KR20200004708A - Apparatus and method of providing intelligent e-learning service - Google Patents

Abstract

According to one embodiment of the present invention, a method for providing an artificial intelligence control e-learning service of a server includes: a step (a) of receiving, analyzing, and storing information from a terminal; a step (b) of receiving first data for self-efficacy for learning form (SELF) and studying ability evaluation (SAE); a step (c) of receiving second data for a personalized curriculum template (PCT); a step (d) of analyzing the first data and the second data to receive learning progress evaluation (LPE) data according to analysis content; a step (e) of analyzing the learning progress evaluation (LPE) data and transmitting a curriculum control signal from the terminal according to the analysis content; and a step (f) of controlling performance of study result assessment (SRA) and receiving and analyzing related data to control learning levels. According to the present invention, it is possible to suggest a service platform supporting intelligence or personalized e-learning services.

Description

Apparatus and method for providing AI control e-learning service {APPARATUS AND METHOD OF PROVIDING INTELLIGENT E-LEARNING SERVICE}

The present invention relates to the provision of artificial intelligence controlled e-learning service, and in particular, based on artificial intelligence (AI), personally tailored, that is, artificial intelligence controlled e-learning service (AICeL) The present invention relates to a providing apparatus and a method.

With the development of network technology, the online e-learning service market is being activated. Conventional e-learning services have generally provided contents taught by instructors to learning consumers only through online media. This early e-learning service has the advantage that there is no limit of time, region, etc., unlike the offline education, there is only one-way information transmission and there is a delay in the instructor-student communication. Recently, the real-time e-learning service using the online media is gradually increasing, but it is also possible to communicate with each other in real time, but it is difficult to evaluate the learner's individual learning ability, learning efficiency, etc. There was still a problem with the use of e-learning service.

One object of the present invention is to propose a service platform supporting artificial intelligence controlled e-learning (AICeL).

Another object of the present invention is to propose a method for performing processes for an AI control e-learning service.

Another object of the present invention is to propose a method for collecting individual state data in various forms for the AI control e-learning service.

Another object of the present invention is to propose a method of improving the results of the individualized self-directed learning improved by artificial intelligence control.

Another object of the present invention is to propose an apparatus for implementing the above method.

Technical problems to be achieved in the present invention are not limited to the above technical problems, and other technical problems that are not mentioned will be clearly understood by those skilled in the art from the following description.

According to an embodiment of the present invention, a method for providing an artificial intelligence control e-learning service of a server includes: (a) receiving, analyzing and storing information of a terminal; (b) receiving first data about a learning efficacy psychological evaluation (SELF) and a learning ability diagnostic evaluation (SAE); (c) receiving second data for a personalized curriculum (PCT); (d) analyzing the first data and the second data and receiving LPE data according to the analysis contents; (e) analyzing the learning progress evaluation (LPE) data and transmitting a curriculum control signal of the terminal according to the analysis contents; And (f) controlling the performance of the learning result evaluation (SRA) and controlling the level of learning by receiving / analyzing the relevant data.

In the method for providing an artificial intelligence control e-learning service of a server according to an embodiment of the present invention, the steps (a) and (b) may be performed before the start of the intelligent e-learning learning and are not performed thereafter. Step a) is performed when the terminal information is updated.

In the method of providing artificial intelligence control e-learning service of a server according to an embodiment of the present invention, in step (b), a Vocabulary Memorization Ability Test (VMAT) and English Fluency Evaluation (EFE) are evaluated. Receiving at least one data of the).

In the method for providing artificial intelligence control e-learning service of a server according to an embodiment of the present invention, the steps (c) to (f) may be performed at every learning level preset in the server.

According to an embodiment of the present invention, a method for providing an artificial intelligence control e-learning service for a server may include: receiving lesson data between steps (c) to (f); Receiving course data; Or receiving Level Competency Assessment (LCA) data after completion of the step-by-step learning after the step-by-step learning progress assessment (LPE); It is characterized in that at least one of the more.

In the server artificial intelligence control e-learning service providing method according to an embodiment of the present invention, the learning efficacy psychological evaluation (SELF) relates to the subjective reliability of the learner's own, new knowledge and skills through a general learning method In order to obtain a successful learning, the subjective beliefs about understanding, analysis and memory of the learning content are measured.

In the method of providing artificial intelligence control e-learning service of a server according to an embodiment of the present invention, the learning ability diagnosis evaluation (SAE) may include grammar, vocabulary, reading comprehension, and writing. ), A plurality of questions about subjects for language learning, including items for assessing current language proficiency with respect to listening, speaking, and speaking.

In the method for providing an artificial intelligence control e-learning service of a server according to an embodiment of the present invention, the personalized curriculum (PCT) is a variety of learning subjects developed based on learner's characteristics, learning content preferences, and learning efficacy. Characterized in that the template is made through.

