Educational equipment, teaching methods, and programs

Abstract

To propose an educational device and the like that are suited to deliver a search result of a database to a user.SOLUTION: An educational device 1 distributes a search result of a database part 5 to a user. In the educational device 1, a keyword processing part 11 analyzes condition data inputted by the user and generates a keyword. The database part 5 obtains condition search result data according to retrieval processing using search keyword data contained in the keyword. A thesaurus processing part 13 replaces at least a part of expression keyword data contained in the keyword to another word. An expression adjustment part 15 generates expression adjustment data by using processed expression keyword data after replacement by the thesaurus processing part 13. A distribution control part 17 adjusts an expression by using the expression adjustment data in an output part 19 and distributes condition search result data.SELECTED DRAWING: Figure 1

Description

Technical Field

[0006] Therefore, the present invention aims to propose an educational device or the like that is suitable for conveying database search results to users. [Means for solving the problem]

[0007] The first aspect of the present invention is an educational device for delivering search results from a database unit to a user, comprising a keyword processing unit, a thesaurus processing unit, a distribution control unit, and a database unit, wherein the keyword processing unit analyzes situation data input by the user to generate keywords, the database unit obtains situation search result data by performing a search using the search keyword data contained in the keywords, the thesaurus processing unit replaces at least a portion of the expression keyword data contained in the keywords with other words, and the distribution control unit adjusts the expression using the processed expression keyword data after the thesaurus processing unit has performed the replacement in the output unit and delivers the situation search result data.

[0008] A second aspect of the present invention is the educational device of the first aspect, wherein the user inputs index data separately from the situation data, the database unit searches using the index data to obtain index search result data, and the distribution control unit adjusts the expression using the processed expression keyword data in the output unit and distributes the situation search result data and the index search result data.

[0009] A third aspect of the present invention is the educational device of the first or second aspect, wherein the thesaurus processing unit replaces keywords where different words are used to correspond to different emotions with the same keyword.

[0010] A fourth aspect of the present invention is an educational device relating to any of the first to third aspects, comprising an analysis unit that identifies the user who input the situation data, and a distribution control unit that adjusts the expression according to the user and distributes the situation search result data.

[0011] A fifth aspect of the present invention is an educational method in an educational device that delivers search results from a database unit to a user, wherein the educational device comprises a keyword processing unit, a thesaurus processing unit, a distribution control unit, and a database unit, and includes the steps of: the keyword processing unit analyzing situation data input by the user to generate keywords; the database unit obtaining situation search result data by performing a search process using the search keyword data included in the keywords; the thesaurus processing unit replacing at least a portion of the expression keyword data included in the keywords with other words; and the distribution control unit adjusting the expression using the processed expression keyword data after the thesaurus processing unit has performed the replacements in the output unit and delivering the situation search result data.

[0012] A sixth aspect of the present invention is a program for causing a computer to function as an educational device for any of the first to fourth aspects. [Effects of the Invention]

[0013] According to each aspect of the present invention, by having a user input situational data, searching a database, and then distributing the analysis data obtained after the input situational data has been theatrically processed and its expression adjusted, it is possible to provide users with an expression suitable for conveying the knowledge of experts, etc. [Brief explanation of the drawing]

[0014] [Figure 1] This is a block diagram showing an example of the configuration of an educational system according to an embodiment of the present invention. [Figure 2] Figure 1 is a flowchart illustrating an example of how the education system works. [Figure 3] This block diagram shows an example of the configuration of a system that databases the knowledge of conventional experts. [Figure 4] This is a block diagram showing an example of the configuration of a conventional program production system. [Modes for carrying out the invention]

[0015] The following describes embodiments of the present invention with reference to the drawings. However, the present invention is not limited to these embodiments. [Examples]

[0016] Figure 1 is a block diagram showing an example of the configuration of an educational system according to an embodiment of the present invention. Figure 2 is a flowchart showing an example of the operation of the educational system in Figure 1.

