Computer programs for supporting online classes

Abstract

To transmit information that supports classes on an instructor's behalf when the instructor is busy, in online classes.SOLUTION: A computer program for supporting online classes causes a computer to implement the following functions: a first function of obtaining first information including at least one of operation history information of a student in the online class and video data taken of the student; a second function of evaluating the student's learning state using the first information; a third function of obtaining third information including at least one of operation history information of an instructor in the online class and video data taken of the instructor; a fourth function of evaluating the busyness of the instructor using the third information; and a fifth function of sending fifth information including information for supporting learning to the student according to the student's learning state and the busyness of the instructor.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present disclosure relates to a computer program for supporting online classes. [Background technology]

[0002] In online classes, various technologies have been proposed to support classes according to the learning status of students. For example, Patent Document 1 discloses a technology that determines the learning status of a student based on information about the student's behavior acquired from the student's terminal device, and presents information to the instructor to support the online class according to the learning status. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-25223 Summary of the Invention [Problem to be solved by the invention]

[0004] For example, when one instructor teaches a large number of students, while the instructor is teaching one student, the other students cannot receive instruction from the instructor. The technology in Patent Document 1 simply presents the instructor with information according to the students' learning status, but does not take into account the instructor's busy schedule, and there is a risk that it will not be able to provide sufficient support for online classes. For this reason, there is a demand for technology that supports online classes according to the instructor's busy schedule. [Means for solving the problem]

[0005] The present disclosure can be realized in the following forms. According to one embodiment of the present disclosure, there is provided a computer program for supporting online classes, the computer program causing a computer to implement: a first function for acquiring first information including at least one of operation history information of a student in the online class and video data of the student; a second function for evaluating the student's learning status using the first information; a third function for acquiring third information including at least one of operation history information of a lecturer in the online class and video data of the lecturer; a fourth function for evaluating the lecturer's busyness using the third information; and a fifth function for transmitting fifth information including information for supporting the student's learning depending on the student's learning status and the lecturer's busyness, wherein the first function further includes a function for acquiring the student's answers to exercise problems in the online class, the second function includes a function for evaluating the student's learning status by comparing the difference between the student's answers and correct answers to the exercise problems, and the fifth function includes a function for transmitting the fifth information depending on the student's learning status, the lecturer's busyness, and the difference.

[0006] (1) According to one aspect of the present disclosure, there is provided a computer program for supporting online classes, the program causing a computer to implement a first function of acquiring first information including at least one of operation history information of a student in the online class and video data of the student, a second function of evaluating the student's learning status using the first information, a third function of acquiring third information including at least one of operation history information of a lecturer in the online class and video data of the lecturer, a fourth function of evaluating the lecturer's busyness using the third information, and a fifth function of sending fifth information including information for supporting the student's learning depending on the student's learning status and the lecturer's busyness. According to this type of program, the fifth information is sent to the student based on the student's learning status evaluated using the first information and the instructor's busyness evaluated using the third information, thereby enabling support for online classes according to the instructor's busyness. (2) In the program of the above form, the first function further includes a function of obtaining the student's answer to the exercise problem in the online class, the second function includes a function of evaluating the student's learning status by comparing the difference between the student's answer and the correct answer to the exercise problem, and the fifth function includes a function of transmitting the fifth information depending on the student's learning status, the instructor's busyness, and the difference. According to this type of program, the fifth information is sent to the student depending on the student's learning status, the instructor's busyness, and the difference between the student's answer to the practice problem and the correct answer to the practice problem, so that the fifth information can be sent depending on the content of the student's answer to the practice problem. (3) In the program of the above form, the first function further includes a function of sending questions to the student via a chatbot to determine the student's level of understanding of the online class, and the second function includes a function of evaluating the student's learning status using the first information and the answer to the question to determine the student's level of understanding. This type of program evaluates the learning status of the student using the first information and the answers to the questions for identifying the level of understanding, and therefore can improve the accuracy of the evaluation of the learning status. (4) In the program of the above form, the computer further realizes a sixth function of sending the student at least one question to identify areas of lack of understanding in the online class using the chatbot, and identifying the student's areas of lack of understanding using the answer to the question to identify the areas of lack of understanding, and the fifth function includes a function of sending the fifth information further in accordance with the areas of lack of understanding. This type of program identifies the student's areas of lack of understanding by sending the student at least one question to identify the areas of lack of understanding, and then sends the fifth information according to the identified areas of lack of understanding, so that more appropriate fifth information can be sent to the student to improve their understanding of the areas of lack of understanding. The present disclosure can be realized in various forms, and in addition to a computer program, it can be realized in the form of, for example, a non-transitory recording medium on which the computer program is recorded, a method for supporting online classes, etc. [Brief explanation of the drawings]

