affecting teachers’ adoption of AI-based mobile applications. This study addresses the gap in the literature on integrating AI technologies in special education and emphasizes their potential to enhance teaching practices for SWLD. Based on the findings, the study recommends training and support to improve preservice teachers’ self-efficacy and attitudes toward AI-based mobile applications, facilitating their integration into special education settings.
... Satisfaction questionnaires applied to XR students have undoubtedly determined that they increased interest in classes [8]. Some areas in which the use of XR tools has increased critical thinking have been biology [9], primary education [10] Astronomy sessions [11], and virtual science laboratories [12]. ...
... Although the UTAUT-2 model has recently been applied to educational technologies in the context of science education (Ateş & Garzón, 2023;Ogegbo et al., 2024), there remains a significant research gap concerning the adoption of humanoid robots in this domain. Most existing studies focus on general robotics (Suhail et al., 2024), the use of robotics in STEM education (Ateş & Gündüzalp, 2024), or artificial intelligence integration in science education (Al Darayseh, 2023;Ateş, 2024). ...
... For educators, particularly science teachers, technologies that promise improved pedagogical outcomes and efficiency are more likely to be adopted, as they directly align with professional objectives of enhancing teaching quality and improving student engagement (Ateş & Garzón, 2022). Similarly, Effort Expectancy, which parallels perceived ease of use in TAM, has been recognized as a fundamental driver in adoption, especially in educational settings where teachers face substantial time constraints and varying levels of technological proficiency (Ateş & Yilmaz, 2024;Ogegbo et al., 2024). The simplicity of technology implementation minimizes barriers to adoption and is crucial for encouraging educators to experiment with new tools without apprehension. ...
This study examines the factors influencing science teachers’ intentions to adopt humanoid robots in educational settings. It employs the Unified Theory of Acceptance and Use of Technology 2 (UTAUT-2) and the Technology-Organization-Environment (TOE) framework as guiding theoretical models. By integrating UTAUT-2, which emphasizes individual factors, and TOE, which addresses organizational and environmental influences, the study constructs a comprehensive model that explores both personal and contextual drivers of adoption. Utilizing structural equation modeling on a sample of 1,150 pre-service and in-service science teachers, the study reveals that the integrated model demonstrates superior predictive power compared to each framework individually. Results highlight the moderating role of professional experience in the adoption process, with significant differences identified between pre-service and in-service teachers. The findings reveal significant differences between pre-service and in-service teachers, illustrating the moderating role of professional experience in the adoption process. This study provides a deeper understanding of how motivational, organizational, and environmental factors interact to influence adoption intentions. These insights provide practical guidance for developing targeted training programs, promoting institutional readiness through well-crafted policy initiatives, and implementing pilot projects to support schools in the effective integration of humanoid robots into educational curricula. These findings provide actionable insights for educational policymakers and practitioners aiming to enhance teaching quality and student engagement through innovative technologies.
... This is particularly important in the training of pre-service teachers, who need to develop the necessary skills and knowledge to integrate ICT into their future classrooms effectively [17,21,63]. Many nations around the world have adopted technology as a tool to improve learning practices among pre-service teachers [33,46]. Although many countries have taken considerable reforms by introducing ICT policies in education, questions persist regarding the extent to which these reforms have actually improved educational practices [26,41,45]. ...
This study aimed to explore college tutors' perspectives on the integration of information and communication technology (ICT) in teaching pre-service early-grade teachers in teacher colleges in Tanzania. The study was guided by two research objectives: (1) to investigate the professional learning support tutors receive and (2) to examine the factors impeding the integration of ICT in teaching pre-service early childhood teachers in the classroom. The purposive sampling technique was employed in sampling the four teacher colleges and four principals, while the convenience sampling technique was used to sample the 41 tutors who participated in this study. A collective case study design was used to explore participants' perspectives on the deployment of ICT integration in their daily teaching. Data collected from the participants were thematically analysed. The study findings show that the majority of tutors had limited regular professional training opportunities on the integration of ICT in teaching. The study findings revealed several factors hindering tutors from integrating ICT in their teaching, including limited technological resources, lack of technical support, unreliable internet, absence of integration guides, insufficient digital security knowledge, lack of familiarity with learning management systems, low digital competence, and outdated technological devices. The study, therefore, concludes that inadequate integration of ICT among tutors exacerbates limited acquisition of the necessary digital literacy skills among early-grade pre-service teachers. In this regard, the study recommends that the government engage tutors in regular training on the use of ICT in classroom practices. Furthermore, ICT tools and devices should be available in teacher colleges for tutors to utilise in their instructional practices for pre-service early childhood teachers.
