Integrating Exploratory Data Analysis and Explainable AI into Astronomy Education: A Fuzzy Approach to Data-Literate Learning

This record corresponds to the accepted manuscript (post-print) of the following journal article:

"Integrating Exploratory Data Analysis and Explainable AI into Astronomy Education: A Fuzzy Approach to Data-Literate Learning"

This article presents a project-based learning framework that integrates exploratory data analysis, fuzzy logic, and Explainable Artificial Intelligence (XAI) to promote data literacy and critical thinking in astronomy education. Using open astronomical datasets and reproducible computational tools, the approach guides students through the full data science pipeline, from data acquisition to interpretable modeling. The framework demonstrates how fuzzy clustering and XAI support meaningful pattern discovery and enhance conceptual understanding in STEM learning contexts.

The final published version is available at the publisher’s website:
https://doi.org/10.3390/educsci15121688

This deposit is made for open access and dissemination purposes, in accordance with the publisher’s self-archiving policy.