[0007] [Figure 1] 1 is a block diagram showing a schematic configuration of an online class support system 1 according to an embodiment of the present disclosure. [Figure 2] 10 is a flowchart showing the procedure of a lesson support process in the first embodiment. [Figure 3] 10 is a flowchart showing the procedure of a lesson support process in the second embodiment. [Figure 4] 11 is a flowchart showing the procedure of a lesson support process in the third embodiment. [Figure 5] 13 is a flowchart showing the procedure of a lesson support process in the fourth embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0008] A. First embodiment: A1.Device configuration: FIG. 1 is a block diagram showing a schematic configuration of an online class support system 1 according to an embodiment of the present disclosure. In the present disclosure, the online class support system 1 is used when one instructor teaches one or more students online. In online classes, information is transmitted bidirectionally from the instructor to the students and from the students to the instructor via an internet line, wireless communication, etc. The online class support system 1 includes a student terminal 10, an instructor terminal 20, and a server 100.

[0009] The student terminal 10 and the instructor terminal 20 are, for example, smartphones, tablets, laptop computers, or desktop computers. In this disclosure, each student and instructor participating in an online class uses one terminal. In other words, if multiple students participate in an online class, the same number of student terminals 10 as the number of students are required. Because the basic configurations of the student terminal 10 and the instructor terminal 20 are the same, the following description will be given for both the student terminal 10 and the instructor terminal 20.

[0010] The student terminal 10 and the instructor terminal 20 each include a CPU (Central Processing Unit) 11, 21, memory 12, 22, operation reception units 13, 23, cameras 14, 24, display units 15, 25, microphones 16, 26, speakers 17, 27, and communication units 18, 28. The CPUs 11, 21, memory 12, 22, operation reception units 13, 23, cameras 14, 24, display units 15, 25, microphones 16, 26, speakers 17, 27, and communication units 18, 28 are configured to be able to communicate with each other via an internal bus.

[0011] The CPUs 11 and 21 are hardware for executing programs stored in the memories 12 and 22. The CPUs 11 and 21 are configured with a control device, an arithmetic unit, a register, peripheral circuits, and the like.

[0012] The memories 12 and 22 store programs for causing each unit of the student terminal 10 and the instructor terminal 20 to function.

[0013] The operation reception units 13 and 23 are devices that receive input operations from students or instructors to the terminals. The operation reception units 13 and 23 are, for example, touch panels, touch pads, mice, keyboards, etc. The input operations input to the operation reception units 13 and 23 are transmitted to the server 100 via the communication units 18 and 28 as operation history information.

[0014] The cameras 14 and 24 are devices that capture images of students or instructors and output the video data. The cameras 14 and 24 mainly capture the faces of the students or instructors. The captured video data is transmitted to the server 100 and other terminals via the communication units 18 and 28.

[0015] The display units 15 and 25 are configured by displays and display images of students or instructors captured by the cameras 14 and 24, as well as data such as text, images, and videos from online classes.

[0016] The microphones 16 and 26 are devices for inputting the voice of the student or the instructor into the terminal. The input voice is transmitted to the other terminal via the communication units 18 and 28 and output from the speakers 17 and 27.

[0017] The speakers 17 and 27 are devices for outputting audio, and output audio input from the microphones 16 and 26 of other terminals, audio from videos in online classes, and the like.

[0018] The communication units 18 and 28 transmit and receive data between the student terminal 10, the instructor terminal 20, and the server 100.

[0019] The server 100 includes a CPU 110, a memory 120, and a communication unit 130. The CPU 110, the memory 120, and the communication unit 130 are configured to be able to communicate with each other via an internal bus.