In the method for providing an artificial intelligence control e-learning service of a server according to an embodiment of the present invention, the learning progress assessment (LPE) evaluates a learner's progress on a specific subject of the learner, and the learning result assessment (SRA) is a proficiency level for each. Is a writing or / and oral test that can be provided when this is completed, wherein the results are used to determine whether the learner is to level up to the next level.

Artificial intelligence control e-learning service providing system according to another embodiment of the present invention, the terminal; And (a) receiving, analyzing and storing the information of the terminal, (b) receiving first data on a learning efficacy psychological evaluation (SELF) and a learning ability diagnostic evaluation (SAE), and (c) a personalized curriculum. Receive second data for (PCT), (d) analyze the first data and the second data, receive LPE data according to the analysis, and (e) the learning progress assessment (LPE) to analyze the data, to transmit the curriculum control signal of the terminal according to the analysis content, and (f) to control the performance of the learning result evaluation (SRA) and to receive / analyze the relevant data to control the learning level Service server; characterized in that it comprises a.

According to the present invention as described above it can be obtained the effect described below. However, effects obtained through the present invention are not limited thereto.

First, according to the present invention, there is an effect that can propose a service platform that supports intelligent or customized (hereinafter intelligent) e-learning service.

Second, according to the present invention, there is an effect that can propose a method for performing the processes for the artificial intelligence control e-learning service based on artificial intelligence (AI).

Third, according to the present invention, it is possible to propose a method of collecting individual state data in various forms for the AI control e-learning service.

Fourth, according to the present invention, there is an effect that can propose a method for improving the individualized self-directed learning results improved by artificial intelligence control.

Fifth, according to the present invention, there is an effect that can propose an apparatus for implementing the above method.

1 is a diagram illustrating an artificial intelligence control e-learning service network environment to which the present invention can be applied.
2 is a block diagram of the AI control e-learning service server 110 according to an embodiment of the present invention.
3 is a diagram illustrating a method for providing an artificial intelligence control e-learning service according to an embodiment of the present invention.
4 to 7 are diagrams for explaining a learning efficacy psychological evaluation (SELF) according to an embodiment of the present invention.
8 is a diagram illustrating a learning ability diagnosis evaluation (SAE) according to an embodiment of the present invention.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. The detailed description, which will be given below with reference to the accompanying drawings, is intended to explain exemplary embodiments of the present invention and is not intended to represent the only embodiments in which the present invention may be practiced.

The present embodiments are merely provided to complete the disclosure of the present invention and to fully inform the scope of the invention to those skilled in the art, and the present invention is defined by the scope of the claims. It is only.

In some instances, well-known structures and devices may be omitted or shown in block diagram form centering on the core functions of the structures and devices in order to avoid obscuring the concepts of the present invention. In addition, the same components will be described with the same reference numerals throughout the present specification.

Throughout the specification, when a part is said to "comprising" (or including) a component, this means that it may further include other components, except to exclude other components unless specifically stated otherwise. do.

In addition, the term "… unit" described in the specification means a unit for processing at least one function or operation, which may be implemented in hardware or software or a combination of hardware and software. Furthermore, "a" or "an", "one", and the like shall be, in the context of describing the present invention, both singular and plural unless the context clearly dictates otherwise or is clearly contradicted by the context. It can be used as a meaning including.

In addition, specific terms used in the embodiments of the present invention are provided to aid the understanding of the present invention, and unless otherwise defined, all terms used herein, including technical or scientific terms, are used to describe the present invention. It has the same meaning as commonly understood by one of ordinary skill in the art. Use of this specific terminology may be modified in other forms without departing from the spirit of the invention.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. The detailed description, which will be given below with reference to the accompanying drawings, is intended to explain exemplary embodiments of the present invention and is not intended to represent the only embodiments in which the present invention may be practiced.

FIG. 1 is a diagram illustrating an artificial intelligence e-learning service system (AICeL) 100 to which the present invention can be applied.

Referring to FIG. 1, the AI control e-learning system 100 includes at least one terminal 102 and 104 and an AI control e-learning service server 110. Here, communication or data communication (hereinafter, data communication) between devices belonging to the artificial intelligence control e-learning service network environment is performed through a wired / wireless communication network.

Meanwhile, although not illustrated in FIG. 1, the AI control e-learning service system 100 mentioned below may further include at least one of a database (DB), a payment server (PG), and the like. The database (DB), payment server (PG), etc. may be implemented as a separate component from the artificial intelligence control e-learning service server 110 shown in FIG. 1 or of the artificial intelligence control e-learning service server 110 of FIG. It may also be an internal component. On the other hand, the AI control e-learning service server 110 may be implemented in plurality for the service, it may be in the form of a cloud server.

Although not shown, data communication between the terminals, the terminal, and the intelligent service server may be performed through the same or different communication network.

