Concentration degree characteristic determination device and concentration degree characteristic determination method

Abstract

To provide a concentration degree characteristic determination device and a concentration degree characteristic determination method capable of performing learning support having a high effect corresponding to trainee's characteristics.SOLUTION: According to the present disclosure, a concentration degree characteristic determination device includes: a concentration level calculation unit configured to calculate a concentration level indicating a level of a concentration degree during a lecture of a trainee on the basis of biological information of the trainee; a concentration degree characteristic determination unit configured to calculate, on the basis of time series of the concentration degree, a concentration rate indicating a time taken until which the concentration level becomes a high concentration degree equal to or more than a predetermined threshold, and a concentration length indicating a time for which a state of the high concentration degree continues, and determine concentration degree characteristics during the lecture of the trainee; a learning execution information acquisition unit configured to acquire learning execution information on learning execution of the trainee; a trainee identification unit for identifying the trainee; and a presentation control unit configured to perform control for presenting the trainee, the concentration degree characteristics and the learning execution information in association with each other.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a concentration characteristic determination device and a concentration characteristic determination method for determining the concentration characteristic of a student taking online learning. [Background technology]

[0002] A technology has been disclosed for determining a student's level of understanding of a question based on image information of the student taking online learning, the time it took the student to answer the question, the scoring results for the answer, and the student's level of concentration on the question (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2021-81457 Summary of the Invention [Problem to be solved by the invention]

[0004] In Patent Document 1, the level of understanding is judged based on the level of concentration, but there is room for improvement in how concentration is used in order to provide detailed and effective learning support tailored to the characteristics of each student.

[0005] The present disclosure has been made to solve such problems, and aims to provide a concentration characteristic determination device and a concentration characteristic determination method that are capable of providing highly effective learning support tailored to the characteristics of students. [Means for solving the problem]

[0006] In order to solve the above problems, the concentration characteristic determination device disclosed herein comprises a concentration height calculation unit that calculates a concentration height indicating the level of concentration of the student while attending a class based on the student's biometric information, a concentration characteristic determination unit that calculates a concentration speed indicating the time it takes for the concentration height to reach a high concentration level above a predetermined threshold and a concentration length indicating the time the high concentration state continues based on a time series of the concentration level, and determines the concentration characteristics of the student while attending a class, a learning implementation information acquisition unit that acquires learning implementation information regarding the student's learning implementation, a student identification unit that identifies the student, and a presentation control unit that controls the presentation of the student, concentration characteristics, and learning implementation information in association with each other. [Effects of the Invention]

[0007] According to the present disclosure, it is possible to provide highly effective learning support tailored to the characteristics of students. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a block diagram showing an example of the configuration of a concentration characteristic determination device according to a first embodiment. [Figure 2] 4 is a flowchart showing an example of the operation of the concentration characteristic determination device according to the first embodiment. [Figure 3] FIG. 4 is a diagram for explaining a concentration height according to the first embodiment. [Figure 4] 4 is a diagram for explaining the concentration speed and concentration length according to the first embodiment. FIG. [Figure 5] FIG. 3 is a diagram for explaining categorization of concentration characteristics according to the first embodiment. [Figure 6] FIG. 10 is a diagram showing an example of a presentation to students according to the first embodiment. [Figure 7] FIG. 10 is a diagram showing an example of a presentation to students according to the first embodiment. [Figure 8] FIG. 10 is a diagram showing an example of a presentation to students according to the first embodiment. [Figure 9] FIG. 10 is a diagram showing an example of a presentation to students according to the first embodiment. [Figure 10]FIG. 10 is a diagram showing an example of a presentation to students according to the first embodiment. [Figure 11] FIG. 10 is a diagram for explaining a concentrated loss section according to the first modification of the first embodiment. [Figure 12] FIG. 10 is a block diagram showing an example of the configuration of a concentration characteristic determination device according to a second modification of the first embodiment. [Figure 13] 10 is a flowchart showing an example of the operation of the concentration characteristic determination device according to the second modification of the first embodiment. [Figure 14] FIG. 10 is a diagram showing an example of a presentation to students according to the second modification of the first embodiment. [Figure 15] FIG. 10 is a diagram showing an example of a presentation to students according to the second modification of the first embodiment. [Figure 16] FIG. 10 is a diagram showing an example of a presentation to students according to the second modification of the first embodiment. [Figure 17] FIG. 10 is a diagram showing an example of a presentation to students according to the second modification of the first embodiment. [Figure 18] FIG. 10 is a diagram showing an example of a presentation to students according to the second modification of the first embodiment. [Figure 19] FIG. 10 is a block diagram showing an example of the configuration of a concentration characteristic determination device according to a second embodiment. [Figure 20] 10 is a flowchart showing an example of the operation of the concentration characteristic determination device according to the second embodiment. [Figure 21] FIG. 10 is a block diagram showing an example of the configuration of a concentration characteristic determination device according to a modified example of the second embodiment. [Figure 22] FIG. 11 is a block diagram showing an example of the configuration of a concentration characteristic determination device according to a third embodiment. [Figure 23] FIG. 11 is a diagram showing an example of presentation to a third party according to the third embodiment. [Figure 24] FIG. 10 is a block diagram showing an example of the configuration of a concentration characteristic determination device according to a fourth embodiment. [Figure 25] 10 is a flowchart showing an example of the operation of the concentration characteristic determination device according to the fourth embodiment. [Figure 26]FIG. 11 is a block diagram showing an example of the configuration of a concentration characteristic determination device according to a fifth embodiment. [Figure 27] 13 is a flowchart showing an example of the operation of the concentration characteristic determination device according to the fifth embodiment. [Figure 28] FIG. 13 is a diagram showing an example of presentation according to the fifth embodiment. [Figure 29] FIG. 13 is a diagram showing an example of presentation according to the fifth embodiment. [Figure 30] FIG. 1 is a diagram illustrating an example of a hardware configuration of a concentration characteristic determination device according to first to fifth embodiments. [Figure 31] FIG. 1 is a diagram illustrating an example of a hardware configuration of a concentration characteristic determination device according to first to fifth embodiments. DETAILED DESCRIPTION OF THE INVENTION

