Retraction Retraction: Construction of College English Teaching Resource Database under the Background of Big Data ( J.

: At present, the construction of college English network resource database in domestic universities is still in its initial stage in practice, and it is almost a blank in theoretical research. The construction of college English teaching resource database is of great strategic significance for promoting the construction of college English subject resources and improving the talent training mode. In this regard, the purpose of this paper is to study the construction of college English teaching resource database under the background of big data. This paper first discusses the current situation of college English teaching resources construction and resources in China. This paper summarizes the main problems existing in contemporary Chinese college English teaching resources database. According to the previous investigation and research results, and combining with big data technology, this paper constructs a new college English teaching resource library. The new college English teaching resource library puts the feelings of college students at the main position, and its teaching resources are more inclined to the subjective initiative and communication of college students. The resource library also uses the storage architecture of data warehouse, combined with big data and other related technologies, to realize the storage and update of various English teaching resources, and meet the needs of effective management of teaching resources in colleges and universities. Finally, this paper compares the old and new college English teaching resources. The experimental results show that the college English teaching resource database constructed in this paper is more recognized and liked by students, and the degree of students' liking for English has increased by about 55%, which plays a significant role in improving students' English and provides an important reference for the construction of college English teaching resource database

many aspects, the penetration of aesthetics in teaching, and the cultivation of behavior habits in the process of information culture cognition [2].

Under the background of big data, this paper studies the construction of college English teaching resource database.Firstly, this paper combs the present situation of college English teaching resources database in China by consulting relevant data and questionnaire survey, and summarizes the main problems existing in contemporary college English teaching resources database in China.Then, according to the results of previous investigations and studies, combined with big data, data warehouse and other technologies, this paper puts forward a new college English teaching resource library.This teaching resource library greatly improves students' enthusiasm and subjective init ative, and has important reference significance for the further development of higher calligraphy education.


Technical research on the Construction of College English Teaching Resource Database Under the Background of Big Data


Big Data (1) Data acquisition

For any data analysis, the primary thing is data collection, so the first technology of big data analysis software is data collection technology.This tool can collect data distributed on the Internet and data in some mobile clients quickly and widely.At the same time, it can quickly import data from data sources in some other platforms into this tool, and clean, transform and integrate the data, thus forming it in the database or data mart of this tool for contact analysis and processing [3].

(2) Data access After the data is collected, another technology of big data analysis, data access, will continue to play a role.It can relate the database, make it convenient for users to store the original data in use, and collect an use it quickly.Then there is the basic architecture, such as transportation and storage and distributed file storage, which are common.

(3) Data processing Data processing can be said to be one of the core technologies of the software.Facing the huge and complex data, the tool can use some calculation methods or statistical methods to process the data, including its statistics, induction, classification, etc., so that users can deeply understand the deep value of the data [4].

(4) Statistical analysis Statistical analysis is another core function of the software, such as hypothesis testing, which can


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help users analyze the reasons for a certain data phenomenon, and difference analysis can compare the huge differences of product sales in different time and re

tionship between a certain dat
phenomenon and another data phenomenon?Big data analysis can analyze the relationship between the two through data growth, reduction and change, etc.In addition, cluster analysis, principal component analysis and correspondence analysis are commonly used technologies, and the application of these technologies will make data development closer to people's application goals [5].


College English Teaching Resource Bank (1) Content of resource pool

College English basic teaching resource database is generally based on teaching materials.Each unit in all English textbooks has different themes.Students can use new media technology to learn the culture and art under each theme, and then cultivate their comprehensive English listening, speaking, reading and writing skills.English listening and speaking resource library includes audio and video resource library.Audio r source library can contain CET-4 and CET-6 listening, new concept listening, BBC, English songs and so on.For example, translating important news at home and abroad, cultural propaganda at home and abroad, etc., can enable students to achieve comprehensive development in the new media era, and quickly improve their English quality and comprehens ve level [6].

(2) Resource library functional requirements 1) Collection of resources Teachers provide lesson plans and courseware.The resources provided by teachers are generally produced by teachers themselves, and have been modified many times in the process of use, so they have high use value and are one of the essential resources in the network teaching resour e library.The resource builder collects from the Internet according to the content requirements of the resource library.The resources collected from the Internet are characterized by large quantity, various types and complex file types, so it is necessary for resource builders to spend more time sorting and classifying.Buy complete sets of materials, courseware, CD-ROM of online courses, etc.

2) Classification of resources College English network res

rces are aimed at teaching, so after the collection of resources is
ompleted, they need to be carefully sorted and classified according to the teaching needs.A good classification mechanism is conducive to the organization and management of resources and the high efficiency of their use.In the actual construction process of the resource library, we can take the subject as the general classification basis, and then divide it in detail according to the applicable object and material type, or take the applicable object or material type as the priority classification basis, depending on the type of the resource library [7].

3) Resource conversion After sorting and classifying the resources collected by resource builders, they have a good organizational structure, but there are huge differences in file types, which is not conducive to the management, se and sharing of resources.Therefore, it is necessary to convert resources before warehousing, and the conversion of resources is an important part in the standardization process of resource library construction [8].


4) Resource warehousing

Resource warehousing includes the storage of structured data and unstructured data.Structured data mainly refers to text information and metadata information of resources.Unstructured data mainly refers to multimedia files such as pictures, videos, animations and audio.Structured data is mainly stored in the database to facilitate retrieval and query; Unstructured data is mainly stored in computers in the form of files.The access to unstructured data is mainly achieved indirectly by searching and queryin the metadata information of resources in the database.

