Higher Educational Institutions (HEIs) are responsible for creating healthy and sustainable environments for students and teachers through diverse educational paradigms such as gamification. In this sense, the Healthy People 2030 and the Sustainable Development Goals indicated the imperative to provide inclusive and equitable quality education to promote a healthy environment and life. The principal objective was to analyse the impact of gamification on health development in HEIs, highlighting their positive and negative effects. To achieve such an objective, a bibliometric analysis was carried out. The 257 documents showed no significant increasing trend in the last decade (p > 0.05) related to the pandemic. Most of the publications were conferences (45%), and the few published articles were the documents with more citations (p < 0.001). According to their index in Journal Citation Reports, there were significant differences between the citations of articles published in journals (p < 0.001). The analysis of journal co-citations showed that the leading journals (such as Computers in Human Behavior) had a significant part in the clusters formed (p < 0.001), conditioning also the keywords, especially the term “motivation”. These findings were discussed, concluding that the experimental studies focused on the teachers’ adverse effects are yet to come.

Information and communication technologies (ICTs) are key to create sustainable higher education institutions (HEIs). Most researchers focused on the students’ perspective, especially during the online teaching caused by COVID-19; however, university teachers are often forgotten, having their opinion missing. This study’s objective was to determine the factors that contribute to the inclusion of ICTs. The research based on a comparative study through an online qualitative survey focused on the inclusion and use of ICTs in two HEIs and two different moments (pre- and post-lockdowns). There were differences regarding country and working experience (p < 0.001), being linked to the ICTs use, evaluation of obstacles, and the role given to ICTs (p < 0.05). The COVID-19 caused modifications of the teachers’ perspectives, including an improvement of the opinion of older teachers regarding the essentialness of ICTs in the teaching process (p < 0.001) and worsening their perception about their ICTs skill (p < 0.05). Additionally, an initial model focused only on the university teachers and their use of ICTs has been proposed. In conclusion, the less experienced university teachers used more ICTs, identified more greatly the problematic factors, and considered more important the ICTs, with the perception of all teachers modified by COVID-19.

Stress can result in psychopathologies, such as anxiety or depression, when this risk factor continues in time. One major stressor was the COVID-19 pandemic, which triggered considerable emotional distress and mental health issues among different workers, including teachers, with another stressor: technology and online education. A mixed-method approach is presented in this research, combining a cross-sectional study of university teachers from Ecuador and Spain with a medium of twenty years of working experience (N = 55) and a bibliometric analysis carried out in three databases (161 documents). The levels of anxiety and depression, and therefore the risk of developing them as mental disorders, were high. The lack of training (p < 0.01), time (p < 0.05), or research regarding the use of technology in education (p < 0.01) and stress caused by COVID-19 (p < 0.001) were linked to frequency. The most relevant observational study obtained through the bibliometric analysis (138 citations and over 65% of methodological quality) indicated that previous training and behavioral factors are key in the stress related to technology. The combination of the results indicated that mental health in STEM teachers at university is related to diverse factors, from training to the family and working balance.

The ECOTEC_Online Student Risk Dataset contains anonymized institutional records from online higher education programs at Universidad ECOTEC, Ecuador. The dataset comprises 12,632 student-level records, with exactly one record per unique student, and 18 public variables covering demographic, academic, admission, financial, and institutional information relevant to student risk and institutional analytics in digital learning environments. Universidad ECOTEC provided the research team with an institutionally anonymized dataset prepared in accordance with its approved institutional protocol. The public repository is organized around the finalized anonymized dataset and includes variable-level metadata, data-validation and descriptive-analysis scripts, reproducible Logistic Regression and Random Forest benchmark scripts and outputs, supplementary visualizations, software-environment specifications, and FAIR-oriented repository documentation. TARGET_RISK is a binary variable derived during study-level data curation from restricted STUDENT_TYPE and GRADUATION_DATE information. Operationally, Class 1 denotes students who were not recorded as Alumni and had no valid GRADUATION_DATE recorded in the institutional snapshot; it should not be interpreted as confirmed educational risk or as a prospectively observed dropout outcome. It represents a contemporaneous administrative proxy based on recorded completion status rather than a prospectively observed dropout or retention outcome. Potential reuse scenarios include learning analytics, educational data mining, institutional analytics, class-imbalanced classification, explainable artificial intelligence, machine-learning benchmarking, educational decision-support research, responsible AI, and exploratory fairness-aware analyses using the demographic and institutional subgroup variables retained after anonymization. The dataset and associated reproducibility resources are publicly archived in Zenodo as version 1.0.4 (DOI: 10.5281/zenodo.22015963) [1].

Generative artificial intelligence (GenAI) is increasingly being integrated into educational practices, transforming how students access information, develop ideas, and carry out cognitive tasks. While GenAI offers opportunities to foster critical thinking and creativity, its use raises concerns regarding "cognitive offloading"—the delegation of reasoning processes that are fundamental to learning. This study presents a review based on 108 documents from Scopus and Web of Science, which allowed for an examination of the relationships between GenAI, critical thinking, creativity, and cognitive offloading, as well as their pedagogical and institutional implications. The evidence analyzed suggests that GenAI can improve immediate task performance, facilitate idea generation, and support content development. However, these benefits do not necessarily translate into autonomous learning or greater creative originality. Outcomes appear to depend on students' prior knowledge, their AI literacy, task design, metacognitive regulation, and the nature and timing of pedagogical support. Based on this review, an AI-Mediated Cognitive Infrastructure Framework (AMCIF) is proposed, which links GenAI usage patterns with cognitive processes, educational practices, and institutional conditions. This framework distinguishes between forms of assistance that promote cognitive engagement and those that might replace the mental activity necessary for learning, emphasizing the essential role of instructor mediation, source verification, reflective practices, and process-oriented assessment. The AMCIF provides a conceptual foundation for analyzing how to integrate GenAI into educational settings while preserving critical judgment, creativity, and the capacity for independent reasoning. The proposed relationships require rigorous empirical validation.