This study aims to develop a learning model for Topeng Malang (Malang Mask Art) through the story “Laire Kijing Nirmana”. Topeng Malang is a traditional art form native to Malang and is a compulsory course for undergraduate students majoring in Dance and Music Education at Universitas Negeri Malang. The teaching of Topeng art within arts education needs to adopt an adaptive attitude toward technological advancements. The integration of interactive technology in the development of the Topeng Malang learning model applies the technological pedagogical content knowledge (TPACK) approach, which effectively integrates technology into solving learning problems related to Topeng Malang art. This research uses a design-based research (DBR) approach, which includes the stages of design, implementation, evaluation, and refinement of the Topeng Malang learning model. The methods used in this study include literature review, observation, and experimentation. The research emphasizes three key aspects of TPACK: content knowledge, which refers to the understanding of scene structure in the Lahire Kijing Nirmana play; pedagogical knowledge, which refers to the collaborative methods used to teach scene structure; and technological knowledge, which involves the use of augmented reality (AR) technology. The result of this research is a learning model for Topeng Malang art through the story Lahire Kijing Nirmana using an AR-based application. The developed learning model includes materials about wayang topeng characters and the presentation structure of the Lahire Kijing Nirmana story. Understanding the scene structure in Topeng Malang art influences students’ interest by making the content easier to comprehend, offering an alternative to conventional learning approaches, and fostering a more interactive and engaging experience in learning Topeng Malang art.

The integration of English audio-visual (AV) materials has been widely promoted as an effective approach for enhancing speaking skills in English as a Foreign Language (EFL) contexts; however, a persistent gap remains between its theoretical potential and classroom implementation in Indonesia. This qualitative case study aims to investigate perceptions and challenges of using AV materials for speaking skill development, examining both student and teacher perspectives. The study employed an applied qualitative research design, collecting data through Google Forms, classroom observations, and document analysis, involving two English teachers and 13 students at a private language institute in Lhokseumawe, Indonesia. Thematic analysis revealed a systemic misalignment between stakeholders. Students perceived AV materials as engaging, anxiety-reducing, and essential for accessing authentic language input, and they expressed a strong preference for interactive and creative speaking activities. In contrast, teachers, despite recognizing the pedagogical value of AV materials, faced significant constraints, including limited preparation time, unstable technological infrastructure, exam-oriented curricular pressures, and insufficient Technological Pedagogical Content Knowledge (TPACK). This TPACK deficiency led to predominantly input-focused and pedagogically simplified use of AV materials, limiting opportunities for meaningful spoken output. The study concludes that the primary barrier to effective AV integration lies not in technological access but in interconnected institutional, professional, and curricular constraints. To address this gap, the study proposes a tripartite framework consisting of institutional support re-engineering, TPACK-oriented professional development, and curricular realignment to legitimize AV-mediated speaking practice. These findings provide context-sensitive recommendations for transforming AV use from passive consumption into active speaking production in Indonesian EFL classrooms.

ABSTRACT The field of education has witnessed a rapid expansion in the utilization of Artificial Intelligence (AI) technologies, fundamentally transforming classroom instruction. Thus, it is critical for pre-service teachers to implement AI-powered technology in their future teaching. This study was conducted in six higher education institutions (HEIs) in China and is grounded in resource-based theory, the technology acceptance model (TAM), and relevant literature. SmartPLS 4.0 was utilized to develop a partial least squares structural equation model (PLS-SEM) to examine the relationships among AI capability (AIC), creativity, self-efficacy, Technological Pedagogical Content Knowledge (TPACK), and pre-service teachers’ behavioural intentions towards AI-assisted teaching. The findings indicated that HEIs’ AIC is a significant predictor of pre-service teachers’ behavioural intentions towards designing AI-assisted teaching. It also predicts their creativity, self-efficacy, and TPACK. Furthermore, creativity, self-efficacy, and TPACK were found to mediate the relationships between HEIs’ AIC and pre-service teachers’ behavioural intentions. These findings suggest that HEIs should support the development of pre-service teachers by enhancing AIC, including resources (data and technology) and awareness (reform and innovation), providing insights into AI integration in higher education within the Asia-Pacific context.

