Multi-Intelligence English Teaching Model Based on Distance and Open Education

Multi-Intelligence English Teaching Model Based on Distance and Open Education

Jinjin Chu, Maciej Szlagor
DOI: 10.4018/IJWLTT.325617
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Abstract

Distance education between the student and the teacher through online sessions can make it difficult for a student who does not understand a concept to ask for clarification. Lack of a physical campus or social pressure from peers can demotivate students from completing their assignments. The framework of multi-intelligence English teaching based on cloud technology (MIET-CT) is introduced to solve these kinds of issues. The method of blended learning (BL) combines in-person instruction with digital resources to improve distance and open education by examining the efficacy of a learning strategy, with an emphasis on collaborative and autonomous learning (CAL) by artificial intelligence (AI). Cloud technology can potentially encourage students' independent learning as a cognitive tool by providing a cloud platform and multimedia instruction by domain modeling. As a result, various English teaching styles have been shown to increase student's motivation to learn and provide more impressive classroom results than conventional methods.
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Moradimokhles & Hwang (2020) examined the impact of online and blended learning on the English language skills of nursing students. A few pupils participated and were assigned to random groups. Learning management systems (LMS) were designed to teach basic English in a virtual classroom. Exercises based on the tasks for enhancing general English skills were utilized to teach the control group's members how to communicate in English. The blended learning experimental group was taught available English using blended learning. Students then took a post-test designed to assess their overall grasp of the English language, and results showed that the mixed-learning group had fared better than the other two.

Siripongdee et al. (2020) elaborated on the qualitative research's central subject, Blended Learning based on the Internet of Things (BL-IoT). There are many resources available to learn more. The author used analysis and synthesis tables to facilitate the author’s content analysis methodology. Blended learning is an instructional approach that blends in-person training and information and communication technology (ICT) instruction. In contrast, IoT-based technology is any heterogeneous items or devices connected to a network. Authors have implemented many IoT-based devices and things in the classroom to create and enhance a smart learning environment conducive to the pedagogical objectives.

Quvanch & Na (2020) suggested using a variety of technology, such as the blended learning approach, to address the challenges faced by students of English as a second language or English as a foreign language (ESL/EFL). The purpose of the article is to examine previous research on the topic of blended learning and its potential effect on students' writing skills. Twenty-five papers published in the form between 2010 and 2020 were selected using a systematic search approach (SSA). The majority of the research was conducted in Asian countries. Blended learning has been well-received in many ESL/EFL classrooms by both teachers and students.

Sujannah et al. (2020) discovered that some studies have shown that so-called blended learning, in which the internet is integrated into traditional classroom instruction, improves students' ability to express themselves in writing in English, a foreign language. However, so far, no studies have examined how incorporating Google Classroom (GC) into a student's education impacts their writing skills in EFL. Therefore, the research aimed to assess how incorporating GC into EFL classrooms affected student writing across a spectrum of student agencies. The study results showed that the EFL students who were taught using a mixed approach using Google Classroom had better writing skills than the other students.

Octaberlina & Muslimin (2020) suggested the ineffectiveness of English listening classes, and authors offered a proposal for an AI-based self-learning platform (AI-SLP) to enhance students' listening capacity. These difficulties inform the current design concept for AI-assisted listening platforms for English learning and the platform's operation flow. Current AI-assisted listening systems for English listening are analyzed by looking at the characteristics they offer. Based on their examination of the data, the researchers concluded that smart listening solutions offer benefits, such as access to a vast fitness database and several educational avenues. MIET-CT technology leverages artificial intelligence (AI) to provide adaptive, personalized, and interactive learning experiences for students. AI algorithms are used to analyze data such as students' learning preferences, feedback, and performance, which help adjust the teaching approach and content to fit individual needs. Furthermore, MIET-CT technology allows AI to collaborate with human teachers by providing them with essential insights and suggesting strategies for improving student learning outcomes.

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