![Sample our Computer Science journals, sign in here to start your access, latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5928/TOC-Subject-Sample-2021-Computer-Science.jpg"})
Abstract
The development of online virtual simulation test teaching programs has recently been in increasing demand due to the lack of traditional test teaching resources in colleges. This research aims to optimize the delivery of experimental teaching in higher education by harnessing the potential of virtual simulation technology. However, several challenges and limitations must be addressed to attain optimal learning outcomes. Data collection methods encompassed questionnaire surveys, multi-subject interviews, and regression analysis to examine underlying issues and trends in this teaching approach. This study underscores three vital dimensions for enhancing virtual simulation experiment teaching in colleges. Firstly, the integration of online and offline teaching modes is essential to broaden the spectrum of test-teaching scenarios. Secondly, technological advancements are pivotal in bolstering the reliability and authenticity of virtual examinations. The incorporation of virtual reality and artificial intelligence significantly enhances the realism and accuracy of virtual experiments, making them more effective in simulating real-life scenarios. Lastly, adapting the teaching model to accommodate diverse levels and facets is crucial for optimizing student learning experiences and outcomes. Tailoring teaching strategies and methods to individual student needs fosters a more personalized learning experience. Additionally, the paper highlights the significance of evaluating the effectiveness of virtual simulation experiment teaching through various assessment methods, including formative and summative assessments. This evaluation process enables teachers to identify areas for improvement and refine teaching practices to achieve better learning outcomes for students. As a result, this research provides valuable insights into the potential of virtual simulation technology in higher education and offers a roadmap for its successful implementation.
Graphical abstract
HIGHLIGHTS
Virtual simulation integration boosts operational skills, tackles equipment constraints, and fosters learning via error observation and correction.
Synchronous knowledge application drives practical use, sharpens critical thinking, and eases equipment operation.
Integrating diverse virus programs into virtual networks deepens understanding of security principles and defense strategies.
Online and offline integration widens the teaching scope, providing a versatile model beyond science and engineering disciplines.
Virtual simulation broadens experiential learning, promoting adaptive teaching methodologies and skill development.
Authors’ contributions
All authors agreed on the content of the study. JC and DL collected all the data for analysis. JC agreed on the methodology. JC and DL completed the analysis based on agreed steps. Results and conclusions are discussed and written together. The author read and approved the final manuscript.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Human and animal rights
This article does not contain any studies with human or animal subjects performed by any of the authors.
Informed consent
Informed consent was obtained from all individual participants included in the study.
Availability of data and material
Data sharing is not applicable to this article as no new data were created or analyzed in this study.
Additional information
Funding
Notes on contributors
Jing Chang
Jing Chang was promoted to associate professor in 2018. She holds a master’s degree in computer technology from South China University of Technology (2010) and attained a senior engineer title (2017). Her research spans Machine Learning, image processing, and more.
Dong Liu
Dong Liu was promoted to an associate professor in 2019. He obtained a master’s degree in computer technology from South China University of Technology in 2010 and a senior engineer title in 2017. His research areas include Machine Learning, Recommendation System, IoT techonlogy and so on.