Using Learning Objective-based Course Modeling for Complete Exercise Generation: From Course Material to an Aggregated Knowledge Representation

Publikationstyp
Conference Paper
Date Issued
2023-11
Sprache
English
Author(s)
Schmidt, Deniz  
Technische Logistik W-6  
Uzulis, Max Vincent 
Zentrum für Lehre und Lernen ZLL  
TORE-URI
https://hdl.handle.net/11420/45558
Citation
IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE 2023)
Contribution to Conference
IEEE International Conference on Teaching, Assessment and Learning for Engineering, TALE 2023  
Publisher DOI
10.1109/tale56641.2023.10398291
Scopus ID
2-s2.0-85184996094
Publisher
IEEE
Learning objectives are an essential part of teaching, but are rarely accounted for in digitization processes of courses. Instead of naively translating existing material into a digital form, they offer a chance to examine a course’s didactic soundness and to create an aggregated knowledge representation. In this paper we present an applied method to digitally model courses based on learning objectives, coupled with a special exercise generator. This approach includes the extraction and categorization of learning objectives from course contents, the formal definition of subject matter and a topical overview of the course. The resulting model allows for a critical view on the didactics of the course through constructive alignment, while also serving as the basis for the exercise generator. Conclusively the effects of the method on the teaching experience, as well as the usability are discussed.