Image learning monitoring device and method

Abstract

Disclosed is an image learning monitoring device 100. The image learning monitoring device 100 may include: a communication unit 170 configured to receive a student's study video captured by a user terminal 200; and a score calculation unit 140 configured to calculate the student's self-directed learning score based on the study video received by the communication unit 170.

Description

[Technical field]

[0001] The present invention relates to an image learning monitoring device and method thereof, and more specifically, to an image learning monitoring device and method thereof that can enhance students' self-directed learning abilities, including correct learning attitudes, and cultivate correct academic habits so that they can concentrate better during study time. [Background technology]

[0002] Research has shown that the effects of the emphasis on grades and the competition for entrance exams extend all the way to the early years of elementary school, but from the perspective of many parents, the reality is that they rely heavily on private education, such as advanced learning through academies or private tutors, to ensure that their children do not fall behind in the competitive entrance exam race.

[0003] Such excessive private education has the problem that students lose their self-directed learning ability and interest in learning, which in the long term leads to a significant decline in academic achievement. In particular, in research data comparing the improvement in academic performance from private education and self-directed learning, private education showed an achievement result of 1.5%, while self-directed learning showed an achievement result of 4.6%. At the national level, the importance of self-directed learning is gradually being emphasized, with educational processes that strengthen self-directed learning being promoted, and educational methods for this type of self-directed learning have been researched and developed for a long time in educationally advanced countries such as Europe and the United States.

[0004] However, today's students spend a lot of time in mobile environments such as smartphones, which gradually reduces their ability to learn independently. They sit at their desks to study, but waste a lot of time on activities that are unrelated to self-directed learning, such as using their mobile phones, using social media with friends, or watching entertainment video content.

[0005] Therefore, there is a growing social need in the industry, especially in the education industry, for new types of learning monitoring devices, methods, and systems that can utilize smartphones, which have become an essential part of students' lives, to enhance students' self-directed learning abilities and cultivate good academic habits so that they can concentrate better during study time. Summary of the Invention [Problem to be solved by the invention]

[0006] The present invention has been made to solve the above-mentioned problems, and aims to provide an image learning monitoring device and method that can improve students' self-directed learning abilities through image learning monitoring and evaluation.

[0007] Another object of the present invention is to provide an image learning monitoring device and method that can improve a student's sustained learning attitude and academic ability by utilizing a self-directed learning score calculated based on the student's study video.

[0008] Another object of the present invention is to provide an image learning monitoring device and method that can provide a customized online / offline integrated teaching service along with online learning guidance to a student with relatively low self-directed learning ability, thereby enabling the student to develop a study habit and improve his / her self-directed learning ability.

[0009] Another object of the present invention is to provide an image learning monitoring device and method that can increase students' interest in an online self-directed learning management system by providing predetermined rewards to students who have excellent evaluation results in image learning monitoring.

[0010] The technical problems of the present invention are not limited to the technical problems mentioned above, and other technical problems not mentioned can be clearly understood by those skilled in the art from the following description. [Means for solving the problem]

[0011] To solve the above technical problems, an image learning monitoring device according to one embodiment of the present invention may include: a communication unit configured to receive a student's study video captured by a user terminal; and a score calculation unit configured to calculate the student's self-directed learning score based on the study video received by the communication unit.

[0012] The image learning monitoring device may further include an evaluation unit including an environment evaluation unit for evaluating a study environment of the student, and an attitude evaluation unit for evaluating a study attitude of the student.

[0013] The score calculation unit may be further configured to calculate the self-directed learning score using at least one of an assessment result by the environment assessment unit and an assessment result by the attitude assessment unit.

[0014] Moreover, the communication unit may be further configured to transmit the calculated self-directed learning score to at least one of a parent terminal and the user terminal.

[0015] In addition, an image learning monitoring system according to another embodiment of the present invention for solving the above technical problems may include: the image learning monitoring device; and a user terminal communicatively coupled to the image learning monitoring device.

[0016] In addition, an image learning monitoring method according to a further embodiment for solving the above technical problems may include a step of receiving a study video of a student taken by a user terminal; and a step of calculating a self-directed learning score of the student based on the received study video.

[0017] The image learning monitoring method may further include the steps of: evaluating the student's study environment; and evaluating the student's study attitude.

[0018] Also, the step of calculating the self-directed learning score of the student may include the step of calculating the self-directed learning score using at least one of the evaluation result of the study environment and the evaluation result of the study attitude.

[0019] The image learning monitoring method may further include transmitting the calculated self-directed learning score to at least one of a parent terminal and the user terminal.

[0020] Furthermore, the computer program for solving the above technical problem may be stored on a computer-readable recording medium so that the computer program can be combined with a hardware computer and perform the above method. Effect of the Invention

[0021] According to the image learning monitoring apparatus and method according to an embodiment of the present invention, students' self-directed learning ability can be improved through image learning monitoring and evaluation.

[0022] In addition, according to an embodiment of the present invention, the image learning monitoring device and method thereof can improve a student's sustained learning attitude and academic ability by utilizing a self-directed learning score calculated based on the student's study video.

