Tehnički vjesnik, Vol. 30 No. 3, 2023.
Izvorni znanstveni članak
https://doi.org/10.17559/TV-20220814112137
A Novel Model for Language Training Assessment Based on Data Mining and Bayesian Network
Jie Chen
; Yiwu Industrial & Commercial College, Jinhua, Zhejiang, China
Sažetak
At present, the imperfect network language environment has adversely affected cultivation of the language quality. Therefore, it is urgent to use modern information technology to design a novel algorithm model for the cultivation of language quality. To propose a more efficient model for language training assessment, a data mining algorithm and a Bayesian network were used to design a BOPPPS (Bridge-in, Objective/Outcome, Pre-assessment, Participatory learning, Post-assessment, Summary) model, with the model used to cultivate the language quality of adolescents. Regarding adolescents as the research object, a simulation experiment on the BOPPPS model was conducted, evaluating the actual effect by using the multi-level fuzzy comprehensive evaluation model. Results show that the BOPPPS model based on data mining algorithm and Bayesian network can effectively improve the language quality of adolescents. This lifting effect is mainly reflected in the mining and analysis of fMRI brain wave data based on Bayesian network. The resulting BOPPPS model and the traditional simple proposed BOPPPS are more scientific and targeted. During the training of adolescents' language quality, the proposed BOPPPS model can be used directly for teaching applications, which can get a better application effect. The conclusions can provide some reference for the cultivation of language quality and have certain theoretical research significance.
Ključne riječi
Bayesian network; BOPPPS model; cultivation; data mining; fMRI; language quality
Hrčak ID:
300685
URI
Datum izdavanja:
23.4.2023.
Posjeta: 359 *