In the present invention, the terminal (102,104) is an apparatus for requesting the e-learning service and providing the received e-learning service data in a manner such as streaming, AI control e-learning service server for the AI control e-learning service system (100) It can be understood as a device capable of performing data communication with various other devices, including 110, and all related devices may be included.

At this time, the terminal (102,104) in accordance with the present invention, according to an embodiment of the AI control e-learning service application provided by the AI control e-learning service server 110 is previously downloaded and installed.

In this regard, in the present specification, only the terminal is used for the sake of convenience, but a plurality of terminals may be used for one AI control e-learning service, and it may be understood as including the case. Such a terminal may include an artificial intelligence control e-learning service application or an application program interface (API) or embedded software (Embaded Software) related to use thereof.

In other words, the method for providing an artificial intelligence control e-learning service according to the present invention described below is performed through an application including an API or embedded software pre-installed in the terminal, but is not limited thereto. The artificial intelligence control e-learning service may be provided through (WEBSITE).

In FIG. 1, only two terminals are illustrated for convenience of description, but the present disclosure is not limited thereto.

In other words, one or more terminals may be used for the AI control e-learning service. The terminals 102 and 104 used for the AI control e-learning service according to the present invention may transmit and receive data or signals (including those) to the AI control e-learning service server 110 by themselves, and the pre-installed AI control The e-learning service application may transmit or receive data or a signal to the AI control e-learning service server 110.

At this time, the data or signal transmitted or received to the AI control e-learning service server 110 may be related to the content of the application pre-installed in the terminal for the AI control e-learning service according to an embodiment of the present invention. However, it is not necessarily limited thereto.

The terminal may include a terminal device, a terminal, a mobile station (MS), a mobile subscriber station (MSS), a subscriber station (SS), an advanced mobile station (AMS), a wireless terminal (WT), and an MTC ( At least one of a Machine-Type Communication (M2M) device, a Machine-to-Machine (M2M) device, and a Device-to-Device (D2D) device may be provided.

Of course, this is only an example to the last, and the terminal in the present invention should be interpreted as a concept including all devices capable of transmitting data or signals that are currently developed and commercialized or will be developed in addition to the above examples.

In addition, the terminals 102 and 104 in the artificial intelligence control e-learning service system 100 may be necessarily the same type, type, device, or the like, or may not use the same communication network. That is, the terminals 102 and 104 may be devices capable of performing data communication with each other through the artificial intelligence control e-learning service server 110 and the artificial intelligence control e-learning service server 110 through respective communication networks.

Alternatively, the terminals 102 and 104 may be dedicated devices for data communication with the AI control e-learning service server 110 for the AI control e-learning service according to an embodiment of the present invention.

Next, the AI control e-learning service server 110 is an entity capable of performing data communication with at least one or more other devices through a wired / wireless communication network. 110 may be a plurality, and may further include one or more servers, such as a payment server (not shown) and a client server, for the AI control e-learning service.

Meanwhile, the AI control e-learning service server 110 according to the present invention collects, processes, and stores at least one data / big data necessary for the AI control e-learning service such as data regarding the terminals 102 and 104. Database (DB) can be embedded or external.

The payment server may be linked to an external payment server or a payment service platform instead of one component of the AI control e-learning service server 110.

In addition, the AI control e-learning service server 110 may include a cloud server, an IMS (IP Multimedia Subsystem) server, a telephony application server, an instant messaging (IM) server, a media gateway control function (MGCF). At least one of a server, a messaging gateway (MSG) server, a call session control function (CSCF) server, etc. may be at least one embodiment. The intellectual property transaction service server 110 may be a personal computer (PC), a notebook computer, or a tablet. It may be implemented as a device that refers to an entity capable of data communication, such as a PC (Tablet Personal Computer).

Meanwhile, the wired / wireless communication network supports data communication in various formats such as text, digital image, digital image, and digital voice information between the terminal (s) 102 and 104 and the artificial intelligence control e-learning service server 110. Means a data communication network, and the type thereof is not particularly limited. For example, it may be an IP (Internet Protocol) network supporting large data communication through the Internet protocol or an All IP network integrating different IP networks.

The wired / wireless communication network may include a wired network, a wireless broadband network, a mobile communication network including WCDMA, a high speed downlink packet access (HSDPA) network, and a long term evolution (LTE) network, LTE advanced. It may be formed by one or a combination of at least one of a mobile communication network, a satellite communication network and a Wi-Fi network including (LTE-A).

2 is a block diagram of an intelligent e-learning service server 110 according to an embodiment of the present invention.

2, the AI control e-learning service server 110 for the AI control e-learning service according to an embodiment of the present invention is a data communication unit 201 for transmitting and receiving data from the terminal (s) (102, 104) , Speech recognition module 202, language processing module 203, learner data processing module 204, big data processing module 205, artificial intelligence (AI) module 206, and other AI control e-learning services It may be implemented including at least one or more of the service control means (207).