[0023] In addition, according to an embodiment of the present invention, the image learning monitoring device and method thereof can provide a customized online / offline integrated teaching service along with online learning guidance to a student with relatively low self-directed learning ability, thereby enabling the student to develop a study habit and improve his / her self-directed learning ability.

[0024] In addition, according to the image learning monitoring device and method according to an embodiment of the present invention, it is possible to increase students' interest in the online self-directed learning management system by providing predetermined rewards to students who have excellent evaluation results in image learning monitoring.

[0025] In order to more fully understand the drawings referred to in the detailed description of the invention, a brief description of each of the drawings is provided. [Brief description of the drawings]

[0026] [Figure 1a] FIG. 1 is a schematic block diagram of an image learning monitoring system 1000 according to an embodiment of the present invention. [Figure 1b] FIG. 1 is a schematic block diagram of an image learning monitoring system 1000 according to an embodiment of the present invention. [Figure 1c] FIG. 2 is a detailed block diagram of an evaluation unit 130. [Diagram 2] 1A is an exemplary diagram for explaining how to shoot a student's study video according to one embodiment of the present invention, and FIG. 1B and FIG. 1C are exemplary diagrams for explaining various interfaces through which a student's study video can be viewed on the image learning monitoring device 100 side according to one embodiment of the present invention. [Diagram 3] 2 is a flowchart illustrating an image learning monitoring method (S300) according to an embodiment of the present invention. [Figure 4] FIG. 10 is a schematic block diagram of an image learning monitoring system 1000' according to a further embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0027] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. When adding reference numerals to components in each drawing, it should be noted that the same components are denoted with the same numerals as much as possible even if they are displayed in different drawings. In addition, in describing the embodiments of the present invention, if a detailed description of related known configurations or functions is determined to hinder understanding of the embodiments of the present invention, the detailed description will be omitted. In addition, although the embodiments of the present invention will be described below, the technical idea of ​​the present invention is not limited or restricted thereto, and can be modified and variously implemented by those skilled in the art.

[0028] Throughout the specification, when a part is said to be "connected" to another part, this includes not only the case where the part is "directly connected" to another part, but also the case where the part is "indirectly connected" to another part through another element therebetween. Throughout the specification, when a part is said to "include" another component, this means that the part may further include the other component, not excluding the other component, unless otherwise specified. In addition, terms such as first, second, A, B, (a), and (b) may be used to describe the components of the embodiment of the present invention. These terms are used only to distinguish the component from other components, and do not limit the essence, order, or sequence of the components.

[0029] 1a and 1b are schematic block diagrams of an image learning monitoring system 1000 according to an embodiment of the present invention, and FIG. 1c is a detailed block diagram of an evaluator 130. As shown in FIG.

[0030] As shown in FIG. 1a, an image learning monitoring system 1000 according to an embodiment of the present invention may include an image learning monitoring device 100 and a user terminal 200.

[0031] For reference, a service for improving online self-directed learning ability can be installed in the user terminal 200 in the form of an application (also referred to as an "app" or "app") and provided to users, including students. In the following specification, for convenience, an application that provides such a self-directed learning service to users will be referred to as an "image learning monitoring application."

[0032] The image learning monitoring device 100 according to an embodiment of the present invention is a device for managing and operating an image learning monitoring application, and may be embodied as an application server, for example. As shown in Fig. 1a, the image learning monitoring device 100 according to an embodiment of the present invention may include a control unit 110, an input unit 120, an evaluation unit 130, a score calculation unit 140, a feedback unit 150, a matching unit 160, a communication unit 170, a storage unit 180, a notification unit 190, etc.

[0033] For reference, the components 110, 120, 130, 140, 150, 160, 170, 180, and 190 of the image learning monitoring device 100 shown in FIG. 1a are merely exemplary components for explaining the operation, functions, etc. of the image learning monitoring device 100 according to one embodiment of the present invention, and therefore it is apparent that the image learning monitoring device 100 according to one embodiment of the present invention may further include other components (e.g., a power supply unit, a display unit, an output unit, etc.) other than the illustrated components 110, 120, 130, 140, 150, 160, 170, 180, and 190.

[0034] In addition, the image learning monitoring device 100 according to one embodiment of the present invention corresponds to a proprietary computer program-based device produced and operated by an individual or private company, and is referred to by various terms such as device, equipment, server, platform, etc. depending on various expression methods in the related technical field.

[0035] For example, the visual learning monitoring device 100 according to an embodiment of the present invention can receive a video of a student captured by a user terminal 200 in real time and calculate a self-directed learning score of the student based on the video. For this purpose, the visual learning monitoring device 100 can be embodied as an application type or a widget type, and a widget may include a mini-application that allows content or functions to be used immediately without going through an application. Therefore, in the following specification, the term "application" can be interpreted as a comprehensive concept including a widget, and a user can download a visual learning monitoring application operated and managed by the visual learning monitoring device 100 according to the present invention from an online market, etc., and install and use the application on the user terminal 200.

[0036] A user (e.g., a student) of the user terminal 200 can download and install an image learning monitoring application from an online market, etc., where the user can further go through a procedure to subscribe to the application service, and if the application service is operated on a paid basis, a payment procedure for the fee (e.g., 10,000 won / month, 20,000 won / month, etc.) can be involved, and for this purpose, further communication with a payment server (not shown) can also be implemented.

