KR20220091042A - System for mobile contents generation - Google Patents

Abstract

The present invention relates to an automatic mobile content creation system, and to a mobile content automatic creation system that regenerates educational content centered on face-to-face education into non-face-to-face education content. According to the present invention, by innovatively reducing the time and cost required to regenerate face-to-face education-centered educational content into non-face-to-face education content, and by automatically generating new technology-based micro-learning-based content, learners can enjoy more easily and fun It has the effect of enabling learning.

Description

Automatic mobile content generation system {System for mobile contents generation}

The present invention relates to an automatic mobile content creation system, and more specifically, to regenerate educational content centered on face-to-face education and existing online education content, which is an old technology-based knowledge transfer method, into non-face-to-face education content based on the latest technology and brain science. It relates to a mobile content automatic creation system that allows

In the rapidly changing era of digitalization (the 4th industrial revolution), the modern era is a digital society where new technologies and experience-based skills can be accessed quickly and easily anytime, anywhere, in order to promote self-development. This means that not capital is a resource, but digital information, that is, data has become the representative resource of this era. Educational content should also be provided in a variety of ways so that trainees can quickly personalize and provide a variety of content using necessary digital technology, so that they can determine their own needs and needs and select and apply the necessary educational content for themselves. something to do.

Meanwhile, due to the recent COVID-19 outbreak, non-face-to-face services have been rapidly expanded worldwide. Among them, mobile online services that can learn anywhere in the field and on the go are expanding, and as in Patent Publication No. 10-2014-0087777 (Multimedia learning system and method using mobile devices), Many services are being developed centered on content.

In order to provide non-face-to-face services in accordance with this trend of the times, video-based online education contents that are created focused on knowledge transfer based on old technology are used as mobile micro-learning educational contents focusing on the acquisition of experiences and skills based on the latest technology and brain science. Although the necessity is emerging, existing contents are redesigned and developed as micro-learning contents in a mobile environment, but there is a shortage of experienced human resources to produce and design mobile micro-learning educational contents, so it is impossible to respond to changes in the market demand and, moreover, cost and There was a problem that took more than 3 months.

Patent Publication No. 10-2014-0087777

The present invention was devised to solve the above problem, and it is a mobile device that regenerates face-to-face education-centered education content and existing online education content, which is an old technology-based knowledge transfer method, with the latest technology and non-face-to-face education content based on brain science. An object of the present invention is to provide an automatic content creation system.

In addition, in redesigning and developing existing content as microlearning content in a mobile environment, it solves the shortage of experienced talents to create and design mobile microlearning educational content, innovatively reduce the time and cost required, and develop new technologies and brain By automatically creating science-based microlearning educational contents, learners can access them more easily through mobile devices, and by intensive learning of micronized core contents in a short time, the learning effect is maximized and long-term memory and experience through brain science methods. It aims to improve self-confidence-based performance.

The present invention provides an automatic mobile content creation system, comprising: a converter for recognizing voice or image of educational content and converting it into text; a TAG management unit for inputting keywords and core contents related to a specific topic of the educational contents as a TAG so as to be redesigned based on the core contents of the educational contents; an analysis unit for analyzing the text of the conversion unit for each TAG and outputting the keyword and words and sentences for each TAG; and a mobile learning design unit that regenerates a certain amount of educational content with the content calculated as a TAG for each keyword based on the results of the analysis unit.

Preferably, the converter comprises: an extraction module for extracting text by recognizing audio or text of various contents including video, video, audio, document, and website; and a database for storing the text extracted through the extraction module as a cloud-based table.

Preferably, the TAG management unit includes: a keyword input module for inputting main keywords related to a specific topic of the educational content; an importance setting module for setting the importance of the keyword; and a TAG setting module for processing each keyword set according to the importance as a TAG, inputting key contents and storing the keyword as a content text file.

Preferably, the analysis unit includes: a search module for finding the same word in the text of the educational content according to the level set as the importance of the keyword; a source output module for outputting the number of times, sentences, and found positions of the same word; a link input module for recording an original text using the found location as a link location; and a control module that sequentially and repeatedly executes the output according to the keyword importance level, outputs the middle sum and most sentences whenever each importance level changes, and stores all outputs as TAGs in a text file.

Preferably, the mobile learning design unit includes: a first platform for selecting and inputting sentences that set the core content and meaning of the TAG to be learned from among the contents calculated by the TAG; a second platform for selecting and inputting a sentence corresponding to a question to help the understanding of core content to be learned applied to educational content from among the content calculated by the TAG; a third platform for selecting and inputting a sentence corresponding to any one of an application case, method, period, and result for core content to be learned for improving learners' self-confidence among the content calculated by the TAG; a fourth platform for selecting and inputting sentences to motivate through social learning by sharing application examples of the core contents generated by the TAG among the contents calculated by the TAG; and a content regeneration module that regenerates educational content using sentences that are selectively input to any one or more of the first to fourth platforms.

