Learning support system and learning support method

Abstract

To provide a technique for enabling provision of lectures tailored to each student's level.SOLUTION: A learning support system for providing students with lectures consisting of video and audio by an avatar lecturer, the virtual person who imitates a lecturer: includes a storage unit for storing first-level script data, the text data created in advance as a script for a first-level lecture; a script generation unit for creating second-level script data, the text data of a script of a lecture at a second level different from the first level on the basis of the first-level script data; and a lecture output unit for outputting a lecture including a voice that utters text data of the second-level script data and a video of the avatar lecturer.SELECTED DRAWING: Figure 3

Description

Technical Field

[0001] The present invention relates to a technique for assisting learning using a computer system.

Background Art

[0002] Patent Document 1 discloses a learning system that provides lectures including video and audio. The learning system makes a determination as to whether a learner attending the lecture is concentrating based on an image acquired for photographing the learner attending the lecture, records concentration determination result information based on the determination result, makes a determination as to whether the learner understands the content of the lecture based on the image and the concentration determination result information, records understanding determination result information based on the determination result, and controls the lecture based on the concentration determination result information and the understanding determination result information. At that time, the learning system provides a prepared supplementary lecture as a supplementary process to learners for whom the supplementary study is effective.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Lectures created for learners at a certain level may be felt to be boring for learners at a higher level, and the learners may lose motivation. Also, those lectures may not be understandable for learners at a lower level, and again the learners may lose motivation. The level of understanding of a lecture by a learner varies depending on the learner's past learning history and comprehension ability. Therefore, in order to provide supplementary lectures suitable for each learner's level, it is necessary to prepare in advance a large number of lecture contents with different levels for the same field, which requires a great deal of cost, time, and labor.

[0005] This problem exists not only in learning systems that provide virtual lecture content to learners, but also in schools, cram schools, and academies where real human instructors give lectures to learners. It is not easy for a single instructor to appropriately use different explanations of a lecture according to the understanding levels of all learners. Real instructors have their strengths and weaknesses. Some instructors are good at giving concise and pointed lectures for learners with a high understanding level, while some are good at giving easy-to-understand lectures that arouse the interest of learners with a low understanding level.

[0006] One objective included in the present disclosure is to provide a technology for realizing the provision of lectures according to the levels of learners.

Means for Solving the Problem

[0007] A learning support system according to one embodiment of the present disclosure is a learning support system that provides a lecture composed of video and audio to a learner by an avatar instructor, which is a virtual person imitating an instructor, and includes a storage unit that stores first-level script data, which is text data created in advance as a script of a first-level lecture, and a script generation unit that creates second-level script data, which is text data of a script of a lecture at a second level different from the first level, based on the first-level script data, and a lecture output unit that outputs a lecture including voice that pronounces the text data of the second-level script data and video of the avatar instructor.

Effect of the Invention

[0008] According to one aspect of the present disclosure, it is possible to provide a technology for realizing the provision of lectures according to the levels of learners.

Brief Description of the Drawings

[0009]

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Mode for Carrying Out the Invention

[0010] Hereinafter, embodiments of the present invention will be described with reference to the drawings.

[0011] The learning support system of this embodiment is a computer system that provides lecture content composed of video and audio to learners by a virtual person (hereinafter also referred to as an "avatar lecturer") having the appearance of a lecturer. The lecture content is, for example, the content of a lecture on countermeasures for taking a legal qualification examination. The learning support system provides lecture content at a level suitable for the learner and supports effective learning for the learner to pass the qualification examination.

[0012] In basic learning such as compulsory education, learning for high school entrance exams or college entrance exams, and learning to pass qualification exams, it can be said that learning means accumulating knowledge. For example, if one does not have a correct understanding of the multiplication table, one cannot understand arithmetic that uses the multiplication table. Therefore, for a child who cannot study in the fourth grade of elementary school, for example, they should first go back to the learning of the third grade, and if they still cannot do it, go back to the second grade and the first grade to study, and they should be guided to a state where they can accumulate learning.

[0013] In learning support for individual learners, it is effective to add new knowledge through lectures on the premise of the knowledge that the learner already knows. If a learner who already knows almost all of the new knowledge attends a lecture that adds new knowledge on the premise of certain knowledge, that learner will feel that the lecture is boring and the learning effect will not improve. Also, if a learner who lacks the prerequisite knowledge attends a lecture that adds new knowledge on the premise of certain knowledge, that learner will feel completely lost and the learning effect will not improve.

