Aim/Purpose: Evaluate teachers’ perceptions, strategies, and challenges in integrating artificial intelligence (AI) into K-12 education and identify patterns and trends in the data from the reviewed studies. Background: This systematic review examines a decade of innovation to explore the transformative impact of AI on education (2014–2024). Adhering to PRISMA 2020 guidelines, the study uncovers key trends, challenges, and breakthroughs in AI-driven teaching and learning, offering a comprehensive perspective on how AI reshapes educational practices and methodologies. Methodology: The study employs a systematic review to analyze the implementation of AI techniques and tools in primary education, following the PRISMA 2020 guidelines to ensure the reliability and effectiveness of the findings. To achieve this, an extensive search was conducted in academic databases such as Web of Science, Scopus, and ERIC, focusing on empirical studies and peer-reviewed articles published between 2014 and 2024. Only accessible, peer-reviewed articles classified under Education and Educational Research and published in English or Spanish were selected. The search strategy was structured into five categories aligned with the research questions to identify relevant studies accurately. The selection process was carried out in three phases – Identification, Screening, and Inclusion – applying predefined criteria to guarantee the quality and relevance of the selected studies. Of an initial total of 514,919 articles, 488,940 were excluded for not meeting the inclusion criteria. After removing duplicates and evaluating titles, abstracts, and full texts, a final set of 28 studies was included. Contribution: The study explores the integration of AI in primary education, revealing both teachers’ enthusiasm and the challenges they face. While AI is perceived as a tool to enhance critical thinking, problem-solving, and student engagement, its implementation is limited by insufficient training, resources, and institutional support. Despite these obstacles, teachers show confidence in designing AI-integrated curricula, though this is weakened by inadequate infrastructure and technical support, highlighting the need for continuous professional development. The study also stresses the importance of establishing a competency framework for AI literacy and adopting a systemic approach to AI education. Additionally, ensuring safe learning environments by addressing data privacy and AI biases remains a key challenge. Overcoming these issues is essential for the ethical and effective integration of AI, maximizing its benefits while safeguarding student equity and security. Findings: - Educators see the potential of AI to personalize learning. - Barriers are lack of training and resources for teachers. - Importance of continuous training in digital skills. - Need for policies that promote AI literacy. - Collaboration with experts to optimize AI in the classroom. Recommendations for Practitioners: Teachers are encouraged to collaborate in using AI tools to enhance educational outcomes, supported by continuous professional development programs, clear policies that safeguard privacy and promote equality, and a framework that preserves human autonomy in integrating AI technologies. Recommendation for Researchers: The lack of empirical research on AI interventions in education limits understanding of its true impact, highlighting the need for future studies to fill this gap and optimize its application for greater educational benefits. Impact on Society: The integration of AI in K-12 education is not just an opportunity; it is a necessity to prepare future generations for an increasingly digital world. While AI has the potential to revolutionize learning by fostering critical thinking, personalization, and engagement, its impact depends on how effectively it is implemented. To ensure its benefits, it is essential to empower educators and students with AI literacy, address issues like bias and data privacy, and establish robust legal frameworks for fair and transparent use. Without proactive policies, AI could widen educational inequalities instead of reducing them. A responsible, human-centered approach is needed to create an inclusive, ethical, and effective AI-powered education system. Future Research: The article highlights the urgency of future empirical research to better understand the real impact of AI in education, as the lack of intervention studies limits its optimal application. Analyzing how AI influences learning outcomes, teaching dynamics, equity, and accessibility is essential, along with investigating the pedagogical competencies and technological conditions that affect its adoption. To this end, expanding the scope of studies is recommended by incorporating multicultural and multilingual perspectives, exploring AI applications across various disciplines and educational levels, and promoting interdisciplinary approaches that address ethical, social, and pedagogical dimensions.

Incorporating technology into virtual education encourages educational institutions to demand a migration from the current learning management system towards an intelligent virtual educational system, seeking greater benefit by exploiting the data generated by students in their day-to-day activities. Therefore, the design of these intelligent systems must be performed from a new perspective, which will take advantage of the new analytical functions provided by technologies such as artificial intelligence, big data, educational data mining techniques, and web analytics. This paper focuses on primary education in developing countries, showing the design of an intelligent virtual educational system to improve the efficiency of primary education through recommendations based on reliable data. The intelligent system is formed of four subsystems: data warehousing, analytical data processing, monitoring process and recommender system for educational agents. To illustrate this, the paper contains two dashboards that analyze, respectively, the digital resources usage time and an aggregate profile of teachers’ digital skills, in order to infer new activities that improve efficiency. These intelligent virtual educational systems focus the teaching–learning process on new forms of interaction on an educational future oriented to personalized teaching for the students, and new evaluation and teaching processes for each professor.

