Learning Support System and Learning Support Method

Abstract

Providing a learning support system and a learning support method capable of appropriately maintaining the motivation for learning. 【Solution means】 The learner information acquisition unit 11 acquires future image information indicating a future image, which is the desired image of the learner in the future. The teacher data acquisition unit 12 acquires, as teacher data, posting data to the posting site by a model poster who is a poster having a similar portrait to the future image from the posting site where a plurality of posters post. The learning unit 13 constructs a diary generation model for generating a fictional diary based on the teacher data. The future diary generation unit 14 generates a future diary, which is a fictional diary of the learner in the future, using the diary generation model. The presentation unit 15 presents the future diary to the learner terminal 2.

Description

Technical Field

[0001] The present disclosure relates to a learning support system and a learning support method.

Background Art

[0002] In order to pass official examinations such as national examinations and entrance examinations, learners need to continue learning over a long period of time. However, it is not easy for learners to maintain their motivation for learning during that time.

[0003] On the other hand, Non-Patent Document 1 discloses a technique for presenting the future schedule of a user who has made a life choice such as quitting work and becoming independent by using a large language model (LLM) that has learned past data of the user such as calendar data and information related to the user's life values. By using this technique, it becomes possible to show a successful future for oneself, so there is a possibility that the motivation of the learner for learning can be maintained.

Prior Art Documents

Non-Patent Documents

[0004]

Non-Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, in the technique described in Patent Document 1, since the future schedule of the user is presented based on the past data of the user himself / herself, there is a possibility that a schedule reflecting the results of past laziness may be presented, and an appropriate schedule may not always be presented to maintain motivation.

[0006] An object of the present disclosure is to provide a learning support system and a learning support method capable of appropriately maintaining the motivation for learning.

Means for Solving the Problem

[0007] A learning support system according to an aspect of the present disclosure is a learning support system connected to a learner terminal used by a learner who performs predetermined learning, and includes a learner information acquisition unit that acquires future image information indicating a future image that is an expected person image of the learner in the future, a teacher data acquisition unit that acquires, as teacher data, posting data to a posting site by a model poster who is a poster having a person image similar to the future image from a posting site where a plurality of posters post, a learning unit that constructs a diary generation model for generating a fictional diary based on the teacher data, a generation unit that generates a future diary that is a fictional diary of the learner in the future using the diary generation model, and a presentation unit that presents the future diary to the learner terminal.

Effect of the Invention

[0008] According to the present invention, it becomes possible to appropriately maintain the motivation for learning.

Brief Description of the Drawings

[0009]

Figure 1

Figure 2

Figure 3

Mode for Carrying Out the Invention

[0010] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings.

[0011] FIG. 1 is a diagram showing a learning support system according to an embodiment of the present disclosure. The learning support system 1 shown in FIG. 1 is interconnected with the learner terminal 2 via a network 10 such as the Internet, and provides learning support information for supporting a predetermined learning to the learner terminal 2. In this embodiment, the predetermined learning is learning for a predetermined main examination such as a national examination, a skills test, an entrance examination, or an academic ability test. The main examination may be composed of a plurality of subject-specific main examinations corresponding to each of a plurality of subjects.

[0012] The learner terminal 2 is an information terminal used by a learner who conducts a predetermined learning. The learner terminal 2 receives the learning support information provided by the learning support system 1 and performs processing according to the received learning support information. The processing according to the learning support information is, for example, processing for displaying the learning support information, and processing for transmitting the information input according to the learning support information to the learning support system 1. The learning support information includes, for example, lecture information which is moving image data showing a lecture, and problem information including a problem statement and an input form for inputting an answer thereto. Further, the learning support information may be transmitted along a learning curriculum determined according to the learner's living situation, wishes, etc. Further, the learner terminal 2 may transmit various requests to the learning support system 1. The requests include, for example, a provision request for requesting the provision of learning support information.

[0013] The learner terminal 2 may be a dedicated information terminal for receiving the learning support information, or may be a general-purpose information terminal such as a PC (Personal Computer), a smartphone, and a tablet terminal. There may be a plurality of learner terminals 2 used by one learner, or a plurality of learners may jointly use one learner terminal 2. Further, by logging in the information terminal to the learning support system 1 using the learner's ID or the like, the information terminal may be used as the learner terminal 2 while logged in.

