IJIRCSTJournal International Journal of Innovative Research in Computer Science and Technology I S Volume 14 Issue 3 Computer Science English May - June 2026 N N Y 2026 05 01 Computer Sciences Edugenie: AI-Powered Adaptive Quiz Generation and Personalized Learning Platform English Y 8 17 Mohd Nasir English Y Mohd Faheem English N Mohd Faizan English N Ankita Srivastava English N https://doi.org/10.55524/ijircst.2026.14.3.2 Edugenie leverages generative artificial intelligence to transform educational technologies, offering a novel platform for personalized and adaptive learning. Edugenie, a web-based platform, automates quiz and study material production through the Google Gemini API, Streamlit, and Firebase Firestore. It accommodates all six levels of Bloom's Revised Taxonomy Remember, Understand, Apply, Analyze, Evaluate and Create empowering educators and learners to produce targeted assessments attuned to precise cognitive objectives. Supported question formats include Multiple Choice Questions True/False and Short Answer. The platform has two main parts: one that creates quizzes and another that generates study materials. It uses a special technique called structured prompt engineering, which is powered by the Gemini Flash model, to create content. This technique is also aided by a parsing pipeline that uses regular expressions, which demonstrates high practical reliability (estimated ~90% success rate on well-formed outputs), based on iterative development testing rather than a formally controlled evaluation. All the data from the Edugenie including quiz attempts, question level metrics and learning analytics is stored in a layered system using Firebase Firestore. This storage and data help us to keep track of users' performance over time. Edugenie was created and published for the public use in just six months. This report explains how Edugenie was built, the technical problems that were faced and how it was evaluated. It also talks about what's next for Edugenie. Edugenie aims to set a benchmark for AI-driven educational projects by being an open-source platform that others can utilize and learn from, fostering innovation in personalized learning. The platform is publicly accessible [26] and the complete source code is openly available [1], enabling reproducibility and extension by the AIED research community. English Generative AI; Bloom's Taxonomy; Quiz Generation; Adaptive Learning; Firebase Firestore; Streamlit; Google Gemini; Learning Analytics; Prompt Engineering https://ijircst.org/abstract.php?article_id=1460