[0014] From the above, the academic level of the learner can be represented by the ratio of the knowledge already known to the new knowledge in the content of the lecture. And by appropriately classifying the academic levels of the learners and constructing appropriate lectures for each classification, it becomes possible to provide lectures at an appropriate level for many individual learners.

[0015] Figure 1 is a diagram showing a classification table of academic levels. The classification table of academic levels shows an example of the classification of the academic levels of learners.

[0016] Referring to the academic level classification table D01, the academic levels of the participants are classified into four levels: A, B, C, and D. Level A is a classification with a high academic evaluation, and the proportion of "new knowledge" in the whole lecture is 0-20%. Level B is a classification with a slightly high academic evaluation, and the proportion of "new knowledge" in the whole lecture is 21-40%. Level C is a classification with an ordinary academic evaluation, and the proportion of "new knowledge" in the whole lecture is 41-60%. Level D is a classification with a low academic evaluation, and the proportion of "new knowledge" in the whole lecture is 61% or more.

[0017] Next, in order to provide lectures at an appropriate level for participants at each academic level, it is required to match the lecture level with the academic level.

[0018] If a participant already has sufficient knowledge that is a prerequisite for understanding the lecture content, even if the new knowledge part is abstractly explained, they can understand it by connecting it with the known knowledge. However, if a participant does not already have sufficient prerequisite knowledge, when the new knowledge part is abstractly explained, they cannot connect it with the known knowledge and will not be able to understand. In that case, additional explanations using specific examples, metaphors, etc. for the new knowledge part can promote understanding.

[0019] Also, participants who already have sufficient knowledge that is a prerequisite for understanding the lecture content already have a sufficient understanding of the new knowledge part, so when the explanation is repeated, they feel bored and it is a waste of time. On the other hand, participants who do not already have sufficient prerequisite knowledge require a certain amount of time to understand the new knowledge, so if the explanation is not repeated, they will not be able to keep up. In that case, repeating the explanation of the new knowledge part can promote understanding.

[0020] In addition, learners who already have sufficient prerequisite knowledge for understanding the lecture content already have a good understanding of the new knowledge part. Therefore, if it is explained slowly, they will feel bored and that it is a waste of time. On the other hand, learners who do not have sufficient prerequisite knowledge require a certain amount of time to understand the new knowledge, and since there is a large part of the knowledge that needs to be newly understood, if the lecture explanation is fast, they will not be able to keep up. In that case, understanding is promoted by slow explanations.

[0021] From the above, in order to provide lectures at an appropriate level for learners of each academic level, it can be said that it is effective to adjust additional explanations, repetitions, and lecture speed according to the academic level, using specific examples and metaphors.

[0022] Figure 2 is a diagram showing a correspondence table of academic levels and lecture levels. The correspondence table of academic levels and lecture levels exemplifies the appropriate lecture level corresponding to the academic level of the learner and the mode of that lecture.

[0023] In the correspondence table of academic levels and lecture levels D02, the modes of appropriate lecture levels for each academic level A to D are shown. For the lecture level corresponding to academic level A, additional explanations such as specific examples and metaphors are not required, repeated explanations of important parts are not required, and a fast lecture speed is suitable. For the lecture level corresponding to academic level B, additional explanations are not required, repeated explanations of important parts are not required, and an ordinary lecture speed is suitable. For the lecture level corresponding to academic level C, additional explanations are required, repeated explanations of important parts are required, and an ordinary lecture speed is suitable. For the lecture level corresponding to academic level D, additional explanations are required, repeated explanations of important parts are required, and a slow lecture speed is suitable.

[0024] The learning support system according to this embodiment is a computer system in which an avatar lecturer provides lectures at an appropriate level to learners according to the learning level of the learners in the manner shown in Figure 2.

[0025] FIG. 3 is a block diagram showing the functional configuration of the learning support system according to the first embodiment.

[0026] Referring to FIG. 3, the learning support system 10 includes a learner level determination unit 11, a script generation unit 12, a lecture output unit 13, a learner state determination unit 15, and a storage unit 14. In the storage unit 14, pre-prepared data necessary for executing the service is recorded. Details of the data recorded in the storage unit 14 will be described later. The learner level determination unit 11, the script generation unit 12, the lecture output unit 13, and the learner state determination unit 15 are defined by software programs, and are realized by the processor executing the software programs. Details of the processing will be described later.

