JP2015170033A - Education support device, education support processing program and education support processing method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To make it possible to determine the grade level of students who have no interest in a present lecture.SOLUTION: The education support device comprises an identifying unit that identifies, among students who take a lecture, a group of students who are considered to have no interest in the lecture; a determination unit that refers to a storage unit that stores grades of the students on the lecture and, for the grades of the group of students identified by the identifying unit, determines a bias in the grades of the students who take the lecture; and an output unit that outputs a determination result of the determination unit.

Description

  The present invention relates to a technology for supporting education through information processing.

  Lectures are meaningless unless the students listen to them intensively, and they cannot expect to maintain or improve their grades if they are asleep or left on the way. For this reason, the instructor has also made various efforts to make students interested in lectures and concentrate on attendance.

  Patent Documents 1 and 2 disclose a technique for analyzing the attendance state of each student from an image obtained by photographing the student.

JP 2013-61906 A JP 2013-29954 A

For those who fall asleep or leave during the lecture, there are those who take such actions because they cannot keep up with the lecture, and those who take such actions because the level of the lecture does not need to be heard low.
The instructor side uses techniques such as Patent Documents 1 and 2 described above to determine the percentage of students in the class who take such a nap or leave the class, or who can be regarded as not interested in the lecture. Can know.

  However, it was impossible to judge why these students fell asleep or left their seats, that is, whether the content of the lecture was too difficult or too easy.

  Therefore, an object of one aspect is to make it possible to determine what grade of student is not interested in the current lecture.

  In one proposal, referring to a specific unit that identifies a group of students who are considered not interested in the lecture among students taking the lecture, and a storage unit that stores the results of the student about the lecture, A determination unit that determines a deviation in the results of the students receiving the lecture with respect to the results of the student group specified by the specifying unit, and an output unit that outputs a determination result of the determination unit.

  According to one aspect, it is possible to determine what grade of student is not interested in the current lecture.

It is a figure which shows the structural example of the system concerning one Embodiment. It is a figure which shows the example of data of a results management database. It is a figure which shows the example of data of an attendance / lecture attitude management database. It is a figure which shows the example of data of an electronic teaching material management database. It is a figure which shows the example of determination of attendance attitude. It is a flowchart which shows the process example of embodiment. It is a figure which shows the example of distribution of the grade of a class, and grade statistics X. It is FIG. (1) which shows the example of the relationship between the grade statistics value X and the grade statistics value Y of a lecture indifferent student group. It is FIG. (2) which shows the example of the relationship between the grade statistics value X and the grade statistics value Y of a lecture indifferent student group. It is FIG. (3) which shows the example of the relationship between the grade statistics value X and the grade statistics value Y of a lecture indifferent student group.

  Hereinafter, preferred embodiments of the present invention will be described.

<Configuration>
FIG. 1 is a diagram illustrating a configuration example of a system according to an embodiment.

  In FIG. 1, a lecture management device (education support device) 1 includes, via a network 2, a lecturer-side terminal device 3 placed at the hand of a lecturer and a plurality of student-side terminal devices placed at the hand of each student. 4 and the attendance attitude collection device 5 in a position where all students of the class can be seen are connected. The network 2 may be wired or wireless.

  The lecture management device 1 includes, as functional units, a statistical grade calculation unit 11, an attendance recording unit 12, a attendance recording unit 13, a lecture indifferent student group extraction unit 14, a lecture indifferent student group performance statistical value calculation unit 15, and a grade statistical value. A difference calculation unit 16, a lecture difficulty level determination unit 17, a lecture difficulty level output unit 18, and an electronic teaching material change instruction unit 19 are provided. These functional units are realized by a computer program executed on hardware resources such as a CPU (Central Processing Unit), a ROM (Read Only Memory), and a RAM (Random Access Memory) of the computer constituting the lecture management apparatus 1. Is. Each functional unit need not be arranged on a single computer, and may be distributed as necessary.

  In addition, the lecture management apparatus 1 includes a grade management database 101, an attendance / lecture attitude management database 102, and an electronic teaching material management database 103 as parts for holding data used for processing. These databases systematically hold predetermined data in a storage area on a storage medium such as an HDD (Hard Disk Drive) in the lecture management apparatus 1. Each database need not be arranged on a single computer, and may be distributed as necessary.

