The presentation will begin with a brief overview of the project's objectives, highlighting the comparison between generative AI models and traditional statistical software. Students will guide participants through the methodology, showcasing how prompts were used to conduct descriptive and inferential analyses using tools like ChatGPT, Claude, and Gemini. Interactive demonstrations will allow attendees to experiment with AI models in real time, testing statistical queries and observing how the models respond. Participants will be invited to interpret results, compare them with outputs from SPSS or GraphPad, and discuss the implications. The session will include collaborative activities where students and attendees co-design prompts, evaluate statistical accuracy, and reflect on the potential of AI to transform research practices. This dynamic exchange fosters critical thinking, peer learning, and a deeper understanding of how emerging technologies can enhance educational and analytical processes.
Through this session, participants will explore how generative AI tools like ChatGPT, Claude, and Gemini can be used to perform statistical analysis, comparing their outputs with traditional software such as SPSS and GraphPad. They will gain hands-on experience in prompt engineering, data interpretation, and critical evaluation of AI-generated results. By engaging in a design-thinking process, participants will develop competencies in innovation, problem-solving, and digital literacy.
The project’s impact lies in its potential to democratize access to statistical tools, making research more intuitive, cost-effective, and inclusive—especially for learners and educators seeking alternatives to complex and expensive software.
Recent research underscores the transformative role of generative AI in statistical education. Studies show that tools like ChatGPT can assist users with limited statistical training by generating code and guiding analysis. This shift promotes conceptual understanding over software mastery. Comparative analyses reveal that AI models rival traditional tools like SPSS in usability and accessibility, suggesting a democratization of research practices. The project aligns with current trends advocating for AI integration to foster innovation, reduce costs, and expand participation in data-driven inquiry.
https://onlinelibrary.wiley.com/doi/pdf/10.1111/test.12398
https://www.microsoft.com/en-us/education/blog/2025/08/ai-in-education-report-insights-to-support-teaching-and-learning/
https://www.mdpi.com/2227-7102/14/11/1154
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