[0027] FIG. 4 is a block diagram showing the hardware configuration of the learning support system.

[0028] Referring to FIG. 4, the learning support system 10 is composed of a server 20 and an information terminal 30 such as a personal computer or a smartphone that can be connected to the server 20 via a communication network such as the Internet. The learner 90 connects to the server 20 using the browser 33 on the information terminal 30 and uses the service provided by the server 20. The service is a service that provides content related to learning. The service is realized by each unit shown in FIG. 1. In addition, the video of the learner 90 acquired by the camera 31 of the information terminal 30 and the voice of the learner 90 acquired by the microphone 32 are transmitted to the server 20 and used for processing by the server 20.

[0029] As shown in FIG. 4, the server 20 includes, as hardware, a processing device 21, a main memory 22, a storage device 23, a communication device 24, an input device 25, and a display device 26, which are connected to a bus 27.

[0030] The memory device 23 stores data in a writable and readable manner. The storage unit 14 shown in FIG. 3 is realized by this memory device 23. The processing device 21 is a processor that reads the data stored in the memory device 23 into the main memory 22 and executes the processing of software programs using the main memory 22. The processing device 21 realizes the learner level determination unit 11, the script generation unit 12, the lecture output unit 13, and the learner state determination unit 15 shown in FIG. 3. The communication device 24 transmits the information processed by the processing device 21 via a communication network including wired, wireless, or both, and transmits the information received via the communication network to the processing device 21. The received information is used for software processing by the processing device 21. The input device 25 is a device that receives information input by an operator such as a keyboard or a mouse, and the input information is used for software processing by the processing device 21. The display device 26 is a device that displays image and text information on the display screen in accordance with the software processing by the processing device 21. The input device 25 and the display device 26 are mainly provided for use by an administrator (not shown) rather than the learner 90.

[0031] Returning to FIG. 3, the storage unit 14 stores learner information D01 and basic level script data D02. The learner information D01 is information about each learner 90 who receives lectures by the present learning support system 10. The basic level script data D02 is text data created in advance as a script for a basic level lecture.

[0032] FIG. 5 is a diagram showing learner information.

[0033] In the learner information D03, the learner number (No.), name, examination history, home faculty, and whether or not they wish to take basic lectures are registered for each of the 90 learners. The name indicates the name of the relevant learner 90. The examination history indicates the number of times the relevant learner 90 has taken the examination they are about to take in the past. For example, the learner with No. = 001 has not taken any examinations, so they have never taken an examination before, and this is their first time taking an examination. The home faculty indicates the home faculty of the relevant learner 90. For example, the learner with No. = 001 is from the Faculty of Law. Whether or not they wish to take basic lectures indicates whether or not they wish to take lectures on basic content. For example, the learner with No. = 001 wishes to take lectures on basic content. The learner with No. = 004 does not wish to take lectures on basic content.

[0034] Figure 6 is a diagram showing an overview of the basic level script data.

[0035] The basic level script data D04 is text data created in advance as a script for basic level lectures. The basic level lectures are detailed lectures for beginners, and their scripts repeat important lecture content or provide additional explanations such as metaphors or specific examples for important lecture content. In the example of Figure 6, the script for the basic level lectures is created to first explain lecture content A, then repeat the explanation of lecture content B twice, and then provide an explanation of lecture content C and additional explanations to supplement it. The script for the basic level lectures may be generated, for example, by voice recognition processing from the voice data of lectures given by experienced real lecturers. Alternatively, it may be created by real lecturers as text data.

[0036] Figure 7 is a flowchart of the overall processing performed by the learning support system.

[0037] First, the learner level determination unit 11 first executes initial level identification processing in step S101. The initial level identification processing is processing for determining the level (initial level) of the lectures to be first provided to the learner 90.

[0038] FIG. 8 is a diagram showing the determination logic of the initial level identification process in the lectures for the legal qualification examination.

[0039] The initial level is determined based on the trainee information D03. The initial level of trainee 90 who has no examination history for the said examination and is taking the examination for the first time and is not from a law department is level D. The initial level of trainee 90 who has taken the said examination one or more times or is from a law department and hopes to take the basic lecture is level C. The initial level of trainee 90 who has taken the said examination one or more times or is from a law department and does not hope to take the basic lecture is level B. This determination logic is an example, and not limited to this, and the initial level may be determined by other logics. Also, the initial levels of all trainees 90 may be unified to one level, for example, level C.

