JP2007226458A - Lesson management device and lesson management method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To efficiently evaluate the contents of a lesson for qualitative improvement of the lesson and a teacher. <P>SOLUTION: This lesson management device supports a lesson by managing the learning situation of a student. This device receives an e-mail from the student, determines whether a predetermined relationship is established between data of a predetermined item of chart data showing the learning situation of the student and a command character string included in the e-mail, and updates the chart data with data described in the e-mail on the condition that the determination result becomes a predetermined result. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to an education support technique for managing a student's learning status.

Japan has finally entered a society with a declining population. Each university is exposed to harsh competition to survive, with the advent of the university era. In order to overcome such competition by building a position as an attractive university, there is a growing need for so-called FD (Faculty Development), a systematic effort to improve class content and methods and improve quality. ing.
JP 2004-252632 A JP 2003-18324 A

  General FD is based on data collection from students. Based on the data collected from the students, the learning situation of each student is grasped, and the content of the lesson is reviewed based on the result. In order to use various data obtained from students to improve class content, it is necessary to determine whether the collected data correctly reflects the current situation.

  A main object of the present invention is to provide an educational support technique for efficiently managing a student's learning situation for class evaluation.

An aspect of the present invention relates to a lesson management apparatus that supports lessons by managing a student's learning status.
This device receives an e-mail from a student, determines whether a predetermined relationship is established between data of a predetermined item of medical record data indicating a student's learning status and a command character string included in the e-mail, On the condition that the determination result is a predetermined result, the chart data is updated with the data described in the e-mail.

Students receive various types of e-mail, such as e-mails indicating class attendance (hereinafter referred to as “attendance mails”) and e-mails describing impressions about the classes (hereinafter referred to as “impression mails”). You may send it. Also, in these e-mails, simple commands for classifying e-mail types such as attendance mails and impression mails may be described. Various data obtained from these e-mails may be integrated as medical chart data for managing the student's learning status.
Since the student only sends an e-mail from a communication terminal such as a mobile phone or a laptop computer that is usually used, there is an advantage that the student can easily obtain cooperation with the operation of the class management apparatus.

When constructing medical chart data from e-mail data, it is necessary to determine whether the original data correctly reflects the student's learning status. For example, even if an impression e-mail describing an impression of a lesson is received from a student who does not actually attend the lesson, such an impression may not be helpful. “Data about student's impressions of the class” can be said to be useful data when students attend the class.
According to the lesson management apparatus shown in the above aspect, when an impression mail is received, the validity of the impression mail is automatically confirmed by referring to the medical record data to confirm whether the student is actually attending the class. Can be judged. For this reason, it is possible to automatically determine that the impression mail from the student absent from the class is not subject to analysis.

Another aspect of the present invention also relates to a lesson management apparatus that supports lessons by managing the learning status of students.
This apparatus receives an e-mail from a student, extracts data from a predetermined part of the e-mail, and updates data of items corresponding to the extracted data with respect to medical chart data indicating a student's learning status by a plurality of items. . Then, it is determined whether or not a predetermined relationship is established between the data of item A in the chart data and the data of another item B.

  According to this aspect, it is possible to easily detect various combinations of data included in the chart data. For example, a student who has a high attendance rate but does not send a lot of comment emails may have a good attendance rate and not actually engage in class. In this way, the student's learning status can be analyzed in a multifaceted manner by comparing the two types of data, the attendance rate and the impression mail reception rate.

Another aspect of the present invention also relates to a lesson management apparatus for supporting lessons by managing the learning status of students.
This apparatus also receives e-mail from the student, extracts data from a predetermined part of the e-mail, and updates the data of the item corresponding to the extracted data in the chart data indicating the student's learning status by a plurality of items. . Then, it is determined whether a predetermined relationship is established between the data of item A of a student α and the data of item A (or another item B) of another student β.

  For example, if it is determined that the contents of the impression emails of a student α and student β are in a similar relationship as a result of natural language processing, at least one of the two students does not state their opinion there is a possibility. Thus, based on the conditions for comparing chart data among a plurality of students, it is also possible to analyze while comparing the learning status of each student.

  It should be noted that any combination of the above-described constituent elements and a conversion of the expression of the present invention between a method, an apparatus, a system, a recording medium, a computer program, etc. are also effective as an aspect of the present invention.

  According to the present invention, a student's learning situation can be managed efficiently for class evaluation.

  In this embodiment, first, the outline of the lesson evaluation system will be described, and the “matching determination process” which is the main feature of the present invention will be mainly described.