According to the mobile content automatic creation system according to an embodiment of the present invention, the time and cost required to regenerate the face-to-face education-oriented educational content into non-face-to-face education content is innovatively reduced, and a new technology-based mobile micro-learning-based By automatically generating contents of It works.

1 is a diagram showing the configuration of a system for automatically generating mobile content according to an embodiment of the present invention.
2 is a view for explaining the conversion unit 110 of the mobile content automatic creation system according to an embodiment of the present invention.
3 is a view for explaining the TAG management unit 120 of the mobile content automatic generation system according to an embodiment of the present invention.
4 is a view for explaining the analysis unit 130 of the mobile content automatic generation system according to an embodiment of the present invention.
5 is a diagram for explaining the mobile learning design unit 140 of the mobile content automatic creation system according to an embodiment of the present invention.

Specific structural or functional descriptions presented in the embodiments of the present invention are only exemplified for the purpose of describing embodiments according to the concept of the present invention, and the embodiments according to the concept of the present invention may be implemented in various forms. In addition, it should not be construed as being limited to the embodiments described herein, and it should be understood to include all modifications, equivalents and substitutes included in the spirit and scope of the present invention.

Meanwhile, in the present invention, terms such as first and/or second may be used to describe various components, but the components are not limited to the terms. The above terms are used only for the purpose of distinguishing one component from other components, for example, within the scope without departing from the scope of the rights according to the concept of the present invention, the first component may be named as the second component, Similarly, the second component may also be referred to as the first component.

Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. In describing the embodiment of the present invention, if it is determined that the description of a related known function or configuration may unnecessarily obscure the gist of the present invention, the description thereof is omitted.

1 is a diagram showing the configuration of a system for automatically generating mobile content according to an embodiment of the present invention. As shown in FIG. 1 , the mobile content automatic creation system 10 according to an embodiment of the present invention includes a conversion unit 110 , a TAG management unit 120 , an analysis unit 130 , and a mobile learning design unit 140 . include

The conversion unit 110 is configured to recognize the voice or image of the educational content and convert the text. The conversion unit 110 for performing this function includes an extraction module 111 and a database 112 .

The extraction module 111 extracts text by recognizing audio or text of various contents including video, video, audio, document, and website.

The database 112 stores the text extracted through the extraction module as a cloud-based table.

2 is a view for explaining the conversion unit 110 of the mobile content automatic generation system according to an embodiment of the present invention.

As shown in FIG. 2 , the conversion unit according to the present embodiment extracts text from various contents using an existing open solution. For MP3 and MP4, text is extracted using "Daglo" solution, and for websites such as PPT, Word, Hangul, and HTML, text is extracted using "Text publishing". The extracted text is stored in a cloud-based table. However, it is not limited to "Multiglo" solution or "Text publishing" solution, and better open solutions based on the latest technology can be utilized.

The TAG management unit 120 inputs keywords and core contents related to a specific topic of the educational content as a TAG so as to be redesigned by micro-learning based on the core content of the educational content. The TAG management unit 120 for performing these functions includes a keyword input module 121 , an importance setting module 122 , and a TAG setting module 123 .

The keyword input module 121 is configured to input main keywords related to a specific topic of educational content.

The importance setting module 122 sets the importance of major keywords related to a specific topic of educational content.

The TAG setting module 123 processes each keyword set according to the degree of importance as a TAG, inputs key contents, and stores it as a content text file.

3 is a view for explaining the TAG management unit 120 of the mobile content automatic creation system according to an embodiment of the present invention.

As shown in FIG. 3 , the TAG management unit 120 according to the present embodiment inputs a main keyword of the content. Next, input the keyword's importance as L1, ...Ln. Next, each keyword is treated as #TAG, and the key content is entered and saved.

The analysis unit 130 analyzes the text of the conversion unit for each TAG and outputs the keyword and words and sentences for each TAG. The analysis unit 130 for performing this function includes a search module 131 , a source output module 132 , a link input module 133 , and a control module 134 .

The search module 131 is configured to find the same word in the text of the educational content according to the level of importance of the keyword.

The source output module 132 outputs the number of times, sentences, and found positions of the same word searched through the search module.

The link input module 133 is configured to record the text original as the link location using the text location found through the source output module.

The control module 134 sequentially and repeatedly executes the output according to the keyword importance level, but outputs the intermediate sum and the most frequent sentences whenever each importance level changes, and stores all outputs as TAGs in a text file.

