WO2020105413A1

WO2020105413A1 - Learning system and learning method

Info

Publication number: WO2020105413A1
Application number: PCT/JP2019/043226
Authority: WO
Inventors: 秋憲松本
Original assignee: パナソニックＩｐマネジメント株式会社
Priority date: 2018-11-22
Filing date: 2019-11-05
Publication date: 2020-05-28
Also published as: JPWO2020105413A1; JP7113380B2

Abstract

This learning system (1000) comprises: an output unit (210) which outputs a first question to a user (100); an acquisition unit (206) which acquires an answer of the user (100) to the first question; a brainwave measurement unit (201) which measures brainwaves of the user (100); and a control unit (200). The control unit (200) (a) determines the presence or absence of a first inspiration of the user (100) on the basis of a first brainwave, included in the brainwaves, starting from a time when the first question is output, (b) determines the correctness of the answer, and (c) on the basis of the presence or absence of the first inspiration and the correctness, determines contents to be output to the output unit (210), and outputs the contents to the output unit (210).

Description

Learning system and learning method

The present invention relates to a learning system and a learning method.

In recent years, learning support devices have been widely used for the purpose of making learners learn. In Patent Document 1, an understanding level is calculated using a determination result of an answer to a question, and a maximum execution time for executing a specific application is calculated based on the understanding level, thereby motivating continuous learning. A learning support device is disclosed.

JP, 2014-102300, A

However, the learning support device disclosed in Patent Document 1 uses only the determination result of the answer to the question in order to calculate the understanding level. Therefore, the state of detailed proficiency level of the problem is unknown. As a result, it is difficult for the learning support device disclosed in Patent Document 1 to effectively increase the proficiency level for problems and learning.

The present invention provides a learning system and a learning method that effectively improve the learner's proficiency level.

A learning system according to one aspect of the present invention includes an output unit that outputs a first problem to a user, an acquisition unit that acquires an answer of the user to the first problem, and an electroencephalogram measurement that measures an electroencephalogram of the user. And a control unit, wherein the control unit includes (a) a first electroencephalogram of the user based on a first electroencephalogram that is included in the electroencephalogram and starts from a time point when the first problem is output. Of the answer, (b) determining whether the answer is correct or incorrect, and (c) determining the content to be output to the output unit based on the presence or absence of the first inspiration and the accuracy. The contents are output to the output unit.

A learning method according to an aspect of the present invention includes a first output step of outputting a first question to a user, an obtaining step of obtaining an answer of the user to the first question, and measuring an electroencephalogram of the user. An electroencephalogram measurement step and a control step are included, and the control step includes: (a) a user's electroencephalogram based on a first electroencephalogram, which is included in the electroencephalogram and starts from a time point when the first problem is output. Based on a first determination step for determining the presence or absence of a first inspiration, (b) a second determination step for determining the correctness of the answer, (c) the presence or absence of the first inspiration, and the correctness, A second output step of determining the content to be output in the first output step and outputting the content.

A program according to an aspect of the present invention is a computer program for executing a learning method, including (f1) outputting a first problem to a user via an output device, and (f2) responding to the first problem. The answer of the user is acquired, (f3) the electroencephalogram of the user is measured, and (f4) based on the first electroencephalogram, which is included in the electroencephalogram and has the time point at which the first problem is output as a starting point, The presence or absence of the first inspiration of the user is determined, (f5) the correctness of the answer is determined, and (f6) the content output by the output device is determined based on the presence or absence of the first inspiration and the correctness. The computer is made to determine and output to the output device.

According to the present invention, a learning system and a learning method that effectively improve the learner's proficiency level are realized.

FIG. 1 is a diagram showing an external configuration of the learning system according to the first embodiment. FIG. 2 is a diagram showing a hardware configuration of the learning system according to the first embodiment. FIG. 3 is a diagram showing functional blocks of the learning system according to the first embodiment. FIG. 4 is a diagram showing the timing of acquisition and display of the first electroencephalogram performed by the learning system. FIG. 5 is a flowchart showing the processing of the first signal determination unit. FIG. 6 is a flowchart showing the processing of the answer determination unit. FIG. 7 is a diagram showing a state determined by the state determination unit. FIG. 8 is a diagram illustrating processing of the presentation unit corresponding to each state. FIG. 9 is a diagram showing a screen displayed by the output unit. FIG. 10 is a flowchart showing the processing of the learning system according to the first embodiment. FIG. 11 is a flowchart of the learning method according to the first embodiment. FIG. 12 is a diagram showing functional blocks of the learning system according to the second embodiment. FIG. 13 is a diagram showing the timing of acquisition and display of the second electroencephalogram performed by the learning system. FIG. 14 is a flowchart showing the processing of the second signal determination unit. FIG. 15 is a diagram showing functional blocks of the learning system according to the third embodiment. FIG. 16 is a flowchart showing the processing of the authentication unit according to the third embodiment. FIG. 17 is a diagram showing a state determined by the state determination unit in the third embodiment. FIG. 18 is a diagram showing processing of the presentation unit corresponding to each state in the third embodiment. FIG. 19 is a flowchart showing a method for improving the accuracy of determination of the presence or absence of inspiration in the third embodiment. FIG. 20 is a diagram showing another example of the external configuration of the learning system in the embodiment.

Hereinafter, embodiments will be specifically described with reference to the drawings. It should be noted that each of the embodiments described below shows a comprehensive or specific example. Numerical values, shapes, materials, constituent elements, arrangement positions and connection forms of constituent elements, steps, order of steps, and the like shown in the following embodiments are examples, and are not intended to limit the present invention. Further, among the constituent elements in the following embodiments, constituent elements not described in the independent claims are described as arbitrary constituent elements.

Note that each diagram is a schematic diagram, and is not necessarily an exact illustration. Further, in each drawing, the same reference numerals are given to substantially the same configurations, and overlapping description may be omitted or simplified.

(Embodiment 1)
[Overview]
First, an outline of the learning system 1000 according to the embodiment will be described.

1 is a diagram showing an external configuration of a learning system 1000 according to the first embodiment.

The learning system 1000 includes a terminal device 101 and an electroencephalograph 102. The terminal device 101 outputs the problem and presents the problem to the user 100. The electroencephalograph 102 measures the electroencephalogram of the user 100.

A user 100 who is a learner operates the terminal device 101 while wearing the electroencephalograph 102. Specifically, the user 100 inputs the answer to the question by operating the terminal device 101. Thereby, the terminal device 101 acquires the answer.

Furthermore, the terminal device 101 acquires the electroencephalogram of the user 100 for the problem from the electroencephalograph 102. The terminal device 101 determines the content to be output next by the terminal device 101 (for example, a problem that is more difficult than the problem presented earlier), based on the correctness of the answer and the electroencephalogram. The terminal device 101 may be a tablet terminal, a smartphone, a personal computer, a smart speaker, or the like. The electroencephalograph 102 may be any device that can be worn by the user 100 and can measure brain waves, and is, for example, an earhook type device that can be worn on the ear of the user 100. Further, it may be headgear or a headcap installed on the head of the user 100.

According to the learning system 1000, the state of proficiency level for a problem can be determined based on the answer to the problem of the user 100 and the electroencephalogram for the process of solving the problem. Next, by tackling the content according to the state of the proficiency level (for example, a problem that is more difficult than the problem presented earlier), the proficiency level of the user 100 can be effectively improved.

[Hardware configuration]
FIG. 2 is a diagram showing a hardware configuration of the learning system 1000 according to the first embodiment.

The terminal device 101 includes a display device 103, a CPU (Central Processing Unit) 104, a ROM (Read Only Memory) 105, a RAM (Random Access Memory) 107, and a communication unit 108, which are connected to each other via a bus 109. ..

The electroencephalograph 102 wirelessly communicates with the communication unit 108. The communication method may be wired. The display device 103 is hardware, which will be described in detail later, but corresponds to the output unit 210 shown in FIG. 3, and is composed of, for example, a liquid crystal display or an organic EL (Electro Luminescence) display. The CPU 104 is hardware corresponding to the control unit 200 described later. Further, the CPU 104 may execute respective processes of the electroencephalogram measurement unit 201 and the acquisition unit 206 described later. The ROM 105 holds, for example, the program 106 read and executed by the CPU 104. The CPU 104 executes the processing of the control unit 200 by executing the program 106. Further, a database in which a plurality of questions associated with correct answers and a database in which a plurality of questions associated with difficulty levels are stored may be recorded in a part of the ROM 105. The RAM 107 temporarily stores the data generated by the processing of the CPU 104. The terminal device 101 may be provided with a memory for recording the above database and connected to the bus 109. The communication unit 108 wirelessly transmits and receives signals to and from the electroencephalograph 102.

[System configuration]
FIG. 3 is a diagram showing functional blocks of the learning system 1000 according to the first embodiment shown in FIG.

The learning system 1000 shown in FIG. 3 includes an electroencephalogram measurement unit 201, a first signal determination unit 204, an acquisition unit 206, an answer determination unit 207, a state determination unit 208, a presentation unit 209, and an output unit 210. Here, the first signal determination unit 204, the answer determination unit 207, the state determination unit 208, and the presentation unit 209 are components included in the control unit 200. The control unit 200 includes, for example, at least one processor. Further, each component other than the electroencephalogram measurement unit 201 included in the learning system 1000 is included in the terminal device 101.

The electroencephalogram measurement unit 201 includes, for example, an electroencephalograph 102 and a part of the functions of the terminal device 101. Note that a part of this function may be included in the control unit 200 of the terminal device 101. Further, all the functions of the electroencephalogram measurement unit 201 may be included in the control unit 200 of the terminal device 101.