FIG. 1 is a hardware configuration diagram of the lesson evaluation system 10.
The lesson evaluation system 10 is a system for evaluating and verifying lesson contents assuming introduction into an educational institution such as a university. The class evaluation system 10 is a system used by teachers and students, and provides a mechanism for feeding back student responses to classes to class contents.

  The class evaluation system 10 includes a class management apparatus 100, a mail server 202, and a plurality of client terminals 204. These are connected to each other via the Internet 200. The lesson management apparatus 100 is used by a teacher (hereinafter, “teacher” is also referred to as “user” in the sense of clearly indicating that the user is the user of the lesson management apparatus 100). Each client terminal 204 is a general communication terminal equipped with a mail transmission / reception function, such as a mobile phone or a notebook computer used by students.

  First, the teacher sets an e-mail address dedicated to the course when the course is opened (hereinafter referred to as “course address”). For example, a course address such as “fraA@xxx.co.jp” is set for a course consisting of 15 classes “French A”. A student who takes a class in French A sends and receives an e-mail to and from the class management apparatus 100 via the course address. For example, when a student attends a class, an attendance email for notifying attendance is transmitted to the course address. The mail server 202 transfers the attendance mail received from the client terminal 204 to the lesson management apparatus 100. The mail server 202 may be a general known device. The lesson management apparatus 100 automatically counts which students attended which course by attendance mail.

  In addition to this, the student transmits an impression email describing the impression of the class to the course address. The class management device 100 performs natural language analysis of the impression mail and quantitatively evaluates the degree of understanding and motivation of the students. For example, if the impression mail contains many pre-defined “motivated words” such as “done”, “done”, and “want to do”, it can be determined that the student has a high level of understanding and willingness to learn. Thus, the lesson management apparatus 100 shown in the present embodiment can also quantify the student's response to the lesson by analyzing the terms included in the impression mail.

The user may give an assignment to the student. The students collect the answers to the assignments in a report file, attach it to an e-mail, and send it to the course address. The user grasps the degree of understanding of each student according to the result of this report, and in some cases requests re-submission of the report. Hereinafter, an e-mail attached with a report file is referred to as “report mail”.
In this way, various information obtained from student e-mails is used as useful information for improving class content.

FIG. 2 is a functional block diagram of the lesson management apparatus 100.
Each block shown here can be realized in hardware by an element such as a CPU of a computer or a mechanical device, and in software it is realized by a computer program or the like. Draw functional blocks. Therefore, those skilled in the art will understand that these functional blocks can be realized in various forms by a combination of hardware and software.

The lesson management apparatus 100 includes a user interface processing unit 110, a communication unit 120, a data processing unit 130, and a data holding unit 150.
The user interface processing unit 110 is in charge of processing related to the entire user interface, such as input processing from a teacher user and information display for the user. The communication unit 120 is in charge of communication processing with the client terminal 204 via the mail server 202. The data holding unit 150 stores various data such as setting data prepared in advance and an e-mail received from the data processing unit 130. The data processing unit 130 executes various types of data processing based on data acquired from the user interface processing unit 110 and the communication unit 120. The data processing unit 130 also serves as an interface among the user interface processing unit 110, the communication unit 120, and the data holding unit 150.

  The user interface processing unit 110 includes a display unit 112 and an input unit 118. The input unit 118 receives an input operation from the user. The display unit 112 displays various information to the user.

The communication unit 120 includes a mail transmission / reception unit 122 for processing transmission / reception of mail. The mail transmission / reception unit 122 further includes a normal mail transmission / reception unit 124 and an automatic mail transmission unit 126. The normal mail transmission / reception unit 124 transmits emails for various notifications to the client terminal 204, and receives various emails such as attendance emails, impression emails, and report emails from the client terminal 204. The automatic mail transmission unit 126 automatically transmits a predetermined electronic mail when a predetermined condition set in the lesson management apparatus 100 is satisfied. For example, when an impression mail for a class is received from a student who is not actually attending the class, an e-mail in which a message that warns fraud is described is automatically transmitted.
Hereinafter, an e-mail in which such a predetermined message is described and automatically transmitted by the automatic e-mail transmission unit 126 is referred to as “automatic mail”, and other normal e-mail is referred to as “normal e-mail”. Distinguish as “e-mail”

The data holding unit 150 includes a mail data holding unit 152, a report holding unit 160, a chart data holding unit 172, and a form holding unit 170.
The mail data holding unit 152 holds an e-mail received from a student. The report holding unit 160 holds a report file attached to the report mail.

  The chart data holding unit 172 holds chart data that is a basis for the user to determine the student's learning status. The chart data includes, for example, data corresponding to various predetermined items such as a student's name and email address, attendance status, contents described in the impression email, and report file submission status. A specific data structure of the chart data holding unit 172 will be described later with reference to FIG.

  The form holding unit 170 holds form data in which a display layout is defined when the chart display processing unit 114 displays the chart data on the screen. The form data defines the data to be displayed and the display method of the chart data. The form data can also include logic for displaying a result of a predetermined calculation based on the chart data when the chart data is displayed on the chart chart 300 described later. Specifically, this will be described in detail with reference to FIG.

The data processing unit 130 includes a mail processing unit 132, a report processing unit 148, a consistency determination unit 136, and a lesson data management unit 138.
The mail processing unit 132 analyzes the content of the received electronic mail. The mail processing unit 132 includes a mail classification unit 134. The mail classification unit 134 performs classification according to the contents of the email. As already mentioned, there are various types of e-mails received from students, such as attendance mails, impression mails, and report mails. The mail classification unit 134 classifies e-mails in which the command “attendance” is described in the body of the e-mail as attendance mails, and classifies e-mails in which the command “report” is described as report mails. A student writes such various commands at the beginning of the text and sends an e-mail.
The report processing unit 148 acquires a report file from the report mail and stores it in the report holding unit 160.

  The lesson data management unit 138 manages data related to courses as lesson data for each lesson. The course consists of one or more classes. For example, various data such as the average score of the exam, the degree of understanding of the student analyzed from the impression mail, and the lesson plan are managed as lesson data.

The lesson data management unit 138 includes a student management unit 140 and a setting unit 142.
The student management unit 140 manages data related to the student's learning status, such as attendance rate and test results. The student management unit 140 further includes a medical record management unit 168 and a processing module group 146. The medical chart management unit 168 appropriately updates the medical record data in the medical record data holding unit 172 in cooperation with various processing modules included in the processing module group 146.

  The processing module group 146 is a set of various processing modules for acquiring, calculating, and generating data included in the chart data. The processing module group 146 includes various types of processing modules such as an attendance processing module for processing attendance mail, an opinion processing module for processing impression mail, and a report processing module for processing report mail. . The mail classification unit 134 classifies the electronic mail according to the command described in the body of the electronic mail, and transfers the electronic mail to the corresponding processing module.

  The attendance processing module that processes attendance emails determines which class in which course the attendance email sender is attending based on information such as the address of the attendance email address and the date and time of transmission. . The medical chart management unit 168 updates the attendance data in the medical chart data with the data obtained as the processing result of the attendance processing module.

  Similarly, the impression processing module that processes the impression mail detects what type of terminology the student uses by performing natural language processing on the body of the impression mail. For example, when “students have knowledge”, it is considered that many specific terms such as “know” and “remembered” are included in the impression mail. The impression processing module quantifies the degree of understanding, satisfaction, achievement, etc. of the students based on the terms included in the impression email. Moreover, it is considered that the number of characters in the impression mail (hereinafter simply referred to as “the number of impression characters”) increases as the students are motivated in the class. The impression processing module counts the number of impression characters as an index for measuring a student's willingness to class. The medical chart management unit 168 records data obtained as a processing result of the impression processing module as a part of the medical chart data.

In other words, in accordance with the type of electronic mail, in other words, the processing module to process the electronic mail is automatically determined according to the command included in the electronic mail. Each processing module is preferably configured to be arbitrarily added / changed as a plug-in. According to such an aspect, the contents of the chart data can be flexibly changed by changing the processing modules registered in the processing module group.
The setting unit 142 sets conditions for various processes in the lesson management apparatus 100 according to instructions from the user, such as various conditions in the matching determination unit 136, the mail classification unit 134, and the like.

  The matching determination unit 136 executes a matching determination process. The matching determination process can be roughly divided into the following two types of determination processes. The condition for determination is set by the setting unit 142.

1. Judgment process when receiving e-mail (hereinafter referred to as “first matching judgment process”)
The first matching determination process is a process for determining whether an e-mail is an effective e-mail for determining a student's learning status when the e-mail is received. For example, attendance emails received before the start of a lesson are not valid. The matching determination unit 136 determines that an attendance email out of such timing is not subject to processing. Hereinafter, such determination that is not subject to processing is referred to as “invalidity determination”, and determination that is subject to processing is referred to as “validity determination”. The setting unit 142 can set a reception period according to the type of email. For example, when the class day is “August 31 10:00 to 10:45” and the attendance acceptance period is set to “August 31 10:00 to 10:05”, the consistency determination unit 136 Attendance emails acquired outside the acceptance period are determined to be invalid.
All e-mails classified by the mail classification unit 134 are subject to the first matching determination process. Only e-mails that are determined to be valid by the first matching determination process are processed by the processing module group 146. However, as described later, the e-mail that is determined to be invalid is stored in the mail data holding unit 152 without being discarded.

