Artificial Intelligence (AI) has rapidly emerged as a transformative force across diverse sectors worldwide, with policy initiatives signalling its rising prominence. In the realm of education, AI holds promise for revolutionising learning and teaching. However, the incorporation of AI in basic education faces significant challenges for many schools, particularly when explicit curriculum guidelines are absent, and teachers have limited exposure to AI technologies. This study delves into the importance of integrating Artificial Intelligence in Education (AIED), particularly in primary and secondary school settings, with a specific emphasis on the obstacles and facilitators. The research examines the impact of digital leadership and its role in mitigating teachers' barriers to AIED incorporations. These external variables are systematically outlined within the conceptual framework proposed by this study. Furthermore, it conceptualises and considers three AIED approaches—Learning from AI, Learning about AI, and Learning with AI—as internal variables central to basic-education AIED incorporations, as highlighted in previous research. The study gathers quantitative data through a self-constructed questionnaire survey from 204 school principals and management-level teachers across 60 primary and secondary schools in Hong Kong, capturing their perceptions of AIED incorporation. A structural equation model (SEM) is adopted to analyse the relationships between digital leadership, internal and external teacher barriers, and the three AIED approaches. The findings underscore that digital leadership is a significant factor in facilitating AI incorporations in schools, and that teachers' internal and external barriers considerably affect Learning about AI. The paper concludes by proposing strategies to enhance the capabilities of school leaders and teachers in promoting AIED in basic education. Copyright © 2023 The Author(s).

The integration of generative artificial intelligence (AI) in English language teaching presents opportunities and challenges for instructors. This study explores the attitudes of higher education English language instructors towards generative AI tools, their intentions to use them and the institutional support and professional development necessary to teach and learn with them. As the field continues to evolve rapidly, it is essential to comprehend the readiness of front-line language instructors. This qualitative interpretive study seeks to identify the digital competencies and pedagogical knowledge required to implement generative AI in education and provide guidance for the design of professional development programmes that address the challenges and concerns associated with adopting AI. Drawing on semi-structured interviews with twelve instructors at a higher education institution in Hong Kong, the findings reveal the significance of familiarity and confidence with using AI-driven teaching tools, the challenges and concerns language instructors face and the need for tailored support and professional development. The study offers ten practical implications to cultivate language instructors’ digital competencies, pedagogical knowledge and positive attitudes towards integrating AI to enhance their students’ learning experiences. Copyright © 2023 The Authors. Published by Elsevier Ltd.

Artificial Intelligence in Education (AIED) has been the focus of significant attention in recent years because of its growing social importance and pedagogical value. In Hong Kong, an increasing number of K-12 schools are planning or piloting their grassroots AIED incorporation practices. However, progress is reportedly slow due to a number of barriers. Unfortunately, because of their limited scope, disputed interpretations and contextual irrelevance, current research literature seems to be of limited referencing value in aiding schools to address the issues and overcome the barriers. This paper highlights the necessity of embracing AIED as wide-ranging given the current understanding of it as a collective notion. Three major directions of AIED are identified: Learning from AI, Learning about AI, and Learning with AI. A collective case study, which examined the perceived barriers to AIED incorporation in Hong Kong K-12 schools with different AIED directions, was conducted. Qualitative data were gathered via ten semi-structured interviews with key stakeholders from two schools. Ertmer’s (1999) typology was applied to segregate the barriers. The findings showed that both first-order and second-order barriers existed, although they varied between the cases. It was also found that the barriers did not hinder in isolation but appeared to be interconnected. The findings suggest that schools use differentiated strategies to tackle barriers according to their approach to incorporating AIED. Moreover, there is a need to trace the links between barriers and prioritise school efforts to remove or reduce them with high linkage. Several recommendations for practice are given. Copyright © 2021 The Author(s). Published by Elsevier Ltd.