During the COVID-19 pandemic, most Higher Education Institutions (HEIs) across the globe moved towards “emergency online education”, experiencing a metamorphosis that advanced their capacities and competencies as never before. Teaching and Learning Centers (TLCs), the internal units that promote sustainable transformations, can play a key role in making this metamorphosis last. Existing models for TLCs have defined the competencies that they could help develop, focusing on teachers’, students’, and managers’ development, but have mislead aspects such as leadership, organizational processes, and infrastructures. This paper evaluates the PROF-XXI framework, which offers a holistic perspective on the competencies that TLCs should develop for supporting deep and sustainable transformations of HEIs. The framework was evaluated with 83 participants from four Latin American institutions and used for analyzing the transformation of their teaching and learning practices during the pandemic lockdown. The result of the analysis shows that the PROF-XXI framework was useful for identifying the teaching and learning competencies addressed by the institutions, their deficiencies, and their strategic changes. Specifically, this study shows that most institutions counted with training plans for teachers before this period, mainly in the competencies of digital technologies and pedagogical quality, but that other initiatives were created to reinforce them, including students’ support actions.

Learning Analytics is a vast concept and a rapidly growing field in higher education used by professors to measure, collect and analyze digital learning records to improve learning, generate new pedagogies, and make decisions about technology-driven learning. The following article presents a mapping and systematic literature review on Learning Analytics and its link to the teaching skills carried out in university practice. The research process reviewed 7,886 articles during the period from 2016 to 2020. After applying the inclusion and exclusion criteria, 50 articles were analyzed in-depth under the dimensions of (1) purposes of Learning Analytics, (2) teaching competencies, and (3) teaching practice in higher education. This work provides a basis for identifying gaps and research opportunities related to the application of teaching competencies in the field of Learning Analytics and incorporating it into teaching practice in online tutoring.

The digital competencies of university students are developed using a digital learning ecosystem that integrates: (a) virtual learning environments, (b) digital learning tools, and (c) learning methodologies. This research followed the methodology of systematic literature mapping and review, searching the WoS and Scopus databases and obtaining a total of 5,652 articles between 2001 and 2023. Inclusion and exclusion criteria were then applied to reduce the number of selected articles and carry out a systematic literature mapping and review. Among the relevant results of the literature mapping and systematic review, the geographic distribution of scientific publications, the educational areas in which they have been worked on, and the universities were identified. Educational methodologies, technological tools, and virtual learning environments used to develop university students’ digital competences holistically were also determined. This study is useful as it provides a comprehensive, general, and detailed overview of scientific production and its main contributions regarding the methodologies, tools, and environments that contribute to developing students’ the digital competencies in higher education.

Critical thinking is a key competency in higher education, particularly in digital environments that demand analysis, judgment, and informed decision-making. Generative Artificial Intelligence (GenAI) represents an emerging opportunity to enhance complex cognitive skills in educational settings. A quasi-experimental research design with a mixed-methods approach was employed and applied to a sample of university students aiming to address the research question: What is the impact of using GenAI tools on the development of critical thinking in university students? The educational intervention consisted of structured workshops that incorporated GenAI tools into activities aimed at developing six dimensions of critical thinking: remembering, understanding, applying, analyzing, evaluating, and creating. Results showed significant improvements in applying (p =.002), analyzing (p =.0008), and evaluating (p =.003), all associated with higher-order thinking skills. Three dimensions -remembering, understanding, and creating- showed statistically significant changes. However, students’ perception showed a notable increase in the value of GenAI use. Additionally, participants highlighted the usefulness of GenAI for generating ideas, decision making, and promoting deeper reflections. The study concludes that the intentional integration of GenAI technologies, when aligned with clear educational goals, can produce a meaningful and positive impact on the development of critical thinking in university contexts. These findings offer empirical support for designing innovative, ethically grounded learning experiences that incorporate GenAI to strengthen cognitive development in higher education.

The rapid expansion of artificial intelligence in the educational field has configured a broad, dynamic, and constantly evolving research domain. Nevertheless, there remains a need to systematically analyze the evolution of its pedagogical approaches and to identify the conceptual dimensions that structure recent scientific production. For this purpose, a systematic literature review was conducted following the PRISMA protocol, based on searches in Web of Science and Scopus. The final corpus consisted of 235 articles, analyzed using bibliometric and semantic techniques in R, including bibliometrix, tidyverse, and ggplot2, complemented by co-occurrence maps developed with VOSviewer. The thematic classification was carried out through an inductive analysis based on clusters and emerging patterns. The results reveal a progressive transition from technocentric approaches toward more complex and integrative pedagogical perspectives. The semantic analysis made it possible to identify four structuring dimensions of the field: critical, ethical, literacy-oriented, and humanistic. Recent literature also shows a growing emphasis on teacher education, academic integrity, and cognitive coexistence between humans and intelligent systems. These findings indicate that artificial intelligence not only introduces technological innovations but is also reconfiguring the epistemological and pedagogical foundations of contemporary education, demanding conceptual frameworks capable of articulating its ethical, cognitive, and formative implications.