  FIG. 2 is a diagram showing an example of data in the grade management database 101, and includes items such as “class”, “student name (ID)”, and “grade (test score etc.)”. “Class” is information for identifying a lecture. “Student name (ID)” is information for identifying students belonging to the class. “Grade (test score, etc.)” is information on the grade, such as past (most recent) test score of the student in the class.

  FIG. 3 is a diagram illustrating an example of data in the attendance / lecture attitude management database 102, and includes items such as “class”, “student name (ID)”, “attendance”, “attendance attitude”, and the like. “Class” is information for identifying a lecture. “Student name (ID)” is information for identifying students belonging to the class. “Attendance” is information indicating the attendance or absence of the student in the class. The “attendance attitude” is information indicating the attitude of the student in the class, such as “good”, “sleeping”, “withdrawal”, and the like.

  FIG. 4 is a diagram illustrating an example of data in the electronic teaching material management database 103, and includes items such as “class”, “electronic teaching material (ID)”, and “difficulty”. “Class” is information for identifying a lecture. The “electronic teaching material (ID)” is information for identifying an electronic teaching material that can be used for the class. “Difficulty” is information indicating the difficulty of the electronic teaching material. Note that the “difficulty level” can be set as a result of determining each electronic teaching material using machine learning or the like.

  Returning to FIG. 1, the grade statistical value calculation unit 11 of the lecture management apparatus 1 refers to the past grades (test scores, etc.) of the students belonging to the class specified at the start of the lecture from the grade management database 101, and the class. It has a function of calculating a performance statistical value X that represents the characteristics of the overall performance. As the statistics statistic value X, various statistical values such as an average value and a mode value can be used, and any index may be used as long as it indicates a score distribution.

  The attendance recording unit 12 has a function of recording attendance in the attendance / lecture attitude management database 102 based on information of students attending the lecture acquired from the attendance attitude collection device 5. When a student attending is recognized by a card reader provided at the entrance of the classroom or when attendance is reported from the student side terminal device 4, they may be used together for confirmation of attendance.

  The attendance attitude recording unit 13 has a function of recording the attendance attitude in the attendance / lecture attitude management database 102 based on the attendance attitude information of the students attending the lecture acquired from the attendance attitude collection device 5.

  The lecture indifferent student group extraction unit 14 has a function of referring to the attendance / lecture attitude management database 102 and extracting a student group (lecture indifferent student group) that is regarded as not interested in the lecture. The lecture indifferent student group includes, for example, a student who is not concentrated, a student who is asleep, a student who is absent, a student who has left midway, and a student who has been represented by a third party.

  The lecture indifference student group performance statistics calculation unit 15 refers to the past results (test scores, etc.) of the students belonging to the lecture indifference student group extracted by the lecture indifference student group extraction unit 14 from the grade management database 101, and It has a function of calculating a performance statistical value Y that represents the overall performance characteristics of the student group. As the results statistical value Y, various statistical values such as an average value and a mode value can be used as long as they are indices representing the results distribution.

  The grade statistic difference calculation unit 16 is a standard grade statistic X calculated by the grade statistic calculation unit 11, and a grade statistic of the lecture indifferent student group calculated by the lecture indifferent student group performance statistic calculation unit 15. It has a function of calculating a difference Z (= Y−X) of Y. If the difference Z is not zero, the grades of students indifferent to the lecture are biased throughout the class. If the difference Z is a positive value, it is understood that the student in the top grade (excellent grade) is not interested in the lecture. If the difference Z is a negative value, the student in the lower grade (poor grade) in the grade lectures. Is indifferent.

  The lecture difficulty level determination unit 17 has a function of determining the difficulty level of a lecture for a class of indifferent students based on the difference Z calculated by the grade statistical value difference calculation unit 16. The degree of difficulty of the lecture for the indifferent class of students may be a rough level such as “difficult”, “easy”, or “appropriate”, or a finer level. In addition, when the lecture is "difficult", "easy", or "appropriate", it is determined in the form of a request (request difficulty level) to change the lecture, such as "make it easy", "make it difficult", or "maintain the current situation" May be.