[0037] The input unit 120 of the image learning monitoring device 100 according to an embodiment of the present invention may provide an input interface through which the user terminal 200 can input a study plan, for example, a study time. The user terminal 200 can input a study time (for example, 10:00 pm to 11:00 pm) through the input unit 120, and the input study time is stored in the memory unit 180 by user category and can be used for evaluation by the evaluation unit 130 and for notification by the notification unit 190.

[0038] In the following specification, study time is described as a representative example of a study plan input by the user via input unit 120, but according to a further embodiment of the present invention, an interface can be further provided that allows the user to further input study subjects (e.g., mathematics), study materials (e.g., mathematical formulas), study scope (e.g., pages 103 to 107), etc. in addition to study time.

[0039] For reference, the input of the study time of the user terminal 200 through the input unit 120 may be (i) input individually every day, (ii) input as a fixed time during a predetermined period (e.g., 10:00-11:00 PM every day from December 20th to 31st), or (iii) input as a variable time depending on the day of the week (e.g., 10:00-11:00 PM Monday-Friday, 2:00-3:00 PM Saturday-Sunday), but these are merely examples for easy understanding of the present invention, and therefore the present invention is not limited to such a study time input method. The image learning monitoring device 100 according to the present invention can be a so-called study planner for the student's study time input in this way, and can register and manage the study time, and for example, it can be confirmed by using a score table, graph, etc. by date whether the self-directed learning score by date is gradually improving as targeted, or there is no particular improvement, or rather whether the self-directed learning score is decreasing.

[0040] Furthermore, the input unit 120 of the image learning monitoring device 100 according to an embodiment of the present invention may further construct an interface that allows a student to input a changed study time for a previously input study time. For example, if a student has registered a study time from 10:00 to 11:00 p.m., but another schedule inevitably occurs during that time, the student can execute an image learning monitoring application and input a changed study time (e.g., 8:00 to 9:00 p.m. on the current day, or 9:00 to 11:00 a.m. the next day, etc.) via the input unit 120. Here, the image learning monitoring system 1000 may be embodied such that the change in study time is operated on the condition of confirmation from the parent terminal 300 (see FIG. 4).

[0041] Alternatively, the control unit 110 of the image learning monitoring device 100 according to a further embodiment of the present invention may be configured to suggest a customized study time to the user terminal 200 based on the user information stored in the storage unit 180 and / or based on the accumulated learning results of such user information. For example, the user terminal 200 may input user information, such as a student's school arrival time, school departure time, school time, after-school schedule, weekend schedule, etc., via the input unit 120, and the control unit 110 may suggest a customized study time to the user terminal 200 based on such user information, the evaluation result by the evaluation unit 130, the self-directed learning score calculated by the score calculation unit 140, etc. For example, the control unit 110 may statistically analyze a time when the self-directed learning score is relatively high, and by suggesting the analyzed study time to the user terminal 200 or the parent terminal 300, it is possible to improve the student's study efficiency as well as to make the user or parent more interested in studying.

[0042] When the user terminal 200 registers the student's study time and executes the image learning monitoring application on the user terminal 200, the student's study video captured by the user terminal 200 can be transmitted in real time to the image learning monitoring device 100 via the communication unit 170. For accurate and fair evaluation, particularly for AI-based image analysis, the method of capturing the study video (e.g., angle, arrangement, etc.) can be instructed to the user terminal 200 in advance via the image learning monitoring application. For example, as shown in FIG. 2(a), the student can be instructed to hold the user terminal 200 horizontally on the front or side of the desk so that the upper half of the student's body including the face and the teaching materials placed on the desk are clearly captured. If it is determined that the received image does not meet the predetermined requirements, the feedback unit 150 can request the user terminal 200 to rearrange the user terminal 200, adjust the angle, etc. by voice or text, and such an adjustment request by the feedback unit 150 can be continued until the shooting requirements are met.

[0043] Here, according to a further embodiment of the present invention, the student's study video captured by the user terminal 200 can be transmitted in real time not only to the image learning monitoring device 100 but also to the parent terminal 300, and the simultaneous transmission of such study video to the parent terminal 300 can be subject to, for example, the approval of an image learning monitoring manager, which has the advantage that the parent can easily check the child's learning attitude, situation, etc. even in a remote location without direct contact with the child. When the student's study video is also transmitted to the parent terminal 300, the notification unit 190 according to an embodiment of the present invention can provide the parent terminal 300 with a notification to start studying before the study time, for example, about 10 minutes before.

[0044] The evaluation unit 130 of the image learning monitoring device 100 may be configured to evaluate the study environment and study attitude of the student based on the study video received from the user terminal 200 via the communication unit 170. To this end, as shown in FIG. 1c, the evaluation unit 130 may be composed of an environment evaluation unit 131 and an attitude evaluation unit 132.