[0020] The CPU 110 controls the functions of each unit of the server 100 by executing the programs stored in the memory 120. Furthermore, the CPU 110 functions as a learning state assessment unit 111, a busyness assessment unit 112, and a support information transmission unit 113 by executing the programs stored in the memory 120. In the present disclosure, the server 100 can also be said to be a computer for executing programs. The communication unit 130 transmits and receives data between the server 100, the student terminal 10, and the instructor terminal 20.

[0021] The learning status evaluation unit 111 evaluates the learning status of students participating in online classes. The "student's learning status" is evaluated comprehensively based on information including the student's level of concentration in the online class, the student's level of understanding of the content of the online class, and the student's behavior in the online class. The student's learning status is evaluated for each student participating in the online class. The learning status evaluation unit 111 acquires information including at least one of the student's operation history information and video data of the student (hereinafter referred to as "first information"), and evaluates the student's level of concentration, level of understanding, and behavior using the first information. The "student's operation history information" is history information of input operations input by the student to the student terminal 10. Such history information includes, for example, the amount of operation of the touch panel, touchpad, mouse, keyboard, etc.

[0022] A student's concentration level is information indicating whether the student is concentrating on an online class. The student's concentration level is evaluated using feature data, such as the student's facial expression and gaze, in the video data. For example, if the student's gaze is fixed on the display for a long time, the learning state evaluation unit 111 evaluates the student's concentration level as high. On the other hand, if the student's gaze is directed away from the display or if the student looks sleepy, the learning state evaluation unit 111 evaluates the student's concentration level as low. The student's concentration level is also evaluated based on the student's operation history information. For example, if the student performs operations at regular intervals, the learning state evaluation unit 111 evaluates the student's concentration level as high. On the other hand, if the student does not perform operations for a certain period of time or more, the learning state evaluation unit 111 evaluates the student's concentration level as low. The learning state evaluation unit 111 evaluates the concentration level using a numerical value, for example, from 0 to 100.

[0023] A student's level of understanding of the content of an online class is information indicating whether the student understands the content of the online class. The student's level of understanding can be evaluated from the student's facial expression and movements in the video data. For example, if the student has a cheerful expression, the learning state evaluation unit 111 evaluates the student's level of understanding as high. Also, if the student nods in response to the instructor's explanation, the learning state evaluation unit 111 evaluates the student's level of understanding as high. On the other hand, if the student has a thoughtful expression, the learning state evaluation unit 111 evaluates the student's level of understanding as low. The learning state evaluation unit 111 evaluates the level of understanding, for example, as a numerical value from 0 to 100.

[0024] A student's behavior in an online class is information indicating whether the student is behaving in a distinctive manner compared to other students participating in the online class. For example, the learning state evaluation unit 111 uses video data to evaluate a student who is not seated during an online class as behaving in a distinctive manner. The learning state evaluation unit 111 also evaluates a student who inputs more data to the operation reception unit 13 than other students as behaving in a distinctive manner. The learning state evaluation unit 111 also determines a student who inputs very little data to the operation reception unit 13 despite other students inputting data to the operation reception unit 13 as behaving in a distinctive manner. The learning state evaluation unit 111 evaluates the student's behavior using a numerical value from 0 to 100, for example. The learning state evaluation unit 111 also evaluates the student's behavior as "normal" or "abnormal."

[0025] The learning state evaluation unit 111 comprehensively evaluates the student's concentration, comprehension, and behavior to determine whether the student's learning state meets or exceeds a predetermined standard. If the learning state meets or exceeds the standard, the learning state evaluation unit 111 determines that the student's learning state is good. On the other hand, if the learning state is below the standard, the learning state evaluation unit 111 determines that the student's learning state is not good.