  The lecture difficulty level output unit 18 has a function of outputting (notifying) the difficulty level (requested difficulty level) determined by the lecture difficulty level determination unit 17 to the lecturer-side terminal device 3.

  The electronic teaching material change instruction unit 19 appropriately refers to the electronic teaching material management database 103 according to the difficulty level (requested difficulty level) determined by the lecture difficulty level determination unit 17 when electronic teaching materials are used in the lecture. It has a function to give an instruction to automatically change to an electronic teaching material of a certain difficulty level.

  On the other hand, the instructor-side terminal device 3 includes a lecture start / end operation unit 31, an electronic teaching material specifying unit 32, an electronic teaching material display unit 33, a lecture difficulty level display unit 34, and an electronic teaching material change unit 35 as functional units. . These functional units are realized by a computer program that is executed on hardware resources of a computer constituting the instructor-side terminal device 3.

  The lecture start / end operation unit 31 has a function of accepting predetermined operations at the start and end of a lecture and performing processing at the start and end of education support control with the lecture management device 1.

  The electronic teaching material specifying unit 32 has a function of specifying an electronic teaching material to be used in the lecture.

  The electronic teaching material display unit 33 has a function of displaying the electronic teaching material on the instructor side terminal device 3.

  The lecture difficulty level display unit 34 has a function of displaying the difficulty level of the lecture (requested difficulty level) transmitted from the lecture management apparatus 1.

  The electronic teaching material changing unit 35 has a function of changing the electronic teaching material based on an instruction from the lecture management apparatus 1.

  On the other hand, the student side terminal device 4 includes an electronic teaching material display unit 41 and an electronic teaching material change unit 42 as functional units. These functional units are realized by a computer program executed on hardware resources of a computer constituting the student side terminal device 4.

  The electronic teaching material display unit 41 has a function of displaying electronic teaching materials on the student side terminal device 4.

  The electronic teaching material changing unit 42 has a function of changing the electronic teaching material based on an instruction from the lecture management apparatus 1.

  On the other hand, the attendance attitude collection device 5 includes an attendance attitude collection unit 51 and an attendance attitude transmission unit 52 as functional units. These functional units are realized by a computer program executed on hardware resources of a computer constituting the attendance attitude collection device 5. In addition, the attendance attitude collection device 5 has a camera for photographing a student who has attended.

  The attendance attitude collection unit 51 recognizes the attending student based on face feature data (not shown) registered in advance from an image obtained by taking the attending student, and the direction of the line of sight, the blinking It has a function to collect information indicating the attendance status from the presence / absence / number of times, posture, etc. FIG. 5 is a diagram illustrating an example of determination of attendance attitude, and it can be determined from the image of (a) that the head is projecting normally because the head protrudes above the shoulder, but the image of (b) Can be determined to be asleep because the head is buried in the shoulder. More specifically, the techniques described in Patent Documents 1 and 2 can be used.

  Returning to FIG. 1, the attendance attitude transmission unit 52 has a function of transmitting information indicating the attendance state of each student collected by the attendance attitude collection unit 51 to the lecture management apparatus 1.

<Operation>
FIG. 6 is a flowchart showing a processing example of the above embodiment.

  In FIG. 6, when a lecture start operation specifying a class from the lecture start / end operation unit 31 of the lecturer-side terminal device 3 is accepted by the lecture management device 1 at the start of the lecture (step S101), the statistical result value The calculation unit 11 refers to the past grades (test scores, etc.) of students belonging to the specified class from the grade management database 101, and calculates a grade statistical value X representing the overall grade characteristics of the class ( Step S102).

  FIG. 7 is a diagram showing an example of the distribution of class grades and the grade statistical value X, and shows that the grade statistical value X exists near the center of the Yamagata distribution. Note that the shape of the distribution is merely an example, and it goes without saying that it varies greatly depending on the students in the class.

  Next, returning to FIG. 6, the attendance recording unit 12 records attendance in the attendance / lecture attitude management database 102 based on the information of students attending the lecture acquired from the attendance attitude collection device 5 (step S103).

