Students

Efrat Vinker

(M.Sc, graduated 2021)

" Modern digital learning environments collect rich data on the behavior of millions of users and provide a unique opportunity to study human learning and to develop data-driven methods that can address the needs of learners, instructors, and content developers. My research focuses on learners' behavior in CS101 MOOC (Massive Open Online Course), “First Steps in Computer Science and Python Programming” by Tel Aviv University. Using graphical visualization analysis and machine learning methods over students' performance in programming exercises, we provide useful insights about students' interaction with the online learning system. Specially we diagnose student attrition (dropout points), students' common patterns, and facilitate the instructor with data driven tools to estimate the educational value of predefined unit tests."

Raz Landau

(M.Sc, graduated 2022)

" Martin Fowler, a thought leader in software engineering, is (in)famously quoted as writing “Any fool can write code that a computer can understand. Good programmers write code that humans can understand”. However, while the use of autograders for code correctness is widespread, less effort has focused on automating feedback for good programming style. My research focuses on using a variety of computational tools to automatically analyze students’ coding styles in Tel Aviv university’s CS1001.py: Extended Introduction to CS course and provide helpful feedback to those in need."

Or Goren

(M.Sc)

" Applying ML Algorithms to get insights on educational data from MOOCs (Massive Open Online Courses): my research will focus on automated feedback and how to improve its timing and amount of details. Another goal is to cluster students based on their MOOC data to seek patterns of different learning processes and get insights from them. "