In this case, the artificial intelligence control e-learning service server 110 may further include at least one of a database (DB) 208 for storing the above-described various data, a payment server (not shown) according to intelligent e-learning.

The database (DB) 208 is illustrated and described as a component of the AI control e-learning service server 110 for convenience, but is not necessarily limited thereto. As described above, the AI control e-learning service server 110 is described. ) Or receive various data including the AI control e-learning service data from the AI control e-learning service server 110 or store the data according to a stored data read request of the AI control e-learning service server 110. It may include any external (storage) device that can be transmitted to the AI control e-learning service server 110.

The data communication unit 201 transmits / receives data with the terminals 102 and 104 through a dedicated line or a wired / wireless Internet (IP) network. The data input through the Internet (IP) network may include intelligent e-learning terminal identification information and / or terminal user, that is, learner's personal information, intelligent e-learning learning information, artificial intelligence control e-learning service application execution information, and the artificial intelligence control e-learning service application. Among various usage information, service request and usage information through AI control e-learning service application, AI control e-learning service language information, real time AI control e-learning service usage time, information usage history, intelligent e-learning learning level information, etc. At least one may be included. The input data described above may be individually stored in a database (DB) 208 in a terminal unit or a learner unit.

The voice recognition module 202 recognizes and inputs the input data of the terminals 102 and 104 of the AI control e-learning service using the AI control e-learning service platform provided by the AI control e-learning service server 110. As a means for appropriately processing, Speech To Text (STT) or the like may be used in the processing.

For details regarding the specific configuration, function, and the like of the voice recognition module in the present specification, reference will be made to a previously known voice recognition technology, and a detailed description thereof will be omitted.

When voice data is included in data input from the terminals 102 and 104, the voice recognition module 202 is activated to recognize voice data in the input data, identify a language type of the recognized voice data, and recognize and identify the voice data. Can be provided in the form of text or the like. Through this, for example, even a handicapped user may use the intellectual property trading service according to the present invention. In the above description, the language type of the voice data means, for example, Korean, English, Chinese, Japanese, or the like.

On the other hand, although shown and described in the voice recognition module 202 in the present invention, this does not necessarily mean that limited to the voice data, the recognition / processing unit of the data input from the terminals 102 and 104 through the data communication unit 201 Perform the function. Accordingly, the voice recognition module 202 may be combined with or replaced with a touch module, a gesture recognition module, or the like for identifying input information of the terminals 102 and 104 input through the data communication unit 201. It may be.

For example, when text, an image, a video, a voice, etc. are mixed in data input from the terminals 102 and 104, the module 202 may function as a module in charge of processing corresponding to each data. In other words, in this specification, only the voice recognition module is illustrated for the convenience of explanation and for convenience of description, and the present invention is not limited thereto.

In the above description, one embodiment of processing text data by recognizing and processing voice data as input data or for convenience, has been described. In the opposite case, processing the same through TTS (Text to Speech) is also within the scope of the present invention. Will be included in.

As described above, the language processing module 203 first identifies a language type from the input data (voice data) of the recognized terminals 102 and 104, and supports the AI control e-learning service based on the identified language type. The language processing module 203 identifies the type of input language of the corresponding terminal from the input data of each terminal 102, 104, and provides information on the learning data processing module 204, the big data processing module 205, and artificial intelligence. The AI control e-learning service may be supported by directly providing at least one of the modules 206 or transferring the module to the corresponding module under the control of the service control means 207.

The training data processing module 204 generates and transmits a variety of training data for the AI control e-learning service, or, conversely, processes input data, that is, response data, of the terminals 102 and 104 according to the generated and transmitted training data. The function of the learning data processing module 204 may be stored or controlled through data communication with at least one of the big data processing module 205, the artificial intelligence module 206, the service control means 207, and the like.

The big data processing module 205 collects big data based on the data processed by the voice recognition module 202, the language processing module 203, and the like, and the artificial intelligence module 206 and service control means. 207, a database (DB) 208, or the like.

The AI module 206 may include a speech recognition module 202 and a language processing module 203 using an AI processor based on big data or based on machine learning or deep learning. At least one of classification, processing, processing, etc., of the input data of each terminal processed in the intelligent e-learning service is performed.

Here, the AI module 206 is at least one of the processes of the AI control e-learning service provided through the AI control e-learning service application using the AI control e-learning service platform provided by the intelligent e-learning service server 110. By means of or contribute to the means means all means that can be used and control of the AI control e-learning service.

Meanwhile, in the present invention, the artificial intelligence module 206 may be used as it is or in combination with reference to the known contents and various artificial intelligence technologies to be developed in the future. Therefore, detailed description of the artificial intelligence module will be omitted herein.

In addition, the detailed operation of the artificial intelligence module 206 will be described in detail in the corresponding part.