  Next, the attendance attitude recording unit 13 records the attendance attitude in the attendance / lecture attitude management database 102 based on the attendance attitude information of the students attending the lecture acquired from the attendance attitude collection device 5 (step S104).

  Next, the lecture indifferent student group extraction unit 14 refers to the attendance / lecture attitude management database 102 and extracts a student group (lecture indifferent student group) that is regarded as not interested in the lecture (step S105).

  Next, the lecture indifferent student group performance statistics calculation unit 15 refers to the past results (test scores, etc.) of the students belonging to the lecture indifferent student group extracted by the lecture indifferent student group extraction unit 14 from the grade management database 101. Then, a performance statistical value Y representing the overall performance characteristics of the student group is calculated (step S106).

  FIG. 8 is a diagram showing an example of the relationship between the grade statistical value X and the grade statistical value Y of the class indifferent to the lecture. The small mountain is biased to the lower side of the grade statistical value X than the large mountain of the whole student. , It shows that there is a statistical value Y of lecture indifferent students near the center.

  FIG. 9 is a diagram showing another example of the relationship between the grade statistics X and the grade statistics Y of the indifference student group. The smaller peaks are biased to the higher side of the grade statistics X than the large peaks of the entire student. It shows that there is a statistical value Y of the class of students who are not interested in the lecture near the center.

  FIG. 10 is a diagram showing still another example of the relationship between the grade statistical value X and the grade statistical value Y of the lecture indifferent student group. A small mountain is biased with respect to the grade statistical value X as compared with a large mountain of the entire student. In other words, it is shown that the overall statistical score X and the statistical score Y of the indifferent class of students are the same.

  Next, returning to FIG. 6, the grade statistical value difference calculation unit 16 calculates the standard grade statistical value X calculated by the grade statistical value calculation unit 11, and the lecture calculated by the lecture indifferent student group performance statistical value calculation unit 15. A difference Z (= Y−X) of the grade statistics value Y of the indifferent student group is calculated (step S107). The difference Z is also shown in FIGS.

  Next, returning to FIG. 6, the lecture difficulty level determination unit 17 determines the difficulty level of the lecture for the class indifferent student group based on the difference Z calculated by the grade statistical value difference calculation unit 16 (step S <b> 108). The degree of difficulty of the lecture for the indifferent class of students may be a rough level such as “difficult”, “easy”, or “appropriate”, or a finer level. In addition, when the lecture is "difficult", "easy", or "appropriate", it is determined in the form of a request (request difficulty level) to change the lecture, such as "make it easy", "make it difficult", or "maintain the current situation" May be.

  Next, the lecture difficulty level output unit 18 outputs (notifies) the difficulty level (requested difficulty level) determined by the lecture difficulty level determination unit 17 to the instructor terminal device 3 (step S109). In addition to the instructor-side terminal device 3, the degree of difficulty (requested difficulty level) may be notified to a smartphone, a tablet, or the like possessed by the instructor.

  Next, the electronic teaching material change instruction unit 19 refers to the electronic teaching material management database 103 according to the difficulty level (requested difficulty level) determined by the lecture difficulty level determination unit 17 when the electronic teaching material is used in the lecture. The instruction to automatically change to an electronic teaching material of an appropriate difficulty level is issued (step S110).

  In response to this, the electronic teaching material changing unit 35 of the instructor side terminal device 3 and the electronic teaching material changing unit 42 of the student side terminal device 4 change the electronic teaching material. For example, if an electronic teaching material having a difficulty level of “standard” is being used at the present time, if the difficulty level of the lecture for the lecture indifferent student group is “difficult”, the electronic teaching material is changed to an “easy” difficulty level. On the other hand, when the difficulty level of the lecture for the indifferent student group is “easy”, the electronic teaching material is changed to “difficult”.

  Next, when the lecture end / end operation unit 31 of the lecturer side terminal device 3 does not perform the lecture end operation (step S111), the attendance student registration process (step 5) is performed after a predetermined time (for example, 5 minutes). The processing is repeated from S103). This is to cope with changes in attendance as well as attendance changes due to students being late or leaving the room.

  When a lecture end operation is received from the lecture start / end operation unit 31 of the instructor side terminal device 3 (step S111), each unit of the lecture management device 1 performs an end process (step S112) such as data storage. The process ends.