The output unit 210 outputs the first problem to the user 100. Specifically, the output unit 210 is, for example, a liquid crystal display, an organic EL display, or the like, and displays an image of the content according to the signal of the presentation unit 209 included in the control unit 200. That is, outputting the first question to the user 100 means displaying the first question on the display. In addition, the output unit 210 may display at least one of a question next to the first question and a response. The next question or response is the question or response selected by the presentation unit 209. As a matter of course, problems other than the first problem and the next problem may be sequentially displayed. Furthermore, this response may be a message to the user 100, and may be, for example, content prompting a break. That is, the output unit 210 displays the question or the response (message) selected by the presentation unit 209 as an image.

Note that the output unit 210 may be a speaker and may output a voice having contents according to the signal from the presentation unit 209.

The acquisition unit 206 acquires the answer of the user 100 to the first problem. Specifically, the acquisition unit 206 is realized by part of the functions of the processor and hardware. This hardware is, for example, a means such as a keyboard, a mouse, a remote controller, or a microphone for receiving the operation of the user 100, that is, a means for inputting the answer of the user 100 to the learning system 1000. The acquisition unit 206 may be realized by a touch panel that can be input from the screen and / or a partial function of the processor. Further, the acquisition unit 206 may acquire the answer of the user 100 to the next question of the first question, that is, the question other than the first question. The acquisition unit 206 notifies the answer determination unit 207 of the answer and the timing at which the answer is acquired.

The answer determination unit 207 determines whether the answer to the question of the user 100 is correct or incorrect. Specifically, the answer determination unit 207 determines the correctness of the answer to the first question of the user 100 obtained from the acquisition unit 206. In order to make the determination, a database in which a plurality of questions recorded in the ROM 105 and associated with the correct answer are stored may be used. Further, the timing at which the answer is acquired from the acquisition unit 206 is also obtained. Further, the status determination unit 208 is notified of the correctness of the determined answer and the timing at which the answer is acquired.

The electroencephalogram measurement unit 201 measures the electroencephalogram of the user 100. The electroencephalogram measurement unit 201 is realized by the electroencephalograph 102 and a part of the functions of the processor. Alternatively, the electroencephalogram measurement unit 201 may be realized by a part of the functions of the processor. In this case, the electroencephalogram of the user 100 is measured by receiving the output signal from the electroencephalograph 102. As described above, the electroencephalograph 102 is attached to the user 100 and is prepared so that the electroencephalogram of the user 100 can be acquired. The electroencephalograph 102 is an earhook (ear-hook) device, and has a first electrode arranged so as to contact the head and a reference electrode arranged so as to contact the earlobe. As an example, as shown in FIG. 1, the first electrode is included in the support portion 102a that is sandwiched between the auricle and the temporal region and is in contact with the head portion, and the reference electrode is the base portion 102b that is in contact with the surface of the earlobe. May be included in. The ground electrode (the electrode that gives the potential of the body ground) may be included in the base portion 102b that is in contact with the back surface of the earlobe. The electroencephalogram of the user 100, which is measured and output by the electroencephalograph 102, may indicate a time-series change in “voltage value between the first electrode and the reference electrode” with reference to the reference electrode. That is, the plurality of voltage values indicated by the electroencephalogram and the plurality of times when the plurality of voltage values are measured correspond to each other one to one. Further, it may be a device worn on the head, in which case it may include a first electrode worn on the scalp of the user 100 or the forehead of the user 100, and a reference electrode worn on the earlobe of the user 100.

The electroencephalogram measurement unit 201 transmits the electroencephalogram acquired by the electroencephalograph 102 to the first signal determination unit 204. The procedure for transmitting the electroencephalogram from the electroencephalogram measurement unit 201 to the first signal determination unit 204 is as follows. First, the electroencephalogram measurement unit 201 inputs an electric signal indicating the electroencephalogram of the user 100 to the amplifier. The amplifier differentially amplifies the electric signal and outputs it to a low pass filter (low pass filter). Next, the low-pass filter removes unnecessary high frequency components and outputs them to the AD converter. The AD converter converts the analog signal output from the amplifier into a digital signal and outputs the digital signal. Finally, the digital signal converted by the AD converter is wirelessly transmitted to the first signal determination unit 204 as an electric signal. The amplifier, the low-pass filter, and the AD converter may be included in the electroencephalogram measurement unit 201.

The first signal determination unit 204 determines the presence / absence of the first inspiration of the user 100 based on the first electroencephalogram included in the electroencephalogram and starting from the time when the problem is output. The first electroencephalogram is extracted from the electroencephalogram of the user 100 measured by the electroencephalogram measurement unit 201. The time when the problem is output is the time when the presentation unit 209 notifies the problem. Hereinafter, the digital signal obtained by the electroencephalogram measurement unit 201 will be described as the electroencephalogram of the user 100.

Specifically, the first signal determination unit 204 extracts, from the electroencephalogram of the user 100 measured by the electroencephalogram measurement unit 201, a first electroencephalogram starting from the time when the problem is output. Then, the first signal determination unit 204 determines the presence or absence of the first inspiration of the user 100 based on the first brain wave. More specifically, the first signal determination unit 204 extracts the first electroencephalogram from the electroencephalogram in the time range of 200 msec or more and 2000 msec or less, starting from the time when the problem is output. When there is the first inspiration, specifically, it indicates a psychological state in which a reflexive inspiration occurs immediately after the problem is output. Furthermore, the first signal determination unit 204 notifies the state determination unit 208 of the presence or absence of the determined first inspiration.

Also, theta waves included in the brain waves are used as the first method of determining the presence of inspiration. The theta wave will be described here. In the electroencephalogram, a theta wave is a rhythm wave that represents inspiration during mental activity, and its frequency band is 4 to 7 Hz. It is known that the psychological state or physiological state represented by the theta wave is an inspirational state or a slumbering state. In the embodiment, it is utilized that the presence or absence of the theta wave correlates with the presence or absence of inspiration.

Here, the method of determining the presence or absence of the first inspiration by the first signal determination unit 204 will be described in detail.

As described above, the first signal determination unit 204 determines the presence or absence of the first inspiration within the predetermined time range after the problem is displayed, from the electroencephalogram of the user 100 measured by the electroencephalogram measurement unit 201. For example, the predetermined time range is a range from 200 msec to 2000 msec with the timing at which the output unit 210 displays a problem as a starting point (that is, 0 msec), and the first electroencephalogram is extracted from the electroencephalogram in this time range. Further, the first signal determination unit 204 extracts a theta wave band component of the first brain wave from the first brain wave, and based on the extracted theta wave band component, the first inspiration of the user 100. Determine the presence or absence. The procedure for extracting the theta wave component of the first electroencephalogram from the first electroencephalogram is as follows. The digital signal converted by the AD converter included in the electroencephalogram measurement unit 201 is received by the communication unit 108 shown in FIG. Further, the communication unit 108 outputs the digital signal to the bandpass filter. The bandpass filter limits the signal band from 2 Hz to 10 Hz. Through such signal processing, the theta wave band component of the first electroencephalogram is extracted from the first electroencephalogram.

The first signal determination unit 204 determines the presence or absence of the first inspiration in the theta wave band component by using an index such as Vpp (Volt peak-to-peak). Here, Vpp is a value calculated from the difference between the maximum voltage and the minimum voltage in voltage. For example, the first signal determination unit 204 determines that the first inspiration is present when Vpp in the first brain wave of the user 100 is equal to or greater than a predetermined threshold value. The predetermined threshold value is, for example, 10 μV, but is not limited to this. On the other hand, when Vpp is less than this predetermined threshold value, it is determined that there is no first inspiration.

The first signal determination unit 204 extracts the first electroencephalogram starting from the time when the problem is output, but the time range is not limited to the above. For example, the extraction start time may be 50 msec or more and 1000 msec or less, preferably 100 msec or more and 800 msec or less, more preferably 150 msec or more and 300 msec or less, starting from the time when the problem is output. Further, for example, the time to end the extraction may be 1000 msec or more and 4000 msec or less, preferably 1400 msec or more and 3000 msec or less, more preferably 1500 msec or more and 2500 msec or less, starting from the time when the problem is output. ..

Also, the predetermined threshold is not limited to the above. The predetermined threshold may be 1 μV or more and 50 μV or less, preferably 3 μV or more and 30 μV or less, and more preferably 6 μV or more and 20 μV or less. Further, the predetermined threshold does not have to be always constant. It is assumed that the predetermined threshold value varies depending on the individual user 100, and that the same user 100 varies depending on the daily psychological state. Therefore, the first signal determination unit 204 may determine an individual threshold value corresponding to each user 100.

In addition, the electroencephalogram measurement unit 201 measures the electroencephalogram in the above-described time range as the first electroencephalogram, and the first signal determination unit 204 acquires the electroencephalogram from the electroencephalogram measurement unit 201 without extracting the first electroencephalogram. Good.

The state determination unit 208 determines the state of the proficiency level of the user 100 with respect to the question based on the determination result of the first signal determination unit 204 and the determination result of the answer determination unit 207. Specifically, the state determination unit 208 determines four states described below based on the presence / absence of the first inspiration and the correctness of the answer. That is, the state where the first inspiration is present and the answer is correct is state 1, the state where the first inspiration is present and the answer is incorrect is state 2, and the state where the first inspiration is not present and the answer is correct is State 3 is set, and a state in which there is no first inspiration and the answer is incorrect is determined as state 4. Further, the presenting unit 209 is notified of the determined state. Further, a more detailed state may be determined by using the timing when the answer notified by the answer determination unit 207 is acquired.

The presentation unit 209 determines the content to be output to the output unit 210 according to the determination result of the state determination unit 208, and causes the output unit 210 to output the content. For example, the presentation unit 209 refers to a database that stores a plurality of questions associated with the degree of difficulty, selects a question to be presented to the user 100 from the database, and causes the output unit 210 to output the question. Further, the presentation unit 209 may cause the output unit 210 to output the correctness of the response and the answer as well as the question. Of course, the presentation unit 209 may cause the output unit 210 to sequentially output problems other than the first problem and the next problem. Details of the contents displayed by the output unit 210 corresponding to each state will be described with reference to FIG. Further, the presentation unit 209 notifies the first signal determination unit 204 of the timing when the output unit 210 displays the question, that is, the timing when the question is output.

