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).

STEM education has taken on high importance in Hong Kong K-12 education landscape. Despite policy advocacy and curriculum endeavour, the quality of STEM education varies significantly between schools. Research literature indicates that high-quality STEM education requires teachers’ rigorous delivery of topics and appropriate pedagogies, and one approach to improve such practices is teacher professional development (TPD). However, because current research on TPD has not given explicit consideration to the complex nature of STEM education, there remains a lack of a clear blueprint of how TPD should be conducted to build teachers’ capacity for STEM education effectively. This paper presents a case study that explores the necessary attributes and identifies the missing links of STEM education TPD by understanding how various TPD models supported a Hong Kong K-12 school embracing STEM education. Qualitative data collection methods, including semi-structured interviews and classroom observations, were employed to draw a picture of TPD implementations in the selected school. The findings suggest that, at the macro-level, effective STEM TPD should not stop at employing mixed use of TPD models; the models have to be integrated organically with respect to a school-based STEM curriculum implementation approach. A collaborative culture between teachers must be cultivated for effective inter-disciplinary integration. Collaborative action research should also be promoted to develop collective wisdom of STEM pedagogies. At the micro-level, TPACK and cross-disciplinary integration skills need to be focusing areas of STEM TPD. With these guiding principles, some possible strategies for effective STEM education TPD are suggested. Copyright © 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

BACKGROUND: In recent years, there has been considerable interest in taking up the opportunities of Artificial Intelligence (AI) in education. As an emerging concept and a driving technological force, AI is changing the kind of knowledge and skills students need for success in the forthcoming Industrial Revolution 4.0, and at the same time, enabling novel, powerful methods of teaching and learning. Although many school leaders, policy-makers and frontline teachers understand the need for embracing AI, they may lack clarity on what to teach students in the era of AI; how to harness the power of AI tools; and where to start given their own school contexts. This paper describes an ongoing study that uses Communities of Practice (CoPs) as a knowledge management strategy to support Hong Kong K-12 schools in embracing AI. CoPs comprise members who genuinely care about a mutual interest and seek to solve a common problem. The premise underlying this study is that the cultivation of CoPs may present enabling conditions and pave the way for AI adoptions. In these CoPs, members would engage in reflective discussions on the opportunities and challenges of embracing AI in their schools and collaboratively support each other through meaningful knowledge exchange. METHODS: A collective case study is being conducted with members from 20 K-12 schools in Hong Kong to substantiate and illustrate the power of CoPs that aim to support schools in embracing AI. Qualitative data are gathered via semi-structured interviews and focus-group meetings with participants. Thematic analysis is adopted for analysing the data. RESULTS: The preliminary results of this ongoing study have shown that CoPs, if successfully launched, can play an uplifting role for Hong Kong K-12 schools embracing AI. More specifically, the collaborative learning process in CoPs has helped members make sense of AI core concepts and the pedagogical implications as they access authentic, relevant and updated information. The

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.

This case study examines how blended learning professional development for teaching staff is driven and implemented in the Faculty of Education and Human Development (FEHD) at The Education University of Hong Kong (EdUHK). Professional development at EdUHK was first implemented by equipping teaching staff with the technical knowhow to incorporate blended learning into their teaching practices. This Institute-based attempt resulted in a growing number of teaching staff using blended learning. The technology-driven professional development approach was rethought to encourage more teaching staff to adopt blended learning in their courses. Based on strategies identified from the literature, a faculty-driven approach for professional development was developed in the FEHD. This approach included pedagogically focused capacity building strategies that aimed to enhance learning engagement and outcomes and scale up blended learning practices in the faculty. Concerted efforts have also been made at both the institutional and faculty levels to create an environment conducive to supporting blended learning. Based on the challenges identified, future directions are discussed in this paper.
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