[0045] The environment evaluation unit 131 can evaluate the study environment before the student starts studying, and the evaluation of the study environment may include at least an evaluation of the presence or absence of a timely connection. For example, if a student registers a study time from 10:00 to 11:00 p.m., the environment evaluation unit 131 can determine whether the user terminal 200 of the student executed an image learning monitoring application at 10:00 p.m. or a few minutes before and connected to the image learning monitoring device 100. For this purpose, the image learning monitoring device 100 according to an embodiment of the present invention can inform the user terminal 200 of the remote connection conditions to the image learning monitoring system a predetermined time before the registered study time, for example, 10 minutes before, and the user terminal 200 can connect to the image learning monitoring device 100 according to the informed remote connection conditions, for example, by utilizing the image learning monitoring application.

[0046] If the environment evaluation unit 131 evaluates that the user terminal 200 connected in a timely manner, this acts as a positive factor when the score calculation unit 140 calculates the self-directed learning score, whereas if the environment evaluation unit 131 evaluates that the user terminal 200 did not connect in a timely manner, for example, if the user terminal 200 connected to the system 20 minutes late, this can act as a negative factor when the score calculation unit 140 calculates the self-directed learning score. In particular, if the user terminal 200 does not connect at all during the registered study time, the evaluation by the evaluation unit 130 and the score by the score calculation unit 140 can be all zero-point processed, and the fact of such non-connection and the zero-point score can be immediately notified to the parent terminal 300 and / or the user terminal 200.

[0047] In addition to or as an alternative to the evaluation of the timely connection, the environment evaluation unit 131 according to an embodiment of the present invention may evaluate whether the surrounding environment of the student is suitable for studying based on the study video received in real time from the user terminal 200. For example, the environment evaluation unit 131 may evaluate from the captured video based on artificial intelligence (AI) whether teaching materials, writing implements, etc. are prepared on the desk, whether other objects that interfere with studying (e.g., portable game consoles, toys, etc.) are placed on the desk, whether the lighting illuminance of the study environment is appropriate, etc., and the storage unit 180 may store reference video (or images) of teaching materials, tablets, etc., reference video (or images) of lighting illuminance, related image data, etc. for such AI learning and evaluation.

[0048] The attitude evaluation unit 132 can evaluate the student's study attitude by utilizing artificial intelligence (AI) based on the video information during the registered study time. For example, the attitude evaluation unit 132 can evaluate the student's study attitude by comprehensively judging whether the student keeps sitting during the registered study time, whether the student is absent (or leaves) during the study time, whether the student falls asleep while lying face down, whether the student takes a twisted posture, etc., and can further store reference information such as reference video and images, reference values, etc. for various situations that the student can take during the study time, such as sitting, absent (or leaves), and falling asleep, in the storage unit 180 for such AI learning and evaluation.

[0049] Here, in order to immediately satisfy the needs of a student who wants to study beyond the already entered study time during or before starting studying, the image learning monitoring application according to a further embodiment of the present invention can monitor the study by increasing the time in the student's pre-registered study schedule when the student studies beyond the study time. Therefore, the student can further increase the study time at any time before starting or during studying, and such a request for an increase in study time can be notified to the parent terminal 300 in real time, and the attitude evaluation unit 132 and the score calculation unit 140 can consider the request for an increase in study time received from the user terminal 200 as a positive factor in attitude evaluation and in self-directed learning score calculation.

[0050] Similarly, the image learning monitoring application may further include an interface that allows a student to request to stop studying in the middle of studying. When a situation arises in which a student is forced to stop studying in the middle of studying, the control unit 110 may be configured to add the remaining time caused by the interruption to future study time (e.g., the next day or a date entered by the student), or to register a separate study time in the schedule and set and save the study time in the schedule so that further study is conducted according to the time registered in the schedule.

[0051] When the evaluation by the evaluation unit 130, more specifically, the evaluation of the study environment by the environment evaluation unit 131 and the evaluation of the study attitude by the attitude evaluation unit 132 are completed, the score calculation unit 140 of the image learning monitoring device 100 according to an embodiment of the present invention can calculate a self-directed learning score based on at least one of the environment evaluation and the attitude evaluation evaluated by the evaluation unit 130. For example, the self-directed learning score can be set to a maximum of 100 points, and can be scored as a specific numerical value by comprehensively evaluating the presence or absence of timely connection, the study environment before starting to study, the study preparation state, the study attitude during the study time, etc., and the scoring of the self-directed learning environment and attitude can be automatically implemented using AI-based learning.

[0052] Here, when the study time registered by the user terminal 200 exceeds one hour, that is, when the student registers the study time exceeding one hour, the image learning monitoring device 100 according to a further embodiment of the present invention can set a break time, for example, approximately the middle time of the study time, in the middle of the study time and notify it to the user terminal 200 and / or the parent terminal 300, and the set break time may be about 10 to 20 minutes, and the image learning monitoring system 1000 can be embodied so that the evaluation of the study attitude by the attitude evaluation unit 132 and the calculation of the self-directed learning score by the score calculation unit 140 are not performed during the notified break time. Here, the maximum study time (for example, 4 hours, etc.) that the user terminal 200 can register in one day can be set in advance, and the study time entered exceeding the set maximum study time can be corrected to the value of the set maximum study time and returned to the user terminal 200 and / or the parent terminal 300.

