KR102318056B1 - Non-face-to-face learning method and learning system for immersive learning - Google Patents

Abstract

According to an embodiment of the present invention, a non-contact learning method for immersive learning may comprise: a step of connecting to a lecture providing server through terminals; a step of providing a lecture in the lecture providing server; a step of recognizing a graph or a mathematical formula created by a lecturer as an image; a step of storing the recognized image as a file; and a step of providing the stored image file to each of the terminals.

Description

Non-face-to-face learning method and learning system for immersive learning

The present invention relates to a non-face-to-face learning method and learning system for immersion learning.

In recent years, due to the development of Internet technology and communication technology, the existing offline learning system is rapidly being replaced by an online learning system. The popularity of online learning systems that allow students to take their desired lectures at a convenient time and environment, free from time and place constraints, is increasing day by day.

However, in the existing online lectures for online learning, the learner selects and pays for the lecture he or she wants to learn from the lecture list of the online education company, and the online education company unilaterally provides learning contents. There were many cases where people just paid and didn't actually learn.

In addition, unlike general offline academies, there is a problem that the concentration of learning is very low for middle and high school students who lack self-control ability due to the absence of competitors and inducement of teachers to participate in learning.

Therefore, there is a need for a system that improves the concentration of lectures, compensates for the lack of realism in lectures due to the limitations of online, and allows the instructor's knowledge and points to be delivered more efficiently and naturally to learners.

Republic of Korea Patent Publication No. 10-2020-0084204 (2020.07.10)

As devised based on the above technical background, the present invention not only improves the concentration of lectures of students, but also enables continuous tracking management of incorrect answers, tracking management for improving the level of learners, and tracking management of the contents emphasized by the instructor. To provide a non-face-to-face learning method and system for immersion learning.

The non-face-to-face learning method for immersion learning according to an embodiment of the present invention includes the steps of connecting to a lecture providing server with a terminal, providing a lecture from the lecture providing server, and a graph and mathematical formula shown on a blackboard by an instructor It may include the steps of recognizing an image, storing the recognized image as a file, and providing the stored image file to each terminal.

The lecture providing server may include recognizing the lecturer's voice during lecture, extracting the problem when the lecturer speaks a specific keyword, and re-editing the extracted problem into a main problem note. have.

It may include preparing the theory and information according to the extracted problem and inserting the theory and information into the main problem note as a core theory.

The lecture providing server may include recognizing a student's voice during a lecture, changing the recognized student's voice into recording and text, and uploading the changed text to a preset lecture question server.

The student's voice may not be transmitted to the instructor.

The student's voice may be selectively audible when the instructor does not understand the changed text uploaded to the lecture question server.

The lecture question server, dividing the running time section of the lecture and setting it into a plurality of categories, comparing the uploaded text with the running time of the lecture, creating statistics for the category in which the text is written a lot, and Analyzing the statistics may include collecting the students' interest questions.

The category may be set according to the subject of the lecture.

The aggregating step may include collecting the problems corresponding to the questions and re-editing them as student interest problems.

The non-face-to-face learning method and learning system for immersion learning according to an embodiment of the present invention enables not only to improve lecture concentration, but also to track management for improving the level of the learner, and to track and manage the content emphasized by the instructor.

1 is a block diagram of a non-face-to-face learning system according to an embodiment of the present invention.
2 is a flowchart of a non-face-to-face learning method for immersion learning according to the first embodiment of the present invention.
3 is a flowchart of a non-face-to-face learning method for immersion learning according to a second embodiment of the present invention.
4 is a flowchart of a non-face-to-face learning method for immersion learning according to a third embodiment of the present invention.
5 is a flowchart of a non-face-to-face learning method for immersion learning according to a fourth embodiment of the lecture providing server disclosed in FIG. 1 .
6 is a flowchart showing the steps of re-editing the customized problem notes of the present invention.
FIG. 7 is a flowchart illustrating in detail the steps of classifying the problem to be erroneous in FIG. 6 .

Hereinafter, with reference to the accompanying drawings, the embodiments of the present invention will be described in detail so that those of ordinary skill in the art to which the present invention pertains can easily implement them. The present invention may be embodied in many different forms and is not limited to the embodiments described herein. In order to clearly explain the present invention in the drawings, parts irrelevant to the description are omitted, and the same reference numerals are assigned to the same or similar components throughout the specification.

In the present specification, terms such as “comprise” or “have” are intended to designate that a feature, number, step, operation, component, part, or combination thereof described in the specification exists, but one or more other features It is to be understood that it does not preclude the possibility of the presence or addition of numbers, steps, operations, components, parts, or combinations thereof. Further, when a part of a layer, film, region, plate, etc. is said to be “on” another part, this includes not only the case where the other part is “directly on” but also the case where there is another part in between. Conversely, when a part of a layer, film, region, plate, etc. is said to be “under” another part, this includes not only cases where it is “directly under” another part, but also a case where another part is in between.

1 is a block diagram of a non-face-to-face learning system according to an embodiment of the present invention.

Referring to FIG. 1 , the non-face-to-face learning system may include a lecture providing server and a terminal.

The terminal may transmit and receive lectures and materials provided by the lecture providing server to the learner. Lectures may include video and audio. In addition, the learner can send questions in video and audio to the lecture server through the terminal, and can also transmit data in images and files. The lecture providing server can classify and analyze input and output data.

Student data may be input to the lecture providing server. Through this, lecture materials, etc. can be provided to authenticated learners, and it is possible to prevent multiple users from sharing and using a single ID. Through this, it may be possible to track and manage information that is more tailored to the individual student.

The first data unit may be connected to the lecture providing server. The first data unit may be lecture materials of the instructor. That is, the lecturer's live lecture is stored as video and audio, stored in the first data unit, and transmitted to the terminal through the lecture providing server. In this process, the lecture providing server can reprocess the lecture material of the first data part to meet the learner's level and provide more appropriate material efficiently.

The second data unit is connected to the lecture providing server, and can store the reprocessed and re-edited data through the lecture providing server, and provide the stored data to each learner. That is, the re-edited data for each learner is stored in the second data unit, and can be updated in real time according to the learner's lecture progress and provided to each learner in real time. The re-edited data for each learner is different, and the learner's response to the data stored in the second data unit is stored and managed, so that it is possible to track and manage each learner to improve the learner's level.

The third data unit may be connected to the lecture providing server. The first data unit may store data generated by the student. The third data unit may process the data generated by each student and send it to the lecture providing server, and compare and analyze the instructor's data transmitted from the first data unit and the student's data transmitted from the third data. . In the future, such data can collect meaningful data by extracting problems or interests of each student that are not recognized by the instructor or the system, and can create more student-centered results by collecting them.

2 is a flowchart of a non-face-to-face learning method for immersion learning according to an embodiment of the present invention.

Referring to FIG. 2 , the non-face-to-face learning method for immersion learning includes accessing a lecture providing server with a terminal, providing a lecture from the lecture providing server, graphs and mathematical formulas shown on a blackboard by an instructor may include the step of recognizing as an image.

Graphs and mathematical formulas drawn by the instructor on the blackboard may include recognizing them as images. For example, the instructor may write graphs and formulas rather than letters or numbers during class. In particular, in the case of world history lectures, depending on the characteristics of each class, such as drawing a map, the instructor creates image information in addition to information that can be transmitted through text or voice, such as letters or numbers, on the blackboard. This image information is recognized so that it can be delivered to the learner. Through this, it is possible to increase the learning efficiency of the learner and provide better quality information when the learner reviews or organizes the information acquired in the future and acquires it through self-learning. This image is saved as a file and provided to the learner's terminal.

In addition, the lecture providing server may include the step of recognizing the lecturer's voice among the lecturer's data transmitted through the first data unit. Recognizing such a voice may include extracting the problem when the instructor speaks a specific keyword. For example, the instructor mentions specific keywords such as "important" and "remember" during a lecture, and the lecture providing server recognizes this and can extract the problem mentioned by the instructor. For example, by analyzing the lecture running time of the instructor, it is possible to extract a directly related problem or an indirectly related problem by analyzing the topic, theory, or problem of the point mentioned by the specific keyword. It may include the step of extracting the problem as a center, collecting and re-editing the extracted problems in this way, and editing it into a main problem note.

It may include the step of preparing theories and information related to the problems thus extracted. In other words, by analyzing the instructor's class based on the problem, the problem is first extracted, and the theory and information related to the problem are collected again based on the extracted problem, and the lecturer's lecture is re-edited in a different direction from the instructor's intended lecture point of view. will do Through the process of inserting the theory and information related to the problem as the core theory in the main problem note, it is possible to unconsciously rediscover excessive information, collect the information again, and deliver it to the learner.