[0009] <First Embodiment> <Configuration> 1 is a block diagram showing an example of the configuration of a concentration characteristic determination device 1 according to embodiment 1. The concentration characteristic determination device 1 includes a concentration height calculation unit 2, a concentration characteristic determination unit 3, a learning implementation information acquisition unit 4, a student identification unit 5, and a presentation control unit 6. The concentration characteristic determination device 1 is also communicatively connected to a sensing device 7 and a presentation unit 8.

[0010] The concentration height calculation unit 2 acquires biometric information of students taking online classes from the sensing device 7. Then, the concentration height calculation unit 2 calculates a "concentration height" that indicates the level of concentration of the students during the class based on the biometric information.

[0011] The sensing device 7 acquires biometric information of the student and transmits it to the concentration height calculation unit 2. Examples of the sensing device 7 include non-contact sensors such as a camera and a millimeter wave sensor, or wearable devices such as a smart watch and headgear. The sensing device 7 acquires biometric information such as the student's facial expression, movement, heart rate, respiratory rate, blood pressure, and brain waves using known technology.

[0012] Based on the time series of concentration levels, the concentration characteristic determination unit 3 calculates a "concentration speed" that indicates the time it takes for the concentration level to reach a high level of concentration equal to or greater than a predetermined threshold, and a "concentration length" that indicates the time the high concentration state continues. Furthermore, the concentration characteristic determination unit 3 determines the concentration characteristics of the student during the course based on the concentration level, concentration speed, and concentration length. The concentration characteristic determination unit 3 outputs the concentration characteristics, the learning implementation information acquired by the learning implementation information acquisition unit 4, and information on the student identified by the student identification unit 5 to the presentation control unit 6.

[0013] The learning implementation information acquisition unit 4 acquires learning implementation information related to the student's learning. Specifically, the learning implementation information acquisition unit 4 acquires learning implementation information related to online learning from the learning management system of the online learning provider. The learning implementation information includes the subject, unit, implementation page, implementation date and time, and implementation time related to the learning implementation of the online learning content (taking online learning). The learning implementation information acquisition unit 4 outputs the acquired learning implementation information to the concentration characteristic determination unit 3. The learning implementation information acquisition unit 4 may also output the learning implementation information to the presentation control unit 6.

[0014] The student identification unit 5 identifies students taking online learning courses. Methods for identifying students include inputting information for identifying the students (user ID, password, etc.) using the presentation unit 8, or performing personal authentication using biometric information of the students acquired by the sensing device 7. The student identification unit 5 outputs information about the identified students to the concentration characteristic determination unit 3. The student identification unit 5 may also output information about the identified students to the presentation control unit 6.

[0015] The presentation control unit 6 controls the presentation unit 8 to associate and present the student, concentration characteristics, and learning implementation information. Specifically, the presentation control unit 6 controls the presentation unit 8 to present the student's concentration characteristics during online learning to the student identified by the student identification unit 5.

[0016] The presentation unit 8 (student-side interface) presents the concentration characteristics of the student determined by the concentration characteristic determination unit 3. The presentation unit 8 also makes presentations in response to operations by the student.

[0017] 1, the sensing device 7 and the presentation unit 8 are installed on a terminal owned by the student, etc. Furthermore, each component constituting the concentration characteristic determination device 1 may be arranged as a component of the terminal owned by the student or the cloud server, or may be distributed across the terminal owned by the student and the cloud server, taking into consideration the performance of the terminal owned by the student, the amount of biometric information data transmitted by the sensing device 7, the communication bandwidth for transmitting the biometric information, and the level of processing load on the cloud server.

[0018] <Operation> 2 is a flowchart showing an example of the operation of the concentration characteristic determination device 1 according to embodiment 1. The online learning content that a student takes is specific content according to the student's attributes, the course unit, and the date and time of the course, but the student may also select the content.

[0019] When a student starts taking a class (T=t0), in step S101, the concentration height calculation unit 2 determines whether or not the student's biometric information has been acquired from the sensing device 7. The process of step S101 is repeated until the biometric information has been acquired, and if the biometric information has been acquired, the process proceeds to step S102.

[0020] In step S102, the concentration height calculation unit 2 determines whether or not the concentration height has been calculated based on the biological information. If the concentration height has been calculated, the process proceeds to step S103. On the other hand, if the concentration height has not been calculated, the process returns to step S101.