[Operation example]
FIG. 4 is a diagram showing the timing of acquisition and display of the first electroencephalogram performed by the learning system 1000 shown in FIG.

The first signal determination unit 204 extracts, from the electroencephalogram measured by the electroencephalogram measurement unit 201, the first electroencephalogram at the time when the problem is output, that is, the time t1 when the problem is displayed as the starting point. The time when the problem is output is the time when the presentation unit 209 notifies the problem. The first electroencephalogram starting from time t1 is an electroencephalogram in the time range between the time point 200 msec after time t1 and the time point 2000 msec after time t1 (that is, t2). Furthermore, the first signal determination unit 204 determines the presence or absence of the first inspiration of the user 100 based on this first brain wave. Specifically, the theta wave band component of the first electroencephalogram is extracted from the first electroencephalogram, and the presence or absence of the first inspiration of the user 100 is determined based on the extracted theta wave band component.

The acquisition unit 206 acquires the answer at the time when the answer to the question output at the time t1 is acquired, that is, at the time t3 when the answer is input, and the timing at which the answer is acquired. In the first embodiment, as shown in FIG. 4, the answer input time t3 is later than the time t2 at which the acquisition of the first electroencephalogram is completed, that is, t3> t2> t1. , The answer input time t3 may be earlier than the time t2 at which the acquisition of the first electroencephalogram is completed. That is, t2> t3> t1 may be satisfied. Further, the time t2 when the acquisition of the first electroencephalogram is completed and the time t3 when the answer is input may be the same, that is, t2 = t3.

The answer determination unit 207 determines whether the answer is correct at time t4. The time relationship between the time t4 for determining whether the answer is correct and the time t3 for inputting the answer may be t4> t3 as shown in FIG. 3, but the time relationship is not limited to this.

The presentation unit 209 causes the output unit 210 to output the correctness of the answer and the response at time t5. The time relationship between the time t5 at which the correctness of the answer and the response are output and the time t4 at which the correctness of the answer is determined may be t5> t4. In addition, the presenting unit 209 may cause the output unit 210 to output the next question at the same time, at this time t5, in accordance with not only the correctness of the answer and the response but also the state determined by the state determining unit 208. Further, the presentation unit 209 may output the next question to the output unit 210 after the output unit 210 outputs the correctness of the answer and the response, not at the same time.

The time t3 when the answer is input and the time t4 when the correctness of the answer is determined are not particularly set, but are, for example, 100 msec to 10000 msec, preferably 1000 msec to 8000 msec, and more preferably 1500 msec to 5000 msec. is there. In addition, the time t4 for determining the correctness and the time t5 for outputting the correctness of the answer and the response are not particularly defined, but are, for example, 100 msec to 10000 msec, preferably 1000 msec to 8000 msec, and more preferably, It is 1500 msec to 5000 msec.

FIG. 5 is a flowchart showing the process of the first signal determination unit 204 shown in FIG.

The first signal determination unit 204 receives a signal regarding the electroencephalogram of the user 100 from the electroencephalogram measurement unit 201 (step S100). The signal contains brain waves, but may also contain noise. Note that noise sources include device noise from outside the human body, commercial AC noise, myoelectric noise from the human body, ocular noise from the human body, problem presentation, or movements unrelated to answer input. Various noises such as noise and background brain waves can be considered. Further, the number of noise sources is not limited to one, and two or more noise sources may be considered.

The first signal determination unit 204 performs noise removal processing to extract a waveform including a specific frequency band from the received signal (step S101). For example, the first signal determination unit 204 extracts an electroencephalogram including a specific frequency band by performing band limitation processing on the signal, for example, 2 Hz to 10 Hz in a bandpass filter. This removes noise.

Next, the first signal determination unit 204 receives, from the presentation unit 209, information indicating the timing of presenting the question to the user 100 (step S102).

The first signal determination unit 204 cuts out an electroencephalogram signal in a predetermined time range from the signal relating to the electroencephalogram of the user 100 from which noise has been removed in step S101, starting from the timing indicated by the information received in step S102 (step S103). .. For example, the first signal determination unit 204 may cut out an electroencephalogram signal from 200 msec to 2000 msec, starting from the timing of problem display. The cut-out brain wave signal is the first brain wave.

The first signal determination unit 204 calculates the Vpp value for the theta wave component in the predetermined time range cut out in step S103 (step S104).

The first signal determination unit 204 determines whether Vpp calculated in step S104 is greater than or equal to a threshold value. The threshold value may be set using a predetermined value (step S105).

If the determination result of step S105 is YES, the first signal determination unit 204 determines that there is a first inspiration (step S106).

Further, if the determination result in step S105 is NO, the first signal determination unit 204 determines that there is no first inspiration (step S107).

FIG. 6 is a flowchart showing the processing of the answer determination unit 207 shown in FIG.

The answer determination unit 207 receives the answer to the first question of the user 100 from the acquisition unit 206 (step S200).

The answer determination unit 207 refers to a database in which a plurality of questions associated with the correct answer recorded in the ROM 105 are stored in order to determine whether the received answer is correct or incorrect (step S201).

Next, the answer determination unit 207 refers to the database in which a plurality of questions stored in the ROM 105 and associated with the correct answer are stored, and determines whether or not the received answer matches the correct answer (step S202). ..

The answer determination unit 207 determines that the answer to the first question is a correct answer when the determination result in step S202 is YES (step S203).

Further, if the determination result in step S202 is NO, the answer determination unit 207 determines that the answer to the first question is an incorrect answer (step S204).

FIG. 7 is a diagram showing states determined by the state determination unit 208 based on the results of FIGS. 5 and 6. The state determination unit 208 determines whether or not the first inspiration is determined by the first signal determination unit 204 (whether the inspiration is present / absent) and the correctness (correctness / incorrectness) of the answer determined by the answer determination unit 207. Determine the state of proficiency of.

Specifically, the state determination unit 208 determines the state of proficiency as described below.

The state determination unit 208 determines the state of the user 100 as state 1 when the first inspiration is “present” and the answer is “correct”. This state 1 is a state in which the displayed question has a reflexive inspiration and is the correct answer, and the displayed question is sufficiently understood. That is, the user 100 is in a familiar state.

The state determination unit 208 determines the state of the user 100 as state 2 when the first inspiration is “present” and the answer is “wrong answer”. The state 2 is a state in which the displayed question has a reflexive inspiration and is an incorrect answer, and the displayed question has a mistake in the calculation process or entry. That is, the user 100 is in a careless miss state.

The state determination unit 208 determines the state of the user 100 to be state 3 when the first inspiration is “none” and the answer is “correct”. In this state 3, there is no reflexive inspiration to the displayed question, and the answer is correct, and the proficiency level is insufficient because the calculation process up to the answer is not fixed for the displayed question. It shows the state. That is, the user 100 is in a state of being unfamiliar and requiring practice.

The state determination unit 208 determines the state of the user 100 to be state 4 when the first inspiration is “none” and the answer is “wrong answer”. This state 4 is a state in which there is no reflective inspiration for the displayed question, and it is an incorrect answer, and the displayed question cannot be solved. That is, the user 100 is in an unskilled state and needs a break.

As described above, the state determination unit 208 determines the state of the user 100 based on the presence / absence of the first inspiration (whether the inspiration is present / absent) and the correctness of the answer (correctness / incorrectness), but other methods. May be used to determine. For example, the state of the user 100 may be determined by using the timing when the answer acquired by the acquisition unit 206 is acquired. Specifically, when questions are presented one after another, if the timing at which the answer to each question is acquired gradually becomes earlier, it indicates a state where the proficiency level is gradually increasing. On the other hand, when questions are presented one after another, if the timing of obtaining the answer to each question is constant or gradually delayed, the proficiency level remains constant.

On the other hand, as shown in FIG. 7, the state of the user 100 is determined only by the presence / absence of the first inspiration (whether the inspiration is present / absent) and the correctness (correctness / incorrectness) of the answer, and when the answer is acquired. The state of the user 100 may be determined without using a certain timing.

FIG. 8 is a diagram showing processing of the presentation unit 209 corresponding to each state shown in FIG. 7. The presentation unit 209 selects the content to be displayed on the output unit 210 according to the determination result by the state determination unit 208.

Specifically, when the determination result by the state determination unit 208 is the state 1, the presentation unit 209 continuously selects a response that prompts the user to solve the problem as the content to be displayed on the output unit 210. Then, the presentation unit 209 continuously causes the output unit 210 to output a display prompting the user to solve the problem. The reason why such a display is made is that when the user 100 is in state 1, it is considered that the user 100 is in a state of high proficiency. The presentation unit 209 may continuously select a response such as “good condition” as a response prompting the user to solve the problem.

Further, when the determination result by the state determining unit 208 is the state 1, the presenting unit 209 determines the second problem that is more difficult than the first problem as the content to be displayed on the output unit 210. Then, the presentation unit 209 causes the output unit 210 to output the second problem that is more difficult than the first problem.

Further, when the determination result by the state determining unit 208 is the state 2, the presenting unit 209 selects a response prompting the user to calmly solve the problem as the content to be displayed on the output unit 210. Then, the presentation unit 209 causes the output unit 210 to output a display prompting the user to calmly solve the problem. The reason why such a display is performed is that when the user 100 is in state 2, it is considered that the user 100 is in a careless miss. The presentation unit 209 may select a response that prompts a specific action, such as “calmly calculate,” as a response that calmly solves the problem.

Furthermore, when the determination result by the state determination unit 208 is state 2, the presentation unit 209 determines the third problem having the same difficulty level as the first problem as the content to be displayed on the output unit 210. Then, the presentation unit 209 causes the output unit 210 to output the third problem having the same difficulty level as the first problem.

