A Multimodal Teaching Model of College English Based on Human-Computer Interaction

被引:3
作者
Qin, Fei [1 ,2 ]
Sun, Qian [1 ]
Ye, Yongyan [3 ]
Wang, Le [4 ]
机构
[1] Liaocheng Univ, Sch Foreign Languages, Liaocheng, Shandong, Peoples R China
[2] Univ Windsor, Fac Educ, Windsor, ON, Canada
[3] Salle Univ, Coll Liberal Arts & Commun, Dasmarinas, Cavite, Philippines
[4] Jinan Vocat Coll, Dept Publ Educ, Jinan, Shandong, Peoples R China
关键词
Multimodal teaching; human-computer interaction; support vector machine; college English; machine learning;
D O I
10.1080/10447318.2023.2188531
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The experimental results of this paper showed that the final grades of most students would be improved in the class with low English proficiency in the case of textbooks of the same difficulty. However, when multimodal instruction was used, the failure rate in the second semester decreased by 13 percentage points compared with the first semester, while the high-achieving students increased by 6 percentage points. Therefore, by using the multimodal teaching method, the learning effect of students with low English proficiency from the mid-term to the end of the term has been significantly improved, which showed that the multimodal teaching method was more superior than the conventional teaching method. Before and after the use of multi-modal teaching, students in class B had a 24% increase in grades from mid-term to final, mainly because the English level of class B was generally higher.
引用
收藏
页码:1762 / 1770
页数:9
相关论文
共 20 条
  • [1] Abdumalikovna P. Z., 2021, J INT BUS STUD, V11, P1859, DOI [https://doi.org/10.5958/2249-7137.2021.01306.9, DOI 10.5958/2249-7137.2021.01306.9]
  • [2] Djatmika Wibowo., 2020, Systematic Reviews in Pharmacy, V11, P219, DOI [10.5530/srp.2020.2.34, DOI 10.5530/SRP.2020.2.34]
  • [3] Ghaemi F., 2017, International Journal of Information and Communication Sciences, V2, P86, DOI [10.11648/j.ijics.20170205.15, DOI 10.11648/J.IJICS.20170205.15]
  • [4] Simulation of English classroom effectiveness based on human-computer interaction and facial identification
    Hu, Liang
    Zeng, Qi
    Wu, Xinli
    Lv, Zhaofang
    [J]. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2021, 40 (04) : 7025 - 7036
  • [5] Huang R., 2020, Open Journal of Modern Linguistics, V10, P366, DOI [https://doi.org/10.4236/ojml.2020.104021, DOI 10.4236/OJML.2020.104021]
  • [6] RETRACTED: Research on fuzzy English automatic recognition and human-computer interaction based on machine learning (Retracted Article)
    Jing, Yuqin
    [J]. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2020, 39 (04) : 5809 - 5819
  • [7] Kovalchuk O, 2017, ADV EDUC, P146, DOI 10.20535/2410-8286.97295
  • [8] Kummin S., 2020, UNIVERSAL J ED RES, V8, P7015, DOI [https://doi.org/10.13189/ujer.2020.081269, DOI 10.13189/UJER.2020.081269]
  • [9] Lin W., 2017, REV FACULTAD INGENIE, V32, P406
  • [10] Liu H., 2017, Boletin Tecnico/Tech Bull, V55, P110