Search Results (77)

This study aimed to explore the interplay of technological pedagogical content knowledge of games (TPACK-G) and digital game acceptance among pre-service teachers. The relationships between the components of technological pedagogical content knowledge of games and game acceptance factors were explored. The effect of game acceptance levels on technological pedagogical content knowledge of games was also examined. The sample of this study was pre-service teachers enrolled in undergraduate courses from a university in the northeast United States. The data were collected using an online survey. Quantitative methods were used to analyze the data. Results indicated that there were significant positive correlations between TPACK-G and game acceptance components. Pre-service teachers’ TPACK-G, including game knowledge (GK), game content knowledge (GCK), game pedagogical knowledge (GPK), and game pedagogical content knowledge (GPCK), significantly differed in terms of game acceptance levels. The results contribute to the literature of game-based learning. Discussions and suggestions are provided following major findings. Full article

While many studies have acknowledged multifaceted roles of curriculum materials (textbooks) in EFL reading activities, textbooks alone are insufficient, as their effectiveness depends on how teachers use them. Teachers’ textbook usage is strongly related to cognitive and affective factors. There is limited understanding of how the interplay between teachers’ cognitive and affective factors influences their use of these materials and how they use technology to enhance the effectiveness of textbooks for reading activities in EFL classrooms. The current study fills this gap by investigating the interplay among teachers’ technological pedagogical content knowledge (TPACK), learner-centered pedagogical beliefs (LCPB), teacher-centered pedagogical beliefs (TCPB), and their curriculum material use approach—specifically the constructivist and transmissive approaches—focusing on moderation and mediation effects. This study also investigated how teachers use technology to enhance reading activities in the textbooks. Structural equation modeling analyzed mediation and moderation effects using survey data from 251 Indonesian EFL teachers. Findings indicated that TPACK directly influenced the use of constructivist-oriented curriculum material. At the same time, both LCPB and TCPB acted as mediators in the influence of TPACK on teachers’ orientations towards the use of curriculum materials. Crucially, the relationship between TPACK and LCPB adversely affected constructivist usage, suggesting that robust learner-centered beliefs diminished dependence on TPACK. Conversely, transmissive orientations were primarily guided by beliefs and remained uninfluenced by TPACK. These results highlight that teachers’ knowledge and beliefs influence the way they use curriculum materials—either constructivist or transmissive. The findings inform policymakers in initiating professional development programs that aim to shift teachers toward more constructivist uses of curriculum materials, fostering a more interactive and student-centered language-learning environment. Full article

The Technological Pedagogical Content Knowledge (TPACK) framework is widely used to conceptualize teacher knowledge as an interplay of content, pedagogy, and technology. Following recent research interests in examining TPACK as contextually situated knowledge, this study investigates how pre-service physics teachers (undergraduate students in a physics department) and in-service science teachers perceive the domains of TPACK and explores what these differences imply for university-based teacher education. A total of 48 pre-service physics undergraduates and 27 in-service teachers completed an adapted 21-item self-assessment questionnaire, which combined validated items with context-specific modifications. Data analysis included internal consistency reliability tests, independent samples t-tests, and correlation analysis. Results revealed that pre-service teachers reported higher self-assessed competencies, especially in integrative domains, although their knowledge structures appeared less coherent. In contrast, in-service teachers exhibited more coherent and integrated knowledge frameworks, possibly reflecting their accumulated professional experience, despite reporting lower self-confidence. These findings confirm the contextual and situated nature of TPACK, highlighting the divergence between perceived competence and structural coherence. The study contributes by proposing that university science education programs should not only promote theoretical understanding of TPACK but also deliberately embed technology-rich, practice-oriented experiences. Full article

This study proposes an integrated TAM–TPACK framework that explicates how teachers’ technology acceptance progresses to lesson design and enactment in elementary physical education, using augmented reality (AR) climbing as the focal case. A qualitative case study was conducted with three elementary teachers. Data comprised semi-structured interviews, classroom videos, lesson plans, and satisfaction surveys, and were interpreted through directed content analysis. The findings indicate that perceived usefulness (PU) and perceived ease of use (PEU) systematically informed goal setting, feasibility judgments, and content–curriculum alignment, whereas behavioral intention (BI) shaped pedagogical intent and design decisions. Technological Content Knowledge (TCK) and Technological Pedagogical Knowledge (TPK) functioned as core mechanisms that structurally aligned AR functionalities with curricular aims and instructional procedures. Clear correspondences—PU↔TCK, PEU↔TPK, and BI↔TPACK—were identified, conceptually mapping a pathway from technology acceptance to lesson design and classroom enactment. The study advances a concise, empirically grounded, teacher-centered model for digital physical education and underscores the need for standardized adoption criteria, structured professional development, implementation incentives, and equitable access to local infrastructure to support sustained practice as part of a sustainability-oriented digital transformation of physical education systems. Full article