ABSTRACT Online teaching in emergency situations can be challenging, potentially undermining instructors’ motivation and increasing their stress. In such contexts, instructors’ teaching knowledge may buffer these negative experiences. Guided by the Technological Pedagogical Content Knowledge (TPACK) framework, this study examined the roles of different technology-related knowledge – technological knowledge (TK), technological pedagogical knowledge (TPK), and technological content knowledge (TCK) – in instructors’ motivation (perceived task effort cost and emotional cost) and technostress (stress from using technology) during COVID-19 emergency online teaching. Results showed that TK was associated only with emotional cost and technostress, while TPK and TCK were related to all teaching outcomes. Further, hierarchical regression analyses revealed that TCK uniquely predicted all outcomes beyond TK and TPK, highlighting the importance of integrating technology into discipline-specific teaching practices. These findings emphasize the need to unpack TPACK’s components and suggest that professional development should move beyond generic tech training toward content- and pedagogy-integrated approaches.

The integration of Artificial Intelligence (AI) in education has underscored the urgent need to equip educators with essential AI literacy and related competencies. This paper highlights the critical importance of advancing research on the development of teachers' AI literacy, particularly through targeted professional development programs. To address this need, the study piloted a training program involving 19 mid-career teachers in Singapore. Over the course of six weeks, participants engaged in an intensive 18-hour program designed to enhance their ability to integrate AI into educational practices, with a strong emphasis on ethical considerations. Mixed methods were employed. Data collection included pre-and post- intelligent Technological Pedagogical Content Knowledge (TPACK) surveys, teachers’ perceptions on AI, in-class group discussions, and post-individual written assignments. Data analyses included content analysis and quantitative data analysis. The results showed a significant enhancement in i-TPACK, accompanied by a shift in their overall perceptions of AI. The teachers not only acquired a good understanding of ethical frameworks but also demonstrated adept application in envisioning innovative AI in teaching, schools, and assessment. They formulated tailored action plans for implementing AI in their respective schools. Furthermore, the study employed a novel analytical matrix based on the Aristotelian tripartite division of knowledge—episteme, techne, and phronesis—to compare action plans between teachers with higher and lower perceived i-TPACK levels, focusing on AI’s application in teaching, schools, and assessment. This study contributes valuable insights into teacher professional development concerning AI in education and informs the implementation of AI in teaching practices.

Physical education (PE) is tactile, practical, and participative, making it more challenging to integrate technology than other academic subjects. This study intends to analyse the challenges faced by physical teachers while using digital technology in PE. This research included physical education teachers (PETs) from nine secondary schools in Selangor, Malaysia. Qualitative research design was applied in this study and the data was collected via semi-structured interviews and analysed using thematic analysis. The technological pedagogical content knowledge (TPACK) framework is used to analyse PETs technology education practises and issues. Results revealed that there were seven themes emerged for the obstacles: i) lack of infrastructure; ii) lack of financial support; iii) lack of training; iv) time and space management; v) perception and attitude towards PE; vi) student-related constrains; and vii) lack of educational resources. These findings can be useful to support education in the 21st century whereby the teachers should get extensive technology training to improve their digital skills, as well as regular and ongoing technology integration training.

