Search Results (99)

Collaborative design is recognized as a promising approach to strengthening preservice teachers’ digital competence, yet its potential when design tasks approximate the complexities of classroom practice remains underexplored. This mixed-methods study investigated a Synthesis of Qualitative Evidence (SQD)-aligned collaborative design course in which 23 final-year preservice secondary mathematics teachers, organized in six teams, spent ten weeks designing technology-enhanced lesson materials for authentic design challenges posed by in-service teachers. Using questionnaires and interviews, this study explored preservice teachers’ perceived digital competence development and their perceptions of the SQD-aligned course supports. Regarding competence development, participants indicated increases in self-assessed cognitive (technological knowledge, TPACK) and motivational (technology-integration self-efficacy, perceived ease of use) digital competence dimensions. Qualitative findings linked these perceptions to heightened technological awareness and confidence but noted limited tool mastery due to reliance on familiar technologies and efficiency-driven task division. Concerning course supports, authentic challenges enhanced motivation and context-sensitive reasoning, while layering scaffolds (guidelines, coaching, and microteaching feedback) supported navigating the open-endedness of the design task. Yet calls for earlier feedback and technology-related modeling underscore the need for further scaffolding to adequately support autonomy in technology selection and integration. Findings inform teacher education course design for fostering preservice teachers’ digital competencies. Full article

Generative pre-trained transformers (GPTs) have rapidly entered educational contexts, raising questions about their impact on pedagogy, workload, and professional practice. While their potential to automate resource creation, planning, and administrative tasks is widely discussed, little empirical evidence exists regarding their use in vocational education (VE). This study explores how VE educators in England are currently engaging with AI tools and the implications for workload and teaching practice. Data were collected through a survey of 60 vocational teachers from diverse subject areas, combining quantitative measures of frequency, perceived usefulness, and delegated tasks with open qualitative reflections. Descriptive statistics, cross-tabulations, and thematic analyses were used to interpret responses about the application and allocation of work given by teachers to GPTs. Findings indicate cautious but positive adoption, with most educators using AI tools infrequently (0–10 times per month), yet rating them highly useful (average 4/5) for supporting workload. Resource and assessment creation dominated reported uses, while administrative applications were less common. The choice architecture framing indicates that some GPTs guide teachers to certain resources over others and the potential implications of this are discussed. Qualitative insights highlighted concerns around quality, overreliance, and the risk of diminishing professional agency. The study concludes that GPTs offer meaningful workload support but require careful integration, critical evaluation, and professional development to ensure they enhance rather than constrain VE pedagogy. 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

Environmental education plays a vital role in cultivating environmentally responsible citizens. Although teachers are central to environmental education, their pedagogical practices remain under-researched. Thus, this study targeted to systematically review empirical research on environmental education teaching practices to synthesize findings and identify gaps. 2273 papers between 2015 and 2024 from Teacher Reference Center, ERIC, and GreenFILE were filtered to cover studies focused on environmental education teaching practices by teachers under formal education. To interpret trends of discoveries, we propose an expanded Technological Pedagogical Content Knowledge framework—TPAC+E—by incorporating environmental knowledge alongside existing dimensions. Majority of 111 peer-reviewed articles employed case study designs and interviews, with an increasing emphasis on digital technologies in the post-COVID era. Common teaching practices identified include cross-disciplinary integration, outdoor learning, participatory approaches, and the promotion of critical thinking and empathy. However, widespread reliance on textbooks and teacher-centered instruction persists. The review also highlights significant research gaps in primary education and in underrepresented regions such as the Global South and East Asia. We advocate for more interdisciplinary and context-specific approaches, along with enhanced support for teacher training and curriculum development. This review offers both practical and conceptual insights to advance equitable and effective environmental education worldwide. Full article

Although Artificial Intelligence (AI) is transforming teachers’ knowledge and professional practice, its full potential has yet to be fully realized. To incorporate AI effectively into pedagogical contexts, it is essential that teachers possess the knowledge necessary to guide its responsible use. However, in Latin America, there remains limited empirical evidence to support this process. To address this gap, this empirical study analyzes teachers’ knowledge of AI using the Intelligent-TPACK framework, which includes an ethical dimension. A validated and adapted questionnaire was administered to 709 primary and secondary school teachers from the Metropolitan Region of Chile, using a non-probability sampling method. The sample is compositional–descriptive in nature for the study variables and is not statistically representative of the broader population. Data were analyzed through descriptive and inferential statistical methods. The results reveal mixed levels of knowledge—slightly higher in technological knowledge yet lower in terms of integration and ethical awareness. Significant differences were found by gender, age, teaching level, and subject area. Regression models identified teaching experience, gender, and educational level as the most consistent predictors. Additionally, cluster analysis revealed four exploratory professional profiles characterized by varying degrees of knowledge. These findings are discussed in light of teacher training needs and aim to inform the development of professional learning programs better aligned with the actual demands of the teaching profession. 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

Teachers’ professional digital competence (PDC) refers to digital competence specific to the teaching profession. PDC serves a dual purpose: it encompasses a range of instrumental, professional, ethical, critical, and epistemic dimensions related to, on the one hand, teaching with digital tools and resources and, on the other hand, teaching pupils about digital technologies, digital skills, digital cultural expression, and broader digital and critical competences relevant to study, work, and everyday life. Teachers’ PDC is a dynamic concept that evolves in step with societal development and technological advancement. Full article

In the digital era, integrating technology into education is essential to meet contemporary educational demands. This systematic review examines the competencies and skills in educational technology required from in-service teachers serving in elementary, middle, and high schools, alongside the training models and methods implemented over the past decade. Following PRISMA guidelines, a systematic search was conducted in the Scopus, WOS, and ERIC databases, focusing on studies published between 2014 and 2025. A total of 82 studies were selected based on predefined inclusion criteria. The review analyzed competencies, skills, training models, and methods, identifying prevailing trends in teacher training for educational technology. The review identified seven key competencies, emphasizing skills such as using software, educational applications, and platforms, as well as virtual collaboration. The TPACK model emerged as the predominant framework for teacher training, encompassing various methods, including professional learning communities and Problem-Based Learning. A progressive and structured approach is necessary to develop teachers’ competencies, encompassing both basic technical skills and the adoption of emerging technologies. Continuous and context-specific teacher training in educational technology is critical for sustainable integration and pedagogical transformation. Barriers such as limited infrastructure and resistance to change highlight the need for strong institutional support and mentorship. Future research should aim to expand to diverse educational settings to validate and extend these findings. 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

Teachers’ 21st century technological pedagogical content knowledge affects their performance self-evaluations, and it is considered that their attitudes towards sustainable education disposition and their digital competencies may also have an impact on their performance self-evaluations and thus may significantly affect these relationships. In this study, it was aimed to examine the effect of teachers’ 21st century technological pedagogical content knowledge on their performance self-evaluations, and the moderating role of digital competencies mediated by sustainable educational disposition in the model established for this purpose was examined. The research sample consisted of 478 teachers (305 female (63.8) and 173 (36.2) male teachers) working in various fields in schools in Türkiye. Within the scope of the research, data analyses were carried out in SPSS 21 and PROCESS Macro package programs using Model 4 and Model 58 developed by Hayes (2022). As a result of the analyses, it was seen that sustainable education tendencies had a mediating role in the relationship between teachers’ 21st-century technological pedagogical content knowledge and their performance self-evaluations. In addition to this, it was seen that 21st-century technological pedagogical content knowledge, sustainable educational dispositions and performance self-evaluations depend on the level of digital competencies. 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