4 is a view for explaining the analysis unit 130 of the mobile content automatic generation system according to an embodiment of the present invention.

As shown in FIG. 4 , the analysis unit 130 according to the present embodiment opens the content text file (A). Next, open the #TAG and keyword file (B). Among the #TAGs of file B, read from L1 to find the same word in the text of file A. The COUNT and sentence of the same word and their position are output as OUTPUT. Note the location found so that you can refer to the original text file. Each L1 #TAG to Ln are sequentially executed and output. At each level change from L1 to Ln, the intermediate sum is output. Here, the intermediate sum outputs the total count and the most frequent sentences, as shown in FIG. 4 . And save all output as #TAG to a text file.

The mobile learning design unit 140 is configured to regenerate a certain amount of mobile microlearning educational contents based on the core contents with the contents calculated by the TAG for each keyword based on the results of the analysis unit.

The mobile learning design unit 140 applies KTAS (Know-Think-Apply-Share), a conversion learning method of Jack Mejilow with proven learning effect, and STC (repetition effect-test effect-confidence-based performance effect), a brain science method. Among the contents calculated by the mobile learning design platform structure, the text that sets the core contents to be learned and the exact meaning of the TAG is selectively input for each platform. As a detailed configuration of such a mobile learning design unit, it includes the first to fourth platforms 141 , 142 , 143 , 144 and a content regeneration module 145 .

The detailed configuration of such a mobile learning design unit is described as follows.

As shown in Fig. 5, the mobile learning design unit creates a MID storyboard to which KTAS of the Jack Mejirow method, which has proven learning effects based on conversion learning, and STC, a brain science method, is applied. The first platform 141 for selecting and inputting sentences that set the core content to be learned and the exact meaning of the corresponding TAG, repeating and testing questions to help understand the core content to be learned among the content calculated by the TAG The second platform 142 for selecting and inputting sentences to which the repetition effect of learning and the test effect are applied, among the contents calculated by the TAG, any of the application cases, methods, period, and results for the learner to apply directly to improve self-confidence A third platform 143 for selectively inputting a sentence corresponding to one, a system for selecting and inputting sentences to motivate through social learning by sharing application examples for core contents generated by TAG among contents calculated with TAG 4 platforms 144 and a content regeneration module 145 for regenerating educational content of the MID storyboard to which STC, which is a brain science method, is applied as a sentence selectively input through any one or more of the first to fourth platforms.

In this mobile learning design department, the need for education content focused on acquiring skills and experience based on the latest technology is emerging in the existing educational content such as video, video, ppt, and voice, which are focused on knowledge transfer. of microlearning content. Therefore, after developing the word and sentence analysis output system for each keyword & TAG, the mobile learning design structure of KTAS and STC's MID storyboard based on the proven STC-based brain science method and mobile learning design through the conversion learning of Jack Mejirow (MID) can be created to continuously learn bite-sized core educational contents for 5 to 10 minutes repeatedly, so that the learning effect can be improved due to the improvement of self-confidence. Through this KTAS and brain science-based platform, the knowledge, skills, attitudes, etc. acquired through various educational experiences are transformed so that they can be applied in real life. According to the transition of education, it has the effect of regenerating educational content as a platform that interprets experiences according to individual expectations, values, and beliefs.

5 is a diagram for explaining the mobile learning design unit 140 of the mobile content automatic creation system according to an embodiment of the present invention.

5, the mobile learning design unit 140 according to the present embodiment opens the file (A). Next, it is created as a platform that generates sentences that fit the KTAS structure of micro-learning mobile learning design (MID). This KTAS is a platform of Know, Think, Apply, and Share, and to explain it, the first platform of Know - {L1 TAG} calculated contents, the second platform of the calculated contents of Think - {L1 TAG}, and Appy - The third platform of the calculated content of {L1 TAG}, Share - The fourth platform of the calculated content of {L1 #TAG}, put it in the sentence and output it. And the same KTAS for each level is written and output to reproduce educational contents.

According to this embodiment, based on Cloud Computing, JavaScript, HTML/CSS, and SQL are mainly used to develop microlearning educational contents for mobile solutions, and a solution is developed using Python for big data. In addition, (1) interface is developed so that educational contents such as various types of contents, video, audio, HTML, or text can be created using the existing STT (Sounds to Texts) tool, and based on the core contents of the contents. (2) After developing a system for inputting key keywords and key content to be managed as a TAG for redesign, and (3) developing an output system for analyzing text by keyword & TAG (4) Based on proven brain science, transformational learning of Jack Mejirow, and mobile learning design, we develop solutions that create KTAS' mobile learning design structure and STC basis.

