Processing device, processing method, and program

Abstract

To provide a novel technique for a teacher to get to know the attitude of a student toward a class.SOLUTION: A processor 100 includes: an input word acquisition unit 101 for acquiring input words as words input into each student terminal; a classification unit 102 for classifying the input words in a plurality of categories; and a first output unit 103 for displaying a list of at least a part of the input words and outputting a screen showing the result of the classification of the input words in the list through an output terminal.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] The present invention relates to a processing device, a processing method, and a program. [Background technology]

[0002] Techniques related to the present invention are disclosed in Patent Documents 1 and 2.

[0003] Patent Document 1 discloses a learning system that uses videos and discloses a technology for acquiring a learning log showing the learning attitude during learning, including the number of times the video is paused, the number of times the video is rewound, the start and end points of the rewind points, the number of times the video is fast-forwarded, the start and end points of the fast-forward points, and playback speed adjustments.

[0004] Patent Document 2 discloses a technology that allows teachers to understand students' behavior by detecting and displaying behavioral history information for each student, including other applications operated while working on a learning assignment, the number of times other applications were operated, location information, and the number of times the student looked away from the answer screen while working on a learning assignment. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Publication No. 2020-134878 [Patent Document 2] Japanese Patent Application Laid-Open No. 2017-161783 Summary of the Invention [Problem to be solved by the invention]

[0006] The goal is to provide new technology that will enable teachers to understand students' attitudes toward lessons. [Means for solving the problem]

[0007] According to the present invention, an input word acquisition means for acquiring an input word that is a word input to each of the plurality of student terminals; a classification means for classifying the input words into a plurality of categories; an output means for displaying a list of at least some of the input words and outputting, via an output terminal, a screen showing the classification results for each of the input words displayed in the list; A processing device is provided having:

[0008] Further, according to the present invention, The computer an input word acquisition step of acquiring input words which are words input to each of the plurality of student terminals; a classification step of classifying the input words into a plurality of categories; an output step of displaying a list of at least some of the input words and outputting, via an output terminal, a screen showing the classification results for each of the input words displayed in the list; A processing method for performing the above is provided.

[0009] Further, according to the present invention, Computer, an input word acquisition means for acquiring an input word which is a word input to each of the plurality of student terminals; a classification means for classifying the input words into a plurality of categories; an output means for displaying a list of at least some of the input words and outputting, via an output terminal, a screen showing the classification results for each of the input words displayed in the list; A program is provided to function as a [Effects of the Invention]

[0010] According to the present invention, a new technique is realized that allows teachers to grasp students' attitudes toward lessons. [Brief explanation of the drawings]

[0011] [Figure 1]FIG. 1 is a diagram illustrating an example of a functional block diagram of a system according to an embodiment of the present invention. [Figure 2] FIG. 2 is a diagram schematically illustrating an example of information output by the system of the present embodiment. [Figure 3] FIG. 2 is a diagram schematically illustrating an example of information output by the system of the present embodiment. [Figure 4] FIG. 2 is a diagram illustrating an example of a hardware configuration of the device according to the present embodiment. [Figure 5] FIG. 2 is a diagram illustrating an example of a functional block diagram of the processing apparatus according to the present embodiment. [Figure 6] FIG. 2 is a diagram schematically illustrating an example of information processed by the processing device of the present embodiment. [Figure 7] FIG. 2 is a diagram schematically illustrating an example of information processed by the processing device of the present embodiment. [Figure 8] 10 is a flowchart showing an example of a processing flow of the processing device of the present embodiment. [Figure 9] FIG. 2 is a diagram illustrating an example of a functional block diagram of the processing apparatus according to the present embodiment. [Figure 10] FIG. 2 is a diagram illustrating an example of a functional block diagram of the processing apparatus according to the present embodiment. [Figure 11] FIG. 2 is a diagram schematically illustrating an example of information processed by the processing device of the present embodiment. [Figure 12] FIG. 2 is a diagram illustrating an example of a functional block diagram of the processing apparatus according to the present embodiment. [Figure 13] 10 is a flowchart showing an example of a processing flow of the processing device of the present embodiment. [Figure 14] FIG. 2 is a diagram illustrating an example of a functional block diagram of the processing apparatus according to the present embodiment. [Figure 15] FIG. 2 is a diagram schematically illustrating an example of information processed by the processing device of the present embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0012] Hereinafter, embodiments of the present invention will be described with reference to the drawings. In all the drawings, like components are designated by like reference numerals, and the description thereof will be omitted as appropriate.

[0013] First Embodiment "Overall picture and overview" First, the overall picture and outline of the system of this embodiment will be described. As shown in Fig. 1, the system of this embodiment is realized by a processing device 100, a plurality of student terminals 200, and a teacher terminal 300.

[0014] The student terminal 200 is a terminal used by a student. The student terminal 200 is used, for example, during class. Situations in which the student terminal 200 is used include, but is not limited to, viewing digital textbooks and digital teaching materials, studying using digital workbooks and the like, managing attendance and grades, communicating using chat functions and the like, gathering information using a web browser, and using various applications.