[0026] A student's concentration, comprehension, and behavior may be evaluated by inputting the first information into a pre-trained evaluation model. The evaluation model can be created using well-known neural network technologies, such as deep neural networks and convolutional neural networks. The evaluation model learns the correlation between a student's first information and their concentration, comprehension, and behavior during online classes. This correlation can be obtained by acquiring the student's first information and, when a change occurs in the first information, using a chatbot or similar device to ask the student questions about their concentration, comprehension, or behavior. A change refers to a characteristic change in the amount of operation in the operation history or facial expression in video data. For example, if a student spends a long time looking away from the display, the chatbot may ask the student, "Are you concentrating on the class?" If the student responds, "I'm not concentrating," the long time the student's gaze is directed away from the display is correlated with the student's lack of concentration in the class. The evaluation model may be created for each student, or a generalized model may be created.

[0027] In this disclosure, the function of the program that acquires the first information is referred to as the "first function," and the function of the program that uses the first information to evaluate the learning status of the student is referred to as the "second function."

[0028] The busyness evaluation unit 112 evaluates the busyness of an instructor participating in an online class. The busyness evaluation unit 112 acquires information including at least one of the instructor's operation history information in the online class and video data of the instructor (hereinafter referred to as "third information") to evaluate the instructor's busyness. Specifically, the busyness evaluation unit 112 evaluates the instructor as busy if a large number of operations are input to the instructor-side terminal 20 within a certain period of time. Furthermore, the busyness evaluation unit 112 evaluates the instructor as busy if the instructor is repeatedly engaging in question-and-answer sessions with a student or repeatedly sending chat messages. Furthermore, the busyness evaluation unit 112 evaluates the instructor as busy if it is determined from the video data that the instructor is giving an oral explanation. On the other hand, the busyness evaluation unit 112 evaluates the instructor as not busy if a small number of operations are input to the instructor-side terminal 20 within a certain period of time. Furthermore, the busyness evaluation unit 112 evaluates the instructor as not busy if it is determined that the instructor is not speaking. The busyness evaluation unit 112 evaluates the busyness of the instructor using a numerical value from 0 to 100, for example.

[0029] The busyness evaluation unit 112 determines whether the busyness evaluated using the third information is equal to or greater than a predetermined standard. If the busyness is equal to or greater than the standard, the busyness evaluation unit 112 determines that the instructor is busy. On the other hand, if the busyness is less than the standard, the busyness evaluation unit 112 determines that the instructor is not busy.

[0030] The instructor's busyness may be evaluated by inputting the third information into a pre-trained evaluation model. The evaluation model learns the correlation between the instructor's third information during online classes and the instructor's busyness. Similar to the correlation between the first information and the student's concentration, comprehension, and behavior, this correlation can be obtained by having the chatbot ask the instructor a question about his or her busyness when a change occurs in the third information. For example, if the instructor repeatedly chats with a certain student, the chatbot asks the instructor, "Are you busy right now?" If the instructor responds "I'm busy" to the question, the instructor's repeated chats with students are correlated with the instructor's busyness. The evaluation model may be created for each instructor, or a generalized model may be created.

[0031] In this disclosure, the function of the program that acquires the third information is referred to as the “third function.” Also, the function of the program that uses the third information to evaluate the busyness of the instructor is referred to as the “fourth function.”

[0032] The support information transmission unit 113 transmits information to support learning (hereinafter referred to as "fifth information") to the student depending on the student's learning status and the instructor's busyness. For example, if a student's learning status is below a certain standard, i.e., if the student is unable to concentrate on online classes or does not understand the class content, the instructor needs to encourage the student to concentrate on the class or help them understand the class content by speaking to the student individually. However, when one instructor teaches multiple students, the instructor may not be able to teach other students while teaching one student individually, which may prevent the instructor from providing sufficient instruction to each student. In the present disclosure, the support information transmission unit 113 transmits the fifth information to the student on behalf of the instructor if the student's learning status is below a certain standard and the instructor's busyness is above a certain standard. The "fifth information" includes information to improve the student's concentration, information to improve the student's understanding, and information to increase the student's motivation for the class. Information to improve the student's concentration is, for example, a message to encourage the student to concentrate on the class, such as "Let's concentrate." Examples of information to improve students' understanding include information about review materials that help them understand the class content and information that supplements the class content. Information to increase students' motivation in class is, for example, words of encouragement to students, such as, "This is an important unit, so let's do our best." The fifth information is transmitted by the chatbot. The fifth information may be provided by repeating two-way dialogue between the chatbot and the student multiple times. For example, if the chatbot asks the student, "Is there anything you don't understand?" and the student replies, "I don't understand page 3 of the text," the chatbot will send the student an explanation of the part the student didn't understand or information about review materials as the fifth information.