Further, when the determination result of the state determination unit 208 is the state 3, the presentation unit 209 selects the response prompting the user to practice the problem solving faster than this time as the content to be displayed on the output unit 210. To do. Then, the presentation unit 209 causes the output unit 210 to output a display that prompts the user to solve the problem quickly. The reason why such a display is made is that when the user 100 is in the state 3, it is considered that the user 100 is in an unfamiliar state and requires practice. The presentation unit 209 determines a response that prompts the user 100 to focus on the next problem and promptly solve the problem, for example, a response that prompts a specific action such as “Let's solve the next problem”. You may.

Furthermore, when the determination result by the state determination unit 208 is the state 3, the presentation unit 209 sets the content displayed on the output unit 210 to the third problem of the same difficulty level as the first problem, or the first problem. Determine a fourth problem, which is simpler than the problem. Then, the presentation unit 209 causes the output unit 210 to output the third problem having the same difficulty level as the first problem or the fourth problem that is simpler than the first problem.

Further, when the determination result by the state determining unit 208 is the state 4, the presenting unit 209 selects a response prompting a break as the content to be displayed on the output unit 210. Then, the presentation unit 209 causes the output unit 210 to output a display prompting a break. The reason why such a display is performed is that when the user 100 is in state 4, it is considered that the user 100 is in an unfamiliar state and needs a break. The presentation unit 209 may determine a response that prompts a specific action, such as “let's solve the next problem after the break”, as the response that prompts the break. In addition, specific contents of the response prompting the break include, for example, contents and voice that allow the user 100 to relax.

Furthermore, the presentation unit 209 does not cause the output unit 210 to display a further problem when the determination result of the state determination unit 208 is state 4.

Further, in the above, in any of the states, the presentation unit 209 causes the output unit 210 to output both the question and the response, but either one may be output to the output unit 210.

FIG. 9 is a diagram showing a screen 300 displayed by the output unit 210 according to the display content determined in FIG.

The output unit 210 displays a screen 300 including a question display field 301, a response display field 302, an answer input field 303, and a correctness display field 304. The question selected by the presenting unit 209 is displayed in the question display field 301. In the answer input field 303, the answer entered by the user 100 is displayed. In addition, a plurality of options may be displayed in the answer input field 303. In this case, any one of the plurality of options is selected as the answer of the user 100 and displayed in the answer input field 303 in a mode different from the remaining options. The correct / incorrect display column 304 displays whether or not the user 100's answer to the displayed question was correct. The response display field 302 displays the response determined by the presentation unit 209. For example, when the state determining unit 208 determines that the user 100 is in the state 1, the response display field 302 displays a response of “good condition”. Further, the output unit 210 may display the next question according to the determination result by the state determination unit 208.

FIG. 10 is a flowchart showing the processing of the learning system 1000 according to the first embodiment.

The output unit 210 displays the question selected by the presentation unit 209 (step S300). At this time, the first problem is displayed in the problem display field 301 of the screen 300 shown in FIG.

The first signal determination unit 204 extracts, from the electroencephalogram measured by the electroencephalogram measurement unit 201, a first electroencephalogram within a time range defined starting from the time t1 of the question display shown in FIG. 4 (step S301). In this case, for example, the electroencephalogram measurement unit 201 constantly measures the electroencephalogram of the user 100 and records the electroencephalogram in time series. The first signal determination unit 204 extracts the first electroencephalogram from the recorded electroencephalogram.

Next, the first signal determination unit 204 determines, based on the first electroencephalogram extracted in step S301, whether or not the user 100 has the first inspiration for the question presentation in step S300 (step S302). This determination is performed according to the method of determining the presence or absence of the first inspiration by the above-described first signal determination unit 204. Further, the first signal determination unit 204 notifies the state determination unit 208 of this determination result.

Next, the user 100 inputs the answer to the question displayed in the question display field 301 on the screen 300 into the answer input field 303 on the screen 300. The input of this answer may be a selection from a plurality of options. By such an input of the answer by the user 100, the acquisition unit 206 acquires the answer and notifies the answer determination unit 207 (step S303).

Next, the answer determination unit 207 determines whether the answer is correct or incorrect (step S304). This determination is performed as shown in FIG. 6 described above. The answer determination unit 207 also notifies the state determination unit 208 of this determination result.

Next, the state determination unit 208 determines the state of the user 100 based on the presence or absence of the first inspiration and the correctness of the answer (step S305). This determination is performed as shown in FIG. Further, the state determining unit 208 notifies the presenting unit 209 of the determined state.

Next, the presentation unit 209 determines the content to be output by the output unit 210 based on the determination result of the state of the user 100 (step S306). The content to be output is performed as shown in FIG. 8 described above. At time t5 at which the correctness of the answer and the response shown in FIG. 4 are output, the correctness display field 304 and the response display field 302 in the screen 300 shown in FIG. Displayed in and. Furthermore, the following question may be displayed in the question display field 301.

Moreover, the processing of the learning system 1000 is not limited to the above, and the procedure may be changed. For example, steps S301 and S302 may be processed after steps S303 and 304. That is, the procedure of step S300, step S303, step S304, step S301, step S302, and step S305 may be used. That is, the process related to the first signal determination unit 204 (steps S301 and S302) may be performed after the process related to the acquisition unit 206 (step S303) and the process related to the answer determination unit 207 (step S304).

FIG. 11 is a flowchart of the learning method according to the first embodiment.

In the flowchart shown in FIG. 10, each component included in the learning system 1000 executes each process, but a computer device that executes a computer program may execute the learning method of the embodiment.

The learning method in the embodiment is a learning method using a learning system 1000 having a computer program and an output device. Then, in this learning method, the processes of steps S400 to S406 are executed.

The computer device outputs the first problem to the user 100 via the output device (step S400). The output device is a device corresponding to the output unit 210, and may be a display or a speaker.

The computer device acquires the first electroencephalogram of the user 100 (step S401).

The computer device determines the first inspiration of the user 100 based on the first brain wave starting from the time point when the first problem is output (step S402).

The computer device acquires the answer to the first question of the user 100 (step S403).

The computer device determines the correctness of the answer to the first question of the user 100 (step S404).

The computer device determines the state of the user 100 based on the presence or absence of the first inspiration and the correctness of the answer to the first question (step S405).

The computer device determines the contents to be output to the output device based on the determination result of the state of the user 100 (step S406).

[effect]
As described above, the learning system 1000 measures the output unit 210 that outputs the first question to the user 100, the acquisition unit 206 that acquires the answer of the user 100 to the first problem, and the electroencephalogram of the user 100. The brain wave measuring unit 201 and the control unit 200 are provided. The control unit 200 determines the presence / absence of the first inspiration of the user 100 based on the first brain wave included in (a) the brain wave and starting from the time point when the first problem is output. Further, the control unit 200 determines (b) whether the answer is correct or not, and (c) determines the content to be output to the output unit 210 based on the presence or absence of the first inspiration and the correctness, and outputs the content to the output unit 210. Output.

The learning system 1000 as described above determines the state of proficiency for the problem based on the answer to the problem of the user 100 and the electroencephalogram of the process of solving the problem, and then determines the content according to the state of the proficiency level. You can work on 100. That is, the user 100 can effectively improve the proficiency level.

Further, for example, the control unit 200 further causes the output unit 210 to output at least one of the next problem and the response, and the content is at least one of the problem and the response.

Such a learning system 1000 enables the user 100 to tackle at least one of a problem and a response according to the state of proficiency level. The user 100 can effectively improve the proficiency level.

Further, for example, the response is content that prompts the user 100 to take a break.

Such a learning system 1000 can prompt the user 100 to take a break in accordance with the state of proficiency. The user 100 can take a break effectively.

Further, for example, in (a), the control unit 200 extracts (a1) a theta wave band component of the first brain wave from the first brain wave, and (a2) based on the extracted theta wave band component. , The presence / absence of the first inspiration of the user 100 is determined.

The learning system 1000 as described above can determine a more detailed proficiency level by determining the presence or absence of the first inspiration of the user 100 based on the theta wave band component, and the content according to the state of the proficiency level. Can be made to work on the user 100. That is, the user 100 can effectively improve the proficiency level.

Further, for example, in (a1), the control unit 200 extracts the first electroencephalogram from the electroencephalogram in the time range of 200 msec or more and 2000 msec or less, starting from the time point when the first problem is output.

Such a learning system 1000 extracts the first electroencephalogram from the electroencephalogram in the time range of 200 msec or more and 2000 msec or less, starting from the time point when the first problem is output. Therefore, the learning system 1000 can determine a more detailed proficiency level and allow the user 100 to work on the content according to the proficiency level. The user 100 can effectively improve the proficiency level.

Further, for example, when the answer (d1) is a correct answer and there is the first inspiration, the control unit 200 causes the (e1) output unit 210 to output the second problem that is more difficult than the first problem.

Such a learning system 1000 allows the user 100 to tackle the second problem that is more difficult than the first problem according to the state of proficiency. The user 100 can effectively improve the proficiency level.

In addition, for example, when the answer (d2) is an incorrect answer and there is a first inspiration, the controller 200 causes the output unit 210 to output the third question having the same difficulty level as the first question (e2). ..

Such a learning system 1000 allows the user 100 to work on the third problem having the same difficulty level as the first problem according to the state of proficiency level. The user 100 can effectively improve the proficiency level.

Further, for example, when the answer (d3) is a correct answer and there is no first inspiration, the control unit 200 causes the output unit 210 to (e3) output the third problem of the same difficulty level as the first problem, or the Output one of the fourth problems, which is simpler than the first problem.

Such a learning system 1000 tackles the user 100 with either the third problem having the same difficulty level as the first problem or the fourth problem simpler than the first problem according to the state of proficiency. Can be made. The user 100 can effectively improve the proficiency level.

Further, for example, when the answer (d4) is an incorrect answer and there is no first inspiration, the control unit 200 causes the output unit 210 to (e4) output a fourth problem that is simpler than the first problem, or Output the content that encourages a break.

The learning system 1000 as described above can cause the user 100 to work on the fourth problem, which is easier than the first problem according to the state of proficiency, or prompt the user to take a break. The user 100 can effectively improve the proficiency level.

