Artificial Intelligence (AI) has entered higher education with applications ranging from immediate feedback to institutional analytics. This article analyzes literature published between 2018 and 2025, in both international and Ibero-American contexts, to identify opportunities and risks of its integration in university teaching. The findings highlight three key axes: adaptive teaching, which enables personalized content and strengthens the teacher’s role; intelligent institutional management, which streamlines processes and anticipates risks such as dropout; and ethical and responsible use, which requires clear policies and regulatory frameworks to ensure equity. Based on this analysis, a functional model is proposed that articulates these three axes as a guide for teachers and institutions. The main conclusion is that the real challenge is not technological but pedagogical and ethical, since innovation is only valuable when it ensures integral training and educational equity.
This research focuses on a reflection on the impacts and limitations of research training programs within the framework of Colombian higher education. To this end, it aims to analyze the contribution of research seedbeds in Colombian higher education institutions, using a qualitative documentary approach to propose strategies that strengthen development in the university environment. The methodology was based on a qualitative documentary and autoethnographic paradigm, through which data was obtained by reviewing academic articles. Subsequently, interpretive analysis and triangulation of the information were carried out, identifying four emerging categories: (I) conceptual and epistemological foundations, (II) research seedbeds, (III) the role of research seedbeds in the development of academic skills, and (IV) challenges and policies of research seedbeds. The results showed that research seedbeds influence the strengthening of university research culture, writing skills, and a sense of institutional belonging. However, there are latent challenges related to low state funding and the persistent limitation in the articulation between theory and practice. In conclusion, research seedbeds represent an opportunity for comprehensive training in higher education, promoting autonomy, critical thinking, and scientific production from the undergraduate level. However, their sustainability is contingent upon effective policies supporting financial resources, academic advising, and adaptation to new technologies.
Digital competencies for citizenship are part of the so-called digital divide or digital inequality; this makes it a topic of current importance for conducting a systematic review of research in Spanish-speaking countries (2019-2024) on digital competencies for citizenship in non-formal education contexts. The objective is to identify the approaches used in the research and its impact on the population, which will allow for the establishment of guidelines for future studies seeking to achieve social impact. Therefore, inclusion and exclusion criteria defined using Boolean equations were applied to Google Scholar, Dialnet, SciELO, and Redalyc, using the PRISMA model for screening and selecting studies. Of the initial 566 documents, after three stages of filtering, 19 studies were included, only one of which addressed educational intervention; the rest focused on evaluating methodological proposals or analyzing existing programs. However, the limitation to open-access Spanish-language literature is considered one of the potential biases in the selection of exclusively non-formal education. Therefore, this review offers an updated and regionalized overview (Latin America and Spain) of digital competencies in non-formal settings, where a scarcity of participatory action studies and the need for contextual and adaptable pedagogical approaches that contribute to reducing the digital divide are evident.
Historical consciousness encompasses a process that establishes relationships between the past, present, and future. Historical consciousness seeks to break the boundaries of the classroom. Inquiry-based learning (IBL) is a didactic-pedagogical approach that integrates strategies that promote learning through active participation throughout the teaching-learning process. This study aimed to strengthen historical awareness in high school students through a pedagogical strategy using inquiry-based learning, based on a qualitative methodology and an explanatory and descriptive approach. An educational intervention was conducted with 42 first-semester high school students in the history course. Preliminary results indicate that inquiry-based learning facilitated a greater understanding of socio-historical topics, promoted work among students both individually and collectively, improved their research skills and abilities, and strengthened oral and written communication skills, as well as critical thinking. The results also show significant progress in historical awareness, particularly in the cognitive (knowledge), narrative (historical interpretation), and moral (historical identity) dimensions. The participation dimension presented greater opportunity for strengthening, requiring the strategy to be reinforced with experiential activities and community engagement, greater contextualization, and interaction with historical heritage.
The training of rural teachers in artificial intelligence (AI) has gained importance in recent years, given that AI is considered a tool that has permeated all fields of knowledge. However, significant challenges and limitations persist in rural schools, related to connectivity, a lack of technological resources, and insufficient specific teacher training. In this context, the purpose of this research article is to measure the level of AI literacy among rural teachers in Latin America. To this end, a quantitative methodological approach was implemented. Based on the conceptualization of AI literacy applied to the rural context, and using the instrument inspired by the version by Mohammed et al. (2021), the dimensions of conceptual knowledge, ethics and professional responsibility, educational application, and attitudes toward AI were measured using a Likert scale. This allowed for the identification of the level of AI literacy, and the data was then analyzed based on the results obtained. Finally, it is concluded that the level of literacy among rural teachers in Latin America is at an intermediate level, suggesting the need to strengthen teacher training to achieve a better understanding of the subject. Qualification is necessary, since the application is currently done in a self-taught manner, thus demonstrating a positive attitude towards the arrival of AI in schools.
