SYSTEMATIC LITERATURE REVIEW AND META-ANALYSIS WITH ARTIFICIAL INTELLIGENCE

In the framework of the international cooperation program of the Compostela Group of Universities, the Faculty of Educational Studies at Adam Mickiewicz University (AMU), Poznań, Poland, hosted an advanced methodological workshop entitled “Systematic Literature Review and Meta-Analysis with Artificial Intelligence”, conducted by Prof. Dr. Omar Israel González Peña (University of Monterrey, Mexico). The official certificate issued by the organizing committee formally recognizes his role as workshop leader at AMU on this date.
The primary objective of the workshop was to strengthen participants’ research capacities in conducting systematic literature reviews and meta-analyses through the integration of artificial intelligence–based tools within internationally recognized methodological standards, particularly the PRISMA framework. The training was designed to respond to current challenges in managing large-scale scientific evidence, enhancing methodological rigor, and increasing the transparency and reproducibility of review studies.
The workshop provided hands-on guidance on the strategic use of AI-assisted platforms for literature search, screening, thematic clustering, data extraction, and synthesis. Participants were trained to combine automated tools with critical human judgment to ensure methodological validity and minimize bias throughout the review process. Special emphasis was placed on designing robust search strategies, managing bibliographic databases, and documenting workflows in accordance with PRISMA reporting guidelines.
In addition, Professor González Peña introduced participants to advanced bibliometric and thematic indicators for identifying high-impact, interdisciplinary, and emerging research topics. The session addressed how citation patterns, keyword co-occurrence, thematic evolution, and journal metrics can be systematically analyzed to assess research relevance, societal impact, and publication potential. This component enabled participants to critically evaluate research trends and strategically position their future review studies within high-impact academic contexts.
Overall, the workshop functioned as a capacity-building platform aimed at fostering methodologically sound, AI-enhanced evidence synthesis and promoting international research collaboration. By integrating technological tools with rigorous review standards and impact-oriented analysis, the training contributed to strengthening AMU’s and its partners’ competencies in producing high-quality, interdisciplinary, and globally competitive review publications.