[0053] For reference, the self-directed learning score calculated by the score calculation unit 140 may be implemented as a score based on an environmental assessment and a score based on an attitude assessment, respectively, or as a single score combining the score based on an environmental assessment and the score based on an attitude assessment (e.g., a score obtained by averaging two items, a score obtained by applying different weights to two items, etc.), but the method of evaluating the self-directed learning score according to one embodiment of the present invention is not limited thereto.

[0054] In addition, the feedback unit 150 of the image learning monitoring device 100 may provide feedback to the user terminal 200 in real time during the registered study time based on artificial intelligence (AI). For example, the feedback unit 150 may provide appropriate feedback to the user terminal 200 for a situation in which a student is not concentrating on studying and is falling asleep, a situation in which a student is absent from his / her desk and the absence time exceeds a preset time (e.g., 3 minutes) by analyzing the captured image information received from the user terminal 200 based on AI. For example, the feedback provided to the user terminal 200 may be embodied in voice (or sound / notification), text, video, a combination of voice / text / video, etc. Of course, when a student adheres to self-directed learning, the feedback unit 150 may actively encourage the student's interest in correct study habits by providing positive feedback.

[0055] The evaluation operations by the above-mentioned environment evaluation unit 131 and attitude evaluation unit 132 or the feedback providing operation by the feedback unit 150 can be implemented using AI based on video information analysis, and here, the operator (also called a "master" or "tutor") of the image learning monitoring device 100 can also assist in the evaluation operation of the evaluation unit 130 or the feedback operation of the feedback unit 150.

[0056] According to the image learning monitoring system 1000 as exemplarily shown in Fig. 1a, a single user terminal 200 can be connected to the image learning monitoring device 100 and receive an image learning monitoring service, and an interface through which such one-to-one learning monitoring video is viewed on the image learning monitoring device 100 side is exemplarily shown in Fig. 2(b). As shown in Fig. 2(b), the image learning monitoring device 100 monitors only the study video received from the single user terminal 200 on a one-to-one basis, which enables more focused and specialized learning monitoring and online learning guidance.

[0057] Furthermore, according to the image learning monitoring system 1000 as illustrated in FIG. 1b, multiple user terminals 200-1, 200-2, ..., 200-N (where N is a natural number greater than or equal to 2) can connect to the image learning monitoring device 100 and receive the image learning monitoring service, and an interface through which such one-to-many learning monitoring video can be viewed on the image learning monitoring device 100 side is illustrated in FIG. 2(c) as an example.

[0058] In the example of (c) of Fig. 2, the feedback unit 150 may be configured to communicate (e.g., dialogue, chat, etc.) one-to-one with only one selected user terminal 200 among the multiple user terminals 200 connected to the image learning monitoring device 100, and the content of the one-to-one communication is not transmitted to the other unselected user terminals 200, so that targeted or customized feedback can be provided to a specific student or specific students even in a one-to-many learning monitoring environment. For example, the one-to-one customized feedback provided to the user terminal 200 may include at least content related to online learning instruction.

[0059] Furthermore, according to other embodiments of the present invention, the feedback unit 150 may be configured to communicate with all of the multiple user terminals 200 simultaneously (e.g., for public notice), and for this purpose, the image learning monitoring device 100 may further be provided with a mode switching interface capable of switching between one-to-one communication mode and one-to-many communication mode.

[0060] For reference, as shown in Fig. 1b and Fig. 2(c), when a plurality of user terminals 200 are simultaneously connected to the image learning monitoring device 100 and an image learning monitoring service is provided, the display of each of the plurality of user terminals 200 may display only the image of the user, or may display at least one other student's image together. For this purpose, an interface that allows a non-display mode of the other students' study images and a display mode of the other students' study images to be selected may be provided to the user terminal 200 via the image learning monitoring application, and thus, each student may select whether or not to display images of other students who are currently studying at the same time as him / her according to his / her preference.

[0061] In particular, in the latter case, by displaying the study videos of other students studying at the same time on the user terminal 200, not only can the student visually confirm the learning attitude of the other students, but also further stimulate the student's motivation for self-directed study. Here, the other students displayed on the user terminal 200 may be a randomly selected part of the multiple students who connected to the image learning monitoring device 100 at the same time, or may be students or a part of students grouped based on the user's age (grade), sex, area, school, score, etc.

[0062] In connection with the calculation of the self-directed learning score by the score calculation unit 140 according to an embodiment of the present invention, a standard score (e.g., 50 points, etc.) for customized online / offline joint instruction may be preset. For example, if the self-directed learning score calculated by the score calculation unit 140 does not reach the standard score, or if the average of the self-directed learning scores for a certain period (e.g., one week, etc.) does not reach the standard score, the matching unit 160 according to an embodiment of the present invention may match the student with a tutor who can provide customized online / offline joint instruction, or the control unit 110 may provide additional (or supplementary) study time with reference to the student's schedule and provide it to the user terminal 200 and / or parent terminal 300, thereby providing additional time for the student to improve his / her self-directed learning ability.