[0015] It is preferable that each student has one student terminal 200, but M (M is an integer of 2 or more) students may share one student terminal 200. Examples of the student terminal 200 include, but are not limited to, a PC (personal computer), a tablet terminal, a smartphone, etc.

[0016] The teacher terminal 300 is a terminal used by a teacher. The teacher terminal 300 is used, for example, during class. Situations in which it can be used include, but are not limited to, viewing digital textbooks and digital teaching materials, learning using digital workbooks, attendance and grade management, communication using a chat function, information gathering using a web browser, and use of various applications. Examples of the teacher terminal 300 include, but are not limited to, a PC, a tablet terminal, a smartphone, an electronic whiteboard, etc.

[0017] The processing device 100 acquires input words that are words input to each of the multiple student terminals 200, and classifies the input words into multiple categories. The categories include, for example, NG words that are not recommended to be input during class, interesting words that are recommended to be input during class, high-frequency words whose input frequency is equal to or greater than a threshold, and low-frequency words whose input frequency is less than a threshold.

[0018] Then, the processing device 100 displays a list of at least some of the input words, and outputs a screen (hereinafter referred to as "output screen") showing the results of categorizing the listed input words via an output terminal (for example, the teacher terminal 300). Examples of the output screen are shown in Figures 2 and 3.

[0019] In the example shown in Figure 2, the input words are displayed in a list divided by category. In the example shown in Figure 3, the input words are displayed in chronological order in the order they were entered, and the category and the name of the student who entered them are linked to each input word.

[0020] Simply displaying a list of input words makes it difficult to intuitively grasp the type of words that have been entered. As mentioned above, by classifying input words into multiple categories and displaying a list of input words along with the classification results, it is possible to intuitively grasp the type of words that have been entered. Teachers can then understand students' attitudes toward their lessons based on the trends in input words.

[0021] "Configuration of Student Terminal 200 and Teacher Terminal 300" There are no particular limitations on the configuration of the student terminal 200 and the teacher terminal 300. Any terminal configuration for GIGA (global and innovation gateway for all) schools can be adopted.

[0022] The special features that the student terminal 200 and the teacher terminal 300 have to realize the effect of this embodiment (the teacher can grasp the students' attitudes toward the lesson) will be explained appropriately in the explanation of the configuration of the processing device 100 below.

[0023] "Configuration of processing device 100" Next, the configuration of the processing device 100 will be described in detail.

[0024] -Hardware configuration- First, an example of the hardware configuration of the processing device 100 will be described. Fig. 4 is a diagram showing an example of the hardware configuration of the processing device 100. Each functional unit of the processing device 100 is realized by any combination of hardware and software, centered around a CPU (Central Processing Unit) of any computer, memory, programs loaded into the memory, a storage unit such as a hard disk that stores the programs (this can store programs that are pre-loaded when the device is shipped, as well as programs downloaded from storage media such as CDs (Compact Discs) or servers on the Internet), and a network connection interface. Those skilled in the art will understand that there are many variations in the realization methods and devices.

[0025] As shown in FIG. 4, the processing device 100 has a processor 1A, a memory 2A, an input / output interface 3A, a peripheral circuit 4A, and a bus 5A. The peripheral circuit 4A includes various modules. The processing device 100 does not necessarily have the peripheral circuit 4A. The processing device 100 may be configured as multiple physically and / or logically separated devices, or may be configured as a single physically and logically integrated device. When the processing device 100 is configured as multiple physically and / or logically separated devices, each of the multiple devices may have the above hardware configuration.

[0026] The bus 5A is a data transmission path for the processor 1A, memory 2A, peripheral circuit 4A, and input / output interface 3A to transmit and receive data to and from each other. The processor 1A is an arithmetic processing device such as a CPU or a GPU (Graphics Processing Unit). The memory 2A is a memory such as a RAM (Random Access Memory) or a ROM (Read Only Memory). The input / output interface 3A includes an interface for acquiring information from an input device, an external device, an external server, an external sensor, etc., and an interface for outputting information to an output device, an external device, an external server, etc. Examples of input devices include a keyboard, a mouse, a microphone, etc. Examples of output devices include a display, a speaker, a printer, a mailer, etc. The processor 1A can issue commands to each module and perform calculations based on the results of those calculations.

[0027] -Function configuration- Next, an example of the functional configuration of the processing device 100 will be described. Fig. 5 shows an example of a functional block diagram of the processing device 100 of this embodiment. As shown in the figure, the processing device 100 has an input word acquisition unit 101, a classification unit 102, a first output unit 103, and a first storage unit 104.

[0028] The input word acquisition unit 101 acquires input words that are words input to each of the multiple student terminals 200. The student terminals 200 have a function of monitoring the input words. Then, the student terminals 200 transmit the detected input words to the processing device 100. The input word acquisition unit 101 acquires the input words transmitted from the student terminals 200 in this manner.

