Generative AI in Academic Research — Database on Usage, Perception and Productivity

Structured database on the use of generative AI in academic research and university teaching in Latin America (2022-2025).

Author: Juan Moisés Serna Tuya | ORCID: 0000-0002-8401-8018

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Open the exploratory analysis notebook — no installation needed:

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Dataset Contents

• AI tool adoption rates (ChatGPT, Copilot, Gemini, Claude, etc.)
• Perception metrics: trust, utility, ethical concerns
• Productivity indicators: time savings, output quality
• Demographic breakdown by country, discipline, and institution type
• Latin America focus: 15+ countries, 2022–2025

📖 Citation

If you use this dataset or database in your research, please cite:

APA: Serna Tuya, J. M. (2025). Structured database on the use of generative artificial intelligence (GAI) in academic research and university teaching in Latin America (2022–2025). Zenodo. https://doi.org/10.5281/zenodo.15229868

Chicago: Serna Tuya, Juan Moisés. "Structured Database on the Use of Generative Artificial Intelligence (GAI) in Academic Research and University Teaching in Latin America (2022–2025)." Zenodo, 2025. https://doi.org/10.5281/zenodo.15229868.

BibTeX:

@dataset{sernatuya_2025_genai,
  author    = {Serna Tuya, Juan Moisés},
  title     = {Structured database on the use of generative AI in academic research in Latin America (2022–2025)},
  year      = {2025},
  publisher = {Zenodo},
  doi       = {10.5281/zenodo.15229868},
  url       = {https://doi.org/10.5281/zenodo.15229868}
}

How to Cite

If you use this repository in your research, please cite:

de la Serna, J. M. (2026). Generative Ai In Academic Research Database On Usage Perception And Productivity. Universidad Internacional de La Rioja (UNIR). https://github.com/juanmoisesd/generative-ai-in-academic-research-database-on-usage-perception-and-productivity 10.5281/zenodo.15229868

See CITATION.cff for formatted references.

Overview

This repository contains data and resources related to generative ai in academic research database on usage perception and productivity. It is part of an open science initiative to share research findings and datasets with the global scientific community.

Research Context

The project addresses key questions in the field of neuroscience and social sciences, focusing on providing accessible data for further analysis and validation.

Repository Structure

• data/: Contains the datasets used in this research.
• src/: Source code for data processing and analysis.
• results/: Output files, figures, and metrics.

Usage

To use the resources in this repository, clone the project and ensure you have the necessary dependencies installed. Refer to the specific documentation in each folder for more details.

License

This project is licensed under the MIT License - see the LICENSE file for details.