Further, for example, in (b), the control unit 200 refers to a database in which a plurality of questions associated with correct answers are stored and determines whether or not the answer is a correct answer. Further, in (e1), the control unit 200 refers to the database in which a plurality of questions associated with the degree of difficulty are stored, and causes the output unit 210 to output the second question.

Such a learning system 1000 refers to a database in which a plurality of questions associated with correct answers are stored to determine whether or not an answer is a correct answer, and a question associated with difficulty is Performing reference to multiple stored databases. As a result, the learning system 1000 can determine a more detailed proficiency level and allow the user 100 to tackle the second problem that is more difficult than the first problem according to the proficiency level. The user 100 can effectively improve the proficiency level.

Further, for example, in (b), the control unit 200 refers to a database in which a plurality of questions associated with correct answers are stored and determines whether or not the answer is a correct answer. Further, in (e2), the control unit 200 refers to the database that stores a plurality of questions associated with the difficulty levels, and causes the output unit 210 to output the third question.

Such a learning system 1000 refers to a database in which a plurality of questions associated with correct answers are stored to determine whether or not an answer is a correct answer, and a question associated with difficulty is Performing reference to multiple stored databases. Accordingly, the learning system 1000 can determine a more detailed proficiency level and allow the user 100 to work on the third problem having the same difficulty level as the first problem according to the proficiency level. The user 100 can effectively improve the proficiency level.

Further, for example, in (b), the control unit 200 refers to a database in which a plurality of questions associated with correct answers are stored and determines whether or not the answer is a correct answer. Further, in (e3), the control unit 200 refers to the database in which a plurality of problems associated with the difficulty levels are stored, and outputs either the third problem or the fourth problem to the output unit 210. Is output.

Such a learning system 1000 refers to a database in which a plurality of questions associated with correct answers are stored to determine whether or not an answer is a correct answer, and a question associated with difficulty is Performing reference to multiple stored databases. Accordingly, the learning system 1000 can determine a more detailed proficiency level, and the third problem having the same difficulty level as the first problem or the fourth problem that is simpler than the first problem according to the state of the proficiency level. The user 100 can be made to tackle any of the above problems. The user 100 can effectively improve the proficiency level.

Further, for example, in (b), the control unit 200 refers to a database in which a plurality of questions associated with correct answers are stored and determines whether or not the answer is a correct answer. Further, in (e4), the control unit 200 causes the output unit 210 to output the fourth question by referring to the database in which a plurality of questions associated with the difficulty levels are stored.

Such a learning system 1000 refers to a database in which a plurality of questions associated with correct answers are stored to determine whether or not an answer is a correct answer, and a question associated with difficulty is Performing reference to multiple stored databases. Accordingly, the learning system 1000 can determine a more detailed proficiency level, and can cause the user 100 to work on the fourth problem, which is easier than the first problem according to the proficiency level, or prompt the user to take a break. it can. The user 100 can effectively improve the proficiency level.

Further, for example, the control unit 200 has a processor and a memory, and the memory stores a program for executing (a), (b), and (c), and the processor has the memory. Execute a stored program.

Further, for example, the learning method executed by the computer such as the learning system 1000 includes a first output step of outputting the first question to the user 100 and an acquisition step of acquiring the answer of the user 100 to the first question. .. Further, the learning method executed by the computer such as the learning system 1000 includes an electroencephalogram measurement step of measuring the electroencephalogram of the user 100 and a control step. The control step includes (a) a first determination step of determining the presence / absence of a first inspiration of the user 100 based on a first electroencephalogram that is included in the electroencephalogram and starts from a time point when the first problem is output. , (B) a second determination step for determining the correctness of the answer. Further, the control step has (c) a second output step of determining the content to be output in the first output step based on the presence / absence of the first inspiration and correctness, and outputting the content.

In such a learning method, the state of proficiency level for the problem is determined based on the answer to the problem of the user 100 and the electroencephalogram for the process of solving the problem, and then the content according to the state of the proficiency level is set by the user 100. Can be worked on. That is, the user 100 can effectively improve the proficiency level.

Further, for example, the computer program that executes the learning system 1000 or the like is a computer program for executing the learning method. The computer program outputs the first question to the user 100 via the (f1) output device, (f2) obtains the answer of the user 100 to the first question, and (f3) measures the electroencephalogram of the user 100. Further, the computer program determines whether or not there is a first inspiration of the user 100 based on the first brain wave included in the (f4) brain wave and starting from the time point when the first problem is output, and (f5) ) Determine the correctness of the answer. Further, the computer program determines (f6) the content to be output by the output device based on the presence or absence of the first inspiration and the correctness, and causes the output device to output the content.

(Embodiment 2)
The second embodiment differs from the first embodiment in that the determination result of the second signal determination unit 205 is used to determine a more detailed state of the proficiency level of the user 100. In the first embodiment, when there is no first inspiration, it is difficult to determine the state of the proficiency level of the user 100 in detail after the elapse of the first brain wave time range. However, in the second embodiment, if there is no first inspiration in the first electroencephalogram, the presence or absence of the second inspiration is determined in the second electroencephalogram, and thus the user's proficiency level is more detailed. The state of can be determined. Accordingly, in the present embodiment, the content according to the proficiency level of the user 100 can be output in more detail to the output unit 210, so that the proficiency level of the user 100 can be improved more effectively. ..

[System configuration]
FIG. 12 is a diagram showing functional blocks of the learning system 1000A in the second embodiment. In the second embodiment, the same components as those in the first embodiment are designated by the same reference numerals, and detailed description thereof will be omitted.

The learning system 1000A according to the second embodiment includes a second signal determination unit 205 in addition to the first embodiment. Therefore, in the second embodiment, the first signal determination unit 204, the second signal determination unit 205, the answer determination unit 207, the state determination unit 208, and the presentation unit 209 are components included in the control unit 200. This control unit 200 is configured by, for example, at least one processor, as in the first embodiment.

The second signal determination unit 205 determines the presence or absence of the second inspiration of the user 100 based on the second electroencephalogram, which is included in the electroencephalogram and starts from the time when the problem is output. The second electroencephalogram is extracted from the electroencephalogram of the user 100 measured by the electroencephalogram measurement unit 201. The time when the problem is output is the time when the presentation unit 209 notifies the problem.

Specifically, the second signal determination unit 205 extracts, from the electroencephalogram, the second electroencephalogram starting from the time when the problem is output. Then, the first signal determination unit 204 determines the presence or absence of the second inspiration of the user 100 based on the second electroencephalogram. More specifically, the second signal determination unit 205 extracts the second electroencephalogram from the electroencephalogram after 2000 msec has elapsed, starting from the time when the problem was output. When there is the second inspiration, specifically, there is no reflexive inspiration immediately after the problem is output, but it indicates a psychological state in which there is an inspiration after the image of the problem content is made. Further, the second signal determination unit 205 notifies the state determination unit 208 of the presence / absence of the determined second inspiration and the timing at which the second inspiration occurs.

Also, theta waves included in the brain waves are used as the method for determining the presence or absence of the second inspiration, as in the method for determining the presence or absence of the first inspiration.

Further, the details of the method for determining the presence or absence of the second inspiration are described.

As described above, the second signal determination unit 205 determines the presence or absence of the second inspiration in the predetermined time range after the problem is displayed from the electroencephalogram of the user 100 measured by the electroencephalogram measurement unit 201. For example, the predetermined time range is a range about 2000 msec after the timing when the output unit 210 displays the problem, and the second electroencephalogram is extracted from the electroencephalogram in this time range. Further, the second signal determination unit 205 extracts a theta wave band component of the second brain wave from the second brain wave, and based on the extracted theta wave band component, the second inspiration of the user 100. Determine the presence or absence.

The second signal determination unit 205 determines the presence or absence of the second inspiration in the theta wave band component by using an index such as Vpp. For example, the second signal determination unit 205 determines that the second inspiration is present when Vpp in the second electroencephalogram of the user 100 is equal to or greater than the predetermined threshold. The predetermined threshold value is, for example, 10 μV, but is not limited to this. On the other hand, when Vpp is less than this predetermined threshold value, it is determined that there is no second inspiration.

The second signal determination unit 205 extracts the second electroencephalogram starting from the time when the problem is output, but the time range is not limited to the above. For example, the extraction start time may be 1000 msec or more and 4000 msec or less, preferably 1400 msec or more and 3000 msec or less, and more preferably 1500 msec or more and 2500 msec or less, starting from the time when the problem is output. Further, for example, the time to end the extraction may be 4000 msec or more and 10000 msec or less, preferably 5000 msec or more and 7000 msec or less, more preferably 5500 msec or more and 6500 msec or less, starting from the time when the problem is output. .. Further, as a matter of course, the time when the second signal determination unit 205 starts the extraction of the second brain wave needs to be after the time when the first signal determination unit 204 ends the first brain wave extraction.

[Operation example]
FIG. 13 is a diagram showing the timing of acquisition and display of the second electroencephalogram performed by the learning system 1000A shown in FIG.

The second signal determination unit 205 extracts, from the electroencephalogram measured by the electroencephalogram measurement unit 201, a second electroencephalogram having a time point when the problem is output, that is, a time point t1 when the problem is displayed as a starting point. The time when the problem is output is the time when the presentation unit 209 notifies the problem. The second electroencephalogram starting from the time t1 is an electroencephalogram in a time range between a time point 2000 msec after the time t1 (that is, t2) and a time point 4000 msec after the time t2 (that is, t3). Further, the second signal determination unit 205 determines the presence or absence of the second inspiration of the user 100 based on the second electroencephalogram. Specifically, the theta wave band component of the second electroencephalogram is extracted from the second electroencephalogram, and the presence or absence of the second inspiration of the user 100 is determined based on the extracted theta wave band component.

