SCRIPT: Implementing an Intelligent Tutoring System for Programming in a German University Context

TL;DR

This paper introduces SCRIPT, an adaptable intelligent tutoring system for Python programming tailored for German regulatory standards, supporting advanced hint mechanisms and serving educational and research purposes.

Contribution

The paper presents a novel ITS for Python that integrates large language models, complies with European regulations, and functions as a flexible platform for teaching and research.

Findings

Current system state and future development directions are discussed.

Challenges include regulatory compliance and integration of generative models.

Opportunities involve enhancing personalized tutoring and research capabilities.

Abstract

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.