... For instance, UTAUT has been applied in investigating mobile learning acceptance (Fagan, 2019), students' use of learning management systems (Raza et al., 2021), social-media-based learning (Rahman et al., 2021). Additionally, the UTAUT model is also applied to many of the latest educational technologies, including augmented reality acceptance among university students (Ustun et al., 2024), virtual reality classroom (Ogegbo et al., 2024), metaverse integrated learning environments (Wiangkham & Vongvit, 2024), teachers' and students' acceptance and use of generative artificial intelligence (Xiaohong et al., 2024) such as ChatGPT (Budhathoki et al., 2024), AI-based assessment systems (Shahid et al., 2024), and academic advising chatbot (Bilquise et al., 2024). ...
Artificial intelligence (AI) offers numerous benefits to the field of language education, making it crucial to understand the factors influencing language teachers’ adoption of these technologies. This study investigates the determinants of language teachers’ adoption of AI chatbots in educational settings. Drawing on the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Technological Pedagogical Content Knowledge (TPACK) framework, a comprehensive model of AI adoption among language teachers is proposed and tested. Data were collected from 276 language teachers in Vietnam through an online survey. Partial Least Square-Structural Equation Modeling (PLS-SEM) was employed to analyze the data. Results indicate that AI adoption intent significantly predicts AI integration, while performance expectancy, effort expectancy, and AI self-efficacy are key determinants of AI adoption intent. AI-TPACK emerges as a crucial factor, strongly influencing AI self-efficacy, performance expectancy, and effort expectancy. Facilitation is found to be a significant predictor of AI-TPACK. These findings enhance the theoretical framework of AI adoption in language education and provide valuable insights for fostering effective AI integration among language teachers.
... In addition to practical factors, UTAUT 2 also considers more personal and experiential constructs such as hedonic motivation and habit, which provide insights into the affective and behavioral dimensions of technology use. For example, Ogegbo et al. (2024) examined how hedonic motivation can significantly influence teachers' willingness to experiment with and adopt new tools. Their findings suggest that when teachers perceive VR and AR as enjoyable or engaging, they are more likely to integrate them into their teaching and assessment practices. ...
... Similarly, habit has been shown to affect how seamlessly teachers adopt new technologies. Ogegbo et al. (2024) found that teachers who developed a habit of using educational technologies were more likely to continue using them over time, thus reinforcing their long-term integration into classroom practices. ...
This investigation elucidates the adoption and integration of Augmented Reality (AR) and Virtual Reality (VR) technologies within educational assessments, focusing on the distinctions between pre-service and in-service teachers. Leveraging an integrated theoretical framework that combines the General Extended Technology Acceptance Model for E-Learning (GETAMEL) with the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), this study rigorously examines the multifaceted factors influencing educators' acceptance and utilization of these emergent technologies. Data were meticulously gathered from a sample of 862 teachers—457 pre-service and 405 in-service—via detailed surveys tailored separately for AR and VR technologies. Employing confirmatory factor analysis and structural equation modeling, the study validates the measurement model and evaluates the hypothesized relationships within the framework. Results underscore significant pathways, accentuating the roles of perceived ease of use, perceived enjoyment, and social influence in shaping educators’ intentions to adopt AR and VR technologies. Notably, the analysis reveals divergent perceptions and integration strategies between pre-service and in-service teachers concerning these technologies. While pre-service teachers predominantly value usability and enjoyment, in-service teachers focus on the pragmatic integration and benefits of AR and VR in existing pedagogical practices. The findings furnish critical insights for policymakers, educational technology developers, and practitioners, aiming to amplify the efficacy and appeal of AR and VR applications in educational settings.
