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Xiaoyi Ge

Biographic Data

ID9949646
NAMEXiaoyi Ge
GIVEN NAMESXiaoyi
FAMILY NAMEGe
SIGNATUREGE X
AFFILIATIONSJilin Agricultural University
ORCID0009-0006-7493-8749
VERIFIEDYes
TOTAL WORKS1
TOTAL CITATIONS0
WORKS AS AUTHOR1
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2026
LATEST PUBLICATION YEAR2026
H-INDEX0
  • GWO-MLP Based Achievement Prediction Model for English Learning With Different Learning Motivations

    Open Access•Huan Wang, Xiaoyi Ge et al.•ARTICLE•SAGE Open•2026

    English achievement prediction is vital for improving the efficiency of English teaching by addressing the specific needs of students as early as possible. However, traditional English achievement prediction models are not good at the accuracy. Hence, a data-driven and AI-driven achievement prediction model is required to solve this problem. Recently, the increasing popularity of Multiple Layer Perception (MLP) and Gray Wolf Optimizer (GWO) has p…

No prominent works on this page.

  • GWO-MLP Based Achievement Prediction Model for English Learning With Different Learning Motivations

    Open Access•Huan Wang, Xiaoyi Ge et al.•ARTICLE•SAGE Open•2026

    English achievement prediction is vital for improving the efficiency of English teaching by addressing the specific needs of students as early as possible. However, traditional English achievement prediction models are not good at the accuracy. Hence, a data-driven and AI-driven achievement prediction model is required to solve this problem. Recently, the increasing popularity of Multiple Layer Perception (MLP) and Gray Wolf Optimizer (GWO) has p…

Academic achievement (1 work) · Advanced Technologies in Various Fields (1 work) · Educational Technology and Pedagogy (1 work) · Learning styles (1 work) · Perception (1 work) · Popularity (1 work) · Technology-Enhanced Education Studies (1 work) · Wilcoxon signed-rank test (1 work)

Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae