Designing and Generating Lesson Plans combining Open Educational Content and Generative AI Show others and affiliations
2024 (English) In: ACM/IEEE 27TH INTERNATIONAL CONFERENCE ON MODEL DRIVEN ENGINEERING LANGUAGES AND SYSTEMS: COMPANION PROCEEDINGS, MODELS 2024, ASSOC COMPUTING MACHINERY , 2024, p. 78-86Conference paper, Published paper (Refereed)
Abstract [en]
In this paper, we propose an approach for assisting educators in deriving lesson plans for complex learning subjects like ModelDriven Engineering (MDE) from existing educational materials, leveraging generative AI techniques. Our method focuses on guiding teachers in defining learning objectives and suggesting concrete learning activities for students. Central to our approach is the development of a metamodel that characterizes the methodology and serves as the foundation for implementing supporting tools. By utilizing available Open Educational Resources (OERs) and incorporating them into specific learning activities, our method provides a general framework for supporting educators in designing lesson plans. We present the methodology to generate lesson plans, the metamodel conceptualizing plans ingredients, and demonstrate their application through supporting tools, illustrating the potential of our approach in facilitating the development of MDE teaching materials.
Place, publisher, year, edition, pages ASSOC COMPUTING MACHINERY , 2024. p. 78-86
Keywords [en]
Open Educational Resources, OERs, Model-driven engineering, MDE, Generative AI, Educational Paradigms, Tailored Learning Activities, Customizable Learning Content
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers URN: urn:nbn:se:mdh:diva-69429 DOI: 10.1145/3652620.3687773 ISI: 001351589800017 ISBN: 979-8-4007-0622-6 (print) OAI: oai:DiVA.org:mdh-69429 DiVA, id: diva2:1920099
Conference ACM/IEEE 27th International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings (MODELS), SEP 22-27, 2024, Linz, AUSTRIA
2024-12-102024-12-102024-12-10 Bibliographically approved