2. Judgment processing for data included in medical chart data (hereinafter referred to as “second matching judgment processing”)
The second matching determination process is a process for detecting whether a predetermined relationship is established between the data included in the chart data. For example, a process for detecting a student who has a high attendance rate but a poor test result is applicable. The second alignment determination process will be further described in detail with reference to FIGS.

FIG. 3 is a data structure diagram of medical chart data in the medical chart data holding unit 172.
The figure shows the chart data of each student for the course “French A2005”. Here, only a part of various data included in the chart data is shown.

  The ID column 282 indicates an ID (hereinafter referred to as “student ID”) assigned in advance to identify the student. The name column 284 shows a student name. An attendance history column 286 indicates the attendance status of students for 15 classes of “French A2005”. Circles in the figure indicate attendance, and crosses indicate absence. When the attendance mail is received, the chart management unit 168 updates the corresponding data in the attendance history column 286. However, the premise for this is that the attendance mail is determined to be valid by the first matching determination process.

Similarly, in the course of “French A2005”, students are obliged to submit a total of nine reports. The report submission history column 288 indicates the report submission status of each student. The circle in the figure indicates that the submission has been completed, and the cross indicates that the submission has not been made. When the report mail is received and is determined to be valid by the first matching determination process, the chart management unit 168 updates the corresponding data in the report submission history column 288.
The special remarks column 292 is data input by the teacher via the input unit 118. You can write comments about the students freely. Thus, the chart data is composed of data that is automatically described by the chart management unit 168 upon receipt of the electronic mail and data that is input by the user.

FIG. 4 is a screen view of the menu screen of the lesson management apparatus 100.
When a user who is a teacher logs in to the lesson management apparatus 100, first, the menu screen 210 is displayed. The course selection area 212 displays a list of currently opened courses. Here, three courses of “French A2005”, “French B2005” and “French C2005” are opened. In the figure, “French A2005” is selected.

  When one of the buttons included in the menu button group 214 is selected, a screen for accessing various lesson data about the course selected in the course selection area 212 is displayed. The attendance book button 216 is a button for displaying the attendance status of students. The impression acceptance button 218 is a button for displaying a list of the contents of the impression mail received from the student. The submission management button 220 is a button for displaying the report file submission status. The test result button 222 is a button for displaying a list of test results. The consistency check button 224 is a button for displaying a screen for setting consistency conditions. The medical record button 226 is a button for displaying information on the student's lesson attitudes and grades as “karte”. The notification button 228 is a button for displaying a screen for notifying notification items related to lessons such as absence notice. The voting button 230 is a button for displaying a screen for collecting students' opinions.

  Here, as basic functions of the lesson management apparatus 100, attendances displayed when the attendance book button 216, the impression reception button 218, and the submission management button 220 in the button group of the menu button group 214 are selected, respectively. The book screen 240, the impression reception screen 250, and the submission management screen 260 will be described. Thereafter, the consistency check screen 270 displayed when the consistency check button 224 is selected will be described focusing on the second consistency determination process.

FIG. 5 is a screen view of the attendance book screen 240.
The attendance book screen 240 is displayed when the attendance book button 216 is clicked on the menu screen 210 of FIG. The teacher shows the secret words of the class to the students at the start of the class. The secret word may be shown verbally in the classroom. The student who attended the class inputs this password and sends an attendance email to the course address. The mail classification unit 134 classifies the attendance mail and passes the attendance mail to the consistency determination unit 136. The matching determination unit 136 determines whether a correct password is described in the attendance mail as the first matching determination process. Attendance emails that do not contain the correct password are judged invalid. If the correct password is described, it will be processed by the attendance processing module. Then, the lesson data management unit 138 recognizes the student who is the sender of the attendance email as a regular attendee. The display unit 112 displays the names of students attending the class on the attendance list screen 240.

  The class selection area 242 displays the attendance status regarding each class of the “French A2005” class. According to the figure, the lesson of this course is the fourth, and the attendance rate for the four lessons is listed. In the lesson selection area 242, the fourth lesson of the theme “pronunciation of R” is selected. The attendance status display area 244 displays a list of names of students attending the fourth class selected in the class selection area 242. Here, of the 6 students registered in the course, 5 students except for “Takeharu Yoshiharu” attend the class. When the lesson management apparatus 100 accepts the attendance mail, the display unit 112 automatically updates the contents of the attendance book screen 240, so that the teacher can accurately grasp the attendance status of each student in real time by the attendance book screen 240.