The acquisition unit 206 acquires the answer at the time when the answer to the question output at time t1 is acquired, that is, at the time t7 when the answer is input, and the timing at which the answer is acquired. In the first embodiment, as shown in FIG. 4, the answer input time t7 is later than the time t6 when the acquisition of the second electroencephalogram is completed, that is, t7> t6> t1. , The time t7 for answer input may be earlier than the time t6 when the acquisition of the second electroencephalogram is completed. That is, t6> t7> t1 may be satisfied. Further, the time t6 when the acquisition of the second electroencephalogram is completed and the time t7 when the answer is input may be the same, that is, t6 = t7.

The answer determination unit 207 determines whether the answer is correct at time t8. The time relationship between the time t8 for determining whether the answer is correct and the time t7 for inputting the answer may be t8> t6 as shown in FIG. 13, but is not limited to this.

The presentation unit 209 causes the output unit 210 to output the correctness of the answer and the response at time t9. Note that the time relationship between the time t9 at which the correctness of the answer and the response are output and the time t8 at which the correctness of the answer is determined may be t9> t8. Further, the presenting unit 209 may cause the output unit 210 to simultaneously output the next question in accordance with not only the correctness of the answer and the response but also the state determined by the state determining unit 208 at this time t9. Further, the presentation unit 209 may output the next question to the output unit 210 after the output unit 210 outputs the correctness of the answer and the response, not at the same time.

In addition, the time t7 at which the answer is input and the time t8 at which the correctness of the answer is determined are not particularly set, but are, for example, 100 msec to 10000 msec, preferably 1000 msec to 8000 msec, and more preferably 1500 msec to 5000 msec. is there. In addition, the time t8 for determining the correctness and the time t9 for outputting the correctness of the answer and the response are not particularly limited, but are, for example, 100 msec to 10000 msec, preferably 1000 msec to 8000 msec, and more preferably, It is 1500 msec to 5000 msec.

FIG. 14 is a flowchart showing the processing of the second signal determination unit 205.

The second signal determination unit 205 receives a signal regarding the electroencephalogram of the user 100 from the electroencephalogram measurement unit 201 (step S500). The signal contains brain waves, but may also contain noise. Note that noise sources include device noise from outside the human body, commercial AC noise, myoelectric noise from the human body, ocular noise from the human body, problem presentation, or movements unrelated to answer input. Various noises such as noise and background brain waves can be considered. Further, the number of noise sources is not limited to one, and two or more noise sources may be considered.

The second signal determination unit 205 performs noise removal processing on the received signal to extract a waveform including a specific frequency band (step S501). For example, the second signal determination unit 205 extracts an electroencephalogram including a specific frequency band by performing band limitation processing on the signal in a bandpass filter, for example, 2 Hz to 10 Hz. This removes noise.

Next, the second signal determination unit 205 receives information indicating the timing of presenting the question to the user 100 from the presentation unit 209 (step S502).

The second signal determination unit 205 cuts out an electroencephalogram signal within a predetermined time range from the signal relating to the electroencephalogram of the user 100 from which noise has been removed in step S501, starting from the timing indicated by the information received in step S102 (step S503). .. For example, the second signal determination unit 205 may cut out an electroencephalogram signal after 2000 msec, starting from the timing of displaying a question. This cut-out electroencephalogram signal is the second electroencephalogram.

The second signal determination unit 205 calculates the Vpp value for the theta wave component in the predetermined time range cut out in step S503 (step S504).

The second signal determination unit 205 determines whether Vpp calculated in step S504 is equal to or greater than a threshold value (step S505). The threshold value may be set using a predetermined value.

If the determination result of step S505 is YES, the second signal determining unit 205 determines that there is a second inspiration (step S506).

Further, if the determination result in step S505 is NO, the second signal determination unit 205 determines that there is no second inspiration (step S507).

Next, a method for determining the state of the proficiency level of the user 100 by using the presence or absence of the second inspiration and the timing when the second inspiration occurs will be described. Here, as an example, a case where there is no first inspiration is shown. That is, when there is no first inspiration, among the states determined by the state determination unit 208 shown in FIG. 7, the first inspiration is “none” and the answer is “correct answer”, and the third This is the case of the state 4 in which the inspiration of 1 is “none” and the answer is “wrong answer”.

In state 3 (no first inspiration and correct answer), if there is a second inspiration, there is no reflexive inspiration immediately after the question is output, but there is inspiration after the image of the content of the question is given. , Shows a low level of proficiency with the problem.

Also, in this case, pay attention to the timing when the second inspiration occurs. When the questions are given one after another and the timing at which the second inspiration for each question occurs is gradually advanced, it indicates that the skill level is gradually increased. On the other hand, when questions are asked one after another, if the timing at which the second inspiration for each question occurs is constant, or if the timing is gradually delayed, keep the proficiency level constant. Shows.

Further, in the state 3 (without the first inspiration and the answer is correct), when the second inspiration does not exist, there is no reflexive inspiration immediately after the question is output, and the inspiration does not occur even after the image of the question content is given. No, it indicates that the problem is insufficiently proficient.

Next, describe the case where there is a second inspiration in state 4 (the first inspiration is absent and the answer is incorrect). In this case, there is no reflexive inspiration immediately after the problem is output, and there is inspiration after the image of the content of the problem is displayed, but for the displayed problem, make a mistake in the calculation process or in the state of entry. Shows. That is, the user 100 is in a careless miss state.

Further, in state 4 (the first inspiration is not given and the answer is incorrect), when there is no second inspiration, there is no reflexive inspiration immediately after the question is output, and even after the image of the content of the question is given. There is no inspiration and it indicates that the displayed problem cannot be solved.

Note that, in the second embodiment, the first signal determination unit 204 and the second signal determination unit 205 are configured to operate independently of each other. However, whether or not the second signal determination unit 205 determines whether or not there is the second inspiration may be limited to the case where there is no first inspiration. That is, only when the first signal determination unit 204 determines that there is no first inspiration, the second signal determination unit 205 extracts the second brain wave starting from the time point when the problem is output, from the brain wave. You may. In that case, the first signal determination unit 204 notifies the second signal determination unit 205 that there is no first inspiration, and then the second signal determination unit 205 acquires the second brain wave. Then, the presence or absence of the second inspiration is determined.

[effect]
As described above, in the learning system 1000A, in addition to the learning system 1000, the control unit 200 performs the following operations. Following (a), the control unit 200 extracts the second electroencephalogram from the electroencephalogram in the time range after lapse of 2000 msec or more, starting from the time point when the (a3) first problem is output, and The presence or absence of the second inspiration of the user 100 is determined based on the electroencephalogram. Furthermore, the control unit 200 determines (b) whether the answer is correct or not, and in (c), based on (c1) the presence or absence of the first inspiration, the presence or absence of the second inspiration, and the correctness, the output unit 210. Determines the content to be output to and outputs the content to the output unit 210.

The learning system 1000A determines a more detailed proficiency level of the problem based on the answer to the problem of the user 100 and the electroencephalogram of the process of solving the problem, and then determines the proficiency level according to the proficiency level. It is possible for the user 100 to work on the contents. That is, the user 100 can improve the proficiency level more effectively.

(Embodiment 3)
In the third embodiment, the pulse wave measuring unit 202, the movement measuring unit 203, the authentication unit 211a, and the storage unit 211b are used to determine a more detailed state of the user 100. Different from the second embodiment. In the first and second embodiments, the state determination unit 208 determines the state of the user 100 (that is, the state of proficiency) based on the presence or absence of inspiration and the correctness of the answer. In the third embodiment, the state of the proficiency level of the user 100 is further determined because the state of the proficiency level of the user 100 is determined based on the pulse wave and the movement of the user 100. Further, the user 100 can be easily identified by authenticating the user 100. That is, in the third embodiment, the degree of proficiency is determined based on the presence or absence of the first inspiration, the presence or absence of the second inspiration, the correctness of the answer, and the pulse wave or the movement. As a result, it becomes possible to set the optimal question content according to the user 100, and to judge the presence or absence of inspiration with higher accuracy.

[System configuration]
FIG. 15 is a diagram showing functional blocks of the learning system 1000B in the third embodiment. In the third embodiment, the same components as those in the first and second embodiments are designated by the same reference numerals, and detailed description thereof will be omitted.

The learning system 1000B according to the third embodiment includes a pulse wave measuring unit 202, a motion measuring unit 203, an authentication unit 211a, and a storage unit 211b in addition to the second embodiment. Therefore, in the third embodiment, the control unit 200 includes the first signal determination unit 204, the second signal determination unit 205, the answer determination unit 207, the state determination unit 208, the presentation unit 209, the authentication unit 211a, and the storage unit 211b. Is a constituent element. The control unit 200 is composed of, for example, at least one processor, as in the first and second embodiments.

The pulse wave measuring unit 202 measures the pulse wave of the user 100. The pulse wave measuring unit 202 is realized by the electroencephalograph 102 and a partial function of the processor. As described above, the electroencephalograph 102 is attached to the user 100 and is prepared so that the pulse wave of the user 100 can be acquired. The pulse wave measuring unit 202 is included in the electroencephalograph 102, and more specifically, is installed in the base unit 102b shown in FIG. The pulse wave measurement unit 202 also includes a light source and a photodetector. The method for measuring the pulse wave is as follows. A light source (for example, an infrared light emitting diode) emits light, a photodetector (for example, a photodiode) receives the light transmitted through the earlobe, and outputs an electric signal corresponding to the intensity of the received light. The intensity of the light absorbed in the earlobe changes according to the blood flow rate (the number of hemoglobin) in the blood vessel that changes with time according to the heartbeat of the user 100, and thus the intensity of the transmitted light. Change is used to measure the pulse wave of the user 100, for example. That is, the pulse wave measuring unit 202 in this example functions as a transmission type pulse wave meter. Further, the pulse wave measuring unit 202 outputs an electric signal regarding the pulse wave to the authentication unit 211a.