The service control means 207 is a means for managing and controlling the functions of the AI control e-learning service platform by managing and controlling the components of the above-described AI control e-learning service server 110.

In addition, the database (DB) 208 is in data communication with at least one of the above-described configuration to collect, store, extract, transmit, etc. a variety of data, including input data of the terminal (102,104), artificial intelligence control e-learning service data, etc. Do at least one of the The database (DB) 208 may be further included if necessary in connection with the present invention.

Meanwhile, the above-described artificial intelligence control e-learning service, such as the components of FIGS. 1 and 2 and interworking therebetween, will be described in more detail with reference to FIG. 3.

3 is a view for explaining an artificial intelligence control e-learning service providing method according to an embodiment of the present invention, Figures 4 to 7 are shown to explain the learning efficacy psychological evaluation (SELF) according to an embodiment of the present invention 8 is a diagram illustrating a learning ability diagnosis evaluation (SAE) according to an embodiment of the present invention.

Hereinafter, each process described below with reference to FIG. 3 will be described in terms of the AI control e-learning service server 110. However, the present invention is not limited thereto, and it will be apparent to those skilled in the art that the viewpoint and contents of the terminal or / and the artificial intelligence control e-learning service system can also be derived from FIG. 3.

3, the AI control e-learning service according to the present invention is made through the terminal for convenience, and pre-registration is taken as an example for such a service.

In relation to the AI control e-learning service server 110 receives the personal information for the registration from the terminal (102, 104) (S301). Here, the personal information includes a variety of information such as gender, age, place of residence, education degree of the individual using the intelligent service through the terminal. In addition, when the personal information is updated or changed after the registration, the personal information may be retransmitted and stored in the database (DB) 208 of the artificial intelligence control e-learning service server 110. The updated or changed information may include, for example, various levels of learner information generated in the course of using the AI control e-learning service as well as the current level and level recommendation of the learner after service registration. In addition, the personal information may include identification information about the terminal (102, 104).

The artificial intelligence control e-learning service server 110 analyzes the personal information for the learner based on the received personal information of the terminals 102 and 104 (S302). The data thus analyzed may be stored in a database (DB) 208.

When the AI control e-learning service application is executed in the terminal 102 or 104 or the AI control e-learning service request such as a visit to the related website is requested, the AI control e-learning service server 110 analyzes the corresponding learning terminal 102 or 104 in step S302. Self-efficacy for Learning Form (SELF) and Study Ability Evaluation (SAE) data are transmitted to the learning terminals 102 and 104 based on the personal information of In step S303, the learning efficacy psychological evaluation (SELF) and the learning ability diagnostic evaluation (SAE) performance data are returned (S303).

According to an embodiment of the present invention, the learning efficacy psychological evaluation (SELF) and / or learning ability diagnostic evaluation (SAE) is a method for setting a variable curriculum template (VCT) according to learning ability at the start of learning. Can be.

The learning efficacy psychological evaluation (SELF) is, according to one embodiment, subjective reliability of the learner's self, and in order to successfully acquire new knowledge and skills through a general learning method, to understand, analyze, and memorize learning contents. It is a subjective measure of belief about whether or not it can be used, which consists of a total of 19 questions: note taking, reading, writing, test-taking, learning and It may have been developed by previous research (Zimmerman & Kitsantas, 2007) for measuring various learning methods of the same learner. The learner may send a response with a scaling value ranging from 0 to 100 percent for questions such as those shown in FIGS. In this case, the higher the score value, the greater the efficacy, which means that the higher the confidence about learning and the higher the confidence, the higher the learning integrity and success probability. However, FIGS. 4 to 7 and the above definitions are provided as an embodiment for the convenience of explanation and convenience of description, and the present invention is not limited thereto.

Next, Studying Ability Evaluation (SAE) may consist of multiple questions about subjects for language learning. Here, the items refer to items for evaluating current language proficiency regarding grammar, vocabulary, reading comprehension, writing, listening, and speaking. It is set as an Example. In relation to this, FIG. 8 is illustrated to explain the items of Learning Assessment Assessment (SAE) according to an embodiment of the present invention. Referring to FIG. 8, the higher the score, the better the learning ability, the better the learning effect can be expected, and the score result can be reflected in the curriculum adoption.

As described above, the results of the learning efficacy psychological evaluation (SELF) and the learning ability diagnostic evaluation (SAE) are transmitted to the artificial intelligence control e-learning service server 110, the artificial intelligence control e-learning service server 110 is Feedback can be fed back. The AI control e-learning service server 110 controls to provide and perform a personalized curriculum template (PCT) of the learner together or separately with the feedback (S304).

The personalized curriculum (PCT) may be various templates for a learning subject specially developed based on learner's characteristics, learning content preference, learning efficacy, and the like. To this end, the personalized curriculum (PCT) is conducted in the form of lessons, lessons, lectures, etc. and extracts the learner's skill level, learning textbooks, video files, and audio files. Can be analyzed. This can be used by a specific instructor for the subject.