[0063] The matching unit 160 may perform customized matching of students and tutors based on information about students and information about registered tutors stored in the storage unit 180, and may provide the matched information to the user terminal 200, the parent terminal 300, the tutor terminal 400 (see FIG. 4), and the like. For reference, the tutor terminal 400 may be communicatively coupled to the image learning monitoring device 100 according to an embodiment of the present invention, and the term "tutor" used in the following specification may refer to a specialized teacher who is able to provide instruction on a specific subject as well as self-directed learning not only online but also offline, i.e., face-to-face instruction with a student.

[0064] The communication unit 170 may be configured to communicate with the user terminal 200, the parent terminal 300, the tutor terminal 400, a payment server (not shown), etc. For example, the self-directed learning score of the student calculated by the score calculation unit 140 may be transmitted to at least one of the user terminal 200 of the student and the parent terminal 300 of the student via the communication unit 170, and the student-tutor matching information performed by the matching unit 160 for a student who has a score below the standard may be transmitted to at least one of the user terminal 200 of the student, the parent terminal of the student, and the tutor terminal 400 of the matched teacher via the communication unit 170.

[0065] For reference, the communication unit 170 is provided for direct connection to the outside or connection via a network, and may be a wired and / or wireless communication unit 170. Specifically, the communication unit 170 transmits data from the control unit 110, the input unit 120, the evaluation unit 130, the score calculation unit 140, the feedback unit 150, the matching unit 160, the notification unit 190, etc., via a wired or wireless connection, or receives data from the outside, via a wired or wireless connection, and transmits it to the control unit 110, the input unit 120, the evaluation unit 130, the score calculation unit 140, the feedback unit 150, the matching unit 160, the notification unit 190, or stores it in the memory unit 180. The data may include contents such as text, images, and videos.

[0066] The communication unit 170 may communicate via LAN, Wideband Code Division Multiple Access (WCDMA), Long Term Evolution (LTE), Wireless Broadband Internet (WiBro), Radio Frequency (RF) communication, Wireless LAN, Wireless Fidelity, Near Field Communication (NFC), Bluetooth, infrared communication, etc. However, this is merely an example, and various wired and wireless communication technologies applicable in the art may be used depending on the embodiment to which the present invention is applied.

[0067] The storage unit 180 may store any data related to the image learning monitoring device 100, image learning monitoring system 1000, and image learning monitoring service according to an embodiment of the present invention. For example, the data stored in the storage unit 180 may include, but is not limited to, data related to an image learning monitoring application, data related to user information, data related to registered study time, data related to filmed study videos, data related to environmental evaluation results, data related to attitude evaluation results, data related to self-directed learning scores, data related to artificial intelligence algorithms for real-time feedback coaching, and data related to student-tutor matching.

[0068] For reference, the storage unit 180 may be implemented as various types of storage devices capable of inputting and outputting information, such as a hard disk drive (HDD), a read only memory (ROM), a random access memory (RAM), an electrically erasable and programmable read only memory (EEPROM), a flash memory, a compact flash (CF) card, a secure digital (SD) card, a smart media (SM) card, a multimedia (MMC) card, or a memory stick, as known to ordinary skilled artisans, and may be provided inside the image learning monitoring device 100 as shown in Fig. 1, or may be provided in a separate external device. Alternatively, the storage unit 180 may be replaced by a web storage that performs a storage function on the Internet.

[0069] Furthermore, although not explicitly shown in the block diagram of FIG. 1, the image learning monitoring device 100 according to an embodiment of the present invention may further include a display unit (not shown), and may display a video of a student through the display unit, for example, as shown in (b) and (c) of FIG. 2. The display unit may display various information processed by the image learning monitoring device 100 through a display means, and the display means may include at least one of a liquid crystal display (LCD), a thin film transistor-liquid crystal display (TFT LCD), an organic light-emitting diode (OLED), a flexible display, and a three-dimensional display.

[0070] The notification unit 190 can provide various types of notifications to the user terminal 200. For example, for a user terminal 200 that has registered 10:00 PM to 11:00 PM as the study time, the notification unit 190 can provide a predetermined notification to the user terminal 200 in advance (for example, 9:50 PM, etc.), and can also provide a predetermined notification to the parent terminal 300 in advance, thereby significantly improving the convenience and satisfaction of users who are provided with this image learning monitoring service.

[0071] The control unit 110 may generally control the operation of the image learning monitoring device 100 according to an embodiment of the present invention. For example, the control unit 110 may be embodied as a processor, a controller, a micro-processor, a micro-controller, etc. That is, the control unit 110 may operate at least one or more components included in the image learning monitoring device 100 in combination with each other to drive an application program.

[0072] The user terminal 200 can be communicatively coupled to the image learning monitoring device 100, and as described above, a one-to-one learning monitoring environment may be constructed as shown in Fig. 1a and Fig. 2(b), or a one-to-many learning monitoring environment may be constructed as shown in Fig. 1b and Fig. 2(c). In this specification, the user of the user terminal 200 is described as a student who wants to improve his / her self-directed learning ability, but it goes without saying that the user of the user terminal 200 may also include ordinary people who want to cultivate a self-directed attitude and behavior.