3 is a flowchart of a non-face-to-face learning method for immersion learning according to a second embodiment of the present invention.

Referring to FIG. 3 , the method may include recognizing a student's voice during a lecture. In other words, learners take a class alone in an individual space using the terminal. For example, to increase student participation and increase learning efficiency, students can ask questions in real time during lectures. The students' voices may be recorded and recognized separately from the output of the instructor's voice. The recognized student's voice is recorded in real time, but it is not transmitted to the instructor or other students who have access to the class at the same time. Through this, students who have questions can improve their learning efficiency by not interrupting the attention of other students by not interrupting the instructor's lecture while solving their questions in real time. The student's voice is changed to text, and the recorded file and text file are delivered to the instructor. In this case, it may be uploaded to the lecture question server preset in the lecture providing server through the third data unit. The instructor can immediately answer the student's question by checking the text. In this case, in the text converted from the student's voice, the running time of the instructor's class and keywords for the topic lectured by the instructor may be mentioned, thereby guiding the instructor to provide an answer more efficiently.

4 is a flowchart of a non-face-to-face learning method for immersion learning according to a third embodiment of the present invention.

Referring to FIG. 4 , the lecture running time section of the instructor may be divided into a plurality of categories. Instructors do not pay special attention or follow procedures for online lectures, induce lectures as if they are lectures in the field, record the lectures of the lecturers, divide the running time into multiple parts, and quantitatively analyze the lectures of the lecturers. In this case, first, the lectures of the lecturers segmented by the running time are categorized according to the subjects of the lectures of the lecturers.

By comparing the lecture running time with the uploaded text formed from real-time questions of students participating in the lecture, statistics on the category in which the text is formed are created. For example, the instructor gives a lecture at a set time and content without interruption or interruption of the lecture, and students participating in the lecture at the same time can ask questions in real time. At this time, if there are many students' voice recognition at a specific time of the lecture, the students' interest is high or the students may discover a topic or problem that is difficult to understand. Through this, it is possible to obtain statistics that are difficult to find because they do not ask questions well due to the problem of disturbing the attention of nearby students in the field. .

Through the non-face-to-face learning method for immersion learning of the present invention, the lecture point is slightly changed in each class to correct the uneven learning level, and the instructor is not conscious of the online class as in the field, and the blackboard Lectures are given while writing freely in the classroom to deliver information or theories from the unconscious to students more realistically and efficiently, and students can ask questions in real time by voice, increasing their participation in the class, and statistically analyzing the questions students are curious about more efficiently. and has the advantage of being able to accurately recognize it.

5 is a flowchart of a non-face-to-face learning method for immersion learning according to a fourth embodiment of the lecture providing server disclosed in FIG. 1 .

Referring to FIG. 5 , the non-face-to-face learning method for immersion learning may include connecting to a lecture providing server with a terminal and stopping execution of programs other than the program provided by the lecture providing server in the terminal.

Each learner may possess a terminal either personally or through an authorized company. Through the terminal, the learner accesses the lecture providing server, and preset student data and login information may be input to the terminal connected to the lecture providing server. The lecture providing server may analyze student data and log-in information to analyze the student's attendance pattern and provide data on this. For example, by analyzing the time of accessing a lecture, it is possible to check the lecture time focused on each individual, and the lecture concentration can be analyzed through the lecture viewing time and face recognition during the lecture.

In the lecture providing server, the execution of programs other than the provided programs can be stopped. For example, after acquiring the security authority of the operating system, other programs may be forcibly terminated during the time connected to the lecture providing server. This can improve the learner's academic concentration.

Next, the lecture may be provided by the lecture providing server. As described above, the lecture material of the instructor may be made of video, audio, and text, and the data may be stored in the first data unit. The lecture providing server may receive lecture data from the first data unit and provide the lecture to the connected terminal.

It may include popping up a quiz with a time limit set during the lecture and storing the quiz result. The learner takes the lecture untact through the terminal. At this time, it is necessary to check and manage whether the learner is learning with concentration. By popping up quizzes irregularly, you can not only break away from one-sided lectures, but also increase your concentration by encouraging active participation of learners. In particular, the quiz results are stored, and can be used as data to check the learner's patterns and incorrect answers to set the level and provide a solution thereto.

If there is no answer to the quiz within the time limit, it may include the step of giving a penalty. This is to prevent actions such as turning on the terminal, moving, or sleeping, and by setting a time limit for the quiz, it is possible to induce the quiz to be solved within the time limit. Penalties such as sending additional quizzes or giving more self-study time even after the lecture is over can be given by selecting cases for not answering within the time limit.

