This study explores the integration of artificial intelligence (AI) into educational data mining (EDM), human-assisted machine learning (HITL-ML), and machine-assisted teaching, with the aim of improving adaptive and personalized learning environments. A systematic review of the scientific literature was conducted, analyzing 370 articles published between 2006 and 2024. The research examines how AI can support the identification of learning patterns and individual student needs. Through EDM, student data are analyzed to predict student performance and enable timely interventions. HITL-ML ensures that educators remain in control, allowing them to adjust the system according to their pedagogical goals and minimizing potential biases. Machine-assisted teaching allows AI processes to be structured around specific learning criteria, ensuring relevance to educational outcomes. The findings suggest that these AI applications can significantly improve personalized learning, student tracking, and resource optimization in educational institutions. The study highlights ethical considerations, such as the need to protect privacy, ensure the transparency of algorithms, and promote equity, to ensure inclusive and fair learning environments. Responsible implementation of these methods could significantly improve educational quality.

This article provides a comprehensive analysis of the research dynamics on the use of Educational Data Mining (EDM) and predictive modeling (PM) in the era of Artificial Intelligence (AI) based on the review of 793 articles published between 2000 and 2024 in the Scopus database. The study employs bibliometric analysis and systematic literature review to identify emerging trends, methodologies, and applications in these fields. The main objective of the study is to examine the primary methodologies and innovations within AI, especially in the context of EDM and PM. It highlights how these technologies can optimize the prediction of student performance, support personalized learning, and enable timely interventions through the analysis of student data. The study also examines the role of AI in improving teaching practices, ensuring that educators maintain control over the system and minimize potential biases. Furthermore, the article addresses the ethical implications of AI implementation in education, such as privacy protection, algorithm transparency, and equity in access to learning. The findings suggest that AI has the potential to significantly improve educational outcomes and optimize student tracking, resource allocation, and the overall effectiveness of educational institutions. The responsible implementation of AI in education is emphasized to ensure inclusive and fair environments for all students.

Abordar desde una perspectiva profesional la evaluación del alumnado implica reflexionar sobre el modelo educativo tradicional, que ha empleado las pruebas de evaluación consistentes en la reproducción escrita de los contenidos como el referente fundamental para evaluar y calificar los conocimientos del alumnado. Sin embargo, en las últimas décadas la comunidad científica educativa ha planteado alternativas a esa evaluación en el plano estratégico, técnico, temporal e instrumental. El objetivo que se marca la investigación es conocer la producción científica sobre la evaluación formativa, relacionada con un modelo complejo y social, frente a la evaluación sumativa, de carácter más operacional e individual. Para ello se ha empleado una metodología mixta que analiza cuantitativa y cualitativamente la evaluación formativa y sumativa en la literatura científica a través de una revisión bibliográfica de las investigaciones de la última década, comparando sus principales indicadores bibliométricos y usando para ello la base de datos Web of Science. Los resultados arrojan un número de investigaciones sobre evaluación formativa notablemente superior a las investigaciones sobre evaluación sumativa, un dominio de la investigación anglosajona y una relación de la investigación sobre evaluación de la educación con otras áreas científicas. Entre las conclusiones se observa que la evaluación del alumnado es una línea de investigación con larga trayectoria histórica que continúa siendo un objeto de investigación de actualidad y generador de transferencia tecnológica entre las distintas áreas de conocimiento.

The present work presents a conceptual organization scheme based on the latest research in the field of Citizenship Education for Social Studies. In a globalized world, educational systems must equip students with the knowledge, skills, and attitudes to engage proactively in societal issues. Political and social disengagement, particularly among youth experiencing family violence and discrimination, can lead to exclusion and radicalization. School segregation limits the learning of democratic values and harms migrant family participation. Youth tend to favor forms of digital and personal participation over traditional politics. In the digital age, it is crucial to review and adapt civic education, promoting media literacy and the conscious consumption of information. Democratic education should connect knowledge with action to foster active, responsible citizenship, despite the challenge of an academically results-focused environment. To achieve this objective, a literature review was conducted to identify didactics orientations, resulting in a five-dimensional framework: the conceptual dimension advocates for deep and relevant civic education; the participatory dimension encourages active involvement; the prosocial dimension promotes democratic values; the critical dimension develops independent thinking to address inequalities; and the identity dimension strengthens the sense of belonging. These dimensions should be integrated into analog, digital, and immersive contexts to prepare active, critical, and responsible global citizens. This matrix integrates dimensions and contexts to offer better guidance to teachers who impart the subject.

Introducción: Los mensajes sobre el uso pedagógico de los móviles en el aula generan debate en las redes sociales y logran crear opinión en la ciudadanía. Los objetivos de este trabajo son: analizar las características de los discursos que se difunden en Facebook y Twitter sobre el uso educativo de los móviles en el aula, según si los argumentos que defienden se basan en la promoción, la prohibición o la indeterminación, e identificar los perfiles de sus principales agentes emisores, así como el tipo de contenido argumental de los mensajes que tienen mayor impacto. Metodología: Se plantea un estudio descriptivo transversal. Se analizan 142 mensajes en español o inglés, sin excluir su procedencia geográfica, desde una aproximación mixta empleando el criterio de engagement para clasificar su relevancia. Resultados: Los resultados muestran que la argumentación predominante es la de la promoción del uso educativo de móviles en el aula siendo los profesionales de la educación quienes mayoritariamente la publican. Los argumentos de prohibición son emitidos principalmente por los medios de comunicación y los perfiles institucionales, siendo estos mensajes los que tienen mayor repercusión. Discusión: Teniendo en cuenta que el liderazgo informal generado en las redes sociales puede provocar cambios en la agenda social y/o política, se destaca la relación hallada entre el tipo de usuario y el tipo de mensaje emitido. Conclusiones: Entre otras, se observa que las críticas y recelos al uso de los móviles en el aula se deben a la confusión generalizada entre móviles y redes sociales.

Quality in higher education requires the evaluation of the teaching-learning and assessment methodologies used by the teachers, the adaptation of the students, as well as the resources used. To respond to this need, this study aims to analyze the validity and reliability of the Factors Related to Teaching Quality (FRTQ) questionnaire, developed for this research. The sample was obtained among Spanish undergraduate students (n = 291). Validation was performed by a content and construct analysis through a review of the literature on the dimensions of teaching, learning and assessment, in addition to obtaining the measure of sampling adequacy and a factor extraction. Reliability was determined by Cronbach’s alpha. The validity and reliability of the questionnaire was confirmed, and the factor analysis showed a six-factor structured model: Functions of the assessment; Attention to diversity, Clarity and control of the educational process; Learning resources; Teaching resources; Assessment resources. The conclusions indicate the importance of approaching some aspects of the educational process from the dimensions of teaching and learning at the same time due to their transversal nature, as well as the relevance of having a useful instrument to evaluate the processes of change and improvement of teaching in Spanish higher education.