This study investigates how Technological Pedagogical Content Knowledge (TPACK) influences Artificial Intelligence Acceptance (AIA) among Chinese university English teachers, focusing on the dual mediating roles of organisational support and self-efficacy. Drawing on structural equation modelling of survey data from 153 instructors, the results show that TPACK significantly predicts AIA, with self-efficacy accounting for this relationship. Drawing on a structural equation model analysis of survey data from 153 English instructors, we demonstrate that TPACK significantly predicts AIA, and self-efficacy played an explanatory role in this relationship. Organisational support further mediates the pathway from AI-Technical Knowledge (AI-TK) to TPACK, highlighting institutional mechanisms that strengthen teachers’ pedagogical capacity for AI integration. Three critical pathways are identified: (1) a direct TPACK → AIA trajectory, (2) an AI-TK → OS → TPACK → AIA institutional chain and (3) a TPACK → SE → AIA motivational loop. Positioning AI as a form of assistive technology, the findings highlight its role in enhancing teachers’ instructional capacity while promoting accessibility, personalised scaffolding and inclusive opportunities for diverse learners. By integrating Human–Computer Interaction (HCI) and assistive technology perspectives, the study reframes TPACK as interaction readiness, organisational support as a socio-technical affordance, and self-efficacy as interaction efficacy. This interdisciplinary framing highlights that AI acceptance is not only a matter of knowledge and psychology, but also of designing human–AI collaborations that promote usability, accessibility and inclusive pedagogy. The results offer actionable implications for AI training programs, highlighting the importance of integrating technical upskilling with organisational mechanisms.

The integration of pedagogy, content, and technology remains a key challenge in preparing pre-service primary teachers, particularly in Pancasila and Civic Education learning. This study aimed to explore the level of Technological Pedagogical Content Knowledge (TPACK) mastery among pre-service primary teachers enrolled in the Learning Pancasila and Civic Education in Primary Schools course. The research employed a qualitative case study design involving six pre-service primary teachers from a university in Jakarta, selected through purposive sampling based on variations in mid-term academic achievement. Data were collected through semi-structured interviews, classroom observations, and document analysis, including teaching modules, student assignments, and evaluation results. The collected data were analysed using thematic analysis to identify patterns related to students' conceptual understanding, pedagogical competence, initial technology integration, and supporting and constraining factors in the learning process. The findings show that students generally demonstrated adequate content understanding of Pancasila and Civic Education; however, their pedagogical understanding was not yet well developed, particularly in selecting and applying appropriate learning approaches and models. Technology integration tended to focus on technical and media-related aspects rather than supporting pedagogical strategies, indicating limited TPACK integration. Several constraints, such as limited theoretical literacy and learning context challenges, influenced students' ability to integrate pedagogy, content, and technology coherently. This study suggests that teacher education programs need to strengthen pedagogical scaffolding and reflective learning experiences to support more effective TPACK development among pre-service primary teachers.

The incorporation of artificial intelligence in teaching and learning environments, especially in English as a Second Language instruction, is constantly evolving. This has led to studies focusing on students’ perspectives, but there is a lack of research on educators’ experiences with artificial intelligence in classrooms. The paper provides an overview of educators’ perceptions and experiences with AI applications through a systematic review. This review synthesises 34 studies from 435 articles published between 2021 and 2024. The reviewed studies include countries from Asia, the Middle East, Europe and Africa and involve both pre-service and in-service educators across primary, secondary and tertiary levels. Based on the Technological Pedagogical Content Knowledge framework, the Unified Theory of Acceptance and Use of Technology and the Substitution-Augmentation-Modification-Redefinition model, this review identifies themes across pedagogical benefits, ethical concerns and implementation challenges. The findings show that most studies focused on the technical aspects of artificial intelligence rather than educators’ real experience applying it in classrooms. Hence, this paper recognises critical gaps, including the need for longitudinal studies on integration, frameworks for artificial intelligence-driven pedagogy, and professional development initiatives tailored to educators’ diverse levels of competence. This provides valuable guidelines for policymakers, institutions, and future researchers for bridging the gap between artificial intelligence and pedagogy. This review highlights the importance of educator-focused research and the inclusive exploration of artificial intelligence’s role in language instruction

Rapid technological progress calls for continuous professional development in digital literacy for academic staff to accommodate the transformative integration of educational technology within education. This research assesses the effects of faculty participation in such workshops and its subsequent practical application in educational contexts. Utilising purposive sampling, twenty-one academic members who consistently attended educational technology workshops during 2021-2023 completed a closed-response online questionnaire using Microsoft Forms. The study incorporates the Kirkpatrick’s Evaluation Model’s (KEM) and the Technological Pedagogical Content Knowledge (TPACK) framework to provide rigour in its evaluation of training efficacy. Our findings reveal substantial barriers to sustained technology integration, namely limited post-workshop support, insufficient time for practical application, unreliable infrastructure, and varying levels of digital literacy among academic staff. This data highlights the need for strategic enhancements in workshop structure and presentation to better cultivate substantial technological integration within teaching practices.