[0017] Referring to Figure 1, the educational system comprises an input processing unit 3, an output unit 19, and an educational device 1.

[0018] The input processing unit 3 performs input processing by the user. The output unit 19 outputs to the user. The input processing unit 3 and the output unit 19 may be realized in the same device, such as a touch panel with a camera, for example. The input processing unit 3 may be realized by a keyboard, a mouse, a camera, etc., and the output unit 19 may be realized as a separate device by a speaker, a display, etc.

[0019] The educational device 1 can be realized by, for example, a computer that operates under the control of a program. The educational device 1 distributes the search results of the database unit 5 to the user. The educational device 1 includes an analysis unit 9, a keyword processing unit 11, a thesaurus processing unit 13, a presentation adjustment unit 15, a distribution control unit 17, a database unit 5, and a response processing unit 7.

[0020] The database unit 5 can be realized by, for example, a processor that operates under the control of a program. The database unit 5 is a system that standardizes the knowledge (such as know-how) possessed by experts and creates a database, and can be searched by index data or the like.

[0021] When the user inputs index data by the input processing unit 3, the database unit 5 performs a search process using the index data and generates one or more index search result data. The database unit 5 may perform a search process on a database in an external server, for example.

[0022] Also, the user inputs situation data by the input processing unit 3. The situation data includes at least one of character data, voice data, and image data (still images, moving images, etc.). For example, when the user does not know how to use a tool, the user takes a picture of the tool with a camera and inputs image data. It is also possible to input the specific scene of using the tool in character data, voice data, or image data. Note that the situation data may use the results automatically collected by this educational system from surrounding sensors, the Internet, and other information sources.

[0023] Index data is, so to speak, words suitable for searching in database section 5. On the other hand, status data indicates the user's current situation. Therefore, index data and status data are different. Note that processing related to index data may be omitted. If index data is omitted, the following processing can be achieved similarly by assuming that there is no index search result data.

[0024] The analysis unit 9 can be implemented, for example, by a processor that operates under program control. The analysis unit 9 is for analyzing various types of data. For example, it can analyze situational data to make it possible to extract keywords. For example, it can extract strings from audio data to create text data. It can identify objects captured in image data to make them possible to extract keywords. It can also identify people captured in situational data to identify users.

[0025] The keyword processing unit 11 can be implemented, for example, by a processor that operates under program control. The keyword processing unit 11 performs keyword extraction after the analysis unit 9 has made the situation data ready for keyword extraction. The keywords include expression keyword data and search keyword data. The expression keyword data and search keyword data may be the same, different, or partially the same and partially different.

[0026] The database unit 5 performs a search using the search keyword data and generates multiple status search result data.

[0027] The answer processing unit 7 can be implemented, for example, by a processor that operates under program control. The answer processing unit 7 analyzes the index search result data and multiple situational search result data and assigns feature data to each data. For example, in order to make tacit knowledge explicit and organize it, multiple judgment units (multiple different artificial intelligence (AI) processes, etc.) perform event judgments, each judgment unit having its own individuality, and analyze the characteristics of the respective index search result data and multiple situational search result data. For example, when searching for knowledge about the cause and possible solutions when a problem occurs, each cause and solution has its own characteristics, such as those that are generally suspicious, those that rarely occur but result in serious mistakes, and those that rarely occur and are minor. Feature data is assigned to the knowledge obtained through the search to indicate its characteristics. Feature data is, for example, data that indicates the priority that should be conveyed to the user, determined by comparing the judgments of the AI. The answer processing unit 7 may determine the priority using, for example, majority voting. The answer data generated by the answer processing unit 7 is a combination of the index search result data and multiple situational search result data and the feature data.

