The concept of technological pedagogical content knowledge (TPACK) is presented as a framework that guides how to effectively integrate technologies in the educational environment. Through this model, we investigate the ethical implications related to the use of digital tools in teaching, and we outline the necessary knowledge that educators should have to address these issues of ethics and technology in the classroom. We assess the professional, ethical knowledge of pre-service teachers regarding their use of technologies using a descriptive and exploratory mixed-methods approach. The data for this research come from a Likert-scale questionnaire administered to 616 teacher-training students in Spain, as well as from personal interviews with 411 of them. From these data, we identify four of the eight dimensions of ethical knowledge: professional, ethical knowledge, ethics in the use of technologies, pedagogy for their integration in the classroom, and the use of content specific to the disciplines of pre-service teachers. The results obtained indicate that the preparation of educators with professional, ethical knowledge in training is insufficient, which highlights the need to address this issue in the post-pandemic context of the 21st century. Among the difficulties detected, it should be noted that this study is limited to a European university and a sample chosen for convenience, so it would be advisable to extend the study to other European universities.

This study aims to design, produce, and validate an information collection instrument to evaluate the opinions of teachers at non-university educational levels on the quality of training in artificial intelligence (AI) applied to education. The questionnaire was structured around five key dimensions: (a) knowledge and previous experience in AI, (b) perception of the benefits and applications of AI in education, (c) AI training, and (d) expectations of the courses and (e) impact on teaching practice. Validation was performed through expert judgment, which ensured the internal validity and reliability of the instrument. Statistical analyses, which included measures of central tendency, dispersion, and internal consistency, yielded a Cronbach's alpha of .953, indicating excellent reliability. The findings reveal a generally positive attitude towards AI in education, emphasizing its potential to personalize learning and improve academic outcomes. However, significant variability in teachers' training experiences underscores the need for more standardized training programs. The validated questionnaire emerges as a reliable tool for future research on teachers' perceptions of AI in educational contexts. From a practical perspective, the validated questionnaire provides a structured framework for assessing teacher training programs in AI, offering valuable insights for improving educational policies and program design. It enables a deeper exploration of educational AI, a field still in its early stages of research and implementation. This tool supports the development of targeted training initiatives, fostering more effective integration of AI into educational practices.

Research fronts are dynamic, knowledge-driven clusters of scholarly activity that emerge in response to pressing problems and/or groundbreaking discoveries. Clarivate Analytics provided a valuable tool based on Citation Productivity and Trajectory (CPT) indicator, which successfully identified particularly hot research fronts on a global scale. To enhance the accuracy and comprehensiveness of identifying both active and emerging research trends, this study develops an extended Clarivate formulation incorporating a novel Impact Factor (IF) metric. The refined approach incorporates growth rates, publication productivity, and the average publication gap between published and citing publications. This method is applied to exploring key research fronts in the digital education ecosystem using bibliometric data from the Scopus database in the period of 2019-2023. The results reveal that artificial intelligence and online learning are the most prominent and influential fields, with virtual reality, blockchain, hybrid learning, and digital literacy representing fast-growing areas. By analyzing both quantitative and qualitative aspects, this work informs key stakeholders about the evolving priorities and trends in the digital educational landscape.

This study investigates the effectiveness of scaffolded game development activities in enhancing computational thinking (CT) skills among young learners using a graphical programming environment. While prior research highlights the value of block-based programming in CT education, few studies explore how structured scaffolding supports learners in completing full game projects. Grounded in Vygotsky’s Zone of Proximal Development and Wing’s CT framework, this study involved 310 participants aged 10 to 15, including their teachers, in a tiered sequence of programming tasks using mBlock programming platform. Learners progressed from basic to more complex programming constructs, namely, loops, conditionals, variables, and debugging, which are included in the development of a complete Pac-Man or Snake game. Quantitative results demonstrated significant improvements in CT skills across all age groups. Qualitative data revealed increased learner engagement, reduced programming anxiety, and enhanced interest in computational problem-solving. The findings suggest that scaffolded game development is a promising strategy for early CT instruction, offering both cognitive and affective benefits. This work contributes to current literature by demonstrating how structured support and creative programming tasks can jointly promote CT proficiency and learner motivation in foundational computing education.

This article aims to establish a research map of the flipped classroom (FC) model in general education for the period 2014-2024, exploring publication trends, influential authors, organizations, countries, and prominent research topics, while also identifying academic gaps in this field. The study focuses on three main aspects: (1) publication trends and influential authors, organizations, and countries; (2) key research topics and academic gaps; (3) international collaboration networks in FC research. The research employs a bibliometric analysis method, utilizing the Scopus database and the VOSviewer visualization tool, to synthesize information and identify research trends. The results indicate that research on FC in K-12 education increased sharply from 2019, reflecting the impact of digital transformation in education during and after Covid-19. The United States, Hong Kong, and Taiwan are the leading research centers. Authors such as Bergmann, Bishop, and Hew have been highly influential. Prominent research trends include self-regulated learning, learner satisfaction, gamification, and the application of artificial intelligence. The international collaboration network in this field is growing, with strong participation from institutions from Southeast Asia, including Vietnam. The study recommends expanding the scope of analysis beyond Scopus and using qualitative methods and systematic reviews to further evaluate the FC model. The research will provide policymakers, teachers, and researchers with useful evidence for improving programs, enhancing professional development, and promoting digital transformation in general education.