Dogbalou Motognon Wastalas d'Assise

Welcome! I’m Wastalas.

I’m a PhD candidate in Applied Data Science and Artificial Intelligence at the University of Trieste, working on the AI-Enhanced STACK Assessment-Based Interactive Math Quiz System — an AI-powered adaptive assessment platform that delivers intelligent, personalized feedback in mathematics learning.

My research focuses on building AI-powered interactive learning and predictive analytics systems that dynamically adapt to student performance, analyze reasoning patterns, and generate contextual hints and explanations in real time. In the African context, where educators often lack tools to interpret STACK assessment data or identify student errors, my PhD project also designs predictive analytics tools for lecturers including the AI-Powered Student Mistake Analyzer, the Feedback Assistant and the AI Chatbot for Educators—to help them visualize, predict, and act on learning data effectively.

This work is part of the broader PNRR/22 initiative, Machine Learning Techniques for Adaptive Math Higher Education, within the Department of Mathematics, Informatics and Geosciences (MIGe) at UniTS.

I am an active member of the STACK Community, Idems International, and collaborate with international researchers to integrate advanced AI methods into online mathematics assessment. My work bridges educational technology, data science, and pedagogical research, aiming to enhance how students learn and how lecturers evaluate mathematical understanding through intelligent feedback systems.

From 2024 to 2025, I have been conducting a pilot study at Masinde Muliro University of Science and Technology (MMUST) in Kenya, where the AI-STACK Assessment system is being tested with undergraduate mathematics students. This pilot connects European AI research with African educational contexts, contributing to the digital transformation of STEM education in higher institutions.

Research Interests:

My research explores the intersection of Artificial Intelligence, Data Science, and Applied Education, with cross-disciplinary applications extending to medicine and business intelligence.

Through my PhD in Applied Data Science and Artificial Intelligence at the University of Trieste, I designed AI-driven adaptive learning and predictive analytics systems that empower both learners and educators, especially within the African higher-education context—to make data-informed pedagogical decisions.