A study on the development of English reading skills in the MOOC model of English language teaching

被引:0
作者
Ling L. [1 ]
机构
[1] Department of Foreign Languages, Southwest Jiaotong University Hope College, Chengdu
关键词
DBN; deep belief network; English teaching; MOOC; personalised recommendation; reading ability;
D O I
10.1504/IJNVO.2023.133861
中图分类号
学科分类号
摘要
This study proposes a personalised intelligent reading resource recommendation method based on MOOC mode. This method uses a deep belief network (DBN) model to extract students’ reading interests and other related data features, and uses the K-means algorithm to classify users’ interests. The model is applied to a personalised recommendation system in the MOOC environment. When the training set accounts for 100%, 75%, 50%, and 25% of the total dataset, the root mean square errors of the recommendation results of the DBN algorithm are 78%, 83%, 88%, and 96%, respectively. During the training process, the convergence speed of the DBN algorithm is significantly faster, with a minimum root mean square error value of 0.805. In the evaluation of recommendation effectiveness under different indicators, DBN performs the best, indicating that the model can adapt to various situations and has great practical application value. Copyright © 2023 Inderscience Enterprises Ltd.
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收藏
页码:318 / 336
页数:18
相关论文
共 20 条
[11]  
Khasawneh M.A.S., Teacher perspective on language competences relation to learning difficulties in English learning, Journal Educational Verkenning, 2, 1, pp. 29-37, (2021)
[12]  
Laia T., Implementing pair work technique to improve students’ reading ability on descriptive text at the eleventh grade of SMA negeri 1 amandraya, Faguru: Jurnal Ilmiah Mahasiswa Keguruan, 1, 2, pp. 34-46, (2022)
[13]  
Liu .S, Wang B., Deng X., Yang L., Self-attentive graph convolution network with latent group mining and collaborative filtering for personalized recommendation, IEEE Transactions on Network Science and Engineering, 9, 5, pp. 3212-3221, (2021)
[14]  
Liu F., An empirical study on the improvement of English reading ability of Chinese college students based on big data –based on the lens grading system, Journal of Physics: Conference Series, 1744, 3, pp. 2066-2071, (2021)
[15]  
Papadakis S., MOOCs 2012-2022: an overview, Advances in Mobile Learning Educational Research, 3, 1, pp. 682-693, (2023)
[16]  
Tangkijmongkol C., Wasanasomsithi P., Promoting perceived English reading self-efficacy of underserved students using an out-of-class extensive reading module, International Journal of Innovation and Learning, 32, 2, pp. 164-182, (2022)
[17]  
Wang H., Niu B., Tan L., Bacterial colony algorithm with adaptive attribute learning strategy for feature selection in classification of customers for personalized recommendation, Neurocomputing, 452, 10, pp. 747-755, (2021)
[18]  
Wang Q., Tang D., Research on intelligent recommendation business model of tourism enterprise value platform from the perspective of value cocreation, Complexity, 2021, (2021)
[19]  
Yang Y., Zhu Y., Li Y., Personalized recommendation with knowledge graph via dual-autoencoder, Applied Intelligence, 52, 6, pp. 6196-6207, (2022)
[20]  
Zou F., Chen D., Xu Q., Jiang Z., Kang J., A two-stage personalized recommendation based on multi-objective teaching–learning-based optimization with decomposition, Neurocomputing, 452, 10, pp. 716-727, (2021)