Pedagogical Perspectives of Interdisciplinary Teaching and Research: An Energy System Modelling Outlook in Relation to Energy Informatics
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https://hdl.handle.net/10037/30907Dato
2023-08-02Type
Journal articleTidsskriftartikkel
Peer reviewed
Sammendrag
The purpose of this paper is to present and discuss pedagogical frameworks and approaches to developing, delivering, and evaluating a new interdisciplinary course within the domain
of energy informatics at both Master’s and PhD levels. This study is needed because many papers
on sustainable energy engineering education concentrate on course content but provide very little
information on the pedagogical methods employed to deliver that content. The proposed new course
is called “smart energy and power systems modelling” and is aimed at discussing how mathematical
optimization, in the context of computer science, can contribute to more effectively managing smart
energy and power systems. Different pedagogical frameworks are discussed and adapted for the specific domain of energy informatics. An ASSURE model coupled with Bloom’s taxonomy is presented
for the design of the course and identification of learning objectives; self-regulated learning strategies
are discussed to enhance the learning process; a novel model called GPD (Gaussian Progression
of Difficulty) for lecture planning was proposed; a teaching-research nexus is discussed for the
course planning and enhancement. Adopting qualitative analyses and an inductive approach, this
paper offers a thorough reflection on the strengths and weaknesses of the new course, together with
improvement possibilities based on fieldwork and direct experience with the students and colleagues.
Opportunities and challenges of interdisciplinary teaching are presented in light of real-world experience, with a particular focus on the interaction between mathematics and computer science to study
the specific application of energy and power systems.
Forlag
MDPISitering
Bordin, Mishra, Benth. Pedagogical Perspectives of Interdisciplinary Teaching and Research: An Energy System Modelling Outlook in Relation to Energy Informatics. Energies. 2023;16(15)Metadata
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