[0028] The analysis unit 9 can be implemented, for example, by a processor that operates under program control. The analysis unit 9 generates analysis data using information obtained by analyzing situation data and response data. This can be implemented, for example, by adding response data to the situation data as new material data in the example in Figure 4. The analysis data includes, for example, text data, image data, and audio data for use in distribution processing. For example, audio data for reading aloud the content of questions revealed by the situation data. It also includes data obtained by the response processing unit 7 to represent answers to questions, for example, audio data and image data for reading aloud answers showing how to use a tool. Furthermore, it analyzes feature data and prioritizes selecting answers that are appropriate to the user's situation obtained from the situation data. For example, if the user is a beginner, it prioritizes providing general solutions to problems. On the other hand, if, for example, the user is confused by a problem and asks a question despite being familiar with the situation, it prioritizes problems that are less likely to occur but could lead to serious mistakes, rather than problems that are more likely to occur.

[0029] The analysis unit 9 may identify users based on status data, login information, etc. In this case, the analysis unit 9 includes a user information identification unit (not shown in the diagram) that stores history, search history, etc., for each user. The analysis unit 9 may, for example, send user information held by the user information identification unit to the database unit 5 and / or the answer processing unit 7, and the answer processing unit 7 may generate one or more answer data corresponding to the user. Alternatively, the user may be presented with multiple answer data to select from. The analysis unit 9 may also generate analysis data according to the user using the user information held by the user information identification unit. Furthermore, the analysis unit 9 may send user information held by the user information identification unit to the expression adjustment unit 15, and the expression adjustment unit 15 may generate expression adjustment data corresponding to the user. In conventional systems, the user's knowledge was given a low priority, while the knowledge of experts accumulated in the database unit 5 was given a high priority, and information transmission tended to be limited to a one-way process of transmitting the advanced knowledge of experts to inexperienced users. In contrast, the educational device 1 can generate response data containing the knowledge of experts according to the user, express the response data as analysis data such as strings according to the user, and adjust the expression to suit the user using expression adjustment data according to the user, enabling more detailed expression tailored to the user. Furthermore, by accumulating the responses for a single user in various parts such as the user information identification unit and the analysis unit 9, the level of detail in the user-specific responses of the educational device 1 can be increased. Therefore, it does not merely transmit knowledge to the user, but the educational device 1 also changes and grows along with the user's growth, empathizing with the user and accurately providing the user with opportunities to think for themselves, thereby promoting their growth.

[0030] The thesaurus processing unit 13 can be implemented, for example, by a processor that operates under program control. The thesaurus processing unit 13 evaluates the expression keyword data using a thesaurus primarily focused on composure, tailoring the evaluation to each word. This is because, in responding, expressions that calm and soothe the user are needed, rather than expressions that empathize with the user's emotions. For example, the thesaurus processing unit 13 replaces keywords that have the same meaning but use different words to correspond to different emotions with the same keyword. This enables the user to communicate with composure, enabling them to respond to various situations, even when they are in various circumstances.

[0031] The expression adjustment unit 15 can be implemented, for example, by a processor that operates under program control. The expression adjustment unit 15 analyzes the post-processed expression keyword data after processing by the thesaurus processing unit 13 and generates expression adjustment data to adjust the expression conveyed to the user. For example, if the situation data contains an expression that includes anger when asking how to use a tool, the thesaurus processing unit 13 removes the anger from the expression of the question and generates post-processed expression keyword data that makes it seem as if the question was asked calmly. The expression adjustment unit 15 generates expression adjustment data that adjusts the expression to calmly convey how to use the tool, thereby guiding the user to a calm state (calmness).

[0032] The distribution control unit 17 can be implemented, for example, by a processor that operates under program control. The distribution control unit 17 outputs analysis data in the output unit 19. The output includes at least a portion of text, audio, and images. Audio, etc., may be represented by characters. When outputting the analysis data, the distribution control unit 17 adjusts the representation using representation adjustment data.

[0033] Refer to Figure 2 to illustrate an example of how the educational system in Figure 1 works.

[0034] The data input by the input processing unit 3 is provided to the analysis unit 9 and the database unit 5. The analysis unit 9 determines whether only index data has been provided from the input processing unit 3 (step ST1).