<Summary>
As described above, according to the present embodiment, it is possible to determine what grade of student is not interested in the current lecture. Thereby, it is possible to support the lecturer to give a lecture according to the level of the student.

  The lecture indifferent student group extraction unit 14 is an example of a specifying unit. The grade management database 101 is an example of a storage unit. The lecture difficulty level determination unit 17 is an example of a determination unit. The lecture difficulty level output unit 18 is an example of an output unit. The grade statistics value calculation part 11 is an example of a means for calculating the first grade statistics value. The lecture indifference student group performance statistical value calculation unit 15 is an example of a means for calculating a second performance statistical value. The grade statistical value difference calculation unit 16 is an example of a means for calculating a difference between the first grade statistical value and the second grade statistical value.

  In the above, it demonstrated by preferred embodiment. While specific embodiments have been illustrated and described herein, it will be apparent that various modifications and changes may be made thereto without departing from the broad spirit and scope as defined in the claims. . That is, it should not be construed as being limited by the details of the specific examples and the accompanying drawings.

Regarding the above description, the following items are further disclosed.
(Supplementary note 1) A specific section for identifying a group of students who are considered not interested in the lecture among the students receiving the lecture,
With reference to a storage unit that stores the grades related to the lectures of the students, a judgment unit that judges a bias in the grades of the students receiving the lectures with respect to the grades of the students specified by the identification unit;
An output unit for outputting a determination result of the determination unit;
An education support apparatus comprising:
(Supplementary Note 2) In the education support apparatus according to Supplementary Note 1,
The identification unit identifies the student group from the attendance attitude of the students receiving the lecture,
The determination unit
Means for calculating a first performance statistic value representing the characteristics of the performance of the student receiving the lecture;
Means for calculating a second performance statistic value representing characteristics of the performance of the student group;
Means for calculating a difference between the first performance statistic value and the second performance statistic value;
An education support apparatus comprising:
(Appendix 3) In the education support apparatus according to any one of Appendix 1 or 2,
The output unit notifies the lecturer who is performing the lecture of the determination result of the determination unit,
An educational support device characterized by that.
(Appendix 4) In the education support apparatus according to any one of appendices 1 to 3,
The output unit requests that the degree of difficulty of the lecture is lowered when the grade of the student group is biased downward;
An educational support device characterized by that.
(Supplementary Note 5) In the education support apparatus according to any one of Supplementary Notes 1 to 4,
The output unit requests that the degree of difficulty of the lecture be increased when the grade of the student group is biased to the top;
An educational support device characterized by that.
(Appendix 6) In the education support apparatus according to any one of appendices 1 to 5,
Means for changing electronic teaching materials used in the lecture according to the determination result of the determination unit;
An education support apparatus comprising:
(Supplementary note 7) Among the students taking the lecture, identify the group of students who can be considered not interested in the lecture,
With reference to the storage unit storing the grades related to the lectures of the students, for the grades of the students, judging the bias in the grades of the students receiving the lectures,
Outputting the judgment result of the bias,
Education support processing program that causes a computer to execute processing.
(Appendix 8) In the education support processing program described in Appendix 7,
The specifying process specifies the student group from the attendance attitude of the students receiving the lecture,
The determination process is as follows:
Calculating a first performance statistic value indicating the characteristics of the performance of the student receiving the lecture;
Calculating a second performance statistic representing the characteristics of the student group's performance;
Calculating a difference between the first performance statistic value and the second performance statistic value;
Education support processing program.
(Supplementary note 9) In the educational support processing program according to any one of supplementary note 7 or 8,
The output process notifies the lecturer who is performing the lecture of the determination result of the bias.
Education support processing program.
(Supplementary note 10) In the education support processing program according to any one of supplementary notes 7 to 9,
The output process requests that the degree of difficulty of the lecture is lowered when the grade of the student group is biased downward.
Education support processing program.
(Supplementary Note 11) In the education support processing program according to any one of Supplementary Notes 7 to 10,
The output process requests that the degree of difficulty of the lecture is increased when the grade of the student group is biased to the top.
Education support processing program.
(Supplementary note 12) In the education support processing program according to any one of supplementary notes 7 to 11,
Changing the electronic teaching materials used for the lecture according to the judgment result of the bias;
Education support processing program that causes a computer to execute processing.
(Supplementary note 13) Education support device
Identify a group of students who are not interested in the lecture,
With reference to the storage unit storing the grades related to the lectures of the students, for the grades of the students, judging the bias in the grades of the students receiving the lectures,
Outputting the judgment result of the bias,
An education support processing method characterized by the above.
(Supplementary note 14) In the education support processing method according to supplementary note 13,
The specifying process specifies the student group from the attendance attitude of the students receiving the lecture,
The determination process is as follows:
Calculating a first performance statistic value indicating the characteristics of the performance of the student receiving the lecture;
Calculating a second performance statistic representing the characteristics of the student group's performance;
Calculating a difference between the first performance statistic value and the second performance statistic value;
An education support processing method characterized by the above.
(Supplementary Note 15) In the education support processing method according to any one of Supplementary Note 13 or 14,
The output process notifies the lecturer who is performing the lecture of the determination result of the bias.
An education support processing method characterized by the above.
(Supplementary Note 16) In the education support processing method according to any one of Supplementary Notes 13 to 15,
The output process requests that the degree of difficulty of the lecture is lowered when the grade of the student group is biased downward.
An education support processing method characterized by the above.
(Supplementary note 17) In the education support processing method according to any one of supplementary notes 13 to 16,
The output process requests that the degree of difficulty of the lecture is increased when the grade of the student group is biased to the top.
An education support processing method characterized by the above.
(Supplementary note 18) In the education support processing method according to any one of supplementary notes 13 to 17,
Changing the electronic teaching materials used for the lecture according to the judgment result of the bias;
An education support processing method characterized by the above.