[0029] The student terminal 200 may have a function of performing syntactic analysis on an input character string (sentence, word, etc.) and extracting words (input words) from the character string. The word extraction function may be provided by the input word acquisition unit 101 of the processing device 100. In this case, the student terminal 200 transmits the input character string (sentence, word, etc.) to the processing device 100. Then, the input word acquisition unit 101 performs syntactic analysis on the character string transmitted by the student terminal 200 and extracts words (input words).

[0030] The input word acquisition unit 101 stores the acquired input words in the first storage unit 104. FIG. 6 schematically shows an example of the input words stored in the first storage unit 104. In the example shown, the input words, the date and time of input, and the student identification information of the student who input them are associated and registered. For example, based on the login information to the student terminal 200, the student identification information of the student who input each input word can be identified.

[0031] The classification unit 102 classifies the input words acquired by the input word acquisition unit 101 into a plurality of categories. Then, the classification unit 102 registers the classification results in the first storage unit 104. In this embodiment, the types of categories are not particularly limited. Specific examples of the types of categories will be described in the following embodiment.

[0032] The classification unit 102 may perform statistical processing on the input words and classify the input words into a plurality of categories based on the results of the statistical processing. Alternatively, the classification unit 102 may classify the input words into a plurality of categories based on a category dictionary (see FIG. 7) in which each of a plurality of categories is associated with a word included in the category and registered. Alternatively, the classification unit 102 may classify the input words into categories using other methods.

[0033] The first output unit 103 displays a list of at least some (for example, all) of the input words acquired by the input word acquisition unit 101, and outputs an output screen showing the classification results of each of the listed input words via an output terminal. The output terminal is, for example, the teacher terminal 300. Alternatively, the student terminal 200 may be used as the output terminal. Examples of the output screen are shown in Figs. 2 and 3.

[0034] In the example shown in Fig. 2, the input words are displayed in a list divided by category. In the example shown in Fig. 3, the input words are displayed in chronological order in the order they were entered, and the category and the name of the student who entered them are displayed in association with each input word. The detailed configuration of the output screen will be described in the following embodiment.

[0035] Next, an example of the processing flow of the processing device 100 will be described with reference to the flowchart of FIG.

[0036] When the processing device 100 acquires input words that are words input to each of the multiple student terminals 200 (S10), it classifies the input words into multiple categories (S11). Then, the processing device 100 displays a list of at least some of the input words, and outputs an output screen (see FIGS. 2 and 3) showing the classification results for each of the listed input words via an output terminal such as the teacher terminal 300 (S12).

[0037] "Action and effect"

[0038] According to the system of this embodiment, at least a portion of the input words entered into each of the multiple student terminals 200 can be displayed in a list, and an output screen (see Figures 2 and 3) showing the results of classifying the listed input words can be output via an output terminal such as the teacher terminal 300.

[0039] Simply displaying a list of input words makes it difficult to intuitively grasp the trends of the words being entered. By classifying input words into multiple categories and displaying a list of the input words along with the classification results, as in the system of this embodiment, it becomes possible to intuitively grasp the trends of the words being entered. Teachers can then understand students' attitudes toward their lessons based on the trends of the input words.

[0040] <Second embodiment> In this embodiment, the system configuration of the first embodiment is more specific.

[0041] "Category specificity" The categories in this embodiment include at least one of NG words, interesting words, high frequency words, and low frequency words, and may further include other categories.

[0042] NG words are words that are not recommended to be input during class. NG words may be words that are not recommended to be input while at school (including not only during class but also during breaks, lunch, etc.). The types of words that are NG words are a design decision, but for example, NG words may be names of content that are not recommended to be used during class or at school, such as "games" or "manga."

[0043] Interesting words are words that are recommended to be input during class. Interesting words may be words that are recommended to be input while at school (including not only during class but also during breaks, lunch, etc.). What words are considered interesting words is a design matter, but interesting words may be, for example, words related to class, such as "projection" or "overlapping," that are based on a unique perspective.

[0044] A category dictionary (see FIG. 7) is prepared in advance, in which words included in each category, such as NG words and funny words, are linked and registered. Then, the classification unit 102 classifies input words into a plurality of categories based on this category dictionary.

[0045] A category dictionary showing definitions of NG words and interesting words may be prepared for each predetermined attribute. The attribute may include at least one of teacher, subject, school, region, grade, and class. In this case, the classification unit 102 classifies the input word into a category based on the category dictionary that matches the attribute of the lesson to which the input word is input. The attributes of the lesson to which the input word is input include the teacher in charge of the lesson, the subject of the lesson, the school where the lesson is being taught, the region where the school where the lesson is being taught is located, the class where the lesson is being taught, the grade of the class where the lesson is being taught, etc.

