Journal of Statistics and Data Science Education

Building AI-Powered Learning Experiences

The emergence of large language models and multimodal generative AI has transformed how statistics educators create educational resources for their students. Beyond generating explanations and solving statistical problems, these technologies can now assist teachers in designing complete learning environments, including interactive applications, simulations, virtual tutors, adaptive assessments, visualizations, educational games, dashboards, coding assistants, and intelligent learning companions.

One of the four annual issues of the JSDSE will contain a large cluster of contributions by statistics educators that investigate how generative AI can accelerate, democratize, and improve the creation of innovative educational tools for statistics and data science education.

In addition to addressing the classroom use of AI, we are interested in the design process, development methodologies, evaluation, and educational impact of AI-generated learning technologies for statistics and data science education, including AI-Augmented Educational Design. 

Possible topics:

• AI-generated web applications for teaching statistics.
• Intelligent tutors and conversational learning agents.
• Interactive simulations and virtual laboratories.
• Automatic generation of statistical datasets and realistic case studies.
• AI-assisted assessment, feedback and adaptive learning.
• Educational games and gamification powered by generative AI.
• Low-code/no-code development of statistics education tools.
• Multi-agent systems for statistics learning.
• AI copilots for R, Python, SPSS and statistical software.
• Prompt engineering and workflow design for educational tool creation.
• Evaluation of AI-generated educational applications.
• Ethical, privacy and reproducibility issues in AI-generated educational technologies.