[0073] In addition, although this specification describes a service in which the image learning monitoring device 100 monitors a user's autonomous learning as a representative example, it is clear that the image learning monitoring device 100 and image learning monitoring system 1000 can also be applied to various activities other than studying that can cultivate self-directed lifestyle habits, such as reading, writing, speaking a foreign language, home training, cooking, and hobbies, and various types of content to support services for such various activities can also be stored in the memory unit 180.

[0074] For reference, user terminal 200 may also be referred to as a subscriber unit, subscriber station, mobile station, mobile terminal, remote station, remote terminal, mobile device, access terminal, terminal, wireless communication device, user agent, user device, or user equipment (UE). An access terminal may be a cellular telephone, a cordless telephone, a Session Initiation Protocol (SIP) telephone, a Wireless Local Loop (WLL) station, a Personal Digital Assistant (PDA), a handheld device with wireless connectivity capabilities, a computing device, or other processing device connected to a wireless modem.

[0075] FIG. 3 is a flow chart illustrating an image learning monitoring method (S300) according to an embodiment of the present invention.

[0076] First, the user terminal 200, which has downloaded and installed an image learning monitoring application via an online market or the like, can register the study time via the input unit 120 (S310). The study time registered via the input unit 120 is stored in the storage unit 180 and can be used for evaluation by the evaluation unit 130, calculation of the self-directed learning score by the score calculation unit 140, notification by the notification unit 190, and the like.

[0077] When the input unit 120 inputs the student's study time (for example, 10:00 pm to 11:00 pm), the environment evaluation unit 131 of the evaluation unit 130 can determine whether the user terminal 200 is connected in a timely manner (S320). As already described, for a student who is determined to have connected in a timely manner, this acts as a positive factor for the self-directed learning score, and for a student who is not determined to have connected in a timely manner, this acts as a negative factor for the self-directed learning score.

[0078] The presence or absence of a timely connection is determined, and when the registered study time arrives, the student's study video captured by the user terminal 200 can be received in real time via the communication unit 170 (S330). In a one-to-one learning monitoring environment, as shown in FIG. 2(b), the student's study video is displayed on the image learning monitoring device 100 side, whereas in a one-to-many learning monitoring environment, as shown in FIG. 2(c), a plurality of study videos may be displayed on the image learning monitoring device 100 side, and the user terminal 200 side can select a display mode so that the study videos of other students may or may not be displayed together, as described above.

[0079] The environmental evaluation unit 131 can evaluate the study environment (S340), the attitude evaluation unit 132 can evaluate the study attitude (S350), and the score calculation unit 140 can calculate a self-directed learning score based on the evaluation result of the study environment by the environmental evaluation unit 131 and / or the evaluation result of the study attitude by the attitude evaluation unit 132 (S360).

[0080] When the self-directed learning score is calculated, the communication unit 170 can transmit the calculated self-directed learning score to at least one of the user terminal 200 and the parent terminal 300 (S370), and the matching unit 160 can provide customized online / offline collaborative instruction by performing student-tutor matching for students who have a self-directed learning score below the reference score (S380). For reference, the image learning monitoring system 1000 according to an embodiment of the present invention can further include a regional educational location for offline collaborative instruction, and can assist the matched student and tutor to meet at the educational location to proceed with offline learning instruction.

[0081] Furthermore, according to another embodiment of the present invention, a predetermined reward may be provided to a student who has an excellent self-directed learning score. For example, the reward provided to an excellent student may include, but is not limited to, a discount / waiver on service fees, point accumulation, etc.

[0082] In addition to transmitting the calculated self-directed learning score to the user terminal 200 and / or parent terminal 300, the image learning monitoring device 100 according to a further embodiment of the present invention can further transmit specific items related to items such as the environment evaluation results and attitude evaluation results evaluated by the evaluation unit 130, and online learning guidance provided by the feedback unit 150 to the user terminal 200 and / or parent terminal 300.

[0083] FIG. 4 is a schematic block diagram of an image learning monitoring system 1000' according to a further embodiment of the present invention.

[0084] As described above, the self-directed learning score calculated by the score calculation unit 140 of the image learning monitoring device 100 according to one embodiment of the present invention can be transmitted to the parent terminal 300 via the communication unit 170, and for this purpose, the image learning monitoring system 1000' according to a further embodiment of the present invention may further include a parent terminal 300 communicatively coupled to the image learning monitoring device 100 and the user terminal 200.

[0085] In addition, the matching unit 160 of the image learning monitoring device 100 according to one embodiment of the present invention may provide customized online / offline collaborative teaching services by performing student-tutor matching for students who have self-directed learning scores below a standard score, and for this purpose, the image learning monitoring system 1000' according to a further embodiment of the present invention may further include a tutor terminal 400 communicatively coupled to the image learning monitoring device 100.

[0086] For reference, the parent terminal 300 and the tutor terminal 400 may also be referred to as subscriber units, subscriber stations, mobile stations, mobile terminals, remote stations, remote terminals, mobile devices, access terminals, terminals, wireless communication devices, user agents, user devices or user equipment (UE). Although FIG. 4 illustrates an example of a single parent terminal 300 and a single tutor terminal 400, it will be apparent that multiple parent terminals 300 and multiple tutor terminals 400 may be provided.