[0033] The fifth information may be transmitted using a pre-trained evaluation model. The evaluation model has learned the correlation between instructor prompts during online classes and the student's level of concentration or comprehension after the prompts. "Instructor prompts" include not only one-way comments from the instructor to the student, but also comments made by the instructor in a dialogue between the instructor and the student and answers to questions from the student. Such correlation can be obtained by using a chatbot to ask the student whether their level of concentration or comprehension has improved when the instructor prompts the student during an online class. For example, after the instructor answers a student's question, the chatbot may ask the student, "Did your question get resolved?" If the student replies, "My question got resolved," the instructor's response is used as information to improve comprehension and is then learned into the evaluation model. An evaluation model may be created for each learning unit, or a generalized model may be created.

[0034] In this disclosure, the function of the program that transmits the fifth information is referred to as the "fifth function."

[0035] A2. Class support process: 2 is a flowchart showing the procedure of the class support process in the first embodiment. The class support process is executed in an online class, and is a process in which a program transmits the fifth information to students on behalf of the instructor when the instructor is busy.

[0036] The learning state assessment unit 111 acquires first information about the student in the online class (step S105). The first information is transmitted to the server 100 via the communication unit 18 of the student terminal 10.

[0037] The learning state evaluation unit 111 uses the first information to determine whether the student's learning state is above a predetermined standard (step S110). If the learning state evaluation unit 111 determines that the student's learning state is above the standard, that is, if the student's learning state is good, it ends the process.

[0038] If the learning state evaluation unit 111 determines that the student's learning state is below the standard, the busyness evaluation unit 112 acquires third information about the instructor (step S115). The third information is transmitted to the server 100 via the communication unit 28 of the instructor terminal 20.

[0039] The busyness evaluation unit 112 uses the third information to determine whether the instructor's busyness is equal to or greater than a predetermined standard (step S120). If the busyness evaluation unit 112 determines that the instructor's busyness is less than the standard, that is, if it determines that the instructor is not busy, it ends the process.

[0040] If the busyness evaluation unit 112 determines that the instructor's busyness is above the standard, the support information transmission unit 113 transmits the fifth information to students whose learning status was determined to be below the standard in step S110 (step S125).

[0041] According to the program of the first embodiment described above, the fifth information is sent to the student based on the student's learning status evaluated using the first information and the instructor's busyness evaluated using the third information, so that online classes can be supported according to the instructor's busyness. Specifically, if the instructor is busy and cannot directly teach a student whose learning status is below the standard, the program can support the online class by sending the fifth information to the student on behalf of the instructor.

[0042] B. Second embodiment: 3 is a flowchart showing the procedure of the class support processing in the second embodiment. The class support processing in the second embodiment differs from the class support processing in the first embodiment in that it further includes processing in step S205, that processing in step S110b is executed instead of processing in step S110, and that processing in step S125b is executed instead of processing in step S125. The other procedures of the class support processing in the second embodiment are the same as those of the class support processing in the first embodiment, so identical procedures are assigned the same reference numerals and detailed descriptions thereof are omitted. Furthermore, the device configuration of the online class support system 1 in the second embodiment is the same as that in the first embodiment, so detailed descriptions thereof are omitted.

[0043] Following the processing of step S105, the learning state assessment unit 111 acquires answers to exercise questions in the online class (step S205). An "exercise question" is a question posed to a student by an instructor in an online class. For example, if the online class is a programming class, an exercise question is a description of source code. "Answers to exercise questions" include not only answers that students have finished writing, but also answers that are still in progress. Note that acquisition of answers to exercise questions is realized by the first function of the program described above. Note that the processing of step S205 may be performed before the processing of step S105, or may be performed in parallel with the processing of step S105.