[0035] If only index data is provided from the input processing unit 3 and no status data is provided (if the result is NO in step ST1), no processing related to the status data is performed. The database unit 5 performs a search using the index data (step ST6), the response processing unit 7 processes the search results and generates response data (step ST7), the analysis unit 9 analyzes the response data and generates analysis data (step ST8), and the distribution control unit 17 outputs the analysis data in the output unit 19 (step ST9).

[0036] If situation data is provided from the input processing unit 3 (if the answer is YES in step ST1), processing is performed on the situation data. The analysis unit 9 analyzes the situation data and prepares it for keyword extraction (step ST2). The keyword processing unit 11 extracts keyword data that represents the keywords (step ST3). The thesaurus processing unit 13 performs a thesaurus-based keyword replacement process on the expression keyword data included in the keyword data to generate processed expression keyword data (step ST4). The expression adjustment unit 15 analyzes the processed expression keyword data after processing by the thesaurus processing unit 13 and generates expression adjustment data to adjust the expression to be conveyed to the user (step ST5).

[0037] In step ST6, if only status data is provided by the input processing unit 3 and no index data is provided, the database unit 5 performs a search using the search keyword data included in the keyword data. If both status data and index data are provided by the input processing unit 3, the database unit 5 performs a search using the index data and search keyword data.

[0038] The response processing unit 7 processes the search results and generates response data (step ST7), the analysis unit 9 analyzes the response data and generates analysis data (step ST8), and the distribution control unit 17 outputs the analysis data in the output unit 19 (step ST9).

[0039] For example, in this embodiment, it can be achieved as follows.

[0040] First, let's explain using heatstroke prevention in welfare facilities as an example. Staff are required to respond to the heatstroke risk tailored to each individual facility user. However, while general information such as the heat index is easy to judge, a certain amount of specialized training is necessary to be able to judge the response tailored to each individual facility user. Therefore, as support for staff, the education system will provide staff with information on heatstroke prevention tailored to each facility user, using general information, short-term information, and medium- to long-term information as situational data, enabling responses that comprehensively consider the environment and the individual's physical condition and strength. Note that the situational data may be the result of data automatically collected by this education system from surrounding sensors, the internet, or other information sources.

[0041] General information refers to information that indicates the general risk of heatstroke, not limited to individual facility users, and includes, for example, the heat index. The heat index is calculated as temperature × 1 + humidity × 7 + radiant heat × 2. A heat index of 28 or higher is generally considered to indicate a risk of heatstroke. Information such as temperature, humidity, and radiant heat can be obtained by measuring with sensors, and can also be obtained from information published on websites by local governments, etc.

[0042] Short-term information refers to information that indicates the short-term impact on the heatstroke risk of individual facility users. For example, this is judged by factors such as body temperature, physical condition, and psychological state. Body temperature can be obtained using non-contact temperature sensors. Physical condition can be obtained through interviews. Psychological state can be obtained through interviews and whether or not the user responds. For example, staff will interact with individual facility users by taking their body temperature and asking about their condition before they enter the facility. The data obtained from this interaction will be called situational data. For example, when body temperature is measured using a sensor, the body temperature will be included in the situational data. In addition, the interaction between staff and facility users will be filmed with a camera and included in the situational data. Furthermore, the situation of facility users while they are using the facility will be filmed with a camera and included in the situational data.

[0043] Medium- to long-term information refers to information that shows the medium- to long-term impact on the heatstroke risk of individual facility users, such as frailty level and dementia level. Frailty refers to an intermediate state between a healthy state and a state requiring care with support in daily life. For example, it is described as "a state in which physical and mental vitality (motor function, cognitive function, etc.) declines with age, and due to the effects of multiple co-occurring chronic diseases, daily living functions are impaired and physical and mental vulnerability appears, but on the other hand, it is a state in which daily living functions can be maintained and improved with appropriate intervention and support." Frailty level refers to the degree of frailty, with smaller values ​​indicating a state closer to a healthy state and larger values ​​indicating a state closer to a state requiring care. Frailty level can be obtained, for example, through Fried's criteria or fall prediction through interviews. Dementia level can be obtained through screening, etc. Situational data includes frailty level and dementia level.

