AKILAS

Adaptiver KI-Assistent für die Schule
(BMBF, 2021-2024)

Adaptive AI Feedback for Personalized Learning Support

Intelligent tutoring systems (ITS) have been studied since the 1970s. In addition to multiple-choice exercises, which are easier to process automatically, many “classical” English-language ITS have also included the automatic evaluation of free text answers from students using NLP methods, e.g. by computing the semantic similarities between students’ answers and a pre-defined set of reference answers. In addition, ITS interact with students using natural language, give feedback, provide explanations and ask follow-up questions in a manner similar to human instructors.

Moreover, the aspect of adaptivity has gained increasing interest in recent years. From an educational science point of view, it is highly desirable that teachers teach according to each students’ individual learning patterns and needs. In practice, of course, it is impossible to provide a teaching staff member to each student for personalised instruction. Adaptive ITS attempt to narrow this gap by using AI methods to provide e-learning with the possibility of catering for individual students’ learning paths and needs. Not only will an adaptive ITS provide formative and targeted feedback to students as part of its automatic task evaluation module, it will also suggest suitable study material to individual students based on its knowedge of students’ progress and learning habits. As an assistant to teachers, adaptive ITS systems make it possible for a single teacher to provide personalised instruction and supervision to multiple students in heterogeneous groups.

The AKILAS (Adaptiver KI-Assistent für die Schule) project aimed at developing an adaptive AI-based learning assistant for German-language school children which will help teachers select and evaluate study exercises for students according to their individual needs. Funded by BMBF and running from 2021 to 2024, the project brought together the fields of NLP, AI and Education Sciences and was carried out by the University of Potsdam and the the University of Magdeburg, in co-operation with solocode GmbH in Berlin - an experienced provider of digital learning apps for German schools.

final project report

results documentation of the funding intiative

Project Partners