This study aimed to explore the challenges faced by higher education students on the use of digital learning resources in classrooms during and after the COVID-19 pandemic. The study was conducted among higher education students studying in the Master of Education (M.Ed.) programme with specialized in Health Education from Tribhuvan University (TU), Nepal employing an exploratory qualitative research design with a narrative inquiry approach. For this study, three campuses under the TU were selected purposively, where three focus group discussions were conducted to solicit information from 18 participants, with six from each campus. The Technological Pedagogical Content Knowledge (TPACK) explanatory framework was used to analyze the data under four broader themes: technological challenges, pedagogical challenges, content-related challenges, and other challenges. The findings of the study indicated that the students faced multiple levels of challenges such as lack of personal hardware devices, internet service, and appropriate knowledge of using digital learning resources like Zoom, Google Meet, and Microsoft Teams, along with financial and pedagogical challenges that further impeded their access to these resources. Despite the university's adoption of online classroom teaching guidelines, the implementation was ineffective, and the curriculum remained outdated, hindering the ability to envision classroom activities beyond the university's premises. The study underscores the need for systemic reforms, including investments in ICT-based infrastructure, faculty professional development programs, curriculum modernization, and policy reform to ensure equitable access and effective digital learning. Future researchers are encouraged to conduct intervention-based studies in collaboration with stakeholders to address the underlying challenges as identified by this study.

ABSTRACT The rise of artificial intelligence (AI) in education, particularly generative AI, challenges the sufficiency of the established Technological Pedagogical Content Knowledge (TPACK) framework. AI’s agentic autonomy, epistemic complexities, and ethical dimensions necessitate an evolved model. This study investigates the newly proposed Intelligent-TPACK (I-TPACK) framework, designed to address these gaps by integrating five knowledge domains: AI-Technological, AI-Content, AI-Pedagogical, Human-AI Collaborative, and Ethical Knowledge. The research goal was to define the specific knowledge and skills required within these I-TPACK domains from a teacher's perspective. Utilizing a three-round Delphi method, a panel of 30 teachers from diverse subjects developed a consensus list of essential competencies. The findings identified and refined 25 critical knowledge items, providing a foundational and empirically grounded model for the I-TPACK framework. These findings offer a concrete roadmap for teacher education, translating a theoretical model into actionable competencies. This study equips educators to transition from merely using AI to strategically orchestrating human-AI collaborative learning, ensuring they can harness AI's potential ethically, critically, and productively. The I-TPACK and its suggested knowledge serve as a vital tool for developing future-ready teacher training programs and professional development.

The psychology of teaching preparedness: Linking TPACK to self-efficacy in pre-service EFL teachers.

ABSTRACT This study investigates the moderating role of Artificial Intelligence – Technological Pedagogical Content Knowledge (AI-TPACK) in the relationship between teacher candidates’ intercultural sensitivity and multicultural teaching competencies. Using a relational screening model, data were collected from 399 teacher candidates across various departments in Turkish education faculties. Instruments included the Intercultural Sensitivity Scale, the AI-TPACK Scale, and the Multicultural Teaching Competencies Scale. Findings revealed that while intercultural sensitivity positively predicted multicultural teaching competencies, AI-TPACK exerted a negative moderating effect, decreasing the strength of this relationship at higher levels. This negative effect suggests a threshold-like phenomenon in which moderate AI-TPACK supports culturally responsive teaching, but higher AI dependence may weaken culturally grounded decision-making. The results underscore the importance of integrating critical, ethical, and culturally aware AI training in teacher education programmes. Within the Turkish context, the study offers timely implications for enhancing both technological and intercultural competencies in future teachers navigating increasingly diverse classrooms.