The rapid integration of Artificial Intelligence (AI) into higher education underscores the urgent need to assess and foster robust AI literacy among future teachers. This cross-disciplinary competence is a critical, ethical, and equity-oriented foundation that empowers educators to personalize instruction and promote inclusive learning. However, current literature exhibits a methodological gap due to the scarcity of validated Spanish psychometric instruments. Furthermore, previous studies often evaluate pre-service teachers homogeneously, overlooking specialization-specific asymmetries and hindering the development of tailored, realistic, and effective curricula. To address this limitation, this study validates the Spanish adaptation of the Meta AI Literacy Scale (MAILS) to multidimensionally assess AI literacy. The 34-item instrument—measuring application, understanding, detection, ethics, creation, self-efficacy, and self-competence—was administered to a sample of 471 students in the Faculty of Education at the University of Salamanca across Sport and Exercise Sciences (48.6%), Primary Education (34.4%), Early Childhood Education (11.9%), and minor academic tracks (5.1%), providing high ecological validity. Psychometric validation demonstrated excellent internal consistency (overall Cronbach's alpha = .903). Overall, students exhibited strengths in practical application and self-efficacy, but only moderate levels of theoretical understanding and detection. ANOVA tests revealed significant competency disparities across seven of the nine assessed dimensions. Sport Sciences students excelled in creation (M = 7.62) and application (M = 17.22) due to their frequent use of performance-monitoring technologies. Conversely, Early Childhood Education students exhibited high digital vulnerability, scoring lowest in creation (M = 5.41), application (M = 14.38), and problem-solving self-efficacy (M = 6.34). Primary Education students demonstrated the highest resistance to algorithmic persuasion (M = 9.65). Transversely, the ethics dimension showed no significant differences (F = 0.053, p = .948), reflecting a shared, highly developed deontological awareness. In conclusion, these findings highlight the need to abandon one-size-fits-all digital training in higher education. Designing tailored curricular pathways that address the specific epistemological, technical, and affective demands of each degree is essential. Only through targeted preparation can AI literacy drive equity and social justice, empowering future educators to implement AI, open educational resources, and Universal Designfor Learning frameworks safely, ethically, and inclusively.

El presupuesto de una eficaz transmisión de conocimientos es su adecuado almacenamiento, algo que el hombre ha conseguido de modo excelente, merced al lenguaje simbólico, íntimamente ligado a su capacidad de abstraer. La educación debe capacitar para relacionar causalmente los conocimientos dispersos e integrarlos críticamente en una visión holística del mundo. La utilización de las TIC reporta ventajas muy importantes, pero no carece de sombras y aspectos preocupantes. Por ejemplo, el control exhaustivo de todo lo que somos y hacemos. Todos parecen estar de acuerdo en que los criterios por los que se rige el desarrollo humano son unilaterales e insuficientes. Pero va a ser muy difícil luchar eficazmente contra los instintos de agresividad, posesión y dominio, tan profundamente arraigados en nuestras disposiciones genéticas, ya que ello implica sacrificios personales y colectivos, difícilmente aceptables, si no se parte de valoraciones morales distintas de las comúnmente admitidas en nuestros días

En las actuales sociedades avanzadas cada ciudadano genera a diario una ingente cantidad de datos sobre su persona. La masiva utilización de esta información por las tecnologías Big Data (BD) suscita profundos y justificados recelos en muchas personas. Sobre todo por la incidencia que podría tener en derechos humanos como la privacidad, la libertad, la igualdad y la justicia social y porque el formidable poder que representa BD es controlado por un número cada vez más anónimo y reducido de personas. La utilización de herramientas tecnológicas en todos los niveles del aprendizaje podría reportar grandes ventajas, a pesar de los recelos que suscita en algunas personas. En sí mismos, los conoci-mientos no tienen connotaciones éticas, sino que su moralidad radica en el uso que de ellos se haga. Los ángeles y los demonios no están en la técnica, sino en el corazón de quienes se sirven de ella. Será muy difícil enfrentarse a problemas como los arriba mencionados, si los principios morales de que partimos en nuestros debates no son distintos de los habituale