[0021] In step S103, the concentration characteristic determination unit 3 determines whether or not the concentration speed and concentration length have been calculated based on the time series of the concentration level. If the concentration speed and concentration length have been calculated, the process proceeds to step S104. On the other hand, if the concentration speed and concentration length have not been calculated, the process returns to step S101.

[0022] In step S104, the concentration characteristic determination device 1 determines whether or not the online learning has ended. If the online learning has ended (T=t1), the process proceeds to step S105. On the other hand, if the online learning has not ended, the process returns to step S101.

[0023] In step S105, the concentration characteristic determination unit 3 determines the concentration characteristics of the student during the class based on the concentration height, concentration speed, and concentration length.

[0024] In step S106, the learning implementation information acquisition unit 4 acquires learning implementation information related to online learning from the learning management system of the online learning provider.

[0025] In step S107, the student identification unit 5 identifies students who will take the online learning course.

[0026] In step S108, the presentation control unit 6 controls the presentation unit 8 to present the determination result of the concentration characteristic determination unit 3 (the concentration characteristics of the student during online learning) to the student identified by the student identification unit 5. The presentation unit 8 presents the concentration characteristics of the student during online learning to the student in accordance with the instructions of the presentation control unit 6.

[0027] <Calculation of concentration height, concentration speed, and concentration length> Figure 3 is a diagram for explaining concentration height. In Figure 3, the horizontal axis represents time (the time from the start of online learning T=t0 to the end T=t1), and the vertical axis represents the concentration level. The concentration level at a certain time corresponds to the concentration height.

[0028] The concentration level calculation unit 2 determines the student's drowsiness and alertness based on biological information acquired from a sensing device 7 installed near the student, and calculates the concentration level based on the drowsiness and alertness. Specifically, the concentration level calculation unit 2 determines the student's drowsiness and alertness based on any one or any combination of the student's facial direction, gaze state, eye opening state, mouth movement, facial expression, movement, terminal operation, heart rate, and brain waves.

[0029] Here, "facial direction and gaze status" includes whether the student is looking at the screen. "Eye opening status" includes whether the student's eyes are open, whether they are closed frequently, how open their eyes are, how long they are closed, and how often they blink. "Mouth movement" includes whether the student yawns frequently, whether they are eating, and whether they are talking to others. "Facial expression" includes whether the student has facial expression or not, and whether their eyelids or facial muscles are relaxed. "Movement" includes whether the student is looking away from their smartphone and whether they are writing in a notebook. "Device operation" includes whether the student is touching the screen, typing on the keyboard, or using the mouse during online learning. "Heart rate" includes whether the student is asleep. "Brain waves" includes whether alpha waves are present and the student is relaxed.

[0030] For example, the presence or absence of concentration and the level of concentration can be defined by determining the level of drowsiness and alertness based on a combination of the above biological information and restricting the student's gaze direction to the screen or the instructor to which the student should be paying attention. When a student is gazing at online learning content and has low drowsiness and high alertness, the concentration level calculation unit 2 determines that the level of concentration is high (high concentration level). Thus, in Figure 3, the lower the drowsiness and the higher the level of alertness, the higher the level of concentration.

[0031] 4 is a diagram for explaining the concentration speed and concentration length. The graph shown in FIG. 4 is the same as the graph shown in FIG.

[0032] As shown in Fig. 4, the concentration speed corresponds to the time until the concentration level reaches or exceeds a predetermined threshold (high concentration level). The concentration length corresponds to the time during which the high concentration level situation continues. The concentration level characteristic determination unit 3 calculates the concentration speed and concentration height based on the time series of the concentration level as shown in Fig. 4.

[0033] <Classification of concentration characteristics> The concentration characteristic determination unit 3 determines the concentration characteristics of the student during online learning based on the student's concentration level, concentration speed, and concentration length from the start T=t0 of the online learning to the end T=t1 as shown in Figures 3 and 4.

[0034] Fig. 5 is a diagram for explaining the categorization of concentration characteristics. As shown in Fig. 5, the concentration characteristic determination unit 3 classifies concentration characteristics into eight levels based on a combination of the height of concentration, the speed of concentration, and the length of concentration. Note that, although the concentration characteristics are classified into eight levels in the example of Fig. 5, the resolution of the categorization may be increased by classifying them into finer levels.

[0035] By having the concentration characteristic determination unit 3 determine the concentration characteristics as described above, if a specific time during online learning is considered to be a unit of a subject, it becomes possible to grasp the student's concentration characteristics for that unit.

[0036] <Presentation to students> 6 to 10 are diagrams showing examples of presenting the determination result of the concentration characteristic to the student. The presentation control unit 6 controls the presentation unit 8 to present the determination result of the concentration characteristic related to the online learning to the student at the time when the specific online learning ends. The presentation by the presentation unit 8 may be by screen display, audio, or both.

[0037] For example, as shown in Figure 6, the concentration level may be summarized into one rating to improve at-a-glance visibility. When a student selects "Details" as shown in Figure 6, the student may be able to check the details of the speed of concentration, the length of concentration, and the height of concentration as shown in Figure 7. When setting the concentration level rating, a distribution ratio may be set that takes into account the respective advantages of the speed of concentration, the length of concentration, and the height of concentration.