As described above, the results of the personalized curriculum (PCT) of the terminal (102,104) is transmitted to the AI control e-learning service server 110, analyzed and stored in the database (DB) 208 to be used later.

The AI control e-learning service server 110 controls to perform a learning progress evaluation (LPE) after performing the personalized curriculum (PCT), and the terminals 102 and 104 of the learning progress evaluation (LPE) Pass the result (S305).

The learning progress assessment (LPE) is a writing and oral test composed of a plurality of items, and is similar to the learning ability diagnosis assessment (SAE) in evaluating the progress of learning for a specific subject of the learner.

The AI control e-learning service server 110 receives and analyzes the learning progress evaluation (LPE) results of the terminals 102 and 104 and stores them in a database (DB) 208. The learning progress assessment (LPE) may be performed on a weekly or monthly basis and may be different from the personalized curriculum (PCT). However, the present invention is not limited thereto. The evaluation period may be arbitrarily set and may be variously defined according to the schedule progress of the learner.

The AI control e-learning service server 110 generates a control signal (including a first control command) for a curriculum based on at least one of the aforementioned processes, that is, calculating, analyzing, and extracting data. ), And the terminal 102 or 104 may perform an operation corresponding to the control signal of the artificial intelligence control e-learning service server 110, that is, adjust a curriculum (S306 and S307).

Herein, adjusting the curriculum means modifying at least one or more based on a current curriculum provided for the learner, that is, the content and the degree to be adjusted are the AI control e-learning. It may be determined by the service server 110.

In this way, the AI control e-learning service server 110 may adjust the current curriculum to perform a study result assessment (SRA) to determine how the adjusted curriculum affects the current learner. After the control, the terminals 102 and 104 return the SRA data according to the control to the AI control e-learning service server 110 (S308).

The learning outcomes assessment (SRA) is also a writing or / and oral test that can also be provided when each skill level is completed, and the results can be used to determine whether the learner has leveled up to the next level.

The AI control e-learning service server 110 analyzes and stores the big data for the individual learner based on the learning result evaluation (SRA) for the adjusted curriculum through step S308, and stores the second control command in the terminal. It can transmit to (102,104) (S309, S310).

Here, the second control command may be defined in various ways. For example, the second control command controls to perform at least one or more of the above-described steps S303 to S308 again, to perform the whole process, or to perform some or all of the processes more than a predetermined number of times or until a predetermined response result is received. It may be a signal.

Meanwhile, the processes S301 to S310 may be for one learning level or program among various learning levels or programs that can be provided by the artificial intelligence control e-learning service server 110.

Thus, for example, the second control command may be a control signal for level up recommendation upon completion of learning about the learning level.

Although not shown, in addition to the above-described Learning Efficacy Psychology (SELF) and Learning Ability Assessment (SAE), the Vocabulary Memorization Ability Test (VMAT) and English Proficiency Assessment ( At least one or more of EFE: English Fluency Evaluation) may be used.

The vocabulary memory measurement test (VMAT) is made by writing a word to remember after learning English words in the answer, for this purpose, select 10 English words according to the English level, spelling of words, pronunciation related pictures, Chapter 3, Korean translation 20 minutes of explanation, 60 minutes of other questionnaire surveys, memorized words from the English words learned in the answers, depending on the number of correct answers A (9-10), B (8-7), C (5-6) , D (3-4), E (1-2) can be classified into 5 stage groups and suggested discriminatory learning methods based on the results.

On the other hand, the English Language Proficiency Assessment (EFE) is a method of evaluating the current English language ability of the English language learner, there is a reading, listening, speaking, writing in the evaluation area, the reading comprehension (25 questions) is a fingerprint It consists of questions that read and evaluate the grasp of the content, the Listening Comprehension (25 questions), consists of questions to hear a variety of English files and ask about the content, Speaking is a learner for five questions (Writing) consists of essay writing (40 minutes) on a given topic, and scores 25 points in each area, totaling 100 points to learn students' strengths and weaknesses in each area. Recommend improved learning measures.

On the other hand, unlike before the start of the learning, after the start of the lesson may be made of lesson data, course data, step-by-step progress evaluation (LPE), after completion of the step-by-step learning (LCA: Level Competency Assessment). The lesson data and the course data may be personalized curriculum (PCT) data.

First, in relation to the lesson data, the lesson video between the intelligent e-learning instructor and the learner is stored in the server archive along with the recognition data such as the lesson number and the date, the audio data is extracted from the lesson video data, and the extracted audio data is converted into text. Save it to a file. Then, the stored text is searched to understand and analyze the learner's understanding of learning. In this case, the reference time is the time to receive the subject map, the time to the voice response (Yes, etc.) that you understand after the start of the map, the number and number of questions about the part that you do not understand during or after the map, the number of repetitions of the same question, etc. This may be included.

