SCRIPT: Implementing an Intelligent Tutoring System for Programming in a German University Context
For educators and researchers in programming education, this work addresses the need for a compliant, adaptable ITS that supports Python and advanced hint mechanisms, though it is an incremental contribution as it builds on existing ITS concepts.
The paper presents SCRIPT, an intelligent tutoring system for Python programming designed to operate within Germany's strict regulatory environment (GDPR, EU AI Act). It provides a highly adaptable platform that integrates hint mechanisms, including large language models, to support programming education beyond introductory levels.
Practice and extensive exercises are essential in programming education. Intelligent tutoring systems (ITSs) are a viable option to provide individualized hints and advice to programming students even when human tutors are not available. However, prior ITS for programming rarely support the Python programming language, mostly focus on introductory programming, and rarely take recent developments in generative models into account. We aim to establish a novel ITS for Python programming that is highly adaptable, serves both as a teaching and research platform, provides interfaces to plug in hint mechanisms (e.g.\ via large language models), and works inside the particularly challenging regulatory environment of Germany, that is, conforming to the European data protection regulation, the European AI act, and ethical framework of the German Research Foundation. In this paper, we present the description of the current state of the ITS along with future development directions, as well as discuss the challenges and opportunities for improving the system.