[0038] Furthermore, good points and areas for improvement may be fed back from a graph of concentration characteristics, as shown in Figures 8 and 9. In this case, the transition of concentration over time may be displayed as a graph for easy visual understanding, and good sections and sections requiring improvement may be color-coded on the graph.

[0039] Furthermore, as shown in FIG. 10, names, symbols, or icons may be assigned to the levels of concentration characteristics categorized based on FIG. 5, so that each unit can be displayed in an easy-to-understand manner.

[0040] In the first embodiment, the concentration characteristic is determined after the online learning is completed, but the concentration characteristic may be presented to the student in real time during the online learning.

[0041] <Effects> According to the first embodiment, by understanding the student's own concentration characteristics during online learning, the student can realize how well he or she was able to concentrate on the unit he or she attended online. This can foster the student's concentration and lead to an improvement in the student's learning efficiency that is optimal for the student. In other words, the concentration characteristic determination device 1 according to the first embodiment can provide highly effective learning support tailored to the student's characteristics.

[0042] <First Modification of First Embodiment> The concentration characteristic determining unit 3 may calculate a concentration loss section that indicates the time during which a situation in which the concentration height is less than a predetermined threshold continues.

[0043] Fig. 11 is a diagram for explaining the concentration loss period. In Fig. 11, the time when concentration was lost (the time when the concentration level fell below a predetermined threshold) is set to t2, and the concentration loss period (t2-t1) continues until the end of online learning.

[0044] By identifying the sections where concentration is lost, it is possible to identify subjects or units that students find difficult, or areas that students are likely not able to understand, which allows students to reflect on their studies.

[0045] <Second Modification of First Embodiment> <Configuration> In the first embodiment, when a student takes an online learning course, the concentration characteristics during the online learning course are presented to the student. In the second variation of the first embodiment, the concentration characteristics of the student when taking the online learning course in the past are presented.

[0046] 12 is a block diagram showing an example of the configuration of a concentration characteristic determination device 9 according to Modification 2 of Embodiment 1. The concentration characteristic determination device 9 includes a concentration characteristic storage unit 10. Other configurations are similar to those of the concentration characteristic determination device 1 shown in FIG. 1, and therefore detailed description thereof will be omitted here.

[0047] The concentration characteristic storage unit 10 stores a history of concentration characteristics for each subject or unit attended by a student in association with the student and learning implementation information.

[0048] The presentation control unit 6 controls the presentation unit 8 so as to present the student's past concentration characteristics for each subject or unit to the student in a manner that allows comparison.

[0049] <Operation> Fig. 13 is a flowchart showing an example of the operation of the concentration characteristic determining device 9. Note that steps S201 to S207 in Fig. 13 correspond to steps S101 to S107 in Fig. 2, and therefore a description thereof will be omitted here. Steps S208 and S209 will be described below.

[0050] In step S208, the concentration characteristic storage unit 10 stores the concentration characteristic in association with the student and the learning implementation information.

[0051] In step S209, the presentation control unit 6 controls the presentation unit 8 to present the determination result of the concentration characteristic determination unit 3 (the student's concentration characteristics during online learning) to the student identified by the student identification unit 5 in a manner that allows comparison with past determination results stored in the concentration characteristic storage unit 10. Following the instructions of the presentation control unit 6, the presentation unit 8 presents the student's concentration characteristics during online learning to the student in a manner that allows comparison with past concentration characteristics.

[0052] 14 to 18 are diagrams showing examples of presentations to students according to the second modification of the first embodiment.

[0053] Figure 14 shows the concentration characteristics when student A took the Mathematics I unit "Calculation of Algebraic Expressions" through online learning. When student A selects "Mathematics I" shown in Figure 14, the concentration characteristics for each unit of Mathematics I that student A has taken in the past are displayed as shown in Figure 15. The concentration characteristics for each unit shown in Figure 15 may be displayed as graphs such as those shown in Figures 16 to 18.

[0054] <Effects> According to the second modification of the first embodiment, it is possible to visually grasp the units on which students have a low level of concentration, etc. Therefore, it is possible to estimate which units students should study intensively as preparation for a test, for example.

[0055] <Embodiment 2> <Configuration> In the second embodiment, an example will be described in which the concentration characteristics of students are presented to the instructor.

[0056] 19 is a block diagram showing an example of the configuration of a concentration characteristic determination device 9 according to embodiment 2. The concentration characteristic determination device 9 according to embodiment 2 is communicably connected to a presentation unit 11 (instructor-side interface). Other configurations are the same as those of the concentration characteristic determination device 9 shown in FIG. 12, and therefore detailed description thereof will be omitted here.

[0057] The presentation control unit 6 controls the presentation unit 11 to present the past concentration characteristics of the students for each subject or unit to the instructor in a comparable manner. The presentation unit 11 presents the past concentration characteristics of the students for each subject or unit in a comparable manner.

[0058] <Operation> Fig. 20 is a flowchart showing an example of the operation of the concentration characteristic determining device 9 according to embodiment 2. Note that steps S301 to S308 in Fig. 20 correspond to steps S201 to S208 in Fig. 13, and therefore a description thereof will be omitted here. Step S309 will be described below.