Academic Development (AD) represents a fundamental strategy for improving the quality of university teaching in the digital era. This entry proposes a critical analysis of technologies supporting AD, examining theoretical models, emerging practices, and contemporary challenges through a systematic review of academic literature. The TPACK (Technological Pedagogical Content Knowledge) framework emerges as a crucial model for the effective integration of educational technologies, while innovative approaches such as blended learning, flipped classroom, and communities of practice demonstrate significant potential in promoting teaching innovation. However, the analysis highlights structural criticalities: resistance to change, lack of institutional recognition, technological pedagogical gaps, and identity tensions related to the teaching role. The concept of “Age of Evidence” orients future perspectives toward evidence-based, personalized, and collaborative programs. The entry concludes with operational recommendations for policymakers and institutions, emphasizing the need for systemic investments that valorize teaching as a core scholarly activity. The original contribution lies in the critical integration of established theoretical frameworks with analysis of post-pandemic transformations and in identifying strategic directions to make universities “transformative” in addressing global challenges of sustainability, technological innovation, and critical thinking education.

Introduction This study examines the adaptability and resilience of undergraduate students at a French university during an abrupt transition to online learning triggered by a crisis. Grounded in resilience theory and the Technology Acceptance Model (TAM), the research investigates students’ perceptions of digital learning environments and their capacity to cope with academic disruption. It further situates the analysis within Connectivism and Technological Pedagogical Content Knowledge (TPCK) frameworks to assess the transformative potential of information and communication technologies (ICTs) in fostering inclusive and equitable education. Methods A post-crisis quantitative survey was administered to 402 students enrolled at the Institut Universitaire de Technologie (IUT) in Oise. The questionnaire captured students’ experiences, emotional responses, and perceptions of online learning practices during the crisis. Factor analysis was conducted on key survey items (Q7) to identify underlying dimensions related to digital learning experiences. Results The factor analysis revealed three principal dimensions shaping students’ learning experiences: teacher innovation in digital pedagogy, students’ emotional responses, and practical challenges associated with online learning. The findings indicate that social support networks and engagement in virtual communities played a significant role in helping students manage academic difficulties. Moreover, learning perceptions differed according to the level of study, with master’s students demonstrating higher levels of engagement and adaptability compared to undergraduates. Discussion The results underscore the critical role of pedagogical innovation, emotional support, and technical infrastructure in building sustainable and resilient digital learning environments. ICTs emerge not merely as tools for ensuring instructional continuity in times of crisis, but as enablers of pedagogical equity and institutional transformation. This study contributes to ongoing debates on sustainable and inclusive education by highlighting how well-supported digital ecosystems can enhance resilience and accessibility within higher education.

ABSTRACT This study examines how artificial intelligence (AI) can foster knowledge building in hospitality and tourism education (HTE) through the Intelligent TPACK (ITPACK) framework, which extends the Technology Acceptance Model (TAM) and Technological Pedagogical Content Knowledge (TPACK). A dual-stage hybrid PLS-SEM-ANN approach was applied to data from 439 educators to assess the impact of constructs such as content knowledge, pedagogical knowledge, and technological readiness on AI adoption. Findings reveal that content knowledge is a key driver of intelligent pedagogical integration, while perceived ease of use and technological readiness influence educators’ intention to adopt AI tools. Organizational support strengthens AI-enabled pedagogy, whereas technological anxiety hinders adoption. The study contributes a novel AI-driven framework tailored to HTE, offering actionable strategies for curriculum designers and academic leaders. It advances the understanding of GenAI integration and provides practical insights for improving digital readiness, reducing anxiety, and aligning pedagogy with the needs of the tourism industry.