[0046] A high-frequency word is a word whose input frequency in the class is equal to or greater than a threshold. A low-frequency word is a word whose input frequency in the class is less than a threshold. The threshold is a design factor. The input frequency and threshold can be expressed as the number of inputs or the number of people who input. The classification unit 102 calculates the input frequency of each input word based on the input word history shown in FIG. 6, for example, and can classify each input word into a category of high-frequency word or low-frequency word based on the result of comparing the input frequency with the threshold.

[0047] "Specification of output screen" Next, a detailed description will be given of the output screen output by the first output unit 103 of this embodiment. An example of the output screen is shown in Figures 2 and 3.

[0048] In the example shown in FIG. 2, input words are displayed in a list divided by category. The multiple input words included in each category are displayed, for example, sorted in descending order of input frequency or descending order of input frequency. In the example shown, NG words, high-frequency words, and interesting words are displayed in descending order of input frequency. In addition, low-frequency words are displayed in descending order of input frequency. Displaying in this way makes it possible to grasp, for each category, frequently entered words and rare words that are not entered often.

[0049] In addition, when the first output unit 103 receives an input specifying one input word on this input screen, it may display the input frequency of the specified input word, information indicating the student who entered it (name, student identification information, etc.), the time of entry, etc.

[0050] In the example shown in Figure 3, the input words are displayed in chronological order in the order they were entered, and each input word is associated with a category and the name of the student who entered it. It is also possible to display each category in a different color. For example, the text or background color may be displayed in a different color. This makes it easier to intuitively understand which categories of words are frequently entered.

[0051] "Specifying the timing of displaying the output screen" Next, the display timing of the output screen will be described.

[0052] --Example 1-- The input word acquisition unit 101 acquires input words input during a lesson (from the start time of the lesson to the end time of the lesson) during the lesson. Then, the first output unit 103 outputs an output screen during the lesson. In this example, an output screen (see FIGS. 2 and 3) showing the input words input by the students is output in real time via the output terminal. The content displayed on the output screen is updated as needed based on the input words newly acquired by the input word acquisition unit 101.

[0053] --Example 2-- The input word acquisition unit 101 acquires input words input during a class (from the start time of the class to the end time of the class). The input word acquisition unit 101 may acquire the input words input during a class by real-time processing during the class, or may acquire them by batch processing after the class is over. In this example, the first output unit 103 processes all input words input by students during the class and generates an output screen (see FIGS. 2 and 3), which is output via an output terminal after the class, for example, in response to a request from a user (teacher). Theoretically, the output screen displayed in this example will have the same content as the output screen displayed at the end of the class in Example 1.

[0054] --Example 3-- The input word acquisition unit 101 acquires input words input between the start time and the end time of work. That is, it acquires input words input not only during classes but also during other times such as breaks and lunch breaks. The input word acquisition unit 101 may acquire the input words input between the start time and the end time of work by real-time processing, or may acquire them by batch processing after the end time of work.

[0055] In this example, as in Example 1, an output screen (see Figures 2 and 3) showing the input words entered by the students may be output in real time via the output terminal, or as in Example 2, after the end of school hours, an output screen generated by processing all the input words entered by the students during the day may be output via the output terminal.

[0056] Other configurations of the system of this embodiment are the same as those of the first embodiment.

[0057] The system of this embodiment achieves the same effects as those of the first embodiment. Furthermore, the system of this embodiment can classify input words into categories that include at least one of NG words, interesting words, high-frequency words, and low-frequency words. Based on the input trends of each of these categories, teachers can understand students' attitudes toward lessons.

[0058] Furthermore, according to the system of this embodiment, an output screen (see FIGS. 2 and 3) showing the input words entered by students can be output via the output terminal in real time during class, allowing the teacher to grasp the students' attitudes toward the class in real time during class.

[0059] Furthermore, according to the system of this embodiment, after the lesson, an output screen generated by processing all input words entered by students during the lesson can be output via an output terminal. This allows the teacher to grasp the students' attitude toward the lesson throughout the entire lesson and evaluate each student's class attitude, etc.

[0060] Furthermore, the system of this embodiment can acquire input words entered between the start and end of school hours. That is, it can acquire input words entered not only during classes but also during other times such as breaks and lunch. This allows teachers to evaluate not only students' attitudes toward classes but also their behavior at school, including how they spend their breaks and lunch times.

[0061] <Third embodiment> The system of this embodiment differs from the first and second embodiments in that it has a function for updating the category dictionary described above in response to a user operation.

[0062] 9 shows an example of a functional block diagram of the processing device 100 of this embodiment. As shown in the figure, the processing device 100 differs from those of the first and second embodiments in that it includes an update unit 105.

[0063] The update unit 105 updates the category dictionary. When the update unit 105 receives an input specifying one of the input words displayed in a list on the teacher terminal 300 and an input specifying the category of the specified input word, the update unit 105 associates the specified input word with the specified category and registers them in the category dictionary.