[0059] In step S309, the presentation control unit 6 controls the presentation unit 11 to present the determination result of the concentration characteristic determination unit 3 (the student's concentration characteristics during online learning) to the student identified by the student identification unit 5 in a manner that allows comparison with past determination results stored in the concentration characteristic storage unit 10. The presentation unit 11 presents the student's concentration characteristics during online learning to the instructor in a manner that allows comparison with past concentration characteristics, in accordance with the instructions of the presentation control unit 6. The presentation to the instructor is similar to the presentation to the student shown in FIGS. 14 to 18.

[0060] <Effects> According to the second embodiment, the instructor can grasp the concentration characteristics of students during online learning and give advice to students as needed, thereby improving the quality of students' learning. In particular, while conventionally, instructors would identify units that students should reinforce by administering mini-tests, the second embodiment makes it possible to estimate units that students should reinforce and give advice to students without administering mini-tests.

[0061] The content according to the second embodiment may also be used for learning materials or a learning curriculum such as the order of learning levels, formulating a planned rest plan, and giving advice on study methods.

[0062] In the second embodiment, the concentration characteristics are determined after the online learning is completed, but the concentration characteristics may be presented to the instructor in real time during the online learning. In this case, the instructor may use the real-time concentration characteristics to give advice to the students during the online learning lecture.

[0063] <Modification of the second embodiment> In the second embodiment, the case where the concentration characteristics of the students are presented to the instructor has been described. In a modified version of the second embodiment, the case where the concentration characteristics of the students are presented to the parents of the students will be described.

[0064] 21 is a block diagram showing an example of the configuration of a concentration characteristic determination device 9 according to a modification of Embodiment 2. The concentration characteristic determination device 9 according to the modification of Embodiment 2 is communicably connected to a presentation unit 12 (parent-side interface). Other configurations are the same as those of the concentration characteristic determination device 9 shown in FIG. 19, and therefore detailed description thereof will be omitted here.

[0065] The presentation control unit 6 controls the presentation unit 12 to present the student's past concentration characteristics for each subject or unit to the student's guardian in a manner that allows for comparison. The presentation unit 12 presents the student's past concentration characteristics for each subject or unit in a manner that allows for comparison.

[0066] The operation of the concentration characteristic determination device 9 according to the modification of the second embodiment differs from that of the concentration characteristic determination device 9 according to the second embodiment only in the processing of step S309 in the operation of the concentration characteristic determination device 9 according to the second embodiment (see FIG. 20). Specifically, in the concentration characteristic determination device 9 according to the modification of the second embodiment, the processing of step S309 in FIG. 20 becomes "The presentation control unit 6 controls the presentation unit 12 to present the determination result of the concentration characteristic determination unit 3 (the concentration characteristic of the student during online learning) to the student identified by the student identification unit 5 in a manner that allows comparison with past determination results stored in the concentration characteristic storage unit 10. The presentation unit 12, in accordance with the instruction of the presentation control unit 6, presents the concentration characteristic of the student during online learning to the guardian of the student in a manner that allows comparison with past concentration characteristics." The presentation to the guardian of the student is similar to the presentation to the student shown in FIGS. 14 to 18.

[0067] According to a modified example of the second embodiment, by allowing parents who pay the tuition fees for online learning to check the concentration characteristics of students during the online learning, it is possible to visualize the progress of the students' efforts as reflected in their test scores, which can ultimately be used to improve students' sense of satisfaction with the effectiveness of their learning and the tuition fees paid for it.

[0068] <Third Embodiment> <Configuration> In the third embodiment, an example will be described in which the history of concentration characteristics of a plurality of students is utilized as aggregate data of a specific group of students (specific group data).

[0069] 22 is a block diagram showing an example of the configuration of a concentration characteristic determination device 13 according to embodiment 3. The concentration characteristic determination device 13 includes a specific group data storage unit 14, and is communicably connected to a presentation unit 15 (third-party interface). The other configuration is the same as that of the concentration characteristic determination device 9 shown in FIG. 21, and therefore detailed description thereof will be omitted here.

[0070] The specific group data storage unit 14 stores the concentration characteristic history of each of a plurality of students as specific group data in association with each student and learning implementation information. Specifically, the specific group data storage unit 14 stores the concentration characteristic history of each student as metadata and manages the data in any setting, such as by grade, by class, or by instructor.

[0071] The presentation control unit 6 controls the presentation unit 15 to present the specific group data stored in the specific group data storage unit 14. Specifically, the presentation control unit 6 abstracts personal information of individual students or instructors, and enables a third party to view the transition of concentration characteristics of a specific student group (specific group data).

[0072] <Operation> When the concentration characteristic determination device 13 receives a request for a reference to specific group data from a third party via the presentation unit 15, it enables browsing of the specific group data stored in the specific group data storage unit 14. Other operations are the same as those in the first and second embodiments.

[0073] FIG. 23 is a diagram showing an example of a presentation to a third party according to the third embodiment. FIG. 23 shows the transition of the concentration characteristics of all students during online learning of a specific unit (auxiliary verbs) in a specific subject (English). The example in FIG. 23 displays information such as concentration level, alertness, and facial expression (negative, positive). This information is further used to display an "!" mark indicating a time when concentration significantly decreased, a "like" mark indicating a positive "+" facial expression, and a "▽" mark indicating a negative "-" facial expression, allowing students to easily understand at a glance how their online learning went overall in chronological order. Alternatively, the levels of concentration characteristics may be displayed as shown in FIG. 5.