FIG. 6 is a screen view of the impression acceptance screen 250.
The impression acceptance screen 250 is displayed when the impression acceptance button 218 is clicked on the menu screen 210 of FIG. When the class is over, the student sends an impression email to the course address. This feedback email allows the teacher to immediately know the student's reaction to the lesson. The lesson selection area 252 displays the reception status of the impression mail regarding each lesson of the “French A2005” course. In the class selection area 252, the fourth class is selected. The impression list area 256 displays a list of student's impressions regarding the fourth class selected in the class selection area 252. Furthermore, the impression display area 254 displays the impression of the student “Mayumi Arai” selected in the impression list area 256.

Here, when the teacher sets the keyword “question”, the student whose word “question” is included in the impression mail is marked with an asterisk. This feature allows teachers to easily find feedback emails that contain questions.
The medical chart management unit 168 updates the medical record data in the medical record data holding unit 172 when the impression mail is received. However, the content of the comment mail that has not been determined to be valid in the first matching determination process is not reflected as part of the chart data.

FIG. 7 is a screen diagram of the submission management screen 260.
The submission management screen 260 is displayed when the submission management button 220 is clicked on the menu screen 210 of FIG. Students answer the tasks presented by the teacher during the lesson and compile them as a report file. Then, an electronic mail with a report file attached to the course address, that is, a report mail is transmitted. Upon receiving the report mail, the lesson management apparatus 100 updates the data related to the report submission status shown in the unsubmitted column 288 of the medical record data. As the first matching determination process, the matching determination unit 136 checks whether a report file is attached to the report mail. If it is not attached, the report mail is judged invalid.

  The class selection area 262 shows the report submission status for each class of the “French A2005” class. The class selection area 262 indicates the report deadline date, the remaining days until the deadline, the report file submission rate, and the like. In the class selection area 262, the fourth class is selected. The submission status list area 264 displays a report submission status of each student for the fourth class selected in the class selection area 262.

The submission status list area 264 also displays the number of typographical errors and omissions in each student's report file. In addition, when a student submits a report file a plurality of times, the number of typographical and omissions compared to the previous report file is shown to increase or decrease. For example, according to the submission status list area 264, the student “Hideyuki Ishida” has submitted the report file twice in the fourth class “pronunciation of R”. This means that “Hideyuki Ishida” has resubmitted the report file. As a result of the pre-processing for the second report file, the number of detected typographical characters and omissions is two, and an upward arrow indicates that the number is increased compared to the first report.
Such a preprocessing may be executed by a preprocessing unit (not shown) or may be realized as a function of the report processing unit 148. As an algorithm for detecting typographical errors and omissions, a technique used in existing document creation support software may be applied.

FIG. 8 is a screen diagram of the consistency check screen 270.
The consistency check screen 270 is displayed when the consistency check button 224 is clicked on the menu screen 210 of FIG. The detection condition list area 266 displays a list of detection conditions that are determination criteria in the second matching determination process. The matching determination unit 136 searches the chart data for data that matches various detection conditions shown in the detection condition list area 266 and displays the search result in the corresponding person list area 268.

In the figure, five types of detection conditions are set. That is,
1. Are there unsubmitted submissions?
This is a condition for detecting a student who has not submitted a report file (hereinafter referred to as “first detection condition”).
2. Do you have an unsubmitted impression?
This is a condition for detecting a student who has not sent a comment email (hereinafter referred to as “second detection condition”).
3. The length of the comment email text is shorter than the average.
This is a condition for classifying students in comparison with the average value of the number of impression letters in the students of the course. (Hereinafter referred to as “third detection condition”).
4). Impressions on absence days.
This is a condition for detecting a student who is cheating to send an impression mail without attending a class (hereinafter referred to as “fourth detection condition”).
5). Attendance and exam scores are not proportional.
This is a condition for classifying students according to the correlation between the attendance rate and the test result (hereinafter referred to as “fifth detection condition”).
These are five.
The second matching determination process is executed according to each of these detection conditions. Hereinafter, each detection condition will be described. Note that the e-mail that has been determined to be invalid by the first matching determination process is not a target of processing by the processing module group 146, and therefore is not a target of the second matching determination process. In addition to this, the user can arbitrarily set detection conditions.