The movement measuring unit 203 measures the movement of the user 100. The movement measuring unit 203 is realized by the electroencephalograph 102 and a part of the functions of the processor. As described above, the electroencephalograph 102 is attached to the user 100 and is prepared so that the movement of the user 100 can be acquired. The motion measuring unit 203 is included in the electroencephalograph 102, and more specifically, is installed in the base unit 102b shown in FIG. Further, the motion measuring unit 203 is configured by a three-dimensional acceleration sensor, and / or a three-dimensional gyro sensor (angular velocity sensor), etc., and detects a motion to accelerate the acceleration and / or the angular velocity and / or The motion signal indicating the angular acceleration is output to the state determination unit 208.

The authentication unit 211a identifies the user 100 who is currently using the learning system 1000B. Specifically, the authentication unit 211a identifies the user 100 according to the electrical signal regarding the pulse wave obtained from the pulse wave measurement unit 202. Although a detailed method for specifying will be described later, the authentication unit 211a uses and uses the database regarding the user 100 specified in the storage unit 211b and the pulse wave obtained from the pulse wave measurement unit 202. It is specified as the inside user 100.

The storage unit 211b records a database regarding the identification of the user 100. Specifically, the storage unit 211b is configured by the RAM 107. When requested by the authentication unit 211a, the storage unit 211b provides the authentication unit 211a with a database regarding the identification of the user 100. Further, the information regarding the identification of the user 100 may be a database in which the name of the user 100 and / or the ID of the user 100 and the pulse wave of the user 100 are associated with each other.

[motion]
FIG. 16 is a flowchart showing the processing of the authentication unit 211a according to the third embodiment. The method by which the authentication unit 211a authenticates and determines the user 100 currently in use is shown below.

The authentication unit 211a acquires the pulse wave acquired by the pulse wave measurement unit 202 (step S600).

The authentication unit 211a refers to the database regarding the identification of the user 100 recorded in the storage unit 211b (step S601).

Next, the authentication unit 211a collates the electroencephalogram obtained in step S600 with the database relating to the identification of the user 100 referred to in step S601 (step S602). For example, the database regarding the identification of the user 100 is a database in which the name of the user 100 and the pulse wave of the user 100 are associated with each other, and the user 100 that matches the pulse wave obtained from the pulse wave measurement unit 202 is checked.

Finally, the user 100 that matches the pulse wave obtained from the pulse wave measuring unit 202 is determined as the user 100 currently in use (step S603).

FIG. 17 is a diagram showing states determined by the state determination unit 208 according to the third embodiment. The state determination unit 208 determines whether the first inspiration is determined by the first signal determination unit 204 (whether or not the inspiration is present), the correctness (correctness / incorrectness) of the answer determined by the answer determination unit 207, and the motion measurement. The unit 203 determines the state of the user 100. State 1, state 2, state 3, and state 4 are determined in the same manner as in the first embodiment, and therefore are newly added depending on the presence / absence of the second inspiration determined by the motion measuring unit 203 and the second signal determining unit 205. The added state 5 will be described in detail.

Like the first embodiment, the state determination unit 208 determines the state of the user 100 to be state 3 when the first inspiration is “none” and the answer is “correct”. Furthermore, the state determination unit 208 determines the state of the user 100 as the state 5 when the second inspiration is “present” and the acceleration output by the motion measurement unit 203 is less than the threshold value. More specifically, the threshold regarding the acceleration output by the motion measuring unit 203 is, for example, 3G, but is not limited to this. For example, it may be between 0G and 6G. In addition, the acceleration output by the motion measuring unit 203 is less than the threshold value means that the sway of the head of the user 100 having a low proficiency level has subsided, the posture is correct, and the proficiency level gradually improves. Indicates that

In other words, in this state 5, there is no reflexive inspiration for the displayed problem, but there is inspiration after the image of the content of the problem is present, the answer is correct, and the shaking of the head is suppressed. It shows a state where the proficiency level is insufficient for the given problem. That is, the user 100 is in a state of being unfamiliar and requiring practice. On the other hand, as compared with the state 3, the second inspiration is “present”, and the acceleration output from the motion measuring unit 203 is less than the threshold value, which indicates that the proficiency level is gradually increasing. There is.

Further, the state determining unit 208 may determine the state of the user 100 using the pulse wave of the user 100 obtained by the pulse wave measuring unit 202. For example, the state determination unit 208 may determine the state of the user 100 by using the pulse wave of the user 100 from the time when the first problem is output to 2000 msec. When the problem displayed by the output unit 210 is a problem that the user 100 feels difficult, the user 100 is upset and the pulse obtained from the pulse wave becomes faster. That is, the state determination unit 208 determines that the proficiency level of the user 100 is low. On the other hand, when the problem displayed by the output unit 210 is a problem that the user 100 feels easy, the user 100 relaxes and becomes a pulse wave in normal times. That is, the state determination unit 208 determines that the proficiency level of the user 100 is high.

FIG. 18 is a diagram showing processing of the presentation unit 209 corresponding to each state in the third embodiment. The presentation unit 209 selects the content to be displayed on the output unit 210 according to the determination result by the state determination unit 208. Further, as shown in FIG. 17, since the display of the state 1, the state 2, the state 3, and the state 4 is the same as that of the first embodiment, the details of the state 5 newly added by the motion measuring unit 203 will be described. State.

Specifically, when the determination result of the state determining unit 208 is state 5, the presenting unit 209 provides a response prompting to solve the problem next time as the content to be displayed on the output unit 210 next time. select. Then, the presentation unit 209 causes the output unit 210 to output a display that prompts the user to solve the problem quickly. The reason why such a display is performed is that when the user 100 is in the state 5, it is considered that the user 100 is in an unskilled state and needs to practice. The presentation unit 209 may select, as the response to promptly solve the problem, a response to prompt a specific action such as “Let's solve the next problem”.

Furthermore, when the determination result by the state determination unit 208 is the state 5, the presentation unit 209 sets the content displayed on the output unit 210 to the third problem having the same difficulty level as the first problem, or the first problem. Select the fourth problem, which is simpler than the problem. Then, the presentation unit 209 causes the output unit 210 to output the third problem having the same difficulty level as the first problem or the fourth problem that is simpler than the first problem.

Further, the presentation unit 209 may select the content to be displayed on the output unit 210 according to the state determined by the state determination unit 208 based on the pulse wave of the user 100. For example, when the problem displayed by the output unit 210 is a problem that the user 100 feels difficult, the user 100 is upset and the pulse obtained from the pulse wave becomes faster. In this case, the state determination unit 208 determines that the proficiency level is low, and the presentation unit 209 further selects the third problem having the same difficulty level as the first problem as the content to be displayed on the output unit 210. .. On the other hand, when the problem displayed by the output unit 210 is a problem that the user 100 feels easy, the user 100 relaxes and becomes a pulse wave in normal times. In this case, the state determination unit 208 determines that the skill level is high, and the presentation unit 209 further selects the second problem having a higher difficulty level than the first problem as the content to be displayed on the output unit 210. ..

Here, describe the method for improving the accuracy of the determination of the presence of further inspiration. The first signal determination unit 204 in the first embodiment, and the first signal determination unit 204 and the second signal determination unit 205 in the second embodiment are based on the first electroencephalogram or the second electroencephalogram. , Determine the presence of inspiration. Furthermore, the first signal determination unit 204 and the second signal determination unit 205 have the inspiration if the Vpp of the first electroencephalogram or theta wave included in the second electroencephalogram is equal to or greater than the threshold, and is less than the threshold. If there is, there is no inspiration. However, it is assumed that this threshold value varies depending on the individual user 100, and that the same user 100 varies depending on the daily psychological state. Therefore, the threshold value corresponding to each user 100 may be determined before the question is asked. By doing so, the accuracy of determination of the presence or absence of inspiration improves. Specifically, the following method is used.

FIG. 19 is a flowchart showing a method of improving the accuracy of the determination of the presence or absence of inspiration in the third embodiment.

Before the problem is posed, the user 100 is authenticated using the pulse wave measurement unit 202, the authentication unit 211a, and the storage unit 211b as shown in FIG. 16 (step S700).

The presentation unit 209 causes the output unit 210 to output a problem for determining a threshold different from the first problem (step S701). At this time, the question for determining the threshold value is displayed in the question display field 301 of the screen 300 shown in FIG. The problem for deciding the threshold is a problem that the learner with a very low proficiency can answer correctly.

The first signal determination unit 204 extracts the first electroencephalogram for the problem for determining the threshold from the electroencephalogram measured by the electroencephalogram measurement unit 201 (step S702).

Next, the first signal determination unit 204 extracts the theta waveform of the user 100 for the question presentation in step S701 based on the first electroencephalogram extracted in step S702 and notifies the state determination unit 208 (step S703). ).

Next, the user 100 inputs the answer to the question displayed in the question display field 301 on the screen 300 into the answer input field 303 on the screen 300. Regarding the input of the answer, the acquisition unit 206 acquires the answer by the input of the answer by the user 100 and notifies the answer determination unit 207 (step S704).

Next, the answer determination unit 207 refers to the database, and with respect to the received answer, refers to the database in which a plurality of questions stored in the ROM 105 and associated with the correct answer are stored, and determines whether the answer matches the correct answer. (Step S705).

Further, if the determination in step S705 is YES, the first signal determination unit 204 determines a threshold value for determining the presence or absence of the first inspiration based on the theta waveform extracted in step 703 (step S706).

If the determination in step S705 is NO, nothing is executed and the process returns to step S701 again (step S707).

As mentioned above, even a learner with a very low level of proficiency can be expected to have inspiration by giving a question of a difficulty level that can be answered correctly. In other words, the waveform of the theta wave obtained at that time is a waveform indicating that the user 100 in use has an inspiration. By determining the threshold value for determining the presence or absence of the inspiration corresponding to each user 100 based on the waveform of the theta wave, the presence or absence of the inspiration can be determined with higher accuracy.