[0014] As shown in FIG. 1, the learning support system 1 includes a learner information acquisition unit 11, a teacher data acquisition unit 12, a learning unit 13, a future diary generation unit 14, and a presentation unit 15.

[0015] The learner information acquisition unit 11 acquires learner information, which is information about the learner. The learner information includes future image information indicating a future image, which is an image of the person the learner desires to become in the future. The future image includes, for example, attributes related to the image of a person such as future occupation, future position, future family composition, future annual income, and future lifestyle as items. Further, the future image information may include information indicating the period from the current time of the future image (e.g., how many years later). Also, the learner information may include current information indicating the current image of the learner. The current information includes, for example, attributes such as gender, current age, current occupation, current family composition, current annual income, and current lifestyle as items. Note that the above attributes are merely examples, and any one of these, or any combination, or other attributes may be included. The lifestyle includes, for example, the amount and proportion of working hours, sleep habits such as bedtime, wake-up time, and the presence or absence of a midday nap, and how to spend holidays.

[0016] The method for acquiring learner information is not particularly limited. For example, the learner information acquisition unit 11 may transmit information prompting the input of learner information, such as a questionnaire regarding the future image, to the learner terminal 2, and acquire the learner information based on the response (such as the answer to the questionnaire) from the learner terminal 2 or the user to that information.

[0017] Based on the learner information acquired by the learner information acquisition unit 11, the teacher data acquisition unit 12 identifies, as a mentor (model poster), a poster who has a similar image to the learner's future image from the poster sites where multiple posters post. Then, the teacher data acquisition unit 12 acquires, as teacher data, the posting data indicating the posts by the mentor to that poster site. The poster site is, for example, an SNS (Social Networking Service), a blog, and a community site, etc. Note that the teacher data acquisition unit 12 may collect teacher data from multiple poster sites.

[0018] Specifically, the teacher data acquisition unit 12 first acquires attributes related to the profile of each contributor on the posting site. For example, the teacher data acquisition unit 12 uses an API (Application Programming Interface) provided by the posting site to acquire attributes related to the profile of the contributor from the contributor's profile or the like. Subsequently, for each contributor, the teacher data acquisition unit 12 calculates the similarity between the attribute value of the contributor and the attribute value of the future profile of the learner for each of a plurality of predetermined attributes, and identifies a mentor based on these similarities. For example, the teacher data acquisition unit 12 determines that the contributor is a mentor when the statistical value of the similarity of each attribute is equal to or greater than a threshold value. The algorithm for calculating the similarity is not particularly limited. The statistical value of the similarity is, for example, a total value or a weighted sum. The weight value of the weighted sum may be determined according to, for example, the importance of the item. The importance may be determined in advance, or may be determined according to the items that the learner regards as important for the future profile. Also, it is desirable that there be a plurality of mentors, and the teacher data acquisition unit 12 may identify a predetermined number or more of mentors by gradually lowering the threshold value until the number of mentors reaches a predetermined number or more, for example.

[0019] Also, the above method for identifying a mentor is merely an example and is not limited to this example. For example, the teacher data acquisition unit 12 may estimate the attribute value of the contributor's attribute from the contributor's posting data. Also, when the contributor's profile or the like or the contributor's attribute cannot be acquired, the teacher data acquisition unit 12 may estimate the attribute value of the contributor's attribute from the posting data. Also, when the contributor's profile or the like or the contributor's attribute cannot be acquired, the teacher data acquisition unit 12 may set the similarity for that attribute to 0.

[0020] The learning unit 13 constructs a diary generation model, which is a model for generating fictional diaries, based on the teacher data acquired by the teacher data acquisition unit 12. The diary generation model is, for example, a generative AI (Artificial Intelligence) model such as a large language model. The diary generation model may be one obtained by newly fine-tuning the above teacher data as additional learning data (fine-tuning data) for generating fictional diaries for an existing generative AI model. Note that the existing generative AI model and the diary generation model may be provided in an external device (not shown) connected via the network 10, or may be provided in the learning unit 13.

[0021] The future diary generation unit 14 generates future diary information indicating a future fictional diary of the learner using the diary generation model constructed by the learning unit 13. For example, the future diary generation unit 14 causes the diary generation model to generate information indicating a future fictional diary of the mentor, and converts the attributes of the mentor included in the information into the attributes of the future learner, thereby generating future diary information. The future diary generation unit 14 may cause the diary generation model to assume the mentor as the future image of the learner and generate future diary information.

