Adoption of Artificial Intelligence in Schools: Unveiling Factors Influencing Teachers’ Engagement

Cukurova, Mutlu; Miao, Xiangshui; Brooker, Richard A.

doi:10.1007/978-3-031-36272-9_13

Cited by 16 publications

(5 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For instance, teachers can participate in dedicated professional development programmes to learn how to use platforms that evaluate students' written assignments (Nazaretsky, Ariely, et al., 2022). On the other hand, there are platforms designed for teachers that can be implemented in schools to enhance learning (Cukurova et al., 2023). Additionally, instruments have been developed to measure how teachers adopt and use AI‐powered tools and how they address various concerns, such as trust, the absence of human characteristics and transparency in AI decision‐making processes (Nazaretsky, Cukurova, et al., 2022).…”

Section: Discussionmentioning

confidence: 99%

Investigation of the moderation effect of gender and study level on the acceptance and use of generative AI by higher education students: Comparative evidence from Poland and Egypt

Strzelecki,

ElArabawy

2024

Brit J Educational Tech

View full text Add to dashboard Cite

This study delves into the implications of incorporating AI tools, specifically ChatGPT, in higher education contexts. With a primary focus on understanding the acceptance and utilization of ChatGPT among university students, the research utilizes the Unified Theory of Acceptance and Use of Technology (UTAUT) as the guiding framework. The investigation probes into four crucial constructs of UTAUT—performance expectancy, effort expectancy, social influence and facilitating conditions—to understand their impact on the intent and actual use behaviour of students. The study relies on data collected from six universities in two countries and assessed through descriptive statistics and structural equation modelling techniques, and also takes into account participants' gender and study level. The key findings show that performance expectancy, effort expectancy, and social influence significantly influence behavioural intention. Furthermore, behavioural intention, when considered alongside facilitating conditions, influences actual use behaviour. This research also explores the moderating impact of gender and study level on the relationships among these variables. The results not only augment our comprehension of technology acceptance in the context of AI tools but also provide valuable input for formulating strategies that promote effective incorporation of ChatGPT in higher education. The study underscores the need for effective awareness initiatives, bespoke training programmes, and intuitive tool designs to bolster students' perceptions and foster the wider adoption of AI tools in education.Practitioner notesWhat is already known about this topic ChatGPT is a tool that is quickly gaining worldwide recognition. ChatGPT helps with writing essays and solving assignments. ChatGPT raises ethical concerns about authorship, plagiarism and ethics. What this paper adds This study explores students' acceptance of ChatGPT as an aid in their education, which has not been studied previously. We used the extended Unified Technology Acceptance and Use of Technology theory to test what factors mostly influence the use of ChatGPT by students. We conducted a multiple study in Poland and Egypt based on sampling strategy from six universities. Implications for practice and/or policy ChatGPT is a global game changer and should be incorporated into study programmes. The limitations of ChatGPT should be well explained and known since it is prone to making mistakes. Higher education teachers should be aware of ChatGPT's capabilities.

show abstract

Section: Discussionmentioning

confidence: 99%

Investigation of the moderation effect of gender and study level on the acceptance and use of generative AI by higher education students: Comparative evidence from Poland and Egypt

Strzelecki,

ElArabawy

2024

Brit J Educational Tech

View full text Add to dashboard Cite

show abstract

“…It has the potential to support teachers to perceive more about students' engagement during the collaboration process so teachers are able to provide feedback or learning suggestions timely, individually, and specically. This step towards more transparency is signicant, yet there are many other issues in the adoption and use of these approaches in practice that relate to ethical considerations [1], socio-cultural factors of the education system [11], as well as psycho-physiological factors of individual teachers e.g. cognitive load [34] which all require further investigations.…”

Section: Discussionmentioning

confidence: 99%

Harnessing Transparent Learning Analytics for Individualized Support through Auto-detection of Engagement in Face-to-Face Collaborative Learning

