GENERATING
Research project: Generating
Research area: Artificial intelligence, e-learning
Funded by: Federal Ministry of Education and Research
In cooperation with: Institute for Maritime Logistics (MLS), Center for Teaching and Learning (ZLL), TUHH Computer Center (RZ)
Start of the project: 01.03.2021
End of the project: 29.02.2024
ABOUT THE PROJECT
Personal and individual support is a tried and tested way of improving students’ understanding of concepts.
In order to be able to guarantee this under the condition of constantly increasing student numbers, task generators have been increasingly used in recent years as part of blended learning approaches for the automated generation of exercise materials. An adaptive adjustment of the exercises to the learning needs of individual students and consideration of their behavior has not been done sufficiently at this point, especially not in engineering courses.
The aim of the GENERATING project is to develop an adaptive task generator based on artificial intelligence (AI) for engineering subjects at the Hamburg University of Technology (TUHH).
The project is to be carried out by the Institute of Logistics Engineering (ITL), the Institute of Maritime Logistics (MLS), the Center for Teaching and Learning (ZLL) and the Computing Center (RZ). The task generator is to be integrated as a prototype into the TUHH’s existing Learning Management System (LMS) and tested and used in the practical teaching of two teaching modules.
The project is to be carried out by the Institute of Technical Logistics (ITL), the Institute of Maritime Logistics (MLS), the Center for Teaching and Learning (ZLL) and the Computing Center (RZ). The task generator is to be integrated as a prototype into the TUHH’s existing Learning Management System (LMS) and tested and used in the practical teaching of two teaching modules.
The results and students’ behavior when completing tasks will be evaluated using AI-based algorithms and compared with competence profiles. Based on this, students will be provided with personalized tips for finding solutions and individually adapted exercises. This will create a closed loop that will help to improve the individual’s understanding of the concept.
In addition to providing a personalized learning offer, the results and learning statuses should also be available to teachers (pseudonymized if necessary). In this way, courses can also be adapted to the needs of students in face-to-face teaching.
To the official project website: LINK
