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. 2022 Sep 16:13:985887.
doi: 10.3389/fpsyg.2022.985887. eCollection 2022.

Application of virtual simulation situational model in Russian spatial preposition teaching

Yanrong Gao  1   2 , R T Kassymova  1 , Yong Luo  3
Affiliations

Application of virtual simulation situational model in Russian spatial preposition teaching

Yanrong Gao et al. Front Psychol. .

Abstract

The purpose is to improve the teaching quality of Russian spatial prepositions in colleges. This work takes teaching Russian spatial prepositions as an example to study the key technologies in 3D Virtual Simulation (VS) teaching. 3D VS situational teaching is a high-end visual teaching technology. VS situation construction focuses on Human-Computer Interaction (HCI) to explore and present a realistic language teaching scene. Here, the Steady State Visual Evoked Potential (SSVEP) is used to control Brain-Computer Interface (BCI). An SSVEP-BCI system is constructed through the Hybrid Frequency-Phase Modulation (HFPM). The acquisition system can obtain the current SSVEP from the user's brain to know which module the user is watching to complete instructions encoded by the module. Experiments show that the recognition accuracy of the proposed SSVEP-BCI system based on HFPM increases with data length. When the data length is 0.6-s, the Information Transfer Rate (ITR) reaches the highest: 242.21 ± 46.88 bits/min. Therefore, a high-speed BCI character input system based on SSVEP is designed using HFPM. The main contribution of this work is to build a SSVEP-BCI system based on joint frequency phase modulation. It is better than the currently-known brain computer interface character input system, and is of great value to optimize the performance of the virtual simulation situation system for Russian spatial preposition teaching.

Keywords: Russian teaching; SSVEP-BCI; situation simulation; spatial preposition; virtual simulation.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Structure of 3D virtual recording and broadcasting room for Russian teaching.
Figure 2
Figure 2
BCI technical workflow.
Figure 3
Figure 3
International 10–20 standard electrode lead diagram.
Figure 4
Figure 4
Situation-based HCI system.
Figure 5
Figure 5
Correlation coefficients of a single-trial SSVEP of a subject [(A) position 1; (B) position 2; (C) position 3; (D) position 4].
Figure 6
Figure 6
Correlation coefficients between SSVEP and adjacent frequency for a single test at 12.4 Hz [(A) Δϕ = 0; (B) Δϕ = 0.5π; (C) Δϕ = π; (D) Δϕ = 1.5π).
Figure 7
Figure 7
Mixed frequency-phase coding [(A) induced SSVEP under different stimulation phases; (B) time-domain waveform under different stimulation phases; (C) amplitude spectrum of induced SSVEP; (D) complex spectral scatter of induced SSVEP].
Figure 8
Figure 8
Performance of online BCI system under hybrid frequency-phase coding with different data lengths [(A) classification accuracy; (B) ITR].
See this image and copyright information in PMC

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