Generative artificial intelligence (AI) is now embedded in the everyday practice of higher education. This qualitative, multisite study examines how university faculty perceive where generative AI advances or threatens Sustainable Development Goal (SDG) 4, which commits education systems to inclusive, equitable, high-quality learning across the lifespan. We conducted semi-structured interviews and focus groups with 36 academics across three universities, complemented by document and artefact analysis. Guided by critical pedagogy, sociomateriality, and technological pedagogical content knowledge (TPACK), we used reflexive thematic analysis to identify five cross-cutting themes. Faculty reported inclusion gains through rapid accessibility work, multilingual support, and differentiated feedback, alongside risks that undermine SDG 4, including bias, expansion of surveillance, unreliable outputs, paywalled access advantages, and work intensification. Assessment emerged as the decisive site of tension: staff rejected detection-led policing and favoured designs that reward process, critique, and provenance. We offer a practical framework, aligned to SDG 4 targets, that translates these insights into commitments, indicators, and a 12-month programme plan. The sector should move beyond bans and hype. Responsible adoption requires equity by design, assessment redesign, institutionally guaranteed access, transparent evaluation, and protected time for teacher development. Full article

In today’s digital era, teachers are expected to incorporate artificial intelligence (AI) into the classroom. Teacher educators must therefore model its use while evaluating their own AI-related knowledge to guide future teachers effectively. Existing assessments often rely on self-reporting questionnaires, which may introduce bias, and the TPACK (Technological-Pedagogical-Content-Knowledge) framework, which overlooks distinctive AI characteristics. This study develops and validates an AI-TPACK assessment tool for teacher educators, grounded in authentic pedagogy and systematically designed through the ADDIE model (Analysis, Design, Development, Implementation, and Evaluation). The study aims to identify AI-relevant TPACK components and add new ones; test the tool’s validity; and analyze teacher-educator competency patterns. The development involved dual literature reviews (22 TPACK studies; 34 AI studies) and empirical analysis of 60 authentic instructional artifacts. Five experts confirmed their content validity (CVR = 0.86, CVI = 0.91) and the inter-rater reliability (ICC = 0.84, range 0.76–0.88). The tool comprises 4 components—AIK, AIPK, AICK, and Integration—14 criteria, and 65 indicators, and reveals four competency patterns: technological innovator; pedagogical integrator; content developer; and beginner. The strong correlation (r = 0.78) between AIPK and integration underscores the importance of synergy. The tool contributes theoretically and practically to advancing teacher-educators’ AI knowledge and competency assessments. Full article

This study aims to examine the implementation of digital education at SDN Cicurug Caringin and SDIT Nabawi, Sukabumi Regency, with a focus on opportunities, challenges, and gaps in the use of technology for learning at the elementary school level. Using a qualitative approach and a comparative case study design, this study explores the application of digital education in two different contexts, namely in rural areas (SDN Cicurug Caringin) and urban areas (SDIT Nabawi). Data were collected through in-depth interviews with four teachers, two principals, eight students, and four parents, as well as direct observation in both schools. The analysis techniques used are data reduction, data presentation, and conclusion drawing, with Miles and Huberman’s interactive analysis procedures. The results of the study show that SDN Cicurug Caringin faces significant infrastructure constraints, such as a student-computer ratio of 1:15, limited internet connection, and low digital literacy of parents due to their simple socio-economic background. On the other hand, SDIT Nabawi has succeeded in utilizing digital platforms such as Let’s Read to increase students’ interest in reading, although it is limited by teaching time and lack of TPACK (Technological Pedagogical Content Knowledge) training for teachers. The main gaps found between the two schools are unequal access to technology, limited teacher capacity to integrate technology, and low parental support in assisting children in digital learning. This study provides empirical evidence that the success of digital education is highly dependent on adequate infrastructure, TPACK-based training for teachers, and parental involvement in digital literacy. The recommendations included infrastructure improvements, TPACK training for teachers, and the implementation of digital literacy workshops for parents to reduce disparities and improve learning outcomes. Full article