[0044] The learning state assessment unit 111 further uses the student's answers to the exercise questions acquired in step S205 to assess the learning state (step S110b). In the lesson support process of the first embodiment, the learning state assessment unit 111 assessed the learning state using the first information in the process of step S110. However, in the lesson support process of the second embodiment, the learning state assessment unit 111 assesses the student's learning state using the answers to the exercise questions acquired in step S205 in addition to the first information. Specifically, the learning state assessment unit 111 compares the difference between the student's answer and the correct answer to the exercise question to assess the student's level of understanding. If the difference between the student's answer and the correct answer to the exercise question is small, the learning state assessment unit 111 assesses the student's level of understanding as high. On the other hand, if the difference between the student's answer and the correct answer to the exercise question is large, the learning state assessment unit 111 assesses the student's level of understanding as low. The "correct answers to the exercise questions" may be prepared in advance of the online class, or may be prepared by the instructor during the online class. The second function of the program mentioned above compares the difference between the student's answer and the correct answer to the practice question and evaluates the student's learning status.

[0045] The support information transmitting unit 113 transmits fifth information to the student in accordance with the difference between the student's answer compared in step S110b and the correct answer to the exercise question (step S125b). For example, if there is a large difference between the student's answer and the correct answer to the exercise question, i.e., if the student has answered the exercise question incorrectly, the support information transmitting unit 113 transmits information about learning materials for reviewing the portion, information that provides hints for correctly answering the exercise question, and the like as the fifth information. Furthermore, if there is a small difference between the student's answer and the correct answer to the exercise question, i.e., if the student has answered the exercise question correctly, the support information transmitting unit 113 transmits a message to motivate the student, such as "You did a great job!" Note that the transmission of the fifth information in accordance with the difference between the student's answer and the correct answer to the exercise question is realized by the fifth function of the program described above, as in the first embodiment.

[0046] The program of the second embodiment described above achieves the same effects as the program of the first embodiment. Furthermore, the program of the second embodiment acquires students' answers to exercise problems in online classes, compares the difference between the students' answers and the correct answers to the exercise problems, and transmits fifth information according to the compared difference. Therefore, the fifth information according to the students' answers to the exercise problems can be transmitted. In particular, when the difference between the students' answers and the correct answers to the exercise problems is large, i.e., when the students' answers are incorrect, the fifth information can be transmitted, depending on the part of the student's error, including information on learning materials for reviewing the part or information that provides hints for answering the correct answer.

[0047] C. Third embodiment: FIG. 4 is a flowchart showing the steps of the lesson support processing in the third embodiment. The lesson support processing in the third embodiment differs from the lesson support processing in the first embodiment in that it further includes processing in step S305 and in that processing in step S110c is executed instead of processing in step S110. The other steps of the lesson support processing in the third embodiment are the same as those in the lesson support processing in the first embodiment, so the same steps are given the same reference numerals and detailed descriptions thereof are omitted. Furthermore, the device configuration of the online lesson support system 1 in the third embodiment is the same as that in the first embodiment, so detailed descriptions thereof are omitted. Note that the lesson support processing in the third embodiment may be executed in combination with the lesson support processing in the second embodiment.

[0048] Following the processing of step S105, the learning state evaluation unit 111 sends a question to the student via the chatbot to determine the student's level of understanding (step S305). Even if a student is evaluated as having a good learning state using only the first information, there may be cases where the student does not actually understand the content of the class. Therefore, the program of the third embodiment sends a question to the student via the chatbot to determine the student's level of understanding. A "question to determine the level of understanding" is a question to confirm whether the student understands the content of the class, such as "Do you understand the content of the class?". The student who is asked the question responds to such a question with, for example, "I understand the content of the class," "I do not understand the content of the class," or a number from 0 to 10 to indicate the level of understanding of the current class. The sending of the question to determine the level of understanding is realized by the first function of the program described above.

[0049] The learning state assessment unit 111 evaluates the learning state using the first information of the student acquired in step S105 and the student's answer to the question in step S305 (step S110c). In the lesson support process of the first embodiment, the learning state assessment unit 111 evaluated the learning state using the first information in the process of step S110. However, in the lesson support process of the third embodiment, the learning state assessment unit 111 evaluates the learning state using the answer to the question in step S305 in addition to the first information. For example, if the student answers, "I don't understand the content of the lesson," the learning state assessment unit 111 evaluates the student's level of understanding as low. On the other hand, for example, if the student answers, "I understand the content of the lesson," the learning state assessment unit 111 evaluates the student's level of understanding as high. The learning state assessment unit 111 comprehensively uses the first information and the answer to the question to assess the learning state of the student. Note that the assessment of the learning state using the answer to the question is realized by the second function of the program described above, similar to the assessment of the learning state using the first information.

