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Research on Paths and Countermeasures of Artificial Intelligence to Boost the Development of Russian Language Teachers in Colleges and Universities

Zhiqiang Wang

Zhiqiang Wang

School of Foreign Studies, Hebei North UniversityZhangjiakou, China
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Wang, Zhiqiang
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Galina Vasilievna Ulazaeva

Galina Vasilievna Ulazaeva

Institute of History and Philology, Banzarov Buryat State UniversityUlan-Ude, Russia
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Ulazaeva, Galina Vasilievna
  
23. Sept. 2025
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Online veröffentlicht: 23. Sept. 2025
Eingereicht: 07. Jan. 2025
Akzeptiert: 30. Apr. 2025
DOI: https://doi.org/10.2478/amns-2025-0964
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© 2025 Zhiqiang Wang et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Figure 1.

The path of the theoretical model
The path of the theoretical model

Figure 2.

The use frequency of four teaching tools
The use frequency of four teaching tools

Figure 3.

Frequency distribution of Russian teacher group using tools
Frequency distribution of Russian teacher group using tools

Figure 4.

Tools using for different gender teachers
Tools using for different gender teachers

Differences in the different age level teachers

Tools type Age Mean SD F P
Course management Blow 35 56.29 61.97 0.846 0.152
36-40 18.28 68.07
41-45 43.07 50.06
46-50 48.77 38.47
Above 50 49.62 39.11
Content management Blow 35 146.37 95.16 1.639 0.291
36-40 131.14 45.87
41-45 152.02 70.15
46-50 174.87 75.42
Above 50 239.91 89.94
Communication cooperation Blow 35 180.83 55.62 2.408 0.086
36-40 117.97 89.64
41-45 18.95 43.57
46-50 63.55 40.97
Above 50 46.53 26.36
Course evaluation Blow 35 236.61 43.29 0.561 0.694
36-40 202.59 76.66
41-45 60.86 76.76
46-50 229.35 56.92
Above 50 212.07 53.25

Standardized path coefficient of the model

Path Estimate S.E. C.R. P
H1 Teacher development <--- Individual factor 0.571 0.156 5.443 0.001***
H2a Individual factor <---School environment 0.286 0.233 4.495 0.018**
H2b Teacher development <--- School environment 0.471 0.145 4.208 0.004***
H3a Individual factor <--- Artificial intelligence 0.414 0.169 6.719 0.006***
H3b School environment <--- Artificial intelligence 0.315 0.137 5.542 0.011**
H3c Teacher development <--- Artificial intelligence 0.456 0.159 6.411 0.005***

The test results of the fitting degree

Index Evaluation criteria Indexing Fitting judgment
CMIN/DF <3 1.731 Yes
GFI >0.9 0.913 Yes
AGFI >0.9 0.938 Yes
RMSEA <0.08 0.021 Yes
NFI >0.9 0.942 Yes
RFI >0.9 0.939 Yes
IFI >0.9 0.926 Yes
TLI >0.9 0.949 Yes
CFI >0.9 0.921 Yes
PGFI >0.5 0.806 Yes
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