First detection condition:
When the report mail is received and is determined to be valid in the first matching determination process, the chart management unit 168 updates the corresponding part in the report submission history column 288. The matching determination unit 136 refers to the report submission history column 288 and classifies the report submission status of each student into the following three cases.
a) All reports have been submitted b) Some reports have been submitted and some reports have not been submitted c) All reports have not been submitted When the first detection condition is selected in the detection condition list area 266, the corresponding person list area 268 Then, next to each student's name, a circle mark is added to the case of a, a triangle mark is added to the case of b, and a cross mark is added to the case of c.

Second detection condition:
This is also the same as the report submission status, and when the impression mail is received and is determined to be valid in the first matching determination process, the chart management unit 168 updates the data indicating the impression mail submission status in the chart data. The matching determination unit 136 refers to a column (not shown) indicating the impression mail submission history of the chart data, and classifies each student's impression mail submission status into the following three cases.
a) All feedback emails have been received b) There have been received feedback emails and some have not yet received c) All feedback emails have not been received When the second detection condition is selected in the detection condition list area 266, the corresponding In the student list area 268, a circle mark is added to the name of each student, a triangle mark is added to the case of b, a triangle mark is added to the case of c, and a cross mark is added to the case of c.

Third detection condition:
When the impression mail is received and the clear determination is made in the first matching determination process, the impression processing module counts the number of impression characters. The medical chart management unit 168 updates data (not shown) indicating the number of impression characters in the medical chart data. The matching determination unit 136 classifies the students into the following three types by comparing the number of impression characters of the students to be investigated and the average value of the impression characters of all the students registered in the course.
Here, A is the number of lessons in which the number of impression characters of the students to be surveyed falls below the overall average value, and B is the number of lessons in which the number of lesson characters exceeds the overall average value.
a) A> B + 2
Students with fewer impressions than average b) B + 2 ≧ A ≧ B-2
Students with average number of impression characters c) B-2>A> 0
Students with more impressions than average d) A = 0
When the third detection condition is selected in the student detection condition list area 266 where the number of impression characters is always equal to or greater than the average, in the corresponding person list area 268, in the case of a, in the case of a, a cross mark, If it is a case, a triangle mark is displayed, if it is a case c, a circle mark is displayed.

Fourth detection condition:
This is a condition that is satisfied when an impression email is received but no student attends the class. Since such an impression mail is determined to be invalid by the first matching determination process, the impression mail is not an analysis target of the impression processing module. However, the fact that such a fraudulent impression mail is received is recorded as a part of the chart data. In the drawing, the fourth detection condition is selected in the detection condition list area 266, and the corresponding person list area 268 displays that “Mayumi Arai” and “Naoe Takechi” are applicable.

Fifth detection condition:
Since the number of impression letters in the impression email is thought to represent the student's willingness to attend classes, there may be some correlation between the number of impression letters and the test results. In the present example, it is assumed that a test with 100 points is performed at the end of the course of “French A2005”. The test result is input to the lesson management apparatus 100 by the user. The chart data includes data indicating the test results of each student. The matching determination unit 136 assigns each student the following 5 data based on four types of data: the attendance rate of the students to be surveyed, the average attendance rate as a whole, the score of the students to be surveyed, and the average score as a whole. Classify into types.
a) Average attendance rate + 10% <Student attendance rate and Average score + 5 <Student score Excellent students with good attendance rate and good test results.
b) Average attendance rate + 10% <Student attendance rate and average score -5> Student score Students with good attendance but poor test results. The class content may not have been effective for such students.
c) Average attendance rate – 10%> Student attendance rate and Average score + 5 <Student score The attendance rate is poor, but the test results are good. The existence of such a student may have caused the class content and the exam content not to be related.
d) Average attendance rate-10%> Student attendance rate and Average score-5> Student score Those students who need some kind of response with poor attendance rate and poor test results.
e) When not applicable to any of the above a to d According to the determination result, the corresponding person list area 268 displays a symbol corresponding to the case next to each student's name.
By executing the second matching determination process based on these various detection conditions, it becomes easier for the user to grasp the relationship between various data.

FIG. 9 is a flowchart showing an e-mail acceptance process.
First, the normal mail transmitting / receiving unit 124 receives an e-mail from a student (S10). The mail classification unit 134 classifies the email according to the command (S12).

  The matching determination unit 136 executes a first matching determination process (S14). When the validity determination is made by the first matching determination process (Y in S14), the electronic mail is transferred to the corresponding processing module. The processing module extracts data from a predetermined part of the e-mail and generates data for medical chart data (S16). On the other hand, when the invalidity determination is made (N in S14), the matching determination unit 136 instructs the automatic mail transmission unit 126 to transmit an e-mail in which a message that pays attention to the student is described (S18).

