The Study and Application of Adaptive Learning Method Based on Virtual Reality for Engineering Education

  • Yi LinEmail author
  • Shunbo Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11903)


As educational reform efforts continue, a challenge for most adaptive learning software is how to integrate theoretical knowledge with practice, especially in the field of engineering education. Developing an understanding of how to incorporate virtual reality in education to enhance the quality of learning has become a research hotspot in the e-learning field. For this purpose, a novel adaptive virtual reality learning method based on learning styles model is proposed in this paper, then a virtual reality learning system for engineering education is constructed based on the proposed approach. In this method, learning style are categorized via learning style index to predict learning preferences, then differentiated virtual learning environment of engineering education are provided to students according to their individual learning preferences. During the learning process, various types of learning data are recorded and analyzed automatically. Then the prejudged learning preferences are continually adjusted by the learning data when the immersive learning experience is offered to students by the customization of learning scene and teaching material in virtual environment. To adapt to differentiated individuals, the structure and content of virtual learning environment are gradually optimized, with the ultimate goal of equipping the environment to meet an unlimited array of actual student learning needs. Compared with the traditional adaptive learning method based on learning style, a comparison of experimental results shows that the proposed method is more effective in stimulating learner enthusiasm and can greatly improve student academic performance.


Engineering education Learning styles model Virtual reality 



Thanks to the funding of China Scholarship Council and their constant supports. Furthermore, I would like to express my gratitude to the consistent and instruction of researchers from Key Laboratory of Digital Fujian IoT Engineering and Applications.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.College of Physics and Information EngineeringFuzhou UniversityFuzhouChina

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