[0074] <Effects> According to the third embodiment, by utilizing the data of a specific group, it becomes possible to identify areas for improvement in online learning content, which is beneficial for online learning content providers.

[0075] Furthermore, by managing specific group data for each school class and comparing it with past data, schools can grasp the learning trends of each class before the test. This makes it possible to predict weak subjects for each class before the test and to prepare for the test in advance, leading to improved student academic performance, increased teacher motivation, and improved work styles for teachers.

[0076] Furthermore, from the perspective of local boards of education, it will be possible to gain a more detailed understanding of learning effects at each school level.

[0077] <Fourth Embodiment> <Configuration> In the fourth embodiment, an example will be described in which factors of the student's life are reflected in the concentration characteristics.

[0078] Fig. 24 is a block diagram showing an example of the configuration of concentration characteristic determination device 16 according to embodiment 4. Concentration characteristic determination device 16 includes a lifestyle factor information acquisition unit 17. Other configurations are similar to those of concentration characteristic determination device 9 shown in Fig. 21, and therefore detailed description thereof will be omitted here.

[0079] The lifestyle factor information acquisition unit 17 acquires lifestyle factor information related to the student's living environment. The lifestyle factor information includes the student's bedtime, wake-up time, sleep duration, study time before taking online classes, club activity time, meal time, smartphone usage time, etc. Methods by which the lifestyle factor information acquisition unit 17 acquires lifestyle factor information include a self-application by the student, automatic or manual acquisition from a smartphone or smartwatch owned by the student, or various sensors present in the student's living environment.

[0080] The presentation control unit 6 controls the presentation of the concentration level characteristics in association with the lifestyle factor information.

[0081] <Operation> Fig. 25 is a flowchart showing an example of the operation of the concentration characteristic determining device 16 according to embodiment 4. Note that steps S401 to S407 and step S409 in Fig. 25 correspond to steps S301 to S307 and step S308 in Fig. 20, and therefore a description thereof will be omitted here. Steps S408 and S410 will be described below.

[0082] In step S408, the lifestyle factor information acquisition unit 17 acquires lifestyle factor information of the student.

[0083] In step S410, the presentation control unit 6 performs control to associate the concentration level characteristic with the lifestyle factor information and present it. At this time, the presentation control unit 6 may perform control to present it on any or all of the presentation units 8, 11, and 12. Any or all of the presentation units 8, 11, and 12 present the lifestyle factor information in association with the concentration level characteristic.

[0084] <Effects> According to the fourth embodiment, by associating lifestyle factor information with concentration characteristics, it is possible to provide advice on improving lifestyle factors that will lead to improved learning outcomes. For example, by checking meal times, sleep times, club activity times, smartphone usage time, etc. of a student who tends to have a short concentration period, and linking advice on lifestyle improvement points such as going to bed earlier or reducing smartphone use before going to bed to the concentration characteristics, it is possible to expect an improvement in the student's concentration characteristics.

[0085] <Fifth Embodiment> <Configuration> In the fifth embodiment, an example will be described in which a student's test score history is linked to his or her concentration characteristics.

[0086] Fig. 26 is a block diagram showing an example of the configuration of concentration characteristic determination device 18 according to embodiment 5. Concentration characteristic determination device 18 includes a test score history storage unit 19 and a learning outcome confirmation unit 20. Other configurations are similar to those of concentration characteristic determination device 9 shown in Fig. 21, and therefore detailed description thereof will be omitted here.

[0087] The test score history storage unit 19 stores the test score history of students for each subject or unit.

[0088] The learning outcome confirmation unit 20 confirms the learning outcome of the student based on the student's test score history and concentration characteristics, and also creates a future study plan for the student based on the learning outcome.

[0089] The presentation control unit 6 controls the presentation of the future study plan.

[0090] <Operation> Fig. 27 is a flowchart showing an example of the operation of the concentration characteristic determining device 18 according to embodiment 5. Note that steps S501 to S508 in Fig. 27 correspond to steps S301 to S308 in Fig. 20, and therefore a description thereof will be omitted here. Steps S509 to S511 will be described below.

[0091] In step S509 , the learning outcome confirmation unit 20 acquires the test score history of the student from the test score history storage unit 19 .

[0092] In step S510, the learning outcome confirmation unit 20 confirms the learning outcome based on the student's test score history and the concentration characteristics for each unit. The learning outcome confirmation unit 20 also creates a future study plan for the student based on the learning outcome.

[0093] In step S511, the presentation control unit 6 controls the presentation of the future study plan. At this time, the presentation control unit 6 may control the presentation to any one or all of the presentation units 8, 11, 12, and 21. Any one or all of the presentation units 8, 11, 12, and 21 present the student's future study plan. The presentation control unit 6 may also control the presentation to present the learning outcomes.

[0094] 28 and 29 are diagrams showing examples of presentation according to the fifth embodiment.

[0095] Figure 14 shows the learning outcomes of student A when he studied Mathematics I through online learning. The learning outcomes shown in Figure 14 may be displayed as a graph as shown in Figure 29. The example in Figure 29 shows a future learning plan.