[0050] The program of the third embodiment described above provides the same effects as the program of the first embodiment. Furthermore, the program of the third embodiment transmits questions to students to determine their levels of understanding, and evaluates their learning status using the answers to the questions and the first information, thereby enabling the accuracy of evaluating the learning status to be improved compared to a configuration in which the learning status is evaluated using only the first information.

[0051] D. Fourth embodiment: FIG. 5 is a flowchart showing the procedure of the class support processing in the fourth embodiment. The class support processing in the fourth embodiment differs from the class support processing in the third embodiment in that it further includes processing in step S405 and in that processing in step S125d is executed instead of processing in step S125. The other procedures of the class support processing in the fourth embodiment are the same as those of the class support processing in the third embodiment, so the same procedures are assigned the same reference numerals and detailed descriptions thereof are omitted. Furthermore, the device configuration of the online class support system 1 in the fourth embodiment is the same as that in the first embodiment, so detailed descriptions thereof are omitted. Note that the class support processing in the fourth embodiment may be executed in combination with the class support processing in the second embodiment.

[0052] If the busyness evaluation unit 112 evaluates the instructor's busyness as above the standard, the support information transmission unit 113 uses a chatbot to send at least one question to the student to identify areas of insufficient understanding, thereby identifying areas of insufficient understanding for the student (step S405). When the knowledge and experience of students taking online classes vary widely, the areas where students have difficulty understanding may differ significantly. For this reason, the chatbot sends questions to the student on behalf of the instructor, and the student's areas of insufficient understanding are identified using the student's answers to the questions. The support information transmission unit 113 asks a question to identify areas where the student does not understand the lesson content, such as "What do you not understand?" The student responds to the question with the name of the subject they do not understand, the page number of the text, or the like. The support information transmission unit 113 identifies areas of insufficient understanding for the student using the student's answers. The support information transmission unit 113 may send simple multiple-choice test questions as questions to identify areas of insufficient understanding for the student. Furthermore, the support information transmitting unit 113 may transmit questions multiple times to identify areas where the student lacks understanding. The student may answer each of the multiple transmitted questions.

[0053] In this disclosure, the function of using the chatbot to send at least one question to students to identify areas of lack of understanding in online classes and using the answers to the questions to identify areas of lack of understanding in students is referred to as the "sixth function."

[0054] The support information transmitting unit 113 transmits fifth information further depending on the insufficient understanding portion identified in step S405 (step S125d). The support information transmitting unit 113 transmits information for improving the level of understanding of the identified insufficient understanding portion to the student as the fifth information. The "information for improving the level of understanding" is, for example, information on learning materials for reviewing the insufficient understanding portion, supplementary information about the content of the insufficient understanding portion, etc.

[0055] The program of the fourth embodiment described above provides the same effects as the program of the third embodiment. Furthermore, the program of the fourth embodiment identifies areas where a student's understanding is lacking and transmits the fifth information according to the identified areas where understanding is lacking, so that more appropriate fifth information for improving understanding of the areas where understanding is lacking can be transmitted to the student.

[0056] E. Other Embodiments: (E1) In each of the above embodiments, after the support information transmitting unit 113 transmits the fifth information, an alert may be sent to the instructor. The alert includes information for identifying the student who transmitted the fifth information and the content of the transmitted fifth information. In this embodiment, the instructor can know what information the chatbot transmitted to which student. Furthermore, after the instructor's busy state is resolved, the instructor can check the alert and provide direct instruction to the student to whom the fifth information was transmitted. Furthermore, by checking the transmitted fifth information, the instructor can supplement the content of the fifth information and provide direct instruction to the student.