[0064] The method of displaying a list of input words on the teacher terminal 300 may be to display an output screen such as that shown in Figures 2 and 3. That is, input to update the category dictionary may be performed from the output screen such as that shown in Figures 2 and 3. For example, the teacher can determine words to be newly registered as NG words or interesting words from among the high-frequency words and low-frequency words on the output screen such as that shown in Figures 2 and 3, and perform input to register them in the above-mentioned category dictionary. When the output screen is displayed in real time during a lesson, the teacher can determine words to be newly registered as NG words or interesting words from among the high-frequency words and low-frequency words on the output screen during the lesson, and perform input to register them in the above-mentioned category dictionary.

[0065] Other configurations of the system of this embodiment are the same as those of the first and second embodiments.

[0066] The system of this embodiment achieves the same effects as those of the first and second embodiments. Furthermore, the system of this embodiment can update the category dictionary based on user input. Specifically, input words can be newly registered in the category dictionary. The system of this embodiment can register words actually entered by students in the category dictionary, making it possible to create a category dictionary that better suits the actual situation.

[0067] <Fourth embodiment> The system of this embodiment differs from the first to third embodiments in that it has a function of evaluating each student's attitude in class based on the classification results of each student's input words.

[0068] 10 shows an example of a functional block diagram of the processing device 100 of this embodiment. As shown in the figure, the processing device 100 differs from the first to third embodiments in that it includes a first evaluation unit 106. Although not shown, the processing device 100 of this embodiment may also include an update unit 105.

[0069] The first evaluation unit 106 evaluates each student's attitude in class based on the classification results of the input words entered by each student. The first evaluation unit 106 can evaluate the class attitude higher the higher the input frequency of the first category (the more times the input is made). Also, the first evaluation unit 106 can evaluate the class attitude lower the higher the input frequency of the second category (the more times the input is made).

[0070] The first category is words that are recommended to be input during class, such as interesting words. The second category is words that are not recommended to be input during class, such as NG words. For example, the first evaluation unit 106 may evaluate each student's attitude toward class using a five-point scale from A to E. The first evaluation unit 106 registers the evaluation results in the first storage unit 104.

[0071] FIG. 11 shows a schematic example of an evaluation result generated by the first evaluation unit 106. The figure shows the evaluation results of each student's class attitude in the second semester science class for class 1 of the fifth grade. In the figure, each student's class attitude is evaluated for each class. The figure shows the date of the class, the evaluation results of each student's class attitude in class on each day, and the interesting words and NG words entered by each student in class on each day.

[0072] The first output unit 103 can output the evaluation results of each student's attitude in class via an output terminal such as the teacher terminal 300. For example, the first output unit 103 may output a table as shown in Fig. 11. Alternatively, the first output unit 103 may generate and output a graph showing the evaluation results in a time series.

[0073] Other configurations of the system of this embodiment are the same as those of the first to third embodiments.

[0074] The system of this embodiment achieves the same effects as those of the first to third embodiments. Furthermore, the system of this embodiment can evaluate each student's class attitude based on the tendency of input words. Because the evaluation is based on the tendency of input words, objective and reliable evaluation results can be obtained.

[0075] <Fifth embodiment> First, an overview of the processing device 100 of this embodiment will be described. The processing device 100 acquires the operation history of each of the multiple student terminals 200 and detects a predefined NG operation from the operation history. If an NG operation is detected, the processing device 100 outputs warning information via an output terminal (for example, the teacher terminal 300).

[0076] In this way, the processing device 100 of this embodiment can detect students who are not properly attending classes based on the operation status of the student terminals 200 and notify the teacher.

[0077] 12 shows an example of a functional block diagram of the processing device 100 of this embodiment. As shown in the figure, the processing device 100 has an operation history acquisition unit 107, a detection unit 108, a second output unit 109, and a second storage unit 110. Although not shown, the processing device 100 may also have an input word acquisition unit 101, a classification unit 102, a first output unit 103, and a first storage unit 104. Furthermore, the processing device 100 may further have at least one of an update unit 105 and a first evaluation unit 106.

[0078] The operation history acquisition unit 107 acquires the operation history of each of the multiple student terminals 200. The operation history includes the application used, the content used, the login date and time, the logout date and time, the input operation details (the key input details, the touch operation details, etc.), etc. The student terminal 200 has a function for monitoring operations. Then, the student terminal 200 transmits the operation history, which is the history of the detected operations, to the processing device 100. The operation history acquisition unit 107 acquires the operation history transmitted from the student terminal 200 in this way.

[0079] The operation history acquisition unit 107 stores the acquired operation history in the second storage unit 110. An operation history is registered for each student in the second storage unit 110. For example, based on login information for each student terminal 200, it is possible to identify the student who performed an operation on each student terminal 200.

[0080] The detection unit 108 detects predefined NG operations from the operation history. An NG operation is an operation that is not recommended to be performed during class or at school. In this embodiment, the details of the NG operation are not limited. Specific examples of NG operations will be described in the following embodiment.

[0081] When an NG operation is detected, the second output unit 109 outputs warning information via an output terminal. The output terminal is, for example, the teacher terminal 300. The warning information is output via a display, a speaker, etc. of the teacher terminal 300.

