## 2 Materials and Methods
The inclusion criteria for this study focus on research conducted with higher education teachers and students, covering universities and undergraduate, graduate, or postgraduate programs, regardless of whether the institutions operate under hybrid, face-to-face, or virtual models. Studies investigating the use of generative artificial intelligence tools, such as large language models (LLMs), text or image generators, and generative adversarial networks (GANs), assessing transversal competencies are considered if verifiable qualitative or quantitative results are provided. Empirical articles and systematic reviews published in indexed academic journals, in English or Spanish, from 2023 onwards are included, given the novelty of the line of research. As exclusion criteria, especially for the final synthesis, studies focused on educational levels other than higher education, those that do not use generative AI tools, publications in languages other than English or Spanish, documents other than articles or reviews such as Editorial, Note, Letter, Erratum, Conference paper, Book chapter, Book, and studies published before 2023 are discarded. Phase 3: Search strategies. In this phase, we present the search equation, keywords, and combinations of terms using Boolean operators (AND, OR, NOT) and applied filters. For the search, location, and selection of studies in Web of Science (Wos), Scopus, and PubMed, a replicable search equation was designed, consisting of two thematic clusters; each cluster was linked internally with the Boolean operator \"OR\" and both clusters were linked together by the Boolean operator \"AND\", limiting the search field to the title of the article (see Table 2). Phase 4: Study selection process. This phase specifies the entire selection process, data extraction, and list of included data, considering the elimination of duplicates, review by title and abstract to discard irrelevant studies, review of the full text of the pre-selected studies to confirm their eligibility, recording the number of excluded studies and the reasons for their exclusion. Details are provided below (see Table 3). \begin{table}
\begin{tabular}{l c c c c c c} \hline \hline \multicolumn{2}{c}{**Thematic Clusters**} & \multicolumn{4}{c}{**Search Equation**} \\ \hline \multirow{4}{*}{Generative Artificial Intelligence} & \multicolumn{4}{c}{“Generative Artificial Intelligence” OR “Generative AI” OR “Deep generative models” OR “Machine learning generative” OR “AI generation” OR “Generative Adversarial Networks” OR “Variational Autoencoders” OR “Natural Language Generation” OR “Large Language Models” OR “GenAI” OR “LLMs” OR “LLM” OR “GPT-4” OR “ChatGPT”} \\ \hline Boolean Operator & AND & & & & \\ \hline \multirow{2}{*}{Higher Education} & \multicolumn{4}{c}{“Higher education” OR “university” OR “undergrad” OR “bachelor’s degree” OR “postgraduate” OR “tertiary education”} \\ \hline \hline \end{tabular} Note: In PubMed, each descriptor was preceded by the title field as a setting of the platform’s search algorithm, for example: Generative Artificial Intelligence [Title].  
\end{table} 
Table 2: Search equation. \begin{table}
\begin{tabular}{l c c c c c c} \hline \hline \multicolumn{1}{c}{**Database**} & \multicolumn{1}{c}{**Total Documents**} & \multicolumn{1}{c}{**2025**} & \multicolumn{1}{c}{**2024**} & \multicolumn{1}{c}{**2023**} & \multicolumn{1}{c}{**ChatGPT**} & \multicolumn{1}{c}{**ChatGPT**} \\  & & & & & **Manuscripts** & **Percentage** \\ \hline Web of Science & 283 & 3 & 223 & 57 & 165 & 58.3\% \\ Scopus & 574 & 12 & 449 & 113 & 318 & 55.4\% \\ PubMed & 40 & & 32 & 8 & 30 & 75\% \\ Total & 897 & & & & & \\ \hline \hline \end{tabular} Note: The date of the cut-off was 4 January 2025.  
\end{table} 
Table 3: Summary of articles by database. Phase 5: Data coding and synthesis. For data collection, the Zotero bibliographic manager was used, exporting all references in RIS and BibTeX format.