Application Research of Task-Driven Teaching in Helicopter Electrical Courses

DOI

10.2991/978-2-38476-553-9_57How to use a DOI?

Keywords

Task-Driven; Electrical Courses; Adaptive Learning; VR Simulation

Abstract

In view of the strong post orientation of electrical courses in helicopter maintenance professional education, this paper proposes a computer-supported task-driven teaching framework that integrates immersive simulation, data analytics, and adaptive learning technologies. By developing algorithm-driven task modules and an intelligent assessment system, we have implemented a data-enhanced teaching approach for helicopter electrical courses. Technical components include a task recommendation algorithm based on student competency models, VR-based fault simulation parameters, and a Bayesian network-based evaluation model. According to experimental data from two-semester implementation, this method significantly improves students’ operational accuracy (by 32%) and problem-solving speed (by 25%) compared to traditional approaches.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Yabin Fu
AU  - Yue Tang
AU  - Dongfang Zhang
AU  - Canran Li
PY  - 2026
DA  - 2026/03/25
TI  - Application Research of Task-Driven Teaching in Helicopter Electrical Courses
BT  - Proceedings of the 2025 4th International Conference on Educational Science and Social Culture (ESSC 2025)
PB  - Atlantis Press
SP  - 516
EP  - 525
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-553-9_57
DO  - 10.2991/978-2-38476-553-9_57
ID  - Fu2026
ER  -