Globally, inclusive teacher training is a cornerstone of equitable education, yet many low- and middle-income countries (LMICs) face challenges in preparing teachers to integrate technology into diverse classrooms. This study examines the impact of the Interactive Mobile Multimedia Applications (IMMAS) training program, an eight-week blended professional development initiative for 10 Malaysian special education teachers. Designed around Technological Pedagogical Content Knowledge (TPACK) and Universal Design for Learning (UDL) principles, IMMAS aimed to build teachers’ digital capacity, transform professional identity, and promote sustainable instructional innovation. Data were collected through semi-structured interviews, weekly reflective journals, and multimedia lesson portfolios, and analysed using Braun and Clarke’s (2006) thematic analysis. Three themes emerged: (1) a pedagogical shift toward learner-centred, multimodal lesson design; (2) transformation of teacher identity, with participants increasingly viewing themselves as content creators and mentors; and (3) sustainability through reusability of digital resources and grassroots peer collaboration. Findings demonstrate that mobile multimedia training can operationalise UDL principles, foster teacher self-efficacy, and establish school-based ecosystems of innovation. This study contributes new evidence from Southeast Asia to global discussions on inclusive education and educational technology, complementing top-down models in OECD countries with a cost-effective, grassroots-driven approach. IMMAS aligns with Sustainable Development Goal 4, emphasising equity and quality in education, and offers a scalable model for teacher development in resource-constrained settings. Future research should explore long-term sustainability and integration with national policies to scale this innovation.

This study investigates the challenges Azerbaijani pre-service teachers face in adopting innovative teaching practices during their practicum. Guided by the Technological Pedagogical Content Knowledge (TPACK) framework, the research employed a qualitative design using semi-structured interviews with sixteen final-year pre-service teachers across diverse subject areas and practicum schools. Thematic analysis revealed five interconnected challenges: (1) pedagogical difficulties in balancing traditional and modern approaches; (2) limited digital literacy and inadequate preparation for technology integration; (3) classroom management issues, particularly in overcrowded settings; (4) institutional and systemic constraints, including resource disparities and resistance to change; and (5) inconsistent mentorship and feedback from cooperating teachers. These findings highlight tensions between teacher education curricula and practicum realities, particularly in preparing future teachers to integrate technology meaningfully into classroom practice. The study emphasizes the need for curriculum reform, enhanced mentor training, and targeted professional development in digital pedagogy.

This body of knowledge, known as ‘Technological Pedagogical Content Knowledge (TPCK)’, is essential to teaching both today and in the future. Teachers possess a high degree of knowledge that is based on ‘Pedagogical Knowledge (PK)’, ‘Technological Knowledge (TK)’, ‘Content Knowledge (CK)’, ‘Technological Pedagogical Knowledge (TPK)’, ‘Technological Content Knowledge (TCK)’, and ‘Pedagogical Content Knowledge (PCK)’. This research work was done by collecting data from B.Ed. trainee teachers with mathematics as a method subject in West Bengal, India. The objective of the study is to compare the TPCK knowledge base of mathematics trainee teachers with respect to gender and residence. The descriptive Survey Method is followed. Trainee teachers with mathematics as a method subject from West Bengal, India, are taken as a sample. The TPACK-Math Scale by Önal (2016) is used for this study. Collected data is prepared by using MS Excel, analysed by SPSS 26, JASP 0.18.1, and MATLAB 2021b. Descriptive statistics (Mean, SD, and Covariance) and inferential statistics (Mahalanobis Distance) are used for this study. Calculated value of Mahalanobis Distance between male and female is 0.3417 (<1) and between rural and urban is 0.6625 (<1). There is no significant difference between male vs female and rural vs urban mathematics trainee teachers with respect to ‘TK’, ‘PK’, ‘CK’, ‘TPK’, ‘TCK’, ‘PCK’, ‘CNTK’, and ‘TPCK’. It is concluded that the dynamical nature of the knowledge base considered for the present study is independent of gender and residence of trainee teachers. Possible causes for such a non-significant finding in the educational research context are discussed. A comprehensive interpretation of the inherent limitations is acknowledged, and to overcome these limitations and deepen the understanding of TPCK development in mathematics education, further research is suggested.