Application of Massive Open Online Course to Grammar Teaching for English Majors Based on Deep Learning

Abstract

The study aims to explore the roles of Massive Open Online Courses (MOOCs) based on deep learning in college students’ English grammar teaching. The data are collected using a survey. After the experimental data are analyzed, it is found that students have a low sense of happiness and satisfaction and are unwilling to practice oral English and learn language points in English learning. They think that college English learning only meets the needs of CET-4 and CET-6 and does not take it as the ultimate learning goal. After the necessity and problems in English grammar teaching are discussed, the advantages of flipped classrooms of MOOCs are discussed in English grammar teaching. A teaching platform is constructed to study the foreign language teaching mode under MOOCs, and classroom teaching is combined with the advantages of MOOCs following the principle of “teaching students according to their personalities” to improve the listening, speaking, reading, writing, and translation skills of foreign language majors. The results show that high-quality online teaching resources and the deep learning-based teaching environment can provide a variety of interactive tools, by which students can communicate with their peers and teachers online. Sharing open online communication, classroom discussion, and situational simulation can enhance teachers’ deep learning ability, like the ability to communication and transfer thoughts. Constructivism with interaction as the core can help students grasp new knowledge easily. Extensive communication and interaction are important ways for learning and thinking. The new model provides students with profound learning experience, expands the teaching resources of MOOCs around the world, and maximizes the interaction between online and offline teachers and students, making knowledge widely rooted in the campus and realizing the combination of online resources and campus classroom teaching. Students can learn the knowledge through autonomous learning and discussion before class, which greatly broadens the learning time and space. In the classroom and after class, the internalization and sublimation of knowledge are completed through group cooperation, inquiry learning, scenario simulation, display, and evaluation, promoting students to know about new knowledge and highlighting the dominant position of students.

Influencing factors for effective teaching evaluation of massively open online courses in the COVID-19 epidemics: An exploratory study based on grounded theory

“…According to existing references (Graham et al, 2001;Bangert, 2005;Brahimi and Sarirete, 2015;Hewawalpita et al, 2018;Jung and Lee, 2018;Deng et al, 2020;Liu et al, 2020;Reparaz et al, 2020;Blum-Smith et al, 2021;Li et al, 2021;Tang, 2021;Wu and Wu, 2021;Duan, 2022;Du and Qian, 2022), interview results, and a review of the teaching behaviors identified on MOOC platform websites (Such as: China University MOOC, Coursera, Udacity, and edX), the factors that influence effective teaching can be roughly divided into the following categories: (1) effective teachers, (2) effective teaching, (3) effective communication, (4) students' online learning behavior, (5) social support guarantee, and (6) network course design. An effective teaching evaluation index system is constructed by these influencing factors.…”

Understanding, Investigating, and promoting deep learning in language education: A survey on chinese college students' deep learning in the online EFL teaching context

“…One possible explanation might be that behavioral engagement in online EFL teaching might be influenced by numerous external factors, such as comparatively weaker supervision mechanism than face-to-face classroom teaching, instability of network and equipment, low efficient interaction, delayed online instruction, etc. (Chapelle, 2019 ; Du and Qian, 2022 ). It is also worth considering, as some research indicates, that a lower level of students' engagement was an inevitable problem during the COVID-19 pandemic (Yang et al, 2020 ) since perceived COVID-19 event strength and perceived stress can negatively influence learning engagement (Zhao et al, 2021 ).…”

“…(Vos et al, 2011 ; Pegrum et al, 2015 ). Pertaining to language education, with ubiquitous technology application, growing attention is paid to the supporting impacts of technologies on deep language education and learning (Beckett and Iida, 2006 ; Tochon et al, 2014 ; Du and Qian, 2022 ). To illustrate, Tochon et al ( 2014 ) analyzed the impact of online personalized learning on developing deeper levels of language apprenticeship.…”

“…Recent trends in the application of online learning through management systems (LMSs), namely Blackboard, have led to a proliferation of studies, ensuring the utility of Blackboard by measuring the perception and use tends to be pivotal to improve the outcome of online EFL learning, especially in the Saudi context (Almekhlafy, 2020 ; Moawad, 2020 ). In China, due to the less extensive application of Blackboard in online EFL teaching, studies switch more attention to the urgent need for improving the effectiveness of online EFL teaching by providing supports from teachers or establishing effective learning frameworks (Han et al, 2021 ; Zhao et al, 2021 ; Du and Qian, 2022 ). However, very few studies have been shored up by data-driven analysis of large-scale investigation on the current holistic status of students' language learning in online EFL teaching.…”

Mental State Assessment in College English Teaching Courses Based on Deep Learning

“…erefore, it is an important way to correctly adjust the educational method and improve the teaching e ciency to do a good job of mental state assessment in the classroom in time. It is in this context that this paper aims to support the English teaching based on the emotional analysis of students' expressions and speeches during the English teaching classes to obtain their corresponding mental states [1][2][3].…”