Use of Large Language Models for automated evaluation and support in the digital modeling tool KEA-Mod
- Type:Bachelor / Master
- Date:ab sofort
- Supervisor:
Further information
Background
In the context of software development or the digitalization and automation of business processes, for example, modelling tools are becoming increasingly important. In the BMBF-funded project KEA-Mod, a digital modeling tool was developed as a web application in which evaluation services for the automated evaluation of student models, e.g. from exercises, courses, tutorials or written exams(ination), can be integrated. Modeling languages from the divisions of software development and databases (UML, ER) and from the field of business process management (BPMN, Petri nets, EPK) are currently supported. Large Language Models (LLMs) offer great potential to be used profitably in automated assessment by providing students with LLM-generated re-registration, re-enrollment of their models.
Task definition
The target of the work is to investigate different possibilities for the integration of LLM technologies into the modeling platform KEA-Mod and to develop a prototypical implementation.
Possible focal points:
- How can student models be analyzed and evaluated with regard to the task using an LLM? How can, for example, syntactic correctness, content consistency (semantics) and pragmatic aspects (clear layout design) be taken into account according to the teacher's specifications?
- How can an LLM-based chatbot support students directly during the creation of models? How much information can a chatbot give students to support the learning process?
Students can also contribute their own ideas on the topic in consultation with the supervisors.