Next, with regard to the course data, you can watch the live relay course (LiVib) and the course VoD, the evaluation scores for the topic evaluation questions, 10-20 points by topic, the total learning time of the same video content VOD, the same number of repeated video views, etc. Reference may be made.

In addition, the above-described step progress evaluation (LPE) can be stored in the same way as the EFE (EFE) once a month to store the learner's score, and use the monthly score as the basis for determining the level of learning of each step converted to the average. .

Next, the Level Competency Assessment (LCA) stores learning results for each area as measurement data in the same manner as the English Proficiency Assessment (EFE). In addition, if the student scores 70 points or more on the average of the monthly progress evaluation (LPE) score, he / she may recommend progression to the next step.

The AI control e-learning service server 110 stores and analyzes at least one or more of all the above-described data to identify strengths and weaknesses of each area of the learner, and then changes the variable curriculum according to the learner and proposes a more effective learning plan. can do. At this time, at least one or more or all of the following may be referred to: measurement of learning comprehension skills, analysis of self-directed learning data to identify learning trends, recording practice time and improvement of language skills through analysis of practice data, and each learner Each area score and improvement or deterioration record for each subject, the learning period time for each subject step by step analysis, record the strengths and weaknesses of each area in the course of learning or completion (100 points in each area), learner's age, gender, education degree Recommend the variable curriculum prepared according to the inclination according to the learners monthly and step by step, record and review the results according to the newly recommended curriculum, realign the curriculum according to the result, and recommend the individual customized curriculum by analyzing the data. Depending on the curriculum completion time estimate, all data analysis can include individual or overall revenue forecasts. .

4 to 8 described above, that is, learning efficacy psychological evaluation (SELF), learning ability diagnosis evaluation (SAE), vocabulary memory measurement test (VMAT), English ability diagnosis evaluation (EFE), etc. According to an embodiment of the present invention, it is learning ability evaluation reference data for setting a customized curriculum (VCT).

In addition, in the present specification, the AI control e-learning service server may be executed by the AI module 206 or at least one or more of the components of FIG. 2 may be performed.

On the other hand, it is preferable that the terminal includes at least one or more of a display, a speaker, a microphone or can be used in conjunction with such an external device (s) for the artificial intelligence control e-learning service according to the present invention.

According to the present invention described above, based on the artificial intelligence control e-learning service system, the server side can lead the level without dropping the learner's academic efficiency, interest, etc., by providing the appropriate course based on the learner's personal information, The learner can also perform self-directed learning and access various information on the learning level, learning, etc. by upgrading various kinds of feedback data of the service server, upgrade the skills by improving the learning efficiency, and perform various exercises at once.

In addition, although not shown, the above-described contents and processes may be controlled differently by giving different weights according to learner's personal information, in particular, age, gender, and the like. In addition, the control may be performed by using a variety of information provided by the AI control e-learning service server in addition to the above-described data on the conventional learner, such as morning, afternoon, evening, night, and after meal, on a daily basis. The utility can be improved.

In addition, the AI control e-learning service server may vary the control at every learning level according to the learning level. For example, as a learner moves up the level, more data (big data) for that learner will be available, which will allow for more detailed, accurate and varied service control. Such control may include various controls such as the length, order, and contents of the curriculum of the corresponding learning level.

The present invention relates to an artificial intelligence control e-learning service, and according to the age of the learner, using a fairy tale book as learning material or data for the above judgment, or by using objective data such as prominent newspapers or past questions, can increase reliability and increase efficiency.

This is not just for language learning, but for a variety of fields.

According to another aspect of the present invention, there is provided a method for providing an artificial intelligence control e-learning service of a server, the method comprising: (a) receiving, analyzing and storing information of a terminal; (b) receiving first data about a learning efficacy psychological evaluation (SELF) and a learning ability diagnostic evaluation (SAE); (c) receiving second data for a personalized curriculum (PCT); (d) analyzing the first data and the second data and receiving LPE data according to the analysis contents; (e) analyzing the learning progress evaluation (LPE) data and transmitting a curriculum control signal of the terminal according to the analysis contents; And (f) controlling the performance of the learning result evaluation (SRA) and receiving / analyzing the relevant data to control the learning level. However, the steps (a) and (b) start intelligent e-learning learning. Characterized in that it is performed before and not after, the step (a) is performed at the time of updating the terminal information, and in the step (b), a Vocabulary Memorization Ability Test (VMAT), Further receiving at least one data of English Fluency Evaluation (EFE), wherein steps (c) to (f) are performed at every learning level preset in the server, and (c) to ( f) receiving lesson data between steps; Receiving course data; Or receiving Level Competency Assessment (LCA) data after completion of the step-by-step learning after the step-by-step learning progress assessment (LPE); In addition, the learning efficacy psychological assessment (SELF) relates to subjective reliability of the learner's own self, and to understand the contents of learning in order to successfully acquire new knowledge and skills through a general learning method. Subjective beliefs about analysis and memory are carried out using data developed in connection with measurement, and the SAE is based on grammar, vocabulary, reading comprehension, and writing. It consists of a plurality of questions about subjects for language learning, including items for assessing current language proficiency in writing, listening, and speaking. ) Is made through various templates for learning subjects developed based on learner's characteristics, learning content preferences, and learning efficacy. An LPE assesses the learner's progress on a particular subject, and the SRA is a writing or / or oral test that can be provided when each level of proficiency is completed, the result being the learner's next level. Characterized in that it is used to determine whether the level up.