[0044] Experienced staff can understand and respond to the individual circumstances of each facility user. For example, they can respond flexibly to short-term information at any given time, while also taking general and medium- to long-term information into account. However, junior staff will respond without understanding the individual circumstances of each facility user. For example, they may only manage the temperature using air conditioning based on general information, and it will be difficult for them to respond to the short-term and medium- to long-term circumstances of each facility user.

[0045] The educational system of this embodiment can compensate for the skills of entry-level staff. By inputting general information, short-term information, and medium- to long-term information as situational data, the heatstroke risk for individual facility users can be obtained as response data. Here, characteristic data can be assigned to responses to heatstroke risk, such as those that are important and urgent, important but not urgent, not important but urgent, and neither important nor urgent.

[0046] Furthermore, the analysis unit 9 determines the priority of multiple responses from the response data according to the situation of each facility user in the situation data. The analysis unit 9 provides responses that are appropriate to the situation of the facility user. Basically, it makes a judgment based on the facility user's psychological state (whether or not they are panicking) and cognitive ability (level of dementia). For example, if the facility user is calm and not panicking, the response should be made according to the priority of measures to address the risk of heatstroke. If the facility user is panicking, even if the measures to address the risk of heatstroke are not important or urgent, the priority should be on measures that will calm the facility user down. For example, if the facility user has a low level of dementia, the response should be made according to the priority of measures to address the risk of heatstroke. If the facility user has a high level of dementia, they may panic due to an unexpected trigger. As a measure to address the risk of heatstroke, the priority should be on measures that are less likely to cause the facility user to panic, or the wording should be adjusted to make instructions short and easy to understand. In addition, the distribution control unit 17 intervenes as necessary, such as contacting the center, turning the air conditioner on / off, or changing the set temperature.

[0047] In this embodiment, the educational system requires a balance between flexible responses based on situational data and general expert knowledge obtained from the database. The priority of answers in the general expert knowledge obtained from the database may be set for each answer based on interviews with experts, or by using the frequency (importance) order in keyword searches, or by determining the degree of agreement between the typical situation of the solution obtained from the search results and the situational data.

[0048] Furthermore, by using Bayesian updating or similar methods, the system can improve the accuracy of responses by having users input whether or not the responses were helpful to them, in addition to receiving their answers. For example, typical situations, related terms (terms commonly used as substitutes when there is no knowledge of technical terms), keywords, and solutions are linked by their probability of occurrence, so the educational system (e.g., analysis unit 9) can organize and manage these relationships (connections) in a table or similar format. The probability of occurrence of each connection indicates the quality of that connection. Therefore, the accuracy of responses can be improved by modifying the probability of occurrence of each connection based on the information that users input when they receive their responses, indicating whether or not the responses were helpful to them.

[0049] Furthermore, from an educational perspective, it is crucial to raise the staff's skill level to that of a professional. Therefore, it is important to understand the skill level of the users and to work to improve that level.

[0050] From the perspective of understanding the user's skill level, the following could be considered as possible solutions.

[0051] For example, when a user inputs situational data and / or index data, their ability to input it in a way that is suitable for database searching serves as an indicator of the user's level of understanding. Therefore, the analysis unit 9 uses the search results obtained from the keyword processing unit 11 to evaluate the degree to which the search keyword data was suitable for searching. For example, if the user has grasped and entered appropriate search keywords from multiple perspectives, this is evaluated as indicating a very high level of user understanding. If there are no search keywords more appropriate than the ones entered by the user, this is evaluated as indicating a high level of user understanding. If there are search keywords more appropriate than the ones entered by the user, this is evaluated as indicating a low level of user understanding.