[0096] <Operation> According to the fifth embodiment, it is possible to confirm the learning results from the correlation between the improvement in the student's concentration and the test scores, and to present a future study plan suitable for each student.

[0097] <Hardware configuration> The functions of the concentration height calculation unit 2, concentration characteristic determination unit 3, learning implementation information acquisition unit 4, student identification unit 5, and presentation control unit 6 in the concentration characteristic determination device 1 (see FIG. 1) described in the first embodiment are realized by a processing circuit. That is, the concentration characteristic determination device 1 includes a processing circuit for calculating the concentration height, calculating the concentration speed and concentration length, determining the concentration characteristic, acquiring the learning implementation information, identifying the student, and controlling the presentation of the student, the concentration characteristic, and the learning implementation information in association with each other. The processing circuit may be dedicated hardware, or may be a processor (also referred to as a CPU, central processing unit, processing device, arithmetic unit, microprocessor, microcomputer, or DSP (Digital Signal Processor)) that executes a program stored in a memory.

[0098] When the processing circuit is dedicated hardware, the processing circuit 30 may be, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or a combination thereof, as shown in Fig. 30. The functions of the concentration height calculation unit 2, the concentration characteristic determination unit 3, the learning implementation information acquisition unit 4, the student identification unit 5, and the presentation control unit 6 may be realized individually by the processing circuit 30, or these functions may be realized together by a single processing circuit 30.

[0099] When the processing circuit 30 is the processor 40 shown in FIG. 31 , the functions of the concentration height calculation unit 2, the concentration characteristic determination unit 3, the learning implementation information acquisition unit 4, the student identification unit 5, and the presentation control unit 6 are realized by software, firmware, or a combination of software and firmware. The software or firmware is written as a program and stored in memory 41. The processor 40 realizes each function by reading and executing the program stored in memory 41. That is, the concentration characteristic determination device 1 includes memory 41 for storing a program that ultimately executes steps of calculating the concentration height, calculating the concentration speed and concentration length, determining the concentration characteristic, acquiring the learning implementation information, identifying the student, and controlling the presentation of the student, the concentration characteristic, and the learning implementation information in association with each other. These programs can also be said to cause a computer to execute the procedures or methods of the concentration height calculation unit 2, the concentration characteristic determination unit 3, the learning implementation information acquisition unit 4, the student identification unit 5, and the presentation control unit 6. Here, memory may be, for example, non-volatile or volatile semiconductor memory such as RAM (Random Access Memory), ROM (Read Only Memory), flash memory, EPROM (Erasable Programmable Read Only Memory), EEPROM (Electrically Erasable Programmable Read Only Memory), magnetic disk, flexible disk, optical disk, compact disk, DVD (Digital Versatile Disc), or any storage medium that will be used in the future.

[0100] In addition, with regard to each function of the concentration height calculation unit 2, concentration characteristic determination unit 3, learning implementation information acquisition unit 4, student identification unit 5, and presentation control unit 6, some functions may be realized by dedicated hardware, and other functions may be realized by software or firmware.

[0101] Thus, the processing circuitry can implement each of the above-described functions through hardware, software, firmware, or a combination thereof.

[0102] The above describes the hardware configuration of the concentration characteristic determination device 1 (see Figure 1) described in embodiment 1, but the same applies to the hardware configurations of the concentration characteristic determination device 9 (see Figure 12) described in variant example 2 of embodiment 1, the concentration characteristic determination device 9 (see Figure 19) described in embodiment 2, the concentration characteristic determination device 9 (see Figure 21) described in variant example 2 of embodiment 2, the concentration characteristic determination device 13 (see Figure 22) described in embodiment 3, the concentration characteristic determination device 16 (see Figure 24) described in embodiment 4, and the concentration characteristic determination device 18 (see Figure 26) described in embodiment 5.

[0103] Within the scope of the present disclosure, the embodiments can be freely combined, modified, or omitted as appropriate.

[0104] <Additional Notes> Various aspects of the present disclosure are summarized below as appendices.