5) Post-management


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Post-management mainly includes adding, deleting, modifying and adjusting the resources in the resource pool according to the user's usage, requirements and evaluation results.To a great extent, the quality of a resource pool depends on whether the post-management work is done adequately.A resource library with updated content, timely feedback to users, thinking about what users think and anxious for users is a high-quality resource library [9].


Data Warehouse

Data warehouse is not only a data collection, but also a decision support system.It reorganizes and integrates the information from multiple data bases or other data sources, and provides a unified user interface for a topic application at the upper level, so that the end user can directly complete the query, analysis and decision of data.The related algorithm is as follows [10].

Let s be the training sample data set, and the category identification attribute in s has m independent values, that is, m classes are defined, i=1, …,m, i R is the subset of the data set s bel nging to the i C class, and the number of tuples in the subset i R is expressed by i r .The expected information amount of set s in classification can be given by the following formula.


Experimental research on the Construction of College English Teaching Resource Database under the Background of Big Data


Experimental Data

The research object of this paper is 400 randomly selected college students, including 240 boys and 160 girls.Then divide them into a and b groups on average.Group a is the experimental group and group b is the control group.


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Experimental Process

First of all, this paper makes a questionnaire survey among randomly selected college students, and obtains their understanding, liking and cognition of college English teaching resource pool, so as to more truly understand contemporary college students' views on college English teaching resource pool.

After that, the college English teaching resource library proposed in this paper is used to teach English for one month for group A students,

ditions, the tr
ditional college English teaching resource library is also used to teach English for one month for group B students.Finally, a questionnaire survey was conducted and the experimental data were compared.


Experimental analysis on the Construction of College English Teaching Resource Database under the Background of Big Data


College Students' views on College English Teaching Resource

erstanding, liking
and cognition of college English teaching resource bank of contemporary college students, so as to more truly understand the views of contemporary college students on college English teaching resource bank.The purpose of the firs

questionnaire survey
s to understand college students' English level and interest in English learning, and the second questionnaire survey is to understand college students' views on college English teaching resource pool and traditional English teaching resource pool proposed in this paper.The survey results are shown in Table 1 and Figure 1. Figure 1.College students' attitude towards two kinds of resource banks From the survey data, it can be seen that most college students know little about the college English teaching resource database, know little about it and use it rarely, so only a few students express their love for it.On the other hand, students can't realize the importance of college Engl

ng resource library very much, and they don't realize its importan
e to English learning.

After using two kinds of college English teaching resources to teach college students in A and B groups for one month, most college students in A group think that the college English teaching resources proposed in this paper are more effective, interesting, interactive and rich in resources, which improves students' enthusiasm for learning English.However, the B group of college students who use the traditional teaching resource database generally have low evaluation.This is mainly because the college English teaching resource database proposed in this paper adopts big data analysis technology, which can focus on the parts that students like and are interested in, so that students can acquire the English knowledge they want.Big data technology first collects the opinions of college students on the college English teaching resource database, and then stores and analyzes these data, so as to know the English knowledge that college students are eager to learn and teach students in accordance with their aptitude.


Changes in College Students' love for English Learning

In this paper, group A students are allowed to use college English teaching resources for one month's English teaching, and group B students are allowed to use traditional teaching reso rces for one month's English learning under the same conditions.During the experiment, the college students were investigated every five days, and the changes of their love for English learning were counted.We visually show the changes of college students' love for English learning in A and B groups, and curve-fit them according to the mean value respectively.As shown in Figure 2.


Figure 2. Changes of college students' liking for English learning

From the experimental results, it can be seen that the students in Group A who use the college English teaching resource library proposed in this paper are gradually increasing their love for English learning, and the increasing speed is faster than those in Group B who use the traditional resource library.Moreover, students in group A enjoy English much more than students in group B. This proves once again that the college English teaching resource library proposed in this paper has a positive effect on college students' learning English, greatly promotes their enthu

asm for learning English, and is of great significance,
which has an important relationship with big data and data warehouse.Big data has powerful data processing and analysis ability, and can teach English according to college students' interests and hobbies.


Conclusions

Under the background of big data, this paper studies the construction of college English teaching resource database.Based on the actual situation, this paper first combs the current situation of college English teaching resources database in China by consulting relevant data and questionnaire survey, and summarizes the main problems existing in contem

rary colle
e English teaching resources database in China.At the same time, I understand the college students' views on the college English teaching resource pool, so as to make a more targeted research.Then, according to the survey results,



of tuples in the training sample data set.If ij S indicates the number of tuples belonging to j S class in subset i C , the entropy of attribute by the following formula.




weight of j S subset, which indicates the proportion of j S subset in data set S, and the expected information amount of classification j C for each value of attribute A can be calculated by the following formula.




of j S belonging to i C class in the subset.


Table 1 .
1
College students' views on English teaching resource bank
Understand resourceUsed resourceLike resourceThink resource pool is verypoollibrarypoolimportantBoys15610642128Girls108903678
combined with big data, da

warehouse a
d other technologies, this paper puts forward a new college English teaching resource library.This teaching resource library is rich in learning resources, which greatly improves students' enthusiasm and subjective initiative in learning English, meets the needs of effective management of teaching resources in colleges and universities, and has important reference significance for the further development of college English teaching resource library.
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