[0082] Next, an example of the processing flow of the processing device 100 will be described with reference to the flowchart of FIG.

[0083] The processing device 100 acquires the operation history of each of the multiple student terminals 200 (S20), and detects a predefined NG operation from the operation history (S21). If the processing device 100 detects an NG operation (Yes in S22), it outputs warning information via an output terminal such as the teacher terminal 300 (S23). If the processing device 100 does not detect an NG operation (No in S22), the processing device 100 does not execute the process of outputting warning information.

[0084] Other configurations of the system of this embodiment are the same as those of the first to fourth embodiments.

[0085] According to the system of this embodiment, it is possible to detect students who are not properly participating in class and notify the teacher based on the operation status of the student terminal 200. Based on the content of the notification, the teacher can understand the students' attitude toward the class.

[0086] Furthermore, according to the system of this embodiment, when the processing device 100 has the same configuration as in the first to fourth embodiments, the same effects as in the first to fourth embodiments are realized.

[0087] Sixth Embodiment In this embodiment, the system configuration of the fifth embodiment is more concrete.

[0088] "Specification of prohibited operations" The NG actions of this embodiment include at least one of the following NG actions 1 to 3.

[0089] (NG Operation 1) Using content that is not specified. Content that is permitted to be used during classes or at school is designated in advance. For example, digital textbooks and digital teaching materials to be used during classes are designated as content that is permitted to be used.

[0090] (NG Operation 2) Using an application that is not specified. Applications that are permitted to be used during classes or at school are designated in advance. For example, applications that are to be used during classes are designated as content that is permitted to be used.

[0091] (NG operation 3) Repeating the same operation more than the standard number of times. This includes "repeated pressing of the same key," "repeated pressing of only a few (e.g., 2-3) of the same keys," and "repeated tapping within the same area (e.g., one of multiple areas obtained by dividing the touch area into N equal parts (N is an integer of 2 or greater))." Such operations are meaningless and indicate that the student is not concentrating on the lesson. The above criteria are expressed as a specified time, a specified number of times, etc. The specific values ​​of the above criteria are design matters.

[0092] Note that NG operations may be defined for each predetermined attribute. For example, for each predetermined attribute, it may be defined which of the above NG operations 1 to 3 is NG operation. Furthermore, for each predetermined attribute, permitted content, permitted applications, and the details of repeated operations that are NG operations may be specified. The attributes may include at least one of teacher, subject, school, region, grade, and class. In this case, the detection unit 108 identifies the NG operation based on a definition that matches the attribute of the lesson in which the operation indicated in the operation history was performed. The attributes of the lesson in which the operation indicated in the operation history was performed include the teacher in charge of the lesson, the subject of the lesson, the school in which the lesson is being taught, the region in which the school in which the lesson is being taught is located, the class in which the lesson is being taught, and the grade in which the class in which the lesson is being taught.

[0093] "Specifying the timing of warning information output" Next, the timing of outputting warning information will be described.

[0094] --Example 1-- The operation history acquisition unit 107 acquires the operation history for the duration of the lesson (from the start time of the lesson to the end time of the lesson). Then, the second output unit 109 outputs warning information during the lesson. In this example, if a student performs an inappropriate operation, warning information indicating that fact is output in real time via the output terminal.

[0095] --Example 2-- The operation history acquisition unit 107 acquires the operation history during the lesson (from the start time of the lesson to the end time of the lesson). The operation history acquisition unit 107 may acquire the operation history during the lesson by real-time processing during the lesson, or may acquire it by batch processing after the lesson is over. In this example, the second output unit 109 outputs warning information that collectively indicates the inappropriate operations detected during the lesson via the output terminal after the lesson, for example, in response to a request from the user (teacher).

[0096] --Example 3-- The operation history acquisition unit 107 acquires the operation history from the start time to the end time of work. That is, the operation history is acquired not only during classes but also during other periods such as breaks and lunch breaks. The operation history acquisition unit 107 may acquire the operation history from the start time to the end time of work by real-time processing, or may acquire it by batch processing after the end time of work.

[0097] In this example, as in Example 1, warning information may be output in real time processing in response to the detection of an inappropriate operation, or as in Example 2, warning information indicating all inappropriate operations detected that day may be output after the end of work hours.

[0098] "Specific warning information" The warning information includes the details of the detected inappropriate operation and information indicating the student who performed the inappropriate operation (such as name and student identification information).

[0099] In addition, when warning information is output in real time processing in response to the detection of an inappropriate operation, the warning information may further include the cumulative number of inappropriate operations performed by the student up to that point during the lesson, and information indicating the timing of the most recent detection (such as the time, information indicating how many minutes ago, etc.).

[0100] Furthermore, when warning information indicating all detected inappropriate operations is output after class or the end of school hours, the detected inappropriate operations may be displayed collectively by student, by time period, etc. The warning information may include the cumulative number of inappropriate operations performed by each student, the cumulative number of inappropriate operations performed in each time period, etc.