[0022] The format of the future diary information is not particularly limited. For example, the future diary information may be in the same format as the posting data to a predetermined posting site, may be in a predetermined format different from the format of the posting data, or the format may be generated or selected by the diary generation model.

[0023] The prompting unit 15 prompts the learner with the future diary by sending the future diary information generated by the future diary generation unit 14 to the learner terminal 2. Specifically, the prompting unit 15 periodically (in this embodiment, daily, but it may also be weekly or the like) prompts the learner with future diaries of different contents. Note that the future diary generation unit 14 may generate the future diary information for a certain period (for example, for one year) in a batch, and the prompting unit 15 may extract and transmit the future diary information for the current day from the future diary information for a certain period, or the future diary generation unit 14 may generate the future diary information to be prompted on that day every day. The future diary to be prompted is, for example, a diary for the date after a predetermined period from the current time. The predetermined period may be a relatively near future such as one year, but a future such as five to ten years in which the learner's grand dreams can be realized is desirable.

[0024] Note that instead of periodically prompting the future diary information, the prompting unit 15 may transmit learning support information to the learner terminal 2 according to a request from the learner terminal 2, and transmit the future diary information along with the learning support information. For example, the prompting unit 15 may transmit the future diary information before or after transmitting the lecture information or the problem information.

[0025] FIG. 2 is a diagram showing an example of the hardware configuration of the learning support system 1. As shown in FIG. 2, the learning support system 1 includes a storage device 21, a processor 22, a main memory 23, an input device 24, and a display device 25, which are connected via a bus 26.

[0026] The storage device 21 is a device that records data so that writing and reading are possible, and stores various information such as a program that defines the operation of the processor 22, learning support information, learner information and teacher data acquired by the learner information acquisition unit 11 and the teacher data acquisition unit 12. The processor 22 reads the program stored in the storage device 21 into the main memory 23, and uses the main memory 23 to execute processing according to the program. Each part 11 to 15 of the learning support system 1 shown in FIG. 1 is realized by the processor 22.

[0027] The input device 24 is a device to which various information is input from an operator of the learning support system 1, an external device (not shown), etc., and the information is used for processing by the processor 22. For example, the learning support information is recorded in the storage device 21 via the input device 24. The display device 25 is a device that displays various information.

[0028] FIG. 3 is a flowchart for explaining an example of future diary generation processing by the learning support system 1.

[0029] In the future diary generation processing, the learner information acquisition unit 11 transmits a questionnaire prompting the input of learner information to the learner terminal 2, and acquires response information indicating the response to the questionnaire from the learner terminal 2 (step S101). The timing of transmitting the questionnaire is, for example, the timing when the learning curriculum is determined. Also, the questionnaire may be included in the information for determining the learning curriculum.

[0030] The learner information acquisition unit 11 acquires learner information based on the response information (step S102). For example, when the questionnaire prompts information described in an article such as "What kind of occupation / post do you want to have, how much annual income do you want to earn, where, and what kind of life do you want to have in how many years from now", the learner information acquisition unit 11 extracts the items necessary for the learner information from the response to the questionnaire, or predicts the items necessary for the future image information from the response to the questionnaire using an AI model or the like, thereby acquiring the learner information. Also, when the questionnaire is one that allows the learner to select each item of the future image information in a multiple-choice format, the learner information acquisition unit 11 acquires the learner information based on the selected content.

[0031] Based on the learner information acquired by the learner information acquisition unit 11, the teacher data acquisition unit 12 identifies, as a mentor, a contributor having a similar portrait, which is a portrait similar to the future image of the learner, from the posting sites where a plurality of contributors post, and acquires the posting data of the mentor as teacher data (step S103).

[0032] The learning unit 13 constructs a diary generation model, which is a model for generating fictional diaries, based on the teacher data acquired by the teacher data acquisition unit 12 (step S104).

[0033] The future diary generation unit 14 generates future diary information indicating a future diary, which is a fictional diary of the learner in the future, using the diary generation model constructed by the learning unit 13 (step S105).

[0034] The presentation unit 15 presents the future diary to the learner by transmitting the future diary information generated by the future diary generation unit 14 to the learner terminal 2 (step S106). When the learner terminal 2 receives the future diary information, it presents the future diary to the learner by, for example, displaying the future diary information.