  The medical chart management unit 168 records the data generated by the processing module as the processing result of S16 in the medical chart data (S20). When invalidity is determined in the first matching determination process, “invalidity determination has occurred” is recorded in the medical record data. Regardless of the result of the first matching determination process, the received e-mail is stored in the mail data holding unit 152 (S21). Therefore, the determination conditions in the first matching determination process can be set and changed afterwards, and the first matching determination process can be re-executed for the stored e-mail. In this case, an e-mail that has been determined to be invalid may change to a validity determination, and vice versa. Regardless of the result of the first match determination process, the e-mail is stored in the mail data holding unit 152, thereby making it possible to change the conditions regarding the first match determination process.

  After the medical chart data is updated, the consistency determination unit 136 executes a second alignment determination process (S22). As described with reference to FIG. 8, if there is data corresponding to various detection conditions (Y in S24), that fact is also recorded as a part of the chart data (S26). If not (N in S24), the process of S26 is skipped. Note that the processing after S22 may be executed when the consistency check screen 270 is displayed, or may be executed every time an e-mail is received.

FIG. 10 is a screen view of the medical chart screen 300.
Here, only a part of various data to be displayed on the medical chart screen 300 is shown. When the user designates a course on the menu screen 210 of FIG. 4 and clicks the chart button 226, the display unit 112 displays the chart data in the display layout defined in the form data. The ID display area 302 shows the student ID in the ID column 282 of FIG. When the student ID is changed, the chart data for another student is displayed. Thus, the chart screen 300 is displayed on a separate screen for each course and for each student. Here, the medical record data of “Mayumi Arai” who is a student of “French A2005” is displayed.

The name display area 304 displays the student name in the name field 284 of FIG. An attendance status display area 306 shows the attendance status of students in the attendance history column 286 of FIG. In the form data, the column of the attendance status display area 306 is designed on the assumption that there are 15 classes of the “French A2005” course in advance. Users can freely design form data. An attendance status display area 306 corresponds to the data in the attendance history column 286. The attendance rate display area 307 indicates the attendance rate and absence rate (collectively referred to as “attendance rate”) of “French A2005” by “Mayumi Arai”. The form data describes an expression for calculating the attendance rate based on the attendance data shown in the attendance status display area 306. The display unit 112 instructs the medical chart management unit 168 to execute calculation when such calculation formula is described in the form data when displaying the medical chart data. The medical chart management unit 168 calculates the attendance rate and absence rate by referring to the medical record data and form data, and passes the calculation results to the display unit 112. The display unit 112 displays the calculation result in the attendance rate display area 307 as an attendance rate.
The consistency display area 308 shows the result of the second consistency determination process. The detection conditions to be displayed can be selected by form data, but in the figure, all the five detection conditions shown in FIG. 8 are displayed.

  The sentence length transition display area 310 shows, as a graph, changes in the number of impression characters in the text of the impression mail sent by the student after the class ends. The graph in the sentence length transition display area 310 is useful for determining the change in the student's willingness. By utilizing not only the contents of e-mail but also the data that reflects the student's unconscious psychology, such as the number of impression letters, the student's learning status can be explored in many ways.

  The medical record management unit 168 calculates the average value of the number of impression characters for all students. The chart display processing unit 114 displays the average value of the number of impression characters of all the students and the number of impression characters of the student “Mayumi Arai” in the sentence length transition display area 310. For this reason, the user who is a teacher can grasp the overall tendency and the individual tendency together.

The present invention has been described above based on the embodiments.
According to the lesson management apparatus 100 shown in the present embodiment, various data obtained when the lesson evaluation system 10 is operated can be collected as medical record data. The chart screen 300 makes it easy for the user to grasp the learning status of each student in a fine-grained manner at a glance. Since the chart data is generated based on the student's email, the burden on the teacher for creating the chart data can be reduced.

The lesson management apparatus 100 can effectively exclude an unauthorized e-mail as an analysis target by the first matching determination process. By setting various detection conditions for the chart data, it becomes easy to analyze the learning status of the students indicated in the chart data from various aspects. Furthermore, since a set of data included in a plurality of student chart data and an operation result such as an average value calculated based on the data can be included in the variable of the second matching determination process, Raw information obtained from e-mails can be processed into high-quality information for managing the student's learning status.
Such a consistency determination process can reduce the burden for the teacher to manage the learning status of each student while acquiring a large number of e-mails from a large number of students.

  It should be understood by those skilled in the art that the functions to be fulfilled by the constituent elements described in the claims are realized by a single function block shown in the present embodiment or a combination thereof.