The quiz may consist of a quiz on the day set for each progress of a lecture taken by the learner and a mock test set according to the learner's accumulated lecture progress. That is, the quiz may pop-up a plurality of quizzes of the day at irregular times during the lecture in order to confirm the contents taken and to improve concentration. Through this, the learner must answer the quiz on the day based on the content taken.

The mock exam can be set according to the accumulated lecture progress, and the accumulation period can be set by the administrator in the lecture providing server. For example, if the cumulative period is set to one month, the mock exam can be held every month, and if there is no limit on the cumulative period, you can take a mock exam that includes the progress of all lectures. Through this, it is possible to take a mock test for all learners registered in the lecture providing server, and it can be used as data for predicting national rankings and CSAT grades.

In this case, the step of collecting incorrect answers for each learner each time the quiz is conducted and re-editing the incorrect answer notes may be further included. For example, a learner may collect a question with an incorrect answer in a quiz on the day and a problem with an incorrect answer in a mock test, re-edit it as an incorrect answer note, and then store it in the second data unit. This incorrect answer note can be provided to the learner, and each learner's incorrect answer note is made individually, so that the learner's level can be continuously tracked and managed by recording the problems that the learner frequently makes mistakes and overcoming the wrong answers.

6 is a flowchart showing the steps of re-editing the customized problem note of the present invention.

Referring to FIG. 6 , in order to re-edit the customized problem notes, it may include a step of analyzing a mock test and a step of classifying problems that should be avoided in the analyzed mock test.

The mock exam is executed according to the accumulated lecture progress, and based on this result, it is possible to predict the national ranking and the CSAT grade. The mock test results are analyzed to classify the problems that each learner should not be wrong, and the steps are compared with each learner's incorrect answer notes.

If it is recorded in the incorrect answer note and classified as a problem that should not be wrong, information has already been given to the learner.

Conversely, if the question that should not be wrong is not recorded in the incorrect answer notebook, label the classified question that should not be wrong, collect the question that should not be wrong with the label and re-edit it as a customized question note will go through Through this, each learner gets information about the questions that should not be wrong in the mock test in addition to the incorrect notes, and receives information about why they should not be wrong and information about why they should not be wrong, unlike the information that they are simply wrong, to rouse their memory. It can make you more memorable. Through this process, the learner's level is improved more naturally, and above all, it is possible to create basic information about a solution to raise the learner's level while checking and managing the learner's level every time.

FIG. 7 is a flowchart illustrating in detail the steps of classifying the problem to be erroneous in FIG. 6 .

Referring to FIG. 7 , the step of classifying the problem to be not wrong is a step in which the learner selects the CSAT grade to which he or she belongs or wants to correspond, and the step of checking the correct rate of each problem of other learners according to the selected CSAT grade classification may include.

First, the learner can set the correct rate by himself/herself by selecting the SAT grade. For example, if a learner whose CSAT grade was 5th grade is studying for the CSAT grade 3 goal, set the CSAT grade to 3rd grade, and if the CSAT grade is 3rd grade, you can obtain information about the problem . Through this, the learner can acquire and manage information for achieving the goal, which can be more efficient in achieving the goal.

By checking the percentage of correct answers for each problem according to the selected CSAT grade, information on problems that learners could not predict or problems with difficulty in difficulty, etc. can be obtained and managed for each learner. In addition, by checking the percentage of correct answers according to the CSAT grade, it is possible to set standards for the problems that each learner should not be wrong, and help the learners to raise their level through information and management.

It may include the step of analyzing the problem of incorrect answers in the mock test for each learner, and analyzing the influence of the problem of the incorrect answer on the change of the student's CSAT grade in the CSAT grade selected by the learner. For example, the learner sets the CSAT grade 3, analyzes the learner's incorrect answer, evaluates the influence of each incorrect answer on the CSAT grade, and classifies it as a problem that should not be wrong. If it turns out to be a problem with an influence of more than 70%, it can be classified as a problem that should not be wrong. For example, the influence may be information about the probability that the CSAT grade can be changed from grade 3 to grade 2.

Influence can be set to 100% if the rating changes even if only one of the incorrect answers is changed to the correct answer. For example, after setting the CSAT grade to 3rd grade and analyzing the problem of the learner who took the mock test, the difficulty is set based on the average score and correct rate of the mock test that corresponds to the 3rd grade of the CSAT. Even if only one of the questions is answered correctly, the influence on the question that can change the CSAT grade is set to 100%.