In addition, face-to-face education-centered education is changed to non-face-to-face education due to the corona environment. This solution creates new opportunities for non-face-to-face education by automatically generating micro-learning content or mobile content for face-to-face lectures or face-to-face education-oriented content. can help you do

The problem to be solved according to this embodiment is (1) to improve the low learning completion rate (average less than 10%) of the educational content of the e-learning system, which is the purpose of transferring knowledge based on long-term technology, (2) the e-learning-based content development period is at least 3 In order to innovatively shorten the development period to less than one month, (3) to reduce the burden on learners' learning time due to long video content for the purpose of e-learning-based knowledge transfer, ( 4) This is to disseminate more contents inexpensively in a personalized way by quickly and easily reproducing or recycling various contents.

In addition, (1) the latest technology and the brain science-based microlearning system enable continuous learning of bite-sized core educational contents for 5 to 10 minutes, thereby improving the completion rate by more than 70%. (2) Innovatively reduce the content development period with an automatic mobile content creation system. (3) Let learners learn as if they were playing games using mobile technology, and engage in learning and lead learning through participation and discussion. (4) Enables rapid and easy content development through the "automatic mobile content creation system".

According to the mobile content automatic creation system according to an embodiment of the present invention, it is possible to generate TexT using the existing STT (Sounds to Texts) tool for educational content such as various types of content, video, audio, HTML, or text. In order to (1) develop an interface and redesign based on the core contents of the contents, (2) develop a system to input key keywords and key contents to manage them as TAGs, and analyze texts for each TAG (3) ) After developing a word and sentence analysis output system for each keyword & TAG, the proven brain science method, conversion learning of Jack Mejirow, and mobile learning design-based (4) KTAS and STC mobile learning design structures were developed. develop With these features, the time and cost required to regenerate face-to-face education-centered educational content into non-face-to-face education content is innovatively reduced, and new technology-based micro-learning-based mobile content is automatically created, making learning easier and more fun for learners. It has the effect of making it possible.

The present invention described above is not limited by the above-described embodiments and the accompanying drawings, and it will be apparent to those skilled in the art that various substitutions, modifications and changes are possible without departing from the technical spirit of the present invention.

110: conversion unit
120: TAG management department
130: analysis unit
140: mobile learning design department

Claims (5)

a conversion unit that recognizes voice or image of educational content and converts it into text;
a TAG management unit for inputting keywords and core contents related to a specific subject of the educational contents as a TAG so as to be redesigned based on the core contents of the educational contents;
an analysis unit for analyzing the text of the conversion unit for each TAG and outputting the keyword and words and sentences for each TAG; and
A mobile learning design unit that regenerates a certain amount of educational content with the content calculated as a TAG for each keyword based on the results of the analysis unit;
Mobile content automatic creation system. According to claim 1,
The conversion unit,
an extraction module for extracting text by recognizing audio or text of various contents including video, video, audio, document, and website; and
A database for storing the text extracted through the extraction module as a cloud-based table; characterized in that it comprises a
Mobile content automatic creation system. According to claim 1,
The TAG management unit,
a keyword input module for inputting main keywords related to a specific topic of the educational content;
an importance setting module for setting the importance of the keyword; and
A TAG setting module for processing each keyword set according to the importance as a TAG, inputting the core content and storing it as a content text file; characterized in that it comprises a
Mobile content automatic creation system. The method of claim 1,
The analysis unit,
a search module for finding the same word in the text of educational content according to the level set as the importance of the keyword;
a source output module for outputting the number of times, sentences, and found positions of the same word;
a link input module for recording an original text using the found location as a link location; and
A control module that sequentially and repeatedly executes and outputs according to the keyword importance level, but outputs the middle sum and the most sentences whenever each importance level changes, and stores all outputs as TAGs in a text file; characterized by including a doing
Mobile content automatic creation system. According to claim 1,
The mobile learning design unit,
a first platform for selecting and inputting sentences for setting the core content and meaning of the TAG to be learned from among the contents calculated by the TAG;
a second platform for selecting and inputting a sentence corresponding to a question to help the understanding of core content to be learned applied to educational content from among the content calculated by the TAG;
a third platform for selecting and inputting sentences corresponding to any one of application cases, methods, periods, and results for core content to be learned for improving learners' confidence among the content calculated by the TAG;
a fourth platform for selecting and inputting sentences to motivate through social learning by sharing application examples of the core contents generated by the TAG among the contents calculated by the TAG; and
A content regeneration module that regenerates educational content with sentences selectively inputted to one or more of the first to fourth platforms;
Mobile content automatic creation system.

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