  The present invention has been described based on the embodiments. This embodiment is an exemplification, and it will be understood by those skilled in the art that various modifications can be made to combinations of the respective constituent elements and processing processes, and such modifications are also within the scope of the present invention. is there.

It is a hardware block diagram of a lesson evaluation system. It is a functional block diagram of a lesson management device. It is a data structure figure of the chart data in a chart data holding part. It is a screen figure of the menu screen of a lesson management apparatus. It is a screen figure of an attendance book screen. It is a screen figure of an impression reception screen. It is a screen figure of a submission management screen. It is a screen figure of a consistency check screen. It is a flowchart which shows the reception process process of an email. It is a screen figure of a medical chart screen.

Explanation of symbols

  10 class evaluation system, 100 class management device, 110 user interface processing unit, 112 display unit, 118 input unit, 120 communication unit, 122 mail transmission / reception unit, 124 normal mail transmission / reception unit, 126 automatic mail transmission unit, 130 data processing unit, 132 mail processing unit, 134 mail classification unit, 136 consistency judgment unit, 138 lesson data management unit, 140 student management unit, 142 setting unit, 146 processing module group, 148 report processing unit, 150 data holding unit, 152 mail data holding unit 160 report holding unit, 168 chart management unit, 170 form holding unit, 172 chart data holding unit, 200 Internet, 202 mail server, 204 client terminal, 210 menu screen, 240 attendance screen, 250 impression acceptance screen, 260 submission management screen, 270 consistency check screen, 300 chart screen.

Claims (9)

A device for supporting classes by managing the learning status of students,
A chart holding unit for holding chart data indicating a student's learning status by a plurality of items;
An email receiver for receiving emails from students;
A consistency determination unit that determines whether a predetermined relationship is established between a command character string included in the e-mail and data of a predetermined item in the medical record data;
An update processing unit that updates the data of the item associated with the command character string in the medical record data with the data described in the e-mail on condition that the determination by the matching determination unit has a predetermined result;
A class management device comprising:   The matching determination unit refers to a table that defines an abnormal combination of the command character string included in the e-mail and the data of the predetermined item, and the data of the predetermined item in the command character string and the medical record data is the incorrect data. The lesson management apparatus according to claim 1, wherein it is determined whether the combination corresponds to a normal combination. A device for supporting classes by managing the learning status of students,
A chart holding unit for holding chart data indicating a student's learning status by a plurality of items;
An email receiver for receiving emails from students;
An update processing unit that extracts data from a predetermined part of the e-mail and updates data of items corresponding to the extracted data in the medical record data;
A consistency determination unit that determines whether a predetermined relationship is established between data of a predetermined item in the student's medical record data and data of an item different from the predetermined item;
A class management device comprising: A device for supporting classes by managing the learning status of students,
A chart holding unit for holding chart data indicating a student's learning status by a plurality of items;
An email receiver for receiving emails from students;
An update processing unit that extracts data from a predetermined part of the e-mail and updates data of items corresponding to the extracted data in the medical record data;
A consistency determination unit that determines whether a predetermined relationship is established between data of a predetermined item in the student's medical record data and data of a predetermined item in the medical record data of a student different from the student;
A class management device comprising:   The consistency determination unit determines whether a predetermined relationship is established between a set of data for a predetermined item in a plurality of student chart data groups and data for a predetermined item in the student chart data group. The lesson management apparatus according to claim 4, wherein the lesson management apparatus is characterized.   The matching determination unit has a predetermined interval between a processing result when a predetermined calculation is performed using data on a predetermined item in a plurality of student chart data groups as a variable and data on a predetermined item in the student chart data. 6. The lesson management apparatus according to claim 5, wherein it is determined whether or not the relationship is established.   The lesson management apparatus according to claim 1, wherein the update processing unit reflects a determination result by the consistency determination unit as a part of the medical record data. A method for supporting a class by managing the learning status of students,
Receiving e-mails from students;
Regarding chart data indicating a student's learning status by a plurality of items, determining whether a predetermined relationship is established between a command character string included in the e-mail and data of a predetermined item in the chart data;
Updating the data of the item associated with the command character string in the medical record data with the data described in the e-mail on the condition that the determination result is a predetermined result;
Class management method characterized by comprising. A computer program for supporting lessons by managing the learning status of students,
A function to hold medical chart data indicating the student's learning status with multiple items,
The ability to receive email from students,
A function for determining whether a predetermined relationship is established between a command character string included in the e-mail and data of a predetermined item in the medical record data;
A function of updating the data of the item associated with the command character string in the medical record data with the data described in the e-mail on the condition that the determination result is a predetermined result;
A class management program characterized by letting a computer demonstrate.

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