JP7765857B2 - Information processing device, information processing method, and program - Google Patents

Description

The present invention relates to an information processing device, an information processing method, and a program.

2. Description of the Related Art Conventionally, there have been human resource development support systems that assess the business skills of employees in a company or other enterprise and support human resource development based on the assessment results (see, for example, Patent Document 1).
When diagnosing business skills using such conventional systems, the standard is the employee's own self-evaluation, so when an employee takes a course to improve their business skills, they have to select the evaluation elements that need improvement from the many evaluation elements available and take the appropriate course.

Japanese Patent Application Laid-Open No. 2004-246507

However, the course that an employee (participant) chooses is not necessarily suitable for improving their skills, and if they do not see any results after taking the course for several months, they will end up taking a different course.
Users may not know how many courses or other events they should take, that is, how much educational opportunity they should participate in to get the most benefit, and may end up participating in too many at their own discretion.

The present invention was made in light of this situation, and aims to enable users to participate in events at a frequency appropriate for acquiring the necessary and sufficient skills.

In order to achieve the above object, an information processing device according to one embodiment of the present invention comprises:
a proposal means for proposing to the user a future educational plan for improving the basic business skills based on a correspondence relationship between an educational history of the user who participated in an educational event for improving the basic business skills, a behavioral state of the user after participating in the event, and an evaluation result of the basic business skills after participating in the event;
Equipped with.
An information processing method and a program corresponding to the information processing device according to one aspect of the present invention are also provided as an information processing method and a program according to one aspect of the present invention.

This invention allows users to participate in events at a frequency appropriate for acquiring the necessary and sufficient skills.

1 shows the overall configuration of an information processing apparatus according to an embodiment of the present invention. FIG. 2 is a block diagram showing a hardware configuration of a server in the information processing apparatus of FIG. 1 . FIG. 2 is a functional block diagram showing a functional configuration of a server in the information processing apparatus of FIG. 1 . FIG. 10 is a diagram showing an example of a display area of a graph before the score values are plotted. 10A and 10B are diagrams illustrating examples of graphs and comments displayed on a user terminal. 10 is a flowchart showing a course recommendation operation in the server of FIG. 3 . FIG. 10 is a diagram showing an example of a My Page disclosed to a user. FIG. 10 is a diagram showing an example of a course completion screen displayed on My Page. FIG. 10 is a diagram showing an example of a start screen when taking a follow-up test on a user's personal page. FIG. 10 is a diagram showing an example of a question screen displayed following the start screen of FIG. 9 . FIG. 11 is a diagram showing an example of a screen that is displayed when all questions have been answered by answering questions in order starting from the question screen of FIG. 10. FIG. 12 is a diagram showing an example of a confirmation screen displayed following the screen of FIG. 11 . FIG. 13 is a diagram showing an example of a test result screen displayed following the confirmation screen of FIG. 12. FIG. 10 is a diagram showing an example of an input screen for future actions when reporting class actions. FIG. 10 is a diagram showing an example of a check screen for checking the user's behavior after a certain period from the class behavior report. FIG. 10 is a diagram showing an example of a partial screen of My Page. FIG. 10 is a diagram showing an example of a screen displaying comments fed back from a course manager. FIG. 10 is a diagram showing an example of display of feedback points from a course manager. FIG. 10 is a diagram showing a comparison between the number of classes taken and the change in scores for each group, A to E. FIG. 10 is a diagram showing a comparative example of the change in scores and the interval between classes for each group, A to E. FIG. 10 is a diagram showing a comparative example of the action completion rate and score change after taking the course for each of groups A to C. FIG. 10 is a