Date of Defense
19-6-2025 9:00 AM
Location
H1-2024
Document Type
Thesis Defense
Degree Name
Master of Education (Special Education)
College
CEDU
Department
Special and Gifted Education
First Advisor
Dr. Maxwell Peprah Opoku
Keywords
Inclusive education, Artificial intelligence, learning difficulties, United Arab Emirates
Abstract
The integration of Artificial Intelligence (AI) in education offers significant potential for identifying and supporting all students including those with learning difficulties. Although discussions on potential of AI to advance the learning of students is ongoing, AI usage among teachers to support the teaching of students with learning disabilities in non-western context such as the United Arab Emirates, is unresearched. The goal of this study was to explore the synergy between teachers’ behavioural intention and pedagogical content knowledge towards using AI to teach students with learning difficulties. The study was guided by unified theory of acceptance and use of technology and Technological pedagogical and content knowledge model to examine teachers' intentions toward adopting AI tools to enhance educational outcomes for students with learning disabilities in the UAE. Using a quantitative research approach, a structured survey was completed by 244 teachers from both public and private schools. The data was subjected to analysis such as structural equation modelling to test the structural validity of the theory of planned behaviour. More so, multivariate analysis of variance and path analysis were computed to explore the relationship between behavioural intentions towards AI and teachers’ AI pedagogical content knowledge. The findings provided support from instruments used to measure intentions and AI pedagogical content knowledge. Moreover, differences were found between participants on age on AI-Technology Pedagogical Knowledge and AI-Technology Pedagogical Content Knowledge. Specifically, young teachers had higher AI-technological content knowledge than older counterparts. The implications of the study for educational policymakers, school leaders, and AI developers, are discussed in details.
Included in
BEHAVIOURAL INTENTIONS AND TECHNOLOGICAL PEDAGOGICAL AND CONTENT KNOWLEDGE OF TEACHERS TOWARDS USING ARTIFICIAL INTELLIGENCE TO TEACH STUDENTS WITH LEARNING DIFFICULTY/DISABILITIES IN THE UNITED ARAB EMIRATES
H1-2024
The integration of Artificial Intelligence (AI) in education offers significant potential for identifying and supporting all students including those with learning difficulties. Although discussions on potential of AI to advance the learning of students is ongoing, AI usage among teachers to support the teaching of students with learning disabilities in non-western context such as the United Arab Emirates, is unresearched. The goal of this study was to explore the synergy between teachers’ behavioural intention and pedagogical content knowledge towards using AI to teach students with learning difficulties. The study was guided by unified theory of acceptance and use of technology and Technological pedagogical and content knowledge model to examine teachers' intentions toward adopting AI tools to enhance educational outcomes for students with learning disabilities in the UAE. Using a quantitative research approach, a structured survey was completed by 244 teachers from both public and private schools. The data was subjected to analysis such as structural equation modelling to test the structural validity of the theory of planned behaviour. More so, multivariate analysis of variance and path analysis were computed to explore the relationship between behavioural intentions towards AI and teachers’ AI pedagogical content knowledge. The findings provided support from instruments used to measure intentions and AI pedagogical content knowledge. Moreover, differences were found between participants on age on AI-Technology Pedagogical Knowledge and AI-Technology Pedagogical Content Knowledge. Specifically, young teachers had higher AI-technological content knowledge than older counterparts. The implications of the study for educational policymakers, school leaders, and AI developers, are discussed in details.