The integration of artificial intelligence (AI) into education is a defining challenge for achieving a sustainable digital future. This study addresses this challenge by exploring the psychological foundations necessary for teacher readiness, framing this preparation as a matter of social sustainability for the teaching profession. Employing a correlational research design, this study investigates the relationships among key psychological constructs as perceived by pre-service educators. Specifically, it examines how pre-service preschool teachers’ self-reported levels of self-regulation and social-emotional expertise relate to their self-assessed AI—Technological Pedagogical Content Knowledge (AI-TPACK). The findings were revealing: multiple linear regression analyses confirmed perceived self-regulation as a robust predictor of the self-assessed core and composite knowledge elements of AI-TPACK. Counterintuitively, social-emotional expertise did not show a significant correlation with any aspect of AI-TPACK. This suggests that the metacognitive skills inherent in self-regulation are fundamental for empowering educators to engage in the lifelong learning required for a sustainable career. Therefore, teacher education programs must strategically cultivate these skills to foster a resilient teaching workforce, capable of ethically shaping the future of AI in inclusive and sustainable learning environments. Full article

Drawing on the Technological Pedagogical Content Knowledge (TPACK) framework, this qualitative case study investigates how university English teachers integrate AI chatbots into flipped classrooms. Findings reveal that teachers employed chatbots across multiple pedagogical functions—including vocabulary support, grammar explanation, dialogue simulation, and creative content generation—embedded purposefully into both pre-class preparation and in-class collaboration. Rather than passively adopting these tools, teachers strategically positioned chatbots to enhance student autonomy, confidence, and interaction, while tailoring their use to suit specific flipped classroom designs. Meanwhile, teachers acknowledged the risks of over-reliance on AI chatbot content and the disruptions caused by vague or incorrect responses. They responded by developing structured guidance and reforming their roles as facilitators rather than content deliverers. This study contributes new insights into teacher agency in AI-mediated language education, highlighting the complex pedagogical negotiations required to meaningfully integrate emerging technologies into flipped learning environments. Full article

Providing inclusive education and engaging all students in reading and writing activities presents an ongoing challenge for teachers, not necessarily resolved by implementing digital technology. This study addresses the need to better understand teacher competencies within the digitally infused classroom, specifically in relation to inclusive education and reading and writing practices. The study investigates the competencies and supportive strategies of middle school teachers who perceive themselves as successful in this area. The study employs the Delphi technique, using iterative surveys through which these teachers describe and rate aspects of their competencies and strategies. The results are analyzed through a modified version of the Technological, Pedagogical, and Content Knowledge (TPACK) framework, with particular attention to how teachers support students using their content knowledge and digital competency. Findings reveal a range of strategies and competency aspects related to both proactive accessibility and reactive individualization, using a variety of digital tools and text modalities. The teachers describe a dual orientation in their ability to curiously explore digital tools while simultaneously being able to critically appraise their usefulness. The findings contribute insights on what can support teachers when collaboratively developing knowledge of local practices and their agency in relation to available digital tools. Full article

This study sought to explore the extent to which the dimensions of the TPACK framework are present among mathematics teachers at the elementary level from their perspective. The study’s goals were accomplished through the use of a descriptive approach, and a questionnaire was distributed to 107 mathematics teachers in the eastern region of Saudi Arabia to collect data. The results indicated that the dimensions of the TPACK framework were highly present among the participants. The highest level was observed in the dimension of Pedagogical Content Knowledge (PCK) at 78.1%, while the lowest was in the Technological Content Knowledge (TCK) dimension at 68.2%. The findings also revealed no statistically significant differences based on gender or education sector. However, statistically significant differences were found in favor of teachers with higher academic qualifications (postgraduate studies) and more years of teaching experience. The study recommends continuing efforts to enhance teacher training programs dealing with integrating technology into teaching, drawing on global experiences in applying the TPACK framework. Full article