[0101] Other configurations of the system of this embodiment are the same as those of the fifth embodiment.

[0102] The system of this embodiment achieves the same effects as those of the fifth embodiment. Furthermore, the system of this embodiment can detect inappropriate operations, such as the use of unspecified content, the use of unspecified applications, and the repetition of the same operation more than a certain number of times. Based on the detection results of such inappropriate operations, teachers can understand students' attitudes toward their lessons.

[0103] Furthermore, the system of this embodiment can detect any inappropriate actions taken by students during class in real time and output the results via the output terminal, allowing teachers to grasp students' attitudes toward the class in real time during class.

[0104] Furthermore, according to the system of this embodiment, after the lesson, the inappropriate actions taken by the students during the lesson can be summarized and output via an output terminal. This allows the teacher to grasp the students' attitude towards the lesson as a whole and evaluate each student's attitude in class.

[0105] Furthermore, the system of this embodiment can detect any inappropriate actions taken by students between the start and end of school hours and output the results via an output terminal. In other words, it can detect inappropriate actions taken not only during class, but also during breaks, lunch, and other times. This allows teachers to evaluate not only students' attitudes toward class, but also their behavior at school, including how they spend their breaks, lunch, and other times.

[0106] Seventh Embodiment The system of this embodiment differs from the fifth and sixth embodiments in that it has a function of evaluating each student's attitude in class based on the operation history of each student.

[0107] 14 shows an example of a functional block diagram of the processing device 100 of this embodiment. As shown in the figure, the processing device 100 differs from the fifth and sixth embodiments in that it includes a second evaluation unit 111. Although not shown, similar to the fifth and sixth embodiments, the processing device 100 may include an input word acquisition unit 101, a classification unit 102, a first output unit 103, and a first storage unit 104. The processing device 100 may further include at least one of an update unit 105 and a first evaluation unit 106.

[0108] The second evaluation unit 111 evaluates each student's attitude in class based on the operation history of each student. The second evaluation unit 111 evaluates the class attitude higher the fewer the number of times inappropriate operations are detected. The second evaluation unit 111 evaluates the class attitude lower the more the number of inappropriate operations are detected. For example, the second evaluation unit 111 may evaluate each student's attitude in class using a five-point scale from A to E. The second evaluation unit 111 registers the evaluation result in the second storage unit 110.

[0109] 15 is a schematic diagram showing an example of an evaluation result generated by the second evaluation unit 111. The figure shows the evaluation results of each student's class attitude in the second semester science class for class 1 of the fifth grade. In the figure, each student's class attitude is evaluated for each class. The figure shows the dates of the classes, the evaluation results of each student's class attitude in class on each day, and the NG operations performed by each student in class on each day.

[0110] The second evaluation unit 111 may detect a recommended model operation from the operation history of each student. The model operation may be, but is not limited to, the use of designated content or the use of designated applications. The model operation may be defined for each predetermined attribute, similar to the NG operation.

[0111] In this case, the more the number of times the model operation is detected, the higher the second evaluation unit 111 evaluates the teaching attitude.The less the number of times the model operation is detected, the lower the second evaluation unit 111 evaluates the teaching attitude.

[0112] The second output unit 109 can output the evaluation results of each student's attitude in class via an output terminal such as the teacher terminal 300. For example, the second output unit 109 may output a table as shown in Fig. 15. Alternatively, the second output unit 109 may generate and output a graph showing the evaluation results in a time series.

[0113] Other configurations of the system of this embodiment are the same as those of the fifth and sixth embodiments.

[0114] The system of this embodiment achieves the same effects as those of the fifth and sixth embodiments. Furthermore, the system of this embodiment can evaluate each student's class attitude based on their operation history. Since the evaluation is based on their operation history, objective and reliable evaluation results can be obtained.

[0115] In this specification, "acquisition" includes at least one of the following: "the device retrieves data stored in another device or storage medium (active acquisition)" based on user input or program instructions, such as receiving data by making a request or inquiry to another device, or accessing and reading out another device or storage medium; "the device inputs data output from another device (passive acquisition)" based on user input or program instructions, such as receiving data that is distributed (or transmitted, push notification, etc.), and selecting and acquiring data from received data or information; and "the creation of new data by editing data (converting data to text, rearranging data, extracting some data, changing the file format, etc.), and acquiring the new data."