[0087] As described above, the image learning monitoring apparatus and method according to an embodiment of the present invention can improve students' self-directed learning ability through image learning monitoring and evaluation.

[0088] In addition, according to an embodiment of the present invention, the image learning monitoring device and method thereof can improve a student's sustained learning attitude and academic ability by utilizing a self-directed learning score calculated based on the student's study video.

[0089] In addition, according to an embodiment of the present invention, the image learning monitoring device and method thereof can provide a customized online / offline integrated teaching service along with online learning guidance to a student with relatively low self-directed learning ability, thereby enabling the student to develop a study habit and improve his / her self-directed learning ability.

[0090] In addition, according to the image learning monitoring device and method according to an embodiment of the present invention, it is possible to increase students' interest in the online self-directed learning management system by providing predetermined rewards to students who have excellent evaluation results in image learning monitoring.

[0091] It should be noted that various embodiments described herein may be implemented in hardware, middleware, microcode, software, and / or combinations thereof. For example, various embodiments may be implemented as one or more custom application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processor devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, other electronic units designed to perform the functions presented herein, or combinations thereof.

[0092] Further, for example, various embodiments may be stored or encoded on a computer-readable medium that includes instructions. The instructions stored or encoded on the computer-readable medium may cause a programmable processor or other processor to perform a method, for example, when the instructions are executed. Computer-readable media includes computer storage media, which may be any available medium that can be accessed by a computer. For example, such computer-readable media may include RAM, ROM, EEPROM, CD-ROM or other optical disk storage media, magnetic disk storage media or other magnetic storage devices.

[0093] Such hardware, software, firmware, etc. may be embodied within the same device or within separate devices to support the various operations and functions described herein. Additionally, components, units, modules, components, etc. described as "parts" in the present invention may be embodied together or separately as separate but interoperable logic devices. The depiction of different characteristics for modules, units, etc. is intended to highlight different functional embodiments and does not necessarily mean that they must be realized by separate hardware or software components. Rather, functionality associated with one or more modules or units may be performed by separate hardware or software components or integrated within a common or separate hardware or software component.

[0094] Although operations are shown in the figures in a particular order, it should not be understood that these operations must be performed in the particular order or sequential order shown, or that all of the operations shown must be performed, to achieve desired results. In certain environments, multitasking and parallel processing may be advantageous. It should be understood that the partitioning of various components in the above-described embodiments should not be understood to require such partitioning in all embodiments, and that the components described may generally be integrated into a single software product or packaged into multiple software products.

[0095] As described above, the drawings and the specification disclose the best mode for carrying out the present invention. Although specific terms are used herein, they are used merely for the purpose of describing the present invention, and are not used to limit the meaning or the scope of the present invention described in the claims. Therefore, a person having ordinary skill in the art will understand that various modifications and equivalent other embodiments are possible. Therefore, the true technical scope of protection of the present invention must be determined by the technical ideas of the appended claims. [Explanation of symbols]

[0096] 100 Image learning monitoring device 110 Control section 120 Input section 130 Evaluation Department 131 Environmental Assessment Unit 132 Attitude Assessment Unit 140 Score Calculation Section 150 Feedback section 160 Matching Section 170 Communications Department 180 Storage section 190 Notification Department 200 User terminals 300 Parent terminal 400 Tutor Terminal 1000, 1000' Image Learning Monitoring System

Claims

1. An image learning monitoring device 100, A communication unit 170 configured to receive a student's study video captured by the user terminal 200; and a score calculation unit configured to calculate a self-directed learning score of the student based on the study video received by the communication unit.

2. The image learning monitoring device 100 according to claim 1, further comprising an evaluation section 130, which is composed of an environment evaluation unit 131 for evaluating the student's study environment, and an attitude evaluation unit 132 for evaluating the student's study attitude.

3. The image learning monitoring device 100 of claim 2 , wherein the score calculation unit 140 is further configured to calculate the self-directed learning score using at least one of the evaluation results by the environment evaluation unit 131 and the evaluation results by the attitude evaluation unit 132 .

4. The image learning monitoring device (100) of claim 1, wherein the communication unit (170) is further configured to transmit the calculated self-directed learning score to at least one of a parent terminal (300) and the user terminal (200).

5. An image learning monitoring device 100 according to any one of claims 1 to 4; An image learning monitoring system 1000 including: a user terminal 200 communicatively coupled to the image learning monitoring device 100.

6. 1. An image learning monitoring method, comprising: receiving a student's study video captured by a user terminal; and calculating a self-directed learning score of the student based on the received study video.

7. evaluating the student's learning environment; The image learning monitoring method according to claim 6, further comprising: evaluating the student's study attitude.

8. The image learning monitoring method of claim 7, wherein the step of calculating the student's self-directed learning score includes a step of calculating the self-directed learning score using at least one of the evaluation results of the study environment and the evaluation results of the study attitude.

9. The image learning monitoring method of claim 6 , further comprising transmitting the calculated self-directed learning score to at least one of a parent terminal and the user terminal.

10. A computer program stored on a computer-readable recording medium so as to be coupled with a hardware computer and to perform the method according to any one of claims 6 to 9.

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