[0105] (Appendix 1) a concentration level calculation unit that calculates a concentration level indicating the level of concentration of the student during the course based on the student's biological information; a concentration characteristic determination unit that calculates, based on the time series of the concentration level, a concentration speed indicating the time until the concentration level reaches a high concentration level equal to or greater than a predetermined threshold, and a concentration length indicating the time the high concentration level state continues, and determines the concentration characteristic of the student while attending the class; a learning implementation information acquisition unit that acquires learning implementation information related to the learning implementation of the student; a student identification unit for identifying the student; a presentation control unit that controls the presentation of the student, the concentration characteristics, and the learning implementation information in association with each other; A concentration characteristic determination device comprising: (Appendix 2) The concentration characteristic determination device according to claim 1, wherein the presentation control unit controls the presentation of the concentration height in a time series graph. (Appendix 3) The concentration characteristic determination device according to claim 1, wherein the concentration characteristic determination unit calculates a concentration loss section indicating the time during which the concentration height remains below the predetermined threshold. (Appendix 4) a concentration characteristic storage unit that stores a history of the concentration characteristic for each subject or unit attended by the student in association with the student and the learning implementation information; The concentration characteristic determination device described in Appendix 1, wherein the presentation control unit controls the presentation of the student's past concentration characteristics for each subject or unit to the student in a manner that allows for comparison. (Appendix 5) The concentration characteristic determination device described in Appendix 4, wherein the presentation control unit controls the presentation of the student's past concentration characteristics for each subject or unit to the instructor in a manner that allows for comparison. (Appendix 6) The concentration characteristic determination device described in Appendix 4, wherein the presentation control unit controls the presentation of the student's past concentration characteristics for each subject or unit to the student's parents in a manner that allows for comparison. (Appendix 7) a specific group data storage unit that stores the concentration characteristic history of each of the plurality of students as specific group data in association with each of the students and the learning implementation information; 2. The concentration characteristic determination device according to claim 1, wherein the presentation control unit controls the presentation of the specific group data. (Appendix 8) A life factor information acquisition unit that acquires life factor information related to the living environment of the student is further provided, 2. The concentration characteristic determination device according to claim 1, wherein the presentation control unit controls presentation of the concentration characteristic in association with the lifestyle factor information. (Appendix 9) A concentration characteristic determination device as described in Appendix 1, further comprising a learning outcome confirmation unit that confirms the student's learning outcomes based on the test score history for each subject or unit taken by the student and the concentration characteristic. (Appendix 10) Calculating a concentration level indicating the level of concentration of the student during the class based on the student's biological information; Based on the time series of the concentration level, a concentration speed indicating the time until the concentration level reaches a high concentration level equal to or greater than a predetermined threshold, and a concentration length indicating the time the high concentration level continues are calculated, and the concentration level characteristics of the student during the course are determined; Acquire learning implementation information regarding the student's learning implementation; Identifying the student; A concentration characteristic determination method that controls the presentation of the student, the concentration characteristic, and the learning implementation information in association with each other. [Explanation of symbols]

[0106] 1 Concentration characteristic determination device, 2 Concentration height calculation unit, 3 Concentration characteristic determination unit, 4 Learning implementation information acquisition unit, 5 Student identification unit, 6 Presentation control unit, 7 Sensing device, 8 Presentation unit, 9 Concentration characteristic determination device, 10 Concentration characteristic memory unit, 11 Presentation unit, 12 Presentation unit, 13 Concentration characteristic determination device, 14 Specific group data memory unit, 15 Presentation unit, 16 Concentration characteristic determination device, 17 Lifestyle factor information acquisition unit, 18 Concentration characteristic determination device, 19 Test score history memory unit, 20 Learning outcome confirmation unit, 21 Presentation unit, 30 Processing circuit, 40 Processor, 41 Memory.

Claims

1. a concentration level calculation unit that calculates a concentration level indicating the level of concentration of the student during the course based on the student's biological information; a concentration characteristic determination unit that calculates, based on the time series of the concentration level, a concentration speed indicating the time until the concentration level reaches a high concentration level equal to or greater than a predetermined threshold, and a concentration length indicating the time the high concentration level state continues, and determines the concentration characteristic of the student while attending the class; a learning implementation information acquisition unit that acquires learning implementation information related to the learning implementation of the student; a student identification unit for identifying the student; a presentation control unit that controls the presentation of the student, the concentration characteristics, and the learning implementation information in association with each other; A concentration characteristic determination device comprising:

2. The concentration characteristic determination device according to claim 1 , wherein the presentation control unit controls the presentation of the concentration height in a time series graph.

3. The concentration characteristic determining device according to claim 1 , wherein the concentration characteristic determining unit calculates a concentration loss period indicating a period of time during which a state in which the concentration height is less than the predetermined threshold continues.

4. a concentration characteristic storage unit that stores a history of the concentration characteristic for each subject or unit attended by the student in association with the student and the learning implementation information; The concentration characteristic determination device according to claim 1 , wherein the presentation control unit controls to present the past concentration characteristics of the student for each subject or unit to the student in a comparable manner.

5. The concentration characteristic determination device according to claim 4 , wherein the presentation control unit performs control to present the past concentration characteristics of the students for each subject or unit to the instructor in a comparable manner.

6. The concentration characteristic determination device according to claim 4 , wherein the presentation control unit controls the presentation of the student's past concentration characteristics for each subject or unit to the student's guardian in a manner that allows comparison.

7. a specific group data storage unit that stores the concentration characteristic history of each of the plurality of students as specific group data in association with each of the students and the learning implementation information; The concentration characteristic determination device according to claim 1 , wherein the presentation control unit controls presentation of the specific group data.

8. A life factor information acquisition unit that acquires life factor information related to the living environment of the student is further provided, The concentration characteristic determination device according to claim 1 , wherein the presentation control unit performs control to present the concentration characteristic in association with the lifestyle factor information.

9. The concentration characteristic determination device according to claim 1, further comprising a learning outcome confirmation unit that confirms the learning outcomes of the student based on the test score history for each subject or unit taken by the student and the concentration characteristic.

10. Calculating a concentration level indicating the level of concentration of the student during the class based on the student's biological information; Based on the time series of the concentration level, a concentration speed indicating the time until the concentration level reaches a high concentration level equal to or greater than a predetermined threshold, and a concentration length indicating the time the high concentration level continues are calculated, and the concentration level characteristics of the student during the course are determined; Acquire learning implementation information regarding the student's learning implementation; Identifying the student; A concentration characteristic determination method that controls the presentation of the student, the concentration characteristic, and the learning implementation information in association with each other.

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