Meanwhile, the above-described method may be written as a program executable on a computer, and may be implemented in a general-purpose digital computer which operates the program using a computer readable medium. In addition, the structure of the data used in the above-described method can be recorded on the computer-readable medium through various means. Computer-readable media that store executable computer code for carrying out the various methods of the present invention include, but are not limited to, magnetic storage media (eg, ROM, floppy disks, hard disks, etc.), optical reading media (eg, CD-ROMs, DVDs). Storage media).

It will be understood by those skilled in the art that embodiments of the present invention can be implemented in a modified form without departing from the essential characteristics of the above description. Therefore, the disclosed methods should be considered in descriptive sense only and not for purposes of limitation. The scope of the present invention is shown in the claims rather than the detailed description of the invention, and all differences within the equivalent scope should be construed as being included in the scope of the present invention.

Claims (10)

In the artificial intelligence control e-learning service providing method of the server,
(a) receiving, analyzing and storing information of the terminal;
(b) receiving first data about a learning efficacy psychological evaluation (SELF) and a learning ability diagnostic evaluation (SAE);
(c) receiving second data for a personalized curriculum (PCT);
(d) analyzing the first data and the second data and receiving LPE data according to the analysis contents;
(e) analyzing the learning progress evaluation (LPE) data and transmitting a curriculum control signal of the terminal according to the analysis contents; And
(f) controlling the learning level evaluation (SRA) performance and receiving / analyzing relevant data to control the learning level;
Artificial intelligence control e-learning service providing method comprising a.
The method of claim 1,
Step (a) and step (b),
Intelligent e-learning learning is performed before the start but not after,
The step (a) of the artificial intelligence control e-learning service providing method, characterized in that performed when updating the terminal information.
The method of claim 1,
In step (b),
A method for providing an artificial intelligence controlled e-learning service, characterized in that it further receives at least one data from a Vocabulary Memorization Ability Test (VMAT) and an English Fluency Evaluation (EFE).
The method of claim 1,
Step (c) to (f),
The method for providing an artificial intelligence control e-learning service, which is performed at every learning level preset by the server.
The method of claim 1,
Between the steps (c) to (f),
Receiving lesson data;
Receiving course data; or
Receiving Level Competency Assessment (LCA) data after completion of the step-by-step learning after the step-by-step learning progress assessment (LPE);
Method for providing an AI control e-learning service, characterized in that for performing at least one of.
The method of claim 1,
The learning efficacy psychological evaluation (SELF),
Subjective confidence in the learner's self, AI controlled e-learning characterized by measuring subjective beliefs about understanding, analysis and memory of learning content in order to successfully acquire new knowledge and skills through general learning methods How we deliver the service.
The method of claim 1,
The learning ability diagnosis assessment (SAE),
In language learning, including items for assessing current language proficiency in grammar, vocabulary, reading comprehension, writing, listening, and speaking. Method for providing an AI control e-learning service comprising a plurality of questions for the subjects.
The method of claim 1,
The personalized curriculum (PCT),
A method for providing an AI control e-learning service, comprising various templates for a learning subject developed based on a learner's characteristics, learning content preferences, and learning efficacy.
The method of claim 1,
The learning progress assessment (LPE) evaluates the progress of learning for a particular subject of the learner,
The SRA is a writing or / or oral test that can be provided when each skill level is completed, and the result is used to determine whether the learner is to level up to the next level. How to Provide E-Learning Services.
In the artificial intelligence control e-learning service providing system,
Terminal; And
(a) receiving, analyzing and storing the information of the terminal, (b) receiving first data on a learning efficacy psychological assessment (SELF) and a learning ability diagnostic assessment (SAE), and (c) a personalized curriculum ( PCT) receiving second data, (d) analyzing the first data and the second data, receiving LPE data according to the analysis, and (e) learning progress evaluation ( LPE) service for analyzing data, transmitting curriculum control signals of the terminal according to the analysis contents, and (f) controlling performance of learning result evaluation (SRA) and receiving / analyzing relevant data to control learning levels server;
Artificial intelligence control e-learning service providing system comprising a.

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