[0035] As described above, according to the present embodiment, the learner information acquisition unit 11 acquires future image information indicating a future image, which is an expected persona of the learner in the future. The teacher data acquisition unit 12 acquires, as teacher data, posting data on a posting site by a mentor who is a poster having a similar persona to the future image from a posting site where a plurality of posters post. The learning unit 13 constructs a diary generation model for generating fictional diaries based on the teacher data. The future diary generation unit 14 generates a future diary, which is a fictional diary of the learner in the future, using the diary generation model. The presentation unit 15 presents the future diary to the learner terminal 2. Therefore, since a future diary based on posting data by a person similar to the learner's desired future image is presented, it becomes possible to present a diary along the future image the learner wants to become. Therefore, the learner can virtually experience his / her own future after success by continuing learning, so that it becomes possible to appropriately maintain the motivation for learning.

[0036] Also, in the present embodiment, the learning unit 13 constructs a diary generation model by performing additional learning of teacher data on an existing generation AI model. In this case, it becomes possible to easily construct a diary generation model.

[0037] In addition, in this embodiment, the presentation unit 15 periodically transmits future diary information with different contents respectively. In this case, the learner can gradually form the self they want to become by reading the future diary little by little, and it becomes possible to more appropriately maintain the motivation for learning.

[0038] In addition, in this embodiment, the presentation unit 15 transmits future diary information of the date after a predetermined period from the current time, starting from the current time. In this case, since the learner can experience the daily life of their future desired self, it becomes possible to more appropriately maintain the motivation for learning.

[0039] In addition, in this embodiment, the predetermined period is from 5 years to 10 years. In this case, since the learner can read the future diary that realizes their grand dreams, it becomes possible to more appropriately maintain the motivation for learning.

[0040] In addition, in this embodiment, the teacher data acquisition unit 12 calculates the similarity between the future image and the portrait of the poster for each of a plurality of attributes related to the portrait, and selects a mentor based on the similarity of each attribute. In this case, it becomes possible to identify an appropriate mentor.

[0041] In addition, in this embodiment, the teacher data acquisition unit 12 identifies a plurality of mentors, and acquires the posted data by each mentor as teacher data. In this case, since it becomes possible to construct a future diary generation model using the posted data by a plurality of people as teacher data, it becomes possible to generate attractive future diary information.

[0042] The above-described embodiments of the present disclosure are examples for explaining the present disclosure, and are not intended to limit the scope of the present disclosure only to those embodiments. Those skilled in the art can implement the present disclosure in various other modes without departing from the scope of the present disclosure.

Explanation of Reference Numerals

[0043] 1: Learning support system 11: Learner information acquisition unit 12: Teacher data acquisition unit 13: Learning unit 14: Future diary generation unit 15: Presentation unit

Claims

1. A learning support system connected to a learner terminal used by a learner performing a predetermined study, a learner information acquiring unit for acquiring future image information indicating a desired future image of the learner; A teacher data acquisition unit that acquires, from a posting site to which a plurality of contributors post, data posted to the posting site by a model contributor who is a contributor having a similar personality profile to the future image, as teacher data; A learning unit that constructs a diary generation model that generates a fictitious diary based on the training data; A generation unit that generates a future diary, which is a fictitious diary of the learner in the future, by using the diary generation model; A learning support system having a presentation unit that presents the future diary to the learner terminal.

2. The learning support system according to claim 1 , wherein the learning unit constructs the diary generation model by additionally learning the teacher data to an existing generative AI model.

3. The learning support system according to claim 1 , wherein the presenting unit periodically presents the future diary with different contents.

4. The learning support system according to claim 3 , wherein the presenting unit presents the future diary for a date a predetermined period from the present time.

5. 5. The learning support system according to claim 4, wherein the predetermined period is 5 to 10 years.

6. A learning support method using a learning support system connected to a learner terminal used by a learner performing a predetermined study, comprising: Obtaining future image information indicating a future image that is a desired image of the learner in the future; Acquire, as teacher data, data posted to a posting site by a model contributor who is a contributor having a similar personality profile to the future image from a posting site to which a plurality of contributors post; Constructing a diary generation model that generates a fictitious diary based on the training data; Using the diary generation model, a future diary, which is a fictitious diary of the learner in the future, is generated; A learning support method, comprising presenting the future diary to the learner terminal.

Images