Mind Map Construction for English Grammar Teaching Based on Knowledge Map

Fu, Qijun; Kuang, Shouzhong

doi:10.1155/2021/4921825

Cited by 10 publications

(5 citation statements)

References 22 publications

(21 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Knowledge Map is also called scientific knowledge map. It was first proposed by Google in 2012 and published as a large-scale knowledge map based on Freebase [18] knowledge base and Wikipedia. It provides a referential means for the construction of world and domain knowledge [19].…”

Section: Knowledge Map and Knowledgementioning

confidence: 99%

Application of Knowledge Map Based on BiLSTM-CRF Algorithm Model in Ideological and Political Education Question Answering System

Zhao

Liu

2022

Mobile Information Systems

View full text Add to dashboard Cite

Ideological and political education plays an important role in university education and is an important way to realize the function of educating people. It is of great significance to establish a perfect automatic question answering system for ideological and political education. Traditional automatic question answering methods usually rely on predicates and other prior information to achieve knowledge base question answering, which requires a lot of manpower and poor generalization ability. In order to solve this problem, this paper designs a question answering system for ideological and political education based on BiLSTM-CRF algorithm model (BiLSTM: Bidirectional Long Short-Term Memory and CRF: Conditional Random Fields). For the knowledge base question answering method with weak-dependent information, this paper combines BERT (Bidirectional Encoder Representation from Transformers) and BiLSTM-CRF network to extract the named entity in the questions and locate the triplet information related to the entity in the knowledge base. Through the answer matching network, the similarity score is marked for the answers in the triplet set, and the threshold selection strategy is used to select the answers that meet the requirements. And according to the similarity score from high to paper, it is presented to the user. The experimental results show that the method weakens the dependence on prior information, reduces manual intervention and ensures the quality of question answering, and completes the validity verification of the question answering system of ideological and political education.

show abstract

Section: Knowledge Map and Knowledgementioning

confidence: 99%

Application of Knowledge Map Based on BiLSTM-CRF Algorithm Model in Ideological and Political Education Question Answering System

Zhao

Liu

2022

Mobile Information Systems

View full text Add to dashboard Cite

show abstract

“…The similarity matrix was imported into SPSS 20 to unfold the multidimensional scale analysis to generate the hot knowledge map of English teaching research in high schools in China from 2001 to 2016 [25].…”

Section: Knowledge Mapping Of English Teaching Research Hotspots In C...mentioning

confidence: 99%

Knowledge Graph-based Interactive Sharing Platform for Teaching English Majors in Colleges and Universities

Zhang

2023

Applied Mathematics and Nonlinear Sciences

View full text Add to dashboard Cite

In this paper, we found that the traditional FCM clustering algorithm is over-sensitive to noise or outliers, and AP clustering is added on the basis of the FCM algorithm to improve and optimize the FCM algorithm. The improved and optimized algorithm is used to derive high-frequency words for teaching English majors, and the hot knowledge map of English teaching is studied according to the high-frequency words. Construct the knowledge map framework and utilize the knowledge map framework to build the U+ English teaching interactive sharing platform. Adopt a top-down approach to construct the knowledge graph, and after defining entity relationships and attributes, propose the learning path recommendation method of the U+ platform based on the knowledge graph. Comparative experiments are used to analyze the teaching effect of the U+ platform and students’ English learning engagement. After 8 weeks of interactive and shared learning on the U+ platform, the students in the experimental class improved their English single choice, perfect fill-in-the-blank, and reading comprehension scores by 2, 4, and 3 points, respectively, and the U+ platform had obvious help in improving the students’ English scores, and the platform was effective in teaching. The mean value of the positive dimension of learning engagement of the students in the experimental class is 4.1634, with an interval range of [4,4.3], and they are positively engaged in English learning, and the mean value of the negative dimension is 1.8341, with a range of [1.6,2.4], and there are fewer negative performances, and the U+ platform has a positive impact on the student’s English learning engagement.

show abstract

“…Multiple Intelligences Theory serves a strong theoretical supporting role in the reform of English teaching in universities and colleges, which can fully mobilize students' enthusiasm while enhancing teaching efficiency, according to the literature [21], which analyzed the application effect of the theory in college English classrooms and new teaching methods. A knowledge map of English instruction in colleges and universities was ultimately created by Literature [22], which combined multi-source heterogeneous English topic data with the ontology model of the English teaching domain. The development and advancement of English teaching reform can be aided by this knowledge map that explains the current state and growth trend of English teaching.…”

Section: Introductionmentioning

confidence: 99%

Research on Strategies of English Teaching Reform in Colleges and Universities Supported by Artificial Intelligence Technology

Ma,

Wang

2024

Applied Mathematics and Nonlinear Sciences

View full text Add to dashboard Cite

The way that artificial intelligence technology is being developed is causing a progressive evolution in college and university teaching methods and systems. This paper presents the design of the English teaching mode in colleges and universities based on artificial intelligence technology. Research on strategies for English teaching reform in colleges and universities supported by artificial intelligence technology. A weighted inference model was used to design an AI expert system, based on which an intelligent assisted learning system based on a neural network was constructed using the law of knowledge forgetting. Based on information acquisition, the random Linsen method was selected as the assessment methodology for the impact of English instruction in colleges and universities. The assessment model’s performance and errors are examined through comparison tests of the teaching evaluation model. In this article, the educational effect evaluation model has an accuracy rate of 91% and a mean square error of less than 0.002. The impact of AI-assisted English instruction on teaching is evaluated based on this. Results from studies conducted both before and following the experimental group show that the overall score increases by 12.33 points and the P-value of the four dimensions’ teaching effect is less than 0.01. The experimental group using artificial intelligence technology for English instruction received an average comprehensive score of 95 points in the actual English assessment, which is 8 points higher than the control group receiving traditional English instruction. This paper’s artificial intelligence teaching mode is believed to have a significant impact on students’ English, which is confirmed by its effectiveness and rationality. It is beneficial for teaching reform and guides enhancing and advancing English instruction in colleges and institutions.

show abstract

Mind Map Construction for English Grammar Teaching Based on Knowledge Map

Cited by 10 publications

References 22 publications

Application of Knowledge Map Based on BiLSTM-CRF Algorithm Model in Ideological and Political Education Question Answering System

Application of Knowledge Map Based on BiLSTM-CRF Algorithm Model in Ideological and Political Education Question Answering System

Knowledge Graph-based Interactive Sharing Platform for Teaching English Majors in Colleges and Universities

Research on Strategies of English Teaching Reform in Colleges and Universities Supported by Artificial Intelligence Technology

Contact Info

Product

Resources

About