Note that the method for improving the accuracy of the determination of the presence of further inspiration using other methods will be described. For example, it is effective to apply a method for determining the presence or absence of inspiration using machine learning or the like. As a concrete method, there is a method of asking a question to many learners and extracting the theta waves of the learners by using the above method. The theta wave obtained at this time is a theta wave in the case of inspiration. By targeting a large number of learners, it is possible to obtain a large number of theta waves associated with the inspiration. By using this result, it becomes possible to easily select the threshold value for determining the presence or absence of inspiration.

[effect]
As described above, the learning system 1000B includes the pulse wave measuring unit 202 that measures the pulse wave of the user 100 and the motion measuring unit 203 that measures the motion of the user 100, in addition to the learning system 1000A. In (c1), the control unit 200 determines the content based on the presence / absence of the first inspiration, the presence / absence of the second inspiration, the pulse wave, and / or the operation.

The learning system 1000B determines a more detailed state of proficiency with respect to the problem based on the answer to the problem of the user 100, the electroencephalogram for the process of solving the problem, the pulse wave, and the motion, and then The user 100 can be made to work on the content according to the state of proficiency level. That is, the user 100 can improve the proficiency level more effectively.

Further, for example, the control unit 200 authenticates the user 100 based on the pulse wave.

Such a learning system 1000B can easily identify individual users 100. The history of questions and answers about the user 100 can be easily managed.

(Other embodiments)
The learning system 1000, the learning system 1000A, and the learning system 1000B according to the first, second, and third embodiments include the terminal device 101 and the electroencephalograph 102. The configuration is not limited to this.

FIG. 20 is a diagram showing another example of the external configuration of the learning system in the embodiment.

In this example, the learning system 1000C includes an electroencephalograph 102, a terminal device 101, and a server 112. The terminal device 101 and the server 112 function as the terminal device 101 of the first, second, and third embodiments by communicating via the wireless device 110 and the Internet 111. In this case, the terminal device 101 may include at least one of the plurality of components included in the terminal device 101, and the server 112 may include the remaining components. For example, the terminal device 101 may include the acquisition unit 206 and the output unit 210, and the server 112 may include the control unit 200. Even with such a learning system 1000C, the same learning method as that of the learning system according to the first, second, and third embodiments can be performed.

That is, in the example shown in FIG. 20, the processing of the learning method is not closed in the terminal device 101, and the terminal device 101 and the server 112 communicate with each other via the wireless device 110 and the Internet 111 while the learning method is performed. Performs various included processes.

In the embodiment, all or part of the units, devices, members, or parts, or all of the functional blocks in the block diagrams shown in FIGS. 2, 3, 12, and 15, or Some may be performed by: These may be executed by one or a plurality of electronic circuits including, for example, a semiconductor device, a semiconductor integrated circuit (IC (Integrated Circuit)), or a large-scale integrated circuit (LSI (Large Scale Integration)). .. The IC or LSI may be integrated in one chip (system LSI), or may be configured by combining a plurality of chips into one system (chip set). For example, the functional blocks other than the screen display processing may be integrated in one chip. Here, it is called IC or LSI, but the name may be changed depending on the degree of integration, and may be called VLSI (Very Large Scale Integration) or ULSI (Ultra Large Scale Integration). A system LSI equipped with an electronic fuse (eFuse) that is programmed after the LSI is manufactured, a FPGA (Field Programmable Gate Array), or a reconfiguration of the connection relationship inside the LSI, or a dynamic logic circuit inside the LSI. A reconfigurable device that can be reconfigured can also be used for the same purpose.

Furthermore, all or some of the functions, or operations of the units, devices, members, or parts can be executed by software processing. In this case, the software is recorded in a non-transitory recording medium such as one or more ROMs, optical disks, hard disk drives, etc., and the software is a microcontroller (MCU (micro controller)) or a microprocessor (MPU (MPU). When executed by a processing device such as a microprocessor), the functions specified by the software are executed by the processing device and peripheral devices. The system or apparatus may include one or a plurality of non-transitory recording media in which software is recorded, a processing device, and required hardware devices such as a digital interface.

Further, the control unit 200 in each of the above-described embodiments has a processor and a memory, and the memory has a flowchart shown in FIG. 5, FIG. 10, FIG. 11, FIG. 14, FIG. 16, or FIG. A program for executing each step of may be stored. In this case, the processor executes the program stored in that memory.

100 user 200 control unit 201 brain wave measuring unit 202 pulse wave measuring unit 203 motion measuring unit 206 acquisition unit 210 output unit 300

screen

1000, 1000A, 1000B, 1000C learning system

Claims

An output unit that outputs the first problem to the user,
An acquisition unit that acquires the user's answer to the first problem;
An electroencephalogram measuring unit for measuring the electroencephalogram of the user,
And a control unit,
The control unit is
(A) Based on a first electroencephalogram that is included in the electroencephalogram and has a time point when the first problem is output as a starting point, the presence or absence of the first inspiration of the user is determined,
(B) Determine the correctness of the answer,
(C) A learning system in which the content to be output to the output unit is determined based on the presence or absence of the first inspiration and the correctness, and the content is output to the output unit.
The control unit further causes the output unit to output at least one of a problem next to the first problem and a response,
The learning system according to claim 1, wherein the content is at least one of the next problem and the response.
The learning system according to claim 2, wherein the response is the content prompting the user to take a break.
The control unit is
In the above (a),
(A1) extracting a theta wave band component of the first electroencephalogram from the first electroencephalogram,
The learning system according to claim 1, wherein (a2) the presence or absence of the first inspiration of the user is determined based on the extracted component of the theta wave band.
The control unit is
The learning system according to claim 4, wherein in (a1), the first electroencephalogram is extracted from the electroencephalogram in a time range of 200 msec or more and 2000 msec or less, starting from a time point when the first problem is output.
The control unit is
Following (a) above,
(A3) A second electroencephalogram is extracted from the electroencephalogram in a time range after a lapse of 2000 msec or more, starting from the time point when the first problem is output, and the second electroencephalogram of the user is extracted based on the second electroencephalogram. Determine the presence of 2 inspiration,
(B) Determine the correctness of the answer,
In (c) above,
(C1) The content to be output to the output unit is determined based on the presence or absence of the first inspiration, the presence or absence of the second inspiration, and the correctness, and the content is output to the output unit. The learning system according to any one of 1 to 5.
The learning system further comprises:
A pulse wave measuring unit that measures the pulse wave of the user,
And a motion measuring unit that measures the motion of the user,
The control unit is
In (c1) above,
The learning system according to claim 6, wherein the content is determined based on the presence / absence of the first inspiration, the presence / absence of the second inspiration, the pulse wave, and / or at least one of the operations.
The control unit is
The learning system according to claim 7, wherein the user is authenticated based on the pulse wave.
The control unit is
(D1) When the answer is a correct answer and the first inspiration is present,
(E1) The learning system according to any one of claims 1 to 8, wherein the output unit outputs a second problem that is more difficult than the first problem.
The control unit is
(D2) When the answer is a wrong answer and there is the first inspiration,
(E2) The learning system according to any one of claims 1 to 8, wherein the output unit outputs a third problem having the same degree of difficulty as the first problem.
The control unit is
(D3) If the answer is correct and there is no first inspiration,
(E3) Either of the third problem having the same difficulty level as the first problem or the fourth problem simpler than the first problem is output to the output unit. The learning system according to item 1.
The control unit is
(D4) If the answer is a wrong answer and there is no first inspiration,
(E4) The learning system according to any one of claims 1 to 8, wherein the output unit outputs a fourth problem that is simpler than the first problem or a content that prompts the break.
The control unit is
In (b), it is determined whether or not the answer is a correct answer by referring to a database in which a plurality of questions associated with the correct answer are stored.
The learning system according to claim 9, wherein in (e1), the output unit outputs the second question by referring to a database in which a plurality of questions associated with a difficulty level are stored.
The control unit is
In (b), it is determined whether or not the answer is a correct answer by referring to a database in which a plurality of questions associated with the correct answer are stored.
The learning system according to claim 10, wherein in (e2), the output unit outputs the third question by referring to a database in which a plurality of questions associated with the degree of difficulty are stored.
The control unit is
In (b), it is determined whether or not the answer is a correct answer by referring to a database in which a plurality of questions associated with the correct answer are stored.
In (e3), the output unit is caused to output either the third problem or the fourth problem by referring to a database in which a plurality of problems associated with the degree of difficulty are stored. The learning system according to Item 11.
The control unit is
In (b), it is determined whether or not the answer is a correct answer by referring to a database in which a plurality of questions associated with the correct answer are stored.
The learning system according to claim 12, wherein, in (e4), the output unit outputs the fourth question by referring to a database in which a plurality of questions associated with the degree of difficulty are stored.
The control unit has a processor and a memory,
A program for executing the above (a), the above (b), and the above (c) is stored in the memory,
The learning system according to claim 1, wherein the processor executes a program stored in the memory.
A first output step of outputting the first problem to the user,
An acquisition step of acquiring the user's answer to the first question;
An electroencephalogram measuring step of measuring the electroencephalogram of the user,
Including a control step,
The control step is
(A) a first determination step of determining the presence or absence of a first inspiration of the user based on a first electroencephalogram, which is included in the electroencephalogram and has a time point when the first problem is output as a starting point,
(B) a second determination step of determining whether the answer is correct or incorrect;
(C) A learning method, comprising: determining the content to be output in the first output step based on the presence or absence of the first inspiration and the correctness, and outputting the content in the second output step.
A computer program for performing the learning method, comprising:
(F1) outputting the first problem to the user via the output device,
(F2) obtaining the user's answer to the first question,
(F3) measuring the electroencephalogram of the user,
(F4) The presence or absence of the first inspiration of the user is determined based on the first electroencephalogram, which is included in the electroencephalogram and starts from the time point when the first problem is output,
(F5) Determine the correctness of the answer,
(F6) A computer program that causes a computer to determine the content to be output by the output device based on the presence or absence of the first inspiration and the correctness, and to cause the computer to output the content.