... In addition, Alalwan et al. (2020) note that while many teachers are enthusiastic about the potential of VR, factors such as lack of training, limited access to resources, and concerns about the technology's complexity can hinder adoption to large extents. In relation to adoption of VR, many authors contend that when teachers perceive these tools as effective in enhancing student learning outcomes, they are more likely to integrate them into their teaching (Parsons & MacCallum, 2020;Lee & Hwang, 2022;Al Breiki et al., 2023;AlGerafi et al., 2023;Romano et al., 2023;Silva-Díaz et al., 2023;Thohir et al., 2023;Ogegbo et al., 2024). Mystakidis and Christopoulos (2022) too, explore K-12 teachers' perceptions of the Metaverse, finding that teachers who are open to experimenting with new technologies and who perceive the Metaverse as a valuable educational tool are more likely to adopt it in their teaching. ...
... However, price value was not included in this study because teachers' use of digital resources did not generally take into account the effect of price (Zhou et al., 2022). Previous reports have shown that the ability of the UTAUT model to predict technology acceptance can be improved by increasing the number of external variables (Ogegbo et al., 2024). Considering that teachers' ability to integrate technology in this process was a factor that cannot be ignored (Ling Koh et al., 2014), TPACK was included as a variable. ...
Technology integration into education is a significant development that has facilitated using digital resources in teaching mathematical culture (TMC). Despite the potential benefits, there are currently limited reports on factors influencing teachers’ use of these resources for instructional purposes. Therefore, this study aims to determine the influence of Technological Pedagogical Content Knowledge (TPACK) on teachers’ behavioral intention and usage behavior towards digital resources in TMC. The study procedures were carried out based on the revised Unified Theory of Acceptance and Use of Technology (UTAUT-2) model. A quantitative analysis and an online survey were conducted with 418 mathematics teachers from three provinces in central and western China. The data obtained were then analyzed using partial least squares structural equation modeling (PLS-SEM). The results showed that (1) performance expectancy, social influence, hedonic motivation, and habit significantly influenced teachers’ behavioral intention to use digital resources, and (2) behavioral intention as a mediator significantly promoted usage behavior with facilitating conditions, habit, and TPACK having similar effects. These results have managerial and practical implications for scholars, teachers, school principals, and policy-makers who advocate for integrating digital resources in educational contexts.
... Understanding users' EE is critical to designing user-friendly technology solutions that promote adoption. Research suggests a positive relationship between EE and teachers' intentions to adopt technology (Al-Adwan et al., 2024;Du & Liang, 2024;Ogegbo et al., 2024). ...
... Our results also showed that effort expectancy is a significant element explaining pre-service teachers' intention to imploy T-bot. This is consistent with previous research where individuals are more likely to adopt new technologies if they perceived them as easy to use (Al-Adwan et al., 2024;Cortez et al., 2024;Das & Datta, 2024;Du & Liang, 2024;Ogegbo et al., 2024;Salifu et al., 2024;Strzelecki, 2023;Wu et al., 2022). While these studies may not have looked specifically at T-bots, they all consistently show that ease of use leads to a more positive outlook on the integration of AI in education. ...
In the ever-changing landscape of education, the integration of technology has become an inevitable force that reshapes the foundations of teaching and learning. Amidst this transformative wave, the concept of Artificial Intelligence (AI) has taken center stage, promising innovative approaches, and increased efficiency. Within this context, the exploration of preservice teachers’ behavioural intention to employ AI in lesson planning has emerged as a critical issue for examination. This study used a descriptive cross-sectional survey design and employed a purposive sampling technique to recruit 783 preservice teachers. By employing a cutting-edge dual-staged partial least squares structural equation modelling-artificial neural network (PLS-SEM-ANN) approach, this study investigated the influence of the following essential variables on preservice teachers’ intentions to incorporate AI into their lesson planning endeavours: performance expectancy, effort expectancy, habit, hedonic motivation, social influence, and facilitating conditions. Social influence emerged as the most significant positive predictor of preservice teachers’ behavioural intention to use AI in lesson planning. Additionally, habit, performance expectancy, effort expectancy, and facilitating conditions substantially positively influenced preservice teachers’ behavioural intention to use AI in lesson planning. Conversely, hedonic motivation did not significantly affect preservice teachers’ behavioural intention to use AI in lesson planning. This study not only enhances our understanding of technology integration in pedagogy from a theoretical standpoint but also provides practical recommendations for refining educational curricula and instructional strategies that promote effective AI integration.