In addition, if any one of the incorrect answer questions and the set difficulty level are changed to the correct answer, the influence can be set to 80% if the CSAT grade is changed. That is, if one more difficulty is correct, information can be presented to the learner by analyzing the problem in which the CSAT grade changes. Through this, the learner can be induced to make more mistakes by raising awareness and vigilance.

If any one of the incorrect answers and the same difficulty level are changed to the correct answer, it may include a step of setting the influence to 70% when the grade is changed. It is similar to the above example, but in this case, it is a problem of the same class, and the probability of being wrong may be higher than that of an easy problem. However, since the difficulty of the problem is the same for the two incorrect answers selected, it can give information to the learner that they can get both correct if they do not make a mistake. Through this process, it is possible to instill awareness in the learner and provide problems that should not be wrong, so that they do not make more mistakes in practice.

If any one of the incorrect answers and a higher difficulty question are changed to a correct answer, the influence is set to 60% when the grade changes. can be set. In other words, if the CSAT grade can be changed by solving one more difficult problem with a low correct rate, it is not without influence, but it can be excluded from the problem that should not be wrong. In other words, in this case, it can give information that the correct strategy is to focus more on other problems rather than spending time on solving the problems in the SAT grade selected by the learner. In addition, if the CSAT grade changes only by solving one or more incorrect questions and two or more questions, it is difficult to see that the learner's level is still at the boundary of the CSAT grade. can be reduced As a learner's level and ability rise, many problems with high influence appear, and accordingly, more efficient learning can be achieved by checking, setting, and managing these problems that learners must avoid.

The lecture providing server may store data including graphs and mathematical formulas shown on the blackboard by the instructor in the lecture data of the instructor transmitted from the first data unit as an image file, and provide it to each terminal. In other words, if the lecturer is consciously not aware and freely writes information about the theory and problem on the blackboard or board, the lecture providing server uses the image of the lecturer's lecture to provide more visible information to the learners based on these recorded data. It can be provided as a file.

In addition, by recognizing the lecturer's voice during the lecture, when the lecturer mentions a specific keyword, the problem or theory can be extracted and the problem can be re-edited as a main problem note. For example, if the lecturer naturally mentions previous questions or mentions that they are important during the lecture, they will be extracted. Through this, it induces learners to focus on the lecture during the lecture, and at the end of the lecture, by providing information according to the specific keyword mentioned by the lecturer during the lecture, it is possible to take the lecture in a more three-dimensional way, and through this, the learner can take the lecture more efficiently lectures can be accepted.

Although the embodiments of the present invention have been described above, the spirit of the present invention is not limited to the embodiments presented herein, and those skilled in the art who understand the spirit of the present invention can add components, Other embodiments may be easily proposed by changes, deletions, additions, etc., but these will also fall within the scope of the present invention.

100: non-face-to-face learning system 10: first data unit
20: second data unit 30: lecture providing server
40: student data 50: terminal
60: third data unit

Claims (9)

A first data unit for storing lecture materials,
Immersion learning in a non-face-to-face learning system comprising a lecture providing server for re-editing the data by classifying and analyzing the data input from the first data unit, and a terminal for transmitting and receiving the data re-edited in the lecture providing server In a non-face-to-face learning method for

accessing the lecture providing server with the terminal;
providing a lecture from the lecture providing server;
stopping, by the terminal, execution of a program other than the program provided from the lecture providing server;

The first data unit,
Recognizing the graph and mathematical formula shown on the blackboard by the instructor as an image among the stored lecture materials of the lecturer, storing the recognized image as a file, and transmitting the stored image file to the lecture providing server to provide each terminal comprising the steps of

The lecture providing server,
allowing all learners registered in the lecture providing server to take a mock exam;
analyzing the correct rate of the taken mock test; and
Checking the correct rate of each problem of other learners according to the CSAT grade classification based on the student's SAT grade that has been previously entered in the terminal or wants to correspond to, and the learner by analyzing the learner's incorrect answer question in the mock exam categorizing the problems that should not be wrong, comprising the step of analyzing the influence of the incorrect answer question on the change in the CSAT grade of the learner in the CSAT grade selected by the student; and
Non-face-to-face learning method for immersion learning comprising the step of providing the classified problem through the terminal. delete delete delete delete delete delete delete delete

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