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Artificial intelligence (AI) literacy education for young students is gaining traction among researchers and educators. Researchers are developing courses and attempting to teach AI literacy to younger students, using age‐appropriate AI educational learning tools. Although teachers play a crucial role in AI literacy education, their perceptions and attitudes have received little attention. This study explores the perceptions of 60 teachers regarding the use of AI educational learning tools, and examines the factors influencing their attitudes in relation to implementing AI literacy education. The technological acceptance model and the technological, pedagogical, and content knowledge (CK) (TPACK) framework inform the research design, and a mixed method, combining the statistical package for Social Science and thematic analysis, is employed for data analysis. The study reveals that teachers have positive perceptions regarding the usefulness and ease of use of AI educational learning tools in their AI literacy teaching. This paper also reveals that teachers embrace an arts‐based approach to teaching AI literacy. The qualitative data reveal that teachers face challenges such as insufficient CK and experience with AI; and knowledge of TPACK. The five factors affecting their acceptance of AI educational learning tools are: (a) teachers' perceptions of their AI CK and experience in teaching AI literacy (technological content knowledge); (b) technical challenges and stakeholder acceptance; (c) the attributes of AI educational learning tools; (d) school infrastructure and budget constraints; and (e) potential for distraction and negative emotional responses. This study offers insights for policymakers regarding professional development initiatives and technical support mechanisms, thereby facilitating more effective AI literacy implementation.

The rapidly increasing importance of technology integration and generative AI in the fashion industry is prompting changes in fashion design education. This study explored a new design methodology utilizing AI for sustainable and future-oriented fashion design education. The methodology involved consulting practitioners to select ChatGPT and Midjourney as AI tools and technology, pedagogy, and content knowledge (TPACK) as the theoretical framework. An AI prompt guide was developed based on specialized books, from which an educational program was created. An experiment with 30 third- and fourth-year fashion design students showed that their overall satisfaction with AI through TPACK was 4 out of 5, suggesting that TPACK enhances students’ creativity and efficiency through generative AI. Prompt guides received a satisfaction score of 4.7, indicating their usefulness for creative and efficient design outputs. AI-powered educational programs, like ChatGPT and Midjourney, also improved student creativity and learning efficiency, with ChatGPT scoring 4.5. However, concerns about technology dependency were noted. This study offers insights into integrating the latest technology into fashion design to improve process efficiency and creative output. This study not only provides a foundation for future research on AI design methodology but also explores practical directions for sustainable design in the fashion industry.

Design dynamics that evolve during a designer's prototyping process encapsulate important insights about the way the designer is using his or her knowledge, creativity, and reflective thinking. Nevertheless, the capturing of such dynamics is not always an easy task, as they are built through alternations between the self-first and self-third person views. This study aimed at introducing a conceptual framework, namely 2D-ME, to provide an explainable domain that could express the dynamics across the design timeline during a prototyping process of serious games. Within the 2D-ME framework, the Technological-Pedagogical-Content Knowledge (TPACK), its adaptation to the serious games (TPACK-Game), and the activity theory frameworks were combined to produce dynamic constructs that incorporate self-first and self-third person extension of the TPACK-Game to Games TPACK, rules, division of labor, and object. The dynamic interplay between such constructs was used as an adaptation engine within an optimization prototype process, so each sequential version of the latter could converge to the designer's initial idea of the serious game. Moreover, higher-order thinking is scaffolded with the internal Activity Interview Script proposed in this paper. An experimental case study of the application of the 2D-ME conceptual framework in the design of a light reflection game was showcased, revealing all the designer's dynamics, both from internal (via a diary) and external (via the prototype version) views. The findings of this case study exemplified the convergence of the prototyping process to an optimized output, by minimizing the mean square error between the conceptual (initial and updated) idea of the prototype, following explainable and tangible constructs within the 2D-ME framework. The generic structure of the proposed 2D-ME framework allows its transferability to various levels of expertise in serious games mastering, and it is used both for the designer's process exploration and training of the novice ones.

The impetus for this paper stems from a concern about directions and progress in the measurement of the Technological Pedagogical Content Knowledge (TPACK) framework for effective technology integration. In this paper, we develop the rationale for using a seven-criterion lens, based upon contemporary validity theory, for critiquing empirical investigations and measurements using the TPACK framework. This proposed seven-criterion lens may help researchers map out measurement principles and techniques that ensure reliable and valid measurement in TPACK research. Our critique of existing TPACK research using these criteria as a frame suggests several areas of theorizing and practice that are likely impeding the press for measurement. First are contradictions and confusion about the epistemology of TPACK. Second is the lack of clarity about the purpose of TPACK measurement. Third is the choice and use of measurement models and techniques. This article illustrates these limitations with examples from current TPACK and measurement-based research and discusses directions and guidelines for further research.

Technological pedagogical content knowledge (TPACK) has been well accepted as a framework to understand and describe types of knowledge required by teachers to teach specific content with technology effectively. However, limited studies have used the framework in analysing the complexity of technology integration in mathematics classrooms. This study investigates, through examining critical instructional events, the most influential TPACK constructs in understanding and shaping teachers’ pedagogical practices using digital technology. This case study was conducted in an early secondary mathematics classroom in Indonesia that used a web-based resource to support students’ understanding of fractions. The finding suggests that the qualitative examination of the four intersected TPACK constructs assists in understanding the challenges and the opportunities to teachers when utilising an exploratory-based technology. It demonstrates that the combination of pedagogical stances and choice of technology significantly influence the visibility of other TPACK constructs. Implications of this study include the need of thoughtful planning prior to using web-based resources and the importance to utilise critical events in developing and assessing teachers’ TPACK.

In the present paper, we explore the integration of Generative Artificial Intelligence (GenAI) into the teaching, learning and research practices within the Faculty of Instructional Technologies undergraduate programme at the Holon Institute of Technology (HIT), Israel. Our goal is to examine how GenAI has supported transitions in various courses across three study clusters: core topics related to learning and training, user experience and user interface design (UX/UI), and technological development. Through five case studies from these clusters, we demonstrate how the incorporation of GenAI has enhanced student practices as they conceptualise, design, and create technology-enhanced learning (TEL) tools, systems, and architectures designed to meet real-world needs. In this context, we demonstrate how GenAI integration influences the interrelationship among the three study clusters, thereby facilitating a cohesive approach essential for students developing their capstone projects, which require the integration of knowledge and skills from all courses. This paper situates these efforts within the intelligent-technological pedagogical content knowledge (TPACK) framework, illustrating GenAI’s role in TEL. We conclude with recommendations for researchers and practitioners considering the adoption of GenAI to enhance their capabilities in deploying next-generation TEL environments.

Abstract Purpose This chapter is the result of an interest in the professional and research literature exploring the intersection between education and digital technology. Decades of research and press have largely focused on the ways in which particular devices might be productively used in the K-12 classroom. Educational radio, educational television, the computer, and more recently the tablet have all been framed as being valuable for supporting student learning. Critics such as Neil Selwyn have argued that research in educational technology needs to focus less on supporting particular devices and more on the nature of social interactions that are mediated, constrained, and enabled by various technological affordances. Methodology/approach This chapter reviews four theoretical frameworks in terms of their approach the social nature of the use of technology in education. Findings The chapter introduces a number of conceptual frameworks that are helpful for considering the social implications of using digital technologies to support the needs of diverse learners in a teacher education classroom. Research implications Scholars, especially who are also teacher educators can consider using and developing frameworks that are more robust for thinking about digital learning in education. Originality/value The value in this chapter lies in the critical conceptions explored and interrogated. The author demonstrates the complexity of teacher knowledge overlaid with technology.