The rapid integration of artificial intelligence (AI) in education has transformed traditional teaching methodologies, particularly within Outcome-Based Education (OBE), in higher education. Based on the Technological Pedagogical Content Knowledge (TPACK) model and the OBE system, this present study investigates how teachers perceive AI applications, specifically ChatGPT, in enhancing instructional design and student performance. The research develops a new AI-based instructional planning model, incorporating AI ChatGPT capabilities, teacher competencies, and their direct and indirect effects on student outcomes. This study employs quantitative research design using Structural Equation Modeling (SEM) to validate the proposed model. Data were collected from 320 university teachers in Pakistan using a structured survey distributed through WhatsApp and email. Findings from the direct path analysis indicate that AI ChatGPT capabilities significantly enhance instructional planning (β = 0.33, p < 0.001) and directly impact student performance (β = 0.20, p < 0.001). Teacher competencies also play an important role in instructional planning (β = 0.37, p < 0.001) and student performance (β = 0.16, p = 0.020). The indirect path analysis reveals that instructional planning mediates the relationship between AI ChatGPT capabilities and student performance (β = 0.160, p < 0.001), as well as between teacher competencies and student performance (β = 0.180, p < 0.001). The R-square values indicate that instructional planning explains 41% of its variance, while student performance accounts for 56%. These findings provide theoretical contributions by extending AI adoption models in education and offer practical implications for integrating AI tools in teaching. This study emphasizes the need for professional development programs to enhance educators’ AI proficiency and suggests policy recommendations for AI-driven curriculum development. Full article

This paper presents an initial output of the project “Augmented Intelligence in Mathematics Education through Modeling, Automatic Reasoning and Artificial Intelligence (IAxEM-CM/PHS-2024/PH-HUM-383)”. The starting hypothesis of this project is that the use of technological tools, such as mathematical modeling, visualization, automatic reasoning and artificial intelligence, significantly improves the teaching and learning of mathematics, in addition to fostering positive attitudes in students. With this hypothesis in mind, in this article, we describe an investigation that has been developed in initial training courses for mathematics teachers in several universities in Madrid, where students used GeoGebra Discovery automated reasoning tools to explore geometric properties in real objects through mathematical paths. Through these activities, future teachers modeled, conjectured and validated geometric relationships directly on photographs of their environment, with the essential concourse of the automated discovery and verification of geometric properties provided by GeoGebra Discovery. The feedback provided by the students’ answers to a questionnaire concerning this novel approach shows a positive evaluation of the experience, especially in terms of content learning and the practical use of technology. Although technological, pedagogical and disciplinary knowledge is well represented, the full integration of these components (according to the TPACK model) is still incipient. Finally, the formative potential of the approach behind this experience is highlighted in a context where Artificial Intelligence tools have an increasing presence in education, as well as the need to deepen these three kinds of knowledge in similar experiences that articulate them in a more integrated way. Full article

With the rapid proliferation of Generative Artificial Intelligence (AIGC) technologies in higher education, identifying effective integration pathways into design curricula has become a pressing issue in the field of educational technology. This study employs a mixed-methods approach grounded in the Technology Acceptance Model (TAM) and the Technological Pedagogical Content Knowledge (TPACK) framework, incorporating course analysis, questionnaire surveys, structural path modeling, and interview analysis. Focusing on both instructors and students, this research systematically investigates the acceptance, integration mechanisms, and sustainable development potential of AIGC in university-level design education. The findings indicate that students generally acknowledge the value of AIGC in enhancing creativity and improving efficiency, although gaps persist in their understanding of ethical considerations and original expression. On the teachers’ side, technological knowledge exerts a significant positive influence on the integration of content knowledge, while the impact of pedagogical knowledge remains underutilized. Interview data further reveal a structural tension within current teaching practices, characterized by the rapid adoption of technological tools contrasted with the slower evolution of pedagogical systems. Based on these insights, this study offers five strategic recommendations for sustainable teaching, including the development of teacher training systems, curriculum module design, student media literacy enhancement, and pedagogical reconstruction aligned with the Sustainable Development Goals (SDGs). These findings provide both theoretical and practical contributions to the effective and sustainable integration of AIGC into higher design education. Full article

This study examined the effectiveness of an 18-week online blended teacher professional development program for Kenyan in-service teachers. Also, teachers received instruction on the use of an evidence-based early literacy software program for children. The 94 teachers completed two professional development training modules (alphabetics and fluency) and four surveys (one before and one after each module). Surveys assessed teachers’ confidence and knowledge consistent with the primary elements of the TPACK model (i.e., content, pedagogy, technology). Knowledge gains were observed for fluency content, but not alphabetics content. Across the program, there were gains in pedagogical knowledge and teachers’ confidence. Given the importance of technology in the present study, additional analyses involving intersections of key elements with technology were examined. Outcomes supported the importance of technological pedagogy for the overarching integrated TPACK model. Overall, the TPD and accompanying course material provided some support for teachers who struggle with literacy instruction. Full article