DESCRIPTION OF SYMBOLS 1 Lecture management apparatus 11 Grade statistics calculation part 12 Attendance record part 13 Attendance record part 14 Lecture uninterested student group extraction part 15 Lecture indifference student group result statistical value calculation part 16 Grade statistical value difference calculation part 17 Lecture difficulty level determination part 18 Lecture difficulty output unit 19 Electronic teaching material change instruction unit 101 Grade management database 102 Attendance / lecture attitude management database 103 Electronic teaching material management database 2 Network 3 Instructor side terminal device 31 Lecture start / end operation unit 32 Electronic teaching material specification unit 33 Electronic teaching material display Part 34 Lecture difficulty display part 35 Electronic teaching material change part 4 Student side terminal device 41 Electronic teaching material display part 42 Electronic teaching material change part 5 Attendance attitude collection device 51 Attendance attitude collection part 52 Attendance attitude transmission part

Claims (5)

A specific section for identifying a group of students who are considered not interested in the lecture among the students receiving the lecture;
With reference to a storage unit that stores the grades related to the lectures of the students, a judgment unit that judges a bias in the grades of the students receiving the lectures with respect to the grades of the students specified by the identification unit;
An output unit for outputting a determination result of the determination unit;
An education support apparatus comprising: The education support apparatus according to claim 1,
The identification unit identifies the student group from the attendance attitude of the students receiving the lecture,
The determination unit
Means for calculating a first performance statistic value representing the characteristics of the performance of the student receiving the lecture;
Means for calculating a second performance statistic value representing characteristics of the performance of the student group;
Means for calculating a difference between the first performance statistic value and the second performance statistic value;
An education support apparatus comprising: In the education support device according to any one of claims 1 and 2,
An education support apparatus comprising: means for changing an electronic teaching material used for the lecture according to a determination result of the determination unit. Identify a group of students who are not interested in the lecture,
With reference to the storage unit storing the grades related to the lectures of the students, for the grades of the students, judging the bias in the grades of the students receiving the lectures,
Outputting the judgment result of the bias,
Education support processing program that causes a computer to execute processing. Education support device
Identify a group of students who are not interested in the lecture,
With reference to the storage unit storing the grades related to the lectures of the students, for the grades of the students, judging the bias in the grades of the students receiving the lectures,
Outputting the judgment result of the bias,
An education support processing method characterized by the above.

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