[0116] Some or all of the above-described embodiments can be described as, but are not limited to, the following supplementary notes. 1. An input word acquisition means for acquiring input words that are words input to each of a plurality of student terminals; a classification means for classifying the input words into a plurality of categories; an output means for displaying a list of at least some of the input words and outputting, via an output terminal, a screen showing the classification results for each of the input words displayed in the list; A processing device having: 2. The output means A processing device as described in 1, which, when it receives an input specifying one of the input words displayed in the list, outputs information indicating the student who entered the specified input word via the output terminal. 3. The input word acquisition means acquires the input words input during the lesson, 3. The processing device according to 1 or 2, wherein the output means outputs the screen during the lesson. 4. The input word acquisition means acquires the input words input during the lesson, 4. The processing device according to any one of 1 to 3, wherein the output means outputs the screen after the lesson is over. 5. A processing device described in any one of 1 to 4, wherein the categories include at least one of NG words that are not recommended to be input during class, interesting words that are recommended to be input during class, high-frequency words whose input frequency is above a threshold, and low-frequency words whose input frequency is below a threshold. 6. The classification means classifies the input words into a plurality of categories based on a category dictionary in which each category is associated with a word included in the category, The category dictionary is prepared for each attribute, The classification means classifies the input word into the category based on the category dictionary that matches the attribute of the lesson to which the input word is input, 6. The processing device according to any one of 1 to 5, wherein the attributes include at least one of teacher, subject, school, area, grade, and class. 7. Further comprising an update means for updating the category dictionary; The processing device described in 6, wherein the update means, upon receiving an input specifying one of the input words displayed in the list and an input specifying the category of the specified input word, links the specified input word to the specified category and registers it in the category dictionary. 8. A processing device described in any one of 1 to 7, further comprising an evaluation unit that evaluates each student's attitude in class based on the results of the classification of the input words entered by each student. 9. The computer an input word acquisition step of acquiring input words which are words input to each of the plurality of student terminals; a classification step of classifying the input words into a plurality of categories; an output step of displaying a list of at least some of the input words and outputting, via an output terminal, a screen showing the classification results for each of the input words displayed in the list; How to process. 10. Computer an input word acquisition means for acquiring an input word which is a word input to each of the plurality of student terminals; a classification means for classifying the input words into a plurality of categories; an output means for displaying a list of at least some of the input words and outputting, via an output terminal, a screen showing the classification results for each of the input words displayed in the list; A program that functions as a [Explanation of symbols]

[0117] 100 Processing equipment 101 Input word acquisition unit 102 Classification Department 103 First output section 104 First memory unit 105 Update section 106 First Evaluation Section 107 Operation history acquisition unit 108 Detector 109 Second output section 110 Second memory unit 111 Second Evaluation Section 1A processor 2A Memory 3A input / output I / F 4A peripheral circuit 5A Bus

Claims

1. an input word acquisition means for acquiring an input word that is a word input to each of the plurality of student terminals; a classification means for classifying the input words into a plurality of categories; an output means for displaying a list of at least some of the input words and outputting, via an output terminal, a screen showing the classification results for each of the input words displayed in the list; evaluation means for evaluating each student's attitude toward class based on the results of the classification of the input words entered by each student; and The classification means is a processing device that classifies the input words into the categories based on a result of comparing the input frequency of the input words with a threshold value.

2. The output means The processing device according to claim 1, wherein when an input specifying one of the input words displayed in the list is received, information indicating the student who input the specified input word is output via the output terminal.

3. the input word acquisition means acquires the input words input during a lesson, The processing device according to claim 1 or 2, wherein the output means outputs the screen during the lesson.

4. the input word acquisition means acquires the input word input during a lesson, The processing device according to claim 1 , wherein the output means outputs the screen after the lesson has ended.

5. 5. A processing device according to claim 1, wherein the categories include at least one of NG words that are not recommended to be input during class, interesting words that are recommended to be input during class, high-frequency words whose input frequency is equal to or greater than a threshold, and low-frequency words whose input frequency is less than a threshold.

6. the classification means classifies the input words into a plurality of categories based on a category dictionary in which words included in each category are linked to each of the categories; The category dictionary is prepared for each attribute, The classification means classifies the input word into the category based on the category dictionary that matches the attribute of the lesson to which the input word is input, The processing device according to claim 1 , wherein the attributes include at least one of a teacher, a subject, a school, a region, a grade, and a class.

7. further comprising an update means for updating the category dictionary; The processing device according to claim 6, wherein when the update means receives an input specifying one of the input words displayed in the list and an input specifying the category of the specified input word, the update means links the specified input word to the specified category and registers it in the category dictionary.

8. The computer an input word acquisition step of acquiring input words which are words input to each of the plurality of student terminals; a classification step of classifying the input words into a plurality of categories; an output step of displaying a list of at least some of the input words and outputting, via an output terminal, a screen showing the classification results for each of the input words displayed in the list; an evaluation step of evaluating each student's attitude toward class based on the results of the classification of the input words entered by each student; Run In the classification step, the input words are classified into the categories based on a comparison result between the input frequency of the input words and a threshold value.

9. Computer, an input word acquisition means for acquiring an input word which is a word input to each of the plurality of student terminals; a classification means for classifying the input words into a plurality of categories; an output means for displaying a list of at least some of the input words and outputting, via an output terminal, a screen showing the classification results for each of the input words displayed in the list; evaluation means for evaluating each student's attitude toward class based on the results of the classification of the input words entered by each student; It functions as The classification means is a program that classifies the input words into the categories based on the comparison result between the input frequency of the input words and a threshold value.

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