Design and implementation of an experiential learning intervention for a graduate course in system identification

Teaching system identification for control to aerospace engineering students can significantly benefit from actual experiential learning activities in a laboratory environment. In this paper, we present the experience we gathered performing hands-on project-based experimental activities conducted with a multirotor Unmanned Aerial Vehicle (UAV) within a graduate-level course teaching how to learn linear models of dynamical systems from data. We developed the activities to complement face-to-face lectures to illustrate the steps involved in the process of identifying data-driven models in a hands-on manner, and implemented them in the form of a project during the last 8 weeks of the course, to consolidate the knowledge acquired in the theoretical lectures through practical experiences. We present the lecture material we prepared, provide an overview of the obtained results, discuss the pedagogical value of the experiential learning activities, summarize student’s feedback and give an outline for further improvements.

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Publication Details

Published
2024-08-21
DOI
https://doi.org/10.1109/ccta60707.2024.10666645
Primary Topic
Experimental Learning in Engineering
Type
article
Field-Weighted Citation Impact
0.00

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article

Design and implementation of an experiential learning intervention for a graduate course in system identification

Yejin Wi, Marzia Cescon
Experimental Learning in Engineering
article

Design and implementation of an experiential learning intervention for a graduate course in system identification

Yejin Wi, Marzia Cescon
article en

Abstract

Teaching system identification for control to aerospace engineering students can significantly benefit from actual experiential learning activities in a laboratory environment. In this paper, we present the experience we gathered performing hands-on project-based experimental activities conducted with a multirotor Unmanned Aerial Vehicle (UAV) within a graduate-level course teaching how to learn linear models of dynamical systems from data. We developed the activities to complement face-to-face lectures to illustrate the steps involved in the process of identifying data-driven models in a hands-on manner, and implemented them in the form of a project during the last 8 weeks of the course, to consolidate the knowledge acquired in the theoretical lectures through practical experiences. We present the lecture material we prepared, provide an overview of the obtained results, discuss the pedagogical value of the experiential learning activities, summarize student’s feedback and give an outline for further improvements.

University of Houston (US)
University of Houston
Openalex Percentile: Top 75%
Experimental Learning in Engineering
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