Short-bio:
Andrea Zanellati has been a high school math and physics teacher since 2011. Since November 2020 he is pursuing a Ph.D. in Data Science and Computation at the University of Bologna, with an interest in the applications of Machine Learning methods for the analysis of educational data. He has been interested in designing predictive models for low achievement using data collected through large-scale assessment tests and academic dropout. He is also interested in the knowledge tracing problem. Currently, he is a visiting Ph.D. Candidate at the DIPF in Frankfurt.
Current PhD. Project
The research project concerns automated knowledge tracing (KT) and skills development (SD) using machine learning techniques for educational data analysis. We aim to investigate which data can be used for this purpose, how to encode students’ learning, and how to integrate domain knowledge and pedagogical assumptions into the machine learning pipeline to improve the interpretability of the results and the transparency of the predictive/diagnostic machine learning models. The development of automated tools for KT and SD can be used to tackle educational issues such as underachievement, school or academic dropout, and personalized learning.