[0057] (E2) In the second embodiment, the learning state assessment unit 111 may acquire the student's answers to the practice questions acquired in step S205 in real time. Furthermore, in step S125b, the learning state assessment unit 111 may compare the student's answers to the practice questions with the correct answers to the practice questions in real time, and transmit the fifth information to the student using the difference obtained by the comparison. Note that "real time" in this disclosure refers not only to completely simultaneous but also to a broader concept that includes an error of several seconds. According to this embodiment, if a student incorrectly answers the practice questions, the fifth information can be immediately transmitted to the student, thereby further supporting the student's learning.

[0058] (E3) In each of the above embodiments, the first information may include the CPU usage rate, memory usage rate, and network usage status of the student terminal 10 used by the student. The learning status may be evaluated using this information. For example, if at least one of the CPU usage rate, memory usage rate, and network usage status is high, the student's concentration level is evaluated as high.

[0059] (E4) In the second embodiment, the case where the exercise questions are source code descriptions in programming has been described, but the present disclosure is not limited to this. The exercise questions may be, for example, GUI (Graphical User Interface) creation, entrance exam questions, qualification exam questions, etc. When the exercise questions are GUI creation, the difference between the student's answer and the correct answer to the exercise questions may be obtained by comparing the similarity of the screens.

[0060] (E5) In the second embodiment, the comparison of the student's answer to the exercise problem with the correct answer to the exercise problem may be performed by automatically inputting sample data into a program created by the student and checking whether the correct result is obtained. The input of the sample data may be performed by, for example, RPA (Robotic Process Automation) software.

[0061] (E6) In the fourth embodiment, the "area of ​​insufficient understanding" may be content that goes beyond the teaching content of the online class. According to this embodiment, if a student understands the content of the online class and wants to learn more applied content, the applied content can be sent to the student as the fifth information.

[0062] (E7) In each embodiment, the first information and the third information may include audio information input to the terminal via the microphones 16 and 26.

[0063] The present disclosure is not limited to the above-described embodiments and can be realized in various configurations without departing from the spirit thereof. For example, the technical features of the embodiments corresponding to the technical features in each aspect described in the Summary of the Invention section can be appropriately replaced or combined to solve some or all of the above-described problems or achieve some or all of the above-described effects. Furthermore, if a technical feature is not described as essential in this specification, it can be appropriately deleted. [Explanation of symbols]

[0064] 1...Online class support system, 10...Student terminal, 11, 21...CPU, 12, 22...Memory, 13, 23...Operation reception unit, 14, 24...Camera, 15, 25...Display unit, 16, 26...Microphone, 17, 27...Speaker, 18, 28...Communication unit, 20...Lecturer terminal, 100...Server, 110...CPU, 111...Learning state evaluation unit, 112...Busyness evaluation unit, 113...Support information transmission unit, 120...Memory, 130...Communication unit

Claims

1. A computer program for supporting online classes, a first function of acquiring first information including at least one of operation history information of the student in the online class and video data of the student; a second function of evaluating the learning status of the student using the first information; a third function of acquiring third information including at least one of operation history information of the instructor in the online class and video data of the instructor; a fourth function of evaluating the busyness of the instructor using the third information; a fifth function of transmitting fifth information including information for supporting the student's learning depending on the learning state of the student and the busyness of the instructor; This is realized by a computer, The first function further includes a function of obtaining answers to exercise questions from the students in the online class; the second function includes a function of evaluating the learning status of the student by comparing a difference between the student's answer and a correct answer to the exercise question; the fifth function includes a function of transmitting the fifth information in accordance with the learning status of the student, the busyness of the instructor, and the difference between the learning status and the busyness of the instructor; Computer program.

2. 2. The computer program of claim 1, The first function further includes a function of sending questions to the student via a chatbot to determine their level of understanding of the online lesson; the second function includes a function of evaluating the learning state of the student using the first information and the answer to the question for identifying the level of understanding; Computer program.

3. 3. A computer program according to claim 2, comprising: The computer further implements a sixth function of sending at least one question to the student via the chatbot to identify areas of insufficient understanding of the online class, and identifying areas of insufficient understanding of the student using answers to the questions to identify areas of insufficient understanding; The fifth function includes a function of transmitting the fifth information further depending on the part of the insufficient understanding. Computer program.

Images