Zhou,

Suraworachet,

Cukurova

2024

Proceedings of the 14th Learning Analytics and Knowledge Conference

Self Cite

View full text Add to dashboard Cite

Using learning analytics to investigate and support collaborative learning has been explored for many years. Recently, automated approaches with various articial intelligence approaches have provided promising results for modelling and predicting student engagement and performance in collaborative learning tasks. However, due to the lack of transparency and interpretability caused by the use of "black box" approaches in learning analytics design and implementation, guidance for teaching and learning practice may become a challenge. On the one hand, the black box created by machine learning algorithms and models prevents users from obtaining educationally meaningful learning and teaching suggestions. On the other hand, focusing on group and cohort level analysis only can make it dicult to provide specic support for individual students working in collaborative groups. This paper proposes a transparent approach to automatically detect student's individual engagement in the process of collaboration. The results show that the proposed approach can reect student's individual engagement and can be used as an indicator to distinguish students with dierent collaborative learning challenges (cognitive, behavioural and emotional) and learning outcomes. The potential of the proposed collaboration analytics approach for scaolding collaborative learning practice in face-to-face contexts is discussed and future research suggestions are provided. CCS CONCEPTS• Applied computing ! Education; Collaborative learning; • Human-centered computing ! Collaborative and social computing; Empirical studies in collaborative and social computing.

show abstract

“…For example, educators have opportunities to undergo specialized training modules to familiarize themselves with platforms that assess student essays (Nazaretsky et al, 2022a). Similarly, there are specific platforms tailored for educators that can be introduced in educational settings to elevate the learning experience (Cukurova et al, 2023). There are also tools designed to gauge the degree to which educators embrace AI-driven utilities and address potential issues like trustworthiness, the lack of human-like attributes, and clarity in AI's decisionmaking patterns (Nazaretsky et al, 2022b).…”

Section: Discussionmentioning

confidence: 99%

“…With its roots in deep neural network architectures, and further powered by transformer designs, Large Language Models (LLMs) like ChatGPT or LLaMA harness billions of parameters, making strides in various natural language processing tasks (OpenAI, 2023;Touvron et al, 2023). Notably, educators have leveraged the capabilities of such LLMs for diverse purposes, ranging from augmenting learning experiences through dynamic feedback to the facilitation of language acquisition (Cukurova et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

Students’ Acceptance of ChatGPT in Higher Education: An Extended Unified Theory of Acceptance and Use of Technology

Strzelecki

2023

Innov High Educ

View full text Add to dashboard Cite

AI-powered chat technology is an emerging topic worldwide, particularly in areas such as education, research, writing, publishing, and authorship. This study aims to explore the factors driving students' acceptance of ChatGPT in higher education. The study employs the unified theory of acceptance and use of technology (UTAUT2) theoretical model, with an extension of Personal innovativeness, to verify the Behavioral intention and Use behavior of ChatGPT by students. The study uses data from a sample of 503 Polish state university students. The PLS-SEM method is utilized to test the model. Results indicate that Habit has the most significant impact (0.339) on Behavioral intention, followed by Performance expectancy (0.260), and Hedonic motivation (0.187). Behavioral intention has the most significant effect (0.424) on Use behavior, followed by Habit (0.255) and Facilitating conditions (0.188). The model explains 72.8% of the Behavioral intention and 54.7% of the Use behavior variance. While the study is limited by the sample size and selection, it is expected to be a starting point for more research on ChatGPT-like technology in university education, given that this is a recently introduced technology.

show abstract

Adoption of Artificial Intelligence in Schools: Unveiling Factors Influencing Teachers’ Engagement

Cited by 16 publications

References 23 publications

Investigation of the moderation effect of gender and study level on the acceptance and use of generative AI by higher education students: Comparative evidence from Poland and Egypt

Investigation of the moderation effect of gender and study level on the acceptance and use of generative AI by higher education students: Comparative evidence from Poland and Egypt

Harnessing Transparent Learning Analytics for Individualized Support through Auto-detection of Engagement in Face-to-Face Collaborative Learning

Students’ Acceptance of ChatGPT in Higher Education: An Extended Unified Theory of Acceptance and Use of Technology

Contact Info

Product

Resources

About