[0052] The analysis unit 9 generates analysis data according to the user's level of understanding. For example, if the user's level of understanding is low, it prioritizes basic information and provides answers in a sequential manner. If the user's level of understanding is high, it quickly provides the required answers, such as by presenting the conclusion early. Alternatively, it may allow the user to input answers without providing answers directly, and then provide answers according to their level of understanding.

[0053] From the perspective of raising the user's skill level, the following could be considered as possible solutions.

[0054] In explanations, multiple explanatory items are usually presented in sequence. For example, a general introduction might be provided, followed by gradually more specific explanations. Especially for beginners, it is important that they fully understand the prerequisite explanatory items before the next ones are presented. For this reason, for example, the analysis unit 9 may divide the response data into multiple explanatory items, and the distribution control unit 17 may add processing to help the user understand between each explanatory item. For example, if the user is a beginner, the system may be presented with a specialized framework to show the systematic positioning of the explanatory items before the next explanatory item is distributed. For example, a distribution may be made to explain one or more explanatory items, presenting summary points or asking questions based on the content distributed so far, and then a distribution may be made to explain the next explanatory item. The presentation of points and questions may be tailored to the user's level of expertise, or they may be implemented through character actions, etc. The user's level of expertise may be determined by the user identified by the analysis unit 9, by the situation data and / or index data, or by both.

[0055] Furthermore, in education, the user's feelings after receiving an answer are important. Therefore, the distribution control unit 17 provides follow-up distributions after the initial distribution. For example, if the user is a beginner, it may add distributions aimed at helping them improve their skills, or it may present information through the character's actions. In conventional systems, learning was based solely on watching videos of experts. By having the character act, it becomes possible to simulate "demonstrate" and "explain" the process. Also, highly skilled users may feel that they have been given an answer that they already know. By providing follow-up support that addresses such feelings, even highly skilled users can deepen their understanding of the answer. Additionally, by allowing the user to converse with the educational device 1 as a follow-up, the user's understanding can be further enhanced. [Explanation of Symbols]

[0056] 1 Educational equipment 3. Input Processing Unit 5. Database Department 7. Answer Processing 9 Analysis section 11 Keyword Processing Section 13 Thesaurus Processing Unit 15 Expression adjustment section 17 Distribution Control Unit 19 Output section

Claims

1. An educational device that delivers search results from the database to users, It comprises a keyword processing unit, a thesaurus processing unit, a distribution control unit, and a database unit. The keyword processing unit analyzes the situation data entered by the user to generate keywords. The database unit obtains situation search result data by performing a search process using the search keyword data included in the keyword. The thesaurus processing unit replaces at least a portion of the expression keyword data included in the keyword with other words. The distribution control unit is an educational device that distributes the status search result data by adjusting the expression using the processed expression keyword data after the thesaurus processing unit has replaced it in the output unit.

2. The aforementioned user inputs index data separately from the status data, The database unit uses the index data to perform a search and obtains index search result data. The educational apparatus according to claim 1, wherein the distribution control unit adjusts the expression using the processed expression keyword data in the output unit and distributes the status search result data and the index search result data.

3. The thesaurus processing unit replaces keywords where different words are used to correspond to different emotions with the same keyword, according to claim 1.

4. The system includes an analysis unit that identifies the user who input the aforementioned status data, The educational apparatus according to claim 1, wherein the distribution control unit distributes the status search result data after adjusting the expression according to the user.

5. An educational method in an educational device that delivers search results from the database to users, The aforementioned educational device comprises a keyword processing unit, a thesaurus processing unit, a distribution control unit, and a database unit. The keyword processing unit includes the steps of analyzing the situation data entered by the user to generate keywords, The database unit obtains situation search result data by performing a search process using the search keyword data included in the keyword. The thesaurus processing unit includes the steps of replacing at least a portion of the expression keyword data included in the keyword with other words, An educational method comprising the step of the distribution control unit adjusting the expression using the processed expression keyword data after the thesaurus processing unit has replaced it in the output unit and distributing the status search result data.

6. A program for causing a computer to function as the educational device described in claim 1.

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