GENERATING - Development and Implementation of an Adaptive Exercise Generator for Engineering Courses based on Artificial Intelligence

The project GENERATING aims to develop an artificial intelligence (AI) based adaptive task generator for technical and engineering courses at the Hamburg University of Technology. The project is jointly conducted by the Institute of Technical Logistics, Institute of Maritime Logistics, Center for Teaching and Learning and the IT department of the TUHH. 

Project duration 01.03.2021 – 29.02.2024
Project funding funded by grants provided by the Federal Ministry for Education and Research (BMBF)
Our status Project partner
Contact persons Andreas Mohr
Project pages Link 1 Link 2
Project partners The project consortium constits of:
 
  • Institute of Technical Logistics at TUHH
  • Institute of Maritime Logistics at TUHH
  • Center for Teaching and Learning at TUHH
  • IT department at TUHH

Description

Personalized supervision is a proven way to improve learning progress and conceptual knowledge of students. With respect to the increasing amount of students, the use of task generators which create exercises automatically became increasingly popular in the last years. 

A prototype of an automated exercise generator will be implemented in the existing learning management system (LMS) of the TUHH and will be applied in two teaching modules. The task generator will focus on technical and engineering tasks. The students learning behaviour, as well as their results will be evaluated by KI-based algorithms and will be compared to competence profiles. Based on this assessments, personalized feedback and individualized new exercises will be given to the students, to further improve their learning curve.  

 

This research project is funded by grants by the Federal Ministry for Education and Research (BMBF) by code 16DHB4007. The authors are responsible for the contents of this publication.

Publications (excerpt)

  • Grasse, Ole and Mohr, Andreas and Lange, Ann-Kathrin and Jahn, Carlos (2023). AI Approaches in Education Based on Individual Learner Characteristics: A Review. 2023 IEEE 12th International Conference on Engineering Education (ICEED) IEEE: 50--55 [Abstract] [pdf] [doi] [www]