[0040] Returning to FIG. 7, in step S102, the trainee level determination unit 11 sets the lecture level. If it is immediately after determining the initial level in step S101, the trainee level determination unit 11 sets that initial level as the lecture level.

[0041] Next, in step S103, the script generation unit 12 generates a script to be used for the lecture. At this time, the script generation unit 12 acquires the text data of the script of the lecture that conforms to the lecture level. If the lecture level is level C or level D, the script generation unit 12 directly acquires the basic level script data D02 recorded in the storage unit 14. Alternatively, when giving the speaking style of the avatar lecturer characteristics of a specific language system such as dialect or animal language, etc., at this stage, the content of the basic level script data D02 may be directly converted to the desired language system. In that case, for example, the script generation unit 12 has a generative artificial intelligence (generative AI) that generates text, and by giving the generative AI a prompt indicating a predetermined instruction and the basic level script data D04, the language system may be converted.

[0042] If the lecture level is level A or level B, the script generation unit 12 generates upper-level script data from the basic-level script data D02 recorded in the storage unit 14. At this time, for example, the script generation unit 12 has a generation AI, and by giving the generation AI a prompt indicating a predetermined instruction and the basic-level script data D04, the upper-level script data D05 may be generated. At this time, the script generation unit 12 may further cause the generation AI to convert the language system.

[0043] FIG. 9 is a diagram showing an overview of upper-level script data.

[0044] The upper-level script data D05 is text data that serves as a script for an upper-level lecture. Here, the upper level refers to level A or level B. The upper-level lecture is a lecture targeted at students with an exam-taking history or students from the law department, and its script does not include repeated explanations, additional explanations with examples or specific cases. In the example of FIG. 9, the script for the upper-level lecture first explains lecture content A, then explains lecture content B once, and then explains lecture content C.

[0045] Returning to FIG. 7, in step S104, the lecture output unit 13 outputs the video and audio of the lecture in which the avatar lecturer explains the text data of the script data acquired in step S103. At this time, the text data may only be pronounced by the avatar lecturer, or may be further displayed as subtitles on the screen.

[0046] Next, in step S105, the student status determination unit 15 executes a student status determination process. The student status determination process is a process for determining in what state the student 90 is taking the lecture. The state of the student is represented by whether the level of the lecture is high, low, or appropriate for the academic level of the student 90. The determination of the student status is based on the image and voice of the student 90 taking the lecture, acquired by the camera 31 and the microphone 32 of the information terminal 30. Further, vital data such as brain waves and heart rate acquired by a biosensor may be used.

[0047] For example, the expressions and movements of the attendee 90 can be detected from the image of the attendee 90. The emotions of the attendee 90 can be inferred from minute changes in the face, line of sight and pupil size, and their changes, and further from the movements. Also, from the voice of the attendee 90, the words spoken by the attendee 90 and the tone of the voice of the attendee 90 can be detected. For example, from the content of the words spoken by the attendee 90 to the avatar lecturer, the loudness and intonation of the voice, the degree of understanding and emotions of the attendee 90 towards the lecture can be inferred.

[0048] FIG. 10 is a flowchart of the attendee state determination process.

[0049] In the attendee state determination process, first, in step S201, the attendee state determination unit 15 determines whether the attendee 90 understands the lecture. If the attendee 90 understands the lecture, then in step S202, the attendee state determination unit 15 determines whether the attendee 90 is bored. If the attendee 90 is bored, then in step S203, the attendee state determination unit 15 determines that the academic level of the attendee 90 is higher than the lecture level. If in step S202, it is determined that the attendee 90 is not bored, then in step S204, the attendee state determination unit 15 determines that the academic level of the attendee 90 and the lecture level are appropriately matched. If in step S201, it is determined that the attendee 90 does not understand the lecture, then the attendee state determination unit 15 determines that the academic level of the attendee 90 is lower than the lecture level.

[0050] Returning to FIG. 7, in step S106, the attendee state determination unit 15 determines whether it is necessary to change the lecture level based on the result of the attendee state determination process. At this time, the attendee state determination unit 15 determines that it is necessary to change the lecture level when the academic level of the attendee 90 is higher or lower than the lecture level. Also, the attendee state determination unit 15 determines that it is not necessary to change the lecture level when the academic level of the attendee 90 and the lecture level are properly matched.

[0051] If there is no need to change the lecture level, return to step S104 and continue the output of the lecture. If there is a need to change the lecture level, return to step S102, change the lecture level through the processes from step S102 to S104, and continue the output of the lecture. If the academic level of the learner 90 is higher than the lecture level, the lecture level can be raised by one level. If the academic level of the learner 90 is lower than the lecture level, the lecture level can be lowered by one level.

[0052] <Appendix> As described above, the embodiments of the present invention have been described. However, the present invention is not limited to only these embodiments, and within the scope of the technical idea of the present invention, these embodiments may be used in combination, or some configurations may be changed.

[0053] Also, the above-described embodiments include the following matters. However, the matters included in the above-described embodiments are not limited to only those shown below.

[0054] (Matter 1) A learning support system that provides a lecture composed of video and audio to a learner by an avatar lecturer, which is a virtual person imitating a lecturer, the learning support system including: a storage unit that stores first-level script data, which is text data created in advance as a script for a first-level lecture; a script generation unit that creates second-level script data, which is text data of a script for a lecture at a second level different from the first level, based on the first-level script data; a lecture output unit that outputs a lecture including a voice that pronounces the text data of the second-level script data and a video of the avatar lecturer. According to this, since scripts for lectures at multiple levels are generated and output, it is possible to easily provide lectures according to the level of each learner.

[0055] (Matter 2) In the learning support system described in Item 1, the script generation unit includes a generative artificial intelligence that generates text. According to this, since scripts for lectures at different levels are generated by the generative artificial intelligence from a pre-created script, it becomes easier to provide lectures according to the level of the learners.

[0056] (Item 3) In the learning support system described in Item 2, the script generation unit generates the second-level script data by providing the generative artificial intelligence with a prompt indicating a predetermined instruction and the first-level script data.

[0057] (Item 4) In the learning support system described in Item 3, the first-level script data includes a metaphor that replaces the content to be lectured with other matters and / or a specific example that specifically shows the content to be lectured. The script generation unit generates the second-level script data by omitting the metaphor and / or the specific example from the first-level script data. Thereby, by omitting metaphors and specific examples from a pre-created script, it is possible to easily create a script for a lecture at a higher level.

[0058] (Item 5) In the learning support system described in Item 3, the first-level script data includes a part that repeatedly explains the content to be lectured a plurality of times, and the script generation unit generates the second-level script data by making the part that repeatedly explains the content in the first-level script data be explained only once. Thereby, by omitting the repeatedly explained part from a pre-created script, it is possible to easily create a script for a lecture at a higher level.

[0059] (Item 6) In the learning support system described in Item 3, the first-level script data is text data of a script of a lecture that explains the content in the most detail, and the script generation unit generates the second-level script data by summarizing the first-level script data with a smaller number of characters, words, or morphemes than the first-level script data. According to this, by summarizing a previously created script, a script of a high-level lecture can be easily created.

[0060] (Item 7) In the learning support system described in Item 1, it further has a state determination unit that determines the state of the learner based on an image of the learner receiving the lecture or input information obtained from the learner. The lecture output unit determines the script data to be used for the lecture provided to the learner and the speed of reading out the script data based on the state of the learner. According to this, a lecture with a level adjusted individually according to the state of the learner can be provided.

[0061] (Item 8) In the learning support system described in item 1, there are levels A, B, C, and D in descending order of lecture level. The storage unit stores, as the first-level script data, text data that is a script of the lecture at level D and includes a metaphor that replaces the content to be lectured with other matters or a specific example that specifically shows the content to be lectured, and includes a part that repeatedly explains the content to be lectured multiple times. The script generation unit generates the second-level script data by omitting the metaphor or the specific example from the first-level script data and explaining the part that repeatedly explains multiple times only once. The lecture output unit reads out the first-level script data at a first reading speed in the lecture at level D, reads out the first-level script data at a second reading speed faster than the first reading speed in the lecture at level C, reads out the second-level script data at the second reading speed in the lecture at level B, and reads out the second-level script data at a third reading speed faster than the second reading speed in the lecture at level A. According to this, by appropriately selecting the content and speed of the lecture from level A to D, it is possible to provide a lecture suitable for the individual levels of various learners.

[0062] (Item 9) In the learning support system described in item 8, it further has a level determination unit that determines the level of the learner based on the input information acquired from the learner. The lecture output unit reads out the first-level script data at a first reading speed if the learner's academic ability is level D, reads out the first-level script data at a second reading speed faster than the first reading speed if the learner's academic ability is level C, reads out the second-level script data at the second reading speed if the learner's academic ability is level B, and reads out the second-level script data at a third reading speed faster than the second reading speed if the learner's academic ability is level A.

Explanation of symbols

[0063] 10…Learning support system, 11…Learner level determination unit, 12…Script generation unit, 13…Lecture output unit, 14…Memory unit, 15…Learner status determination unit, 20…Server, 21…Processing device, 22…Main memory, 23…Storage device 24…Communication device, 25…Input device, 26…Display device, 27…Bus, 30…Information terminal, 31…Camera, 32…Microphone, 33…Browser, 90…Learner

Claims

1. A learning support system that provides students with a lecture consisting of video and audio by an avatar lecturer, which is a virtual person modeled after a lecturer, comprising: a storage unit for storing first level script data, which is text data created in advance as a script for a first level lecture; a script generating unit that generates second level script data, which is text data of a script of a lecture at a second level different from the first level, based on the first level script data; a lecture output unit that outputs a lecture including a voice that utters text data of the second level script data and a video of the avatar lecturer; A learning support system having the above structure.

2. The script generation unit includes a generation artificial intelligence that generates text. The learning support system according to claim 1 .

3. The script generation unit generates the second level script data by providing the generation artificial intelligence with a prompt indicating a predetermined instruction and the first level script data. The learning support system according to claim 2.

4. The first level script data includes an analogy for explaining the content to be lectured by replacing it with another matter and / or a concrete example for concretely showing the content to be lectured, The script generation unit generates the second level script data by omitting the analogy and / or the specific example from the first level script data. The learning support system according to claim 3 .

5. The first level script data includes a portion in which the content to be lectured is repeatedly explained a plurality of times, the script generation unit generates the second level script data by explaining the part in the first level script data that is to be explained multiple times only once; The learning support system according to claim 3 .

6. The first level script data is text data of a lecture script that explains the contents in the most detail, The script generation unit generates the second level script data by summarizing the first level script data with a number of characters, words, or morphemes that is smaller than that of the first level script data. The learning support system according to claim 3 .

7. a state determination unit that determines a state of the student based on an image of the student attending the lecture or input information acquired from the student, the lecture output unit determines script data to be used in the lecture to be provided to the student and a speed at which the script data is to be read out based on the state of the student; The learning support system according to claim 1 .

8. The levels of the lectures are Level A, Level B, Level C, and Level D, in order from highest to lowest. The storage unit stores text data, which is a script of the lecture of the level D, including an analogy for explaining the content to be lectured by replacing it with another matter or a specific example showing the content to be lectured concretely, and includes a part in which the content to be lectured is explained multiple times, as the first level script data; the script generation unit generates the second level script data by omitting the analogy or the specific example from the first level script data and explaining the part that is to be explained multiple times only once, the lecture output unit recites the first level script data at a first reading speed in the lecture of the level D, recites the first level script data at a second reading speed faster than the first reading speed in the lecture of the level C, recites the second level script data at the second reading speed in the lecture of the level B, and recites the second level script data at a third reading speed faster than the second reading speed in the lecture of the level A. The learning support system according to claim 1 .

9. a level determination unit that determines a level of the student based on input information acquired from the student; the lecture output unit recites the first level script data at a first reading speed if the student's academic ability is level D, recites the first level script data at a second reading speed faster than the first reading speed if the student's academic ability is level C, recites the second level script data at the second reading speed if the student's academic ability is level B, and recites the second level script data at a third reading speed faster than the second reading speed if the student's academic ability is level A. The learning support system according to claim 8.

10. A learning support method for providing a lecture consisting of video and audio to students by an avatar lecturer, which is a virtual person modeled after a lecturer, comprising the steps of: The computer storing first level script data, which is text data created in advance as a script for a first level lecture; creating second-level script data, which is text data of a lecture script at a second level different from the first level, based on the first-level script data; outputting a lecture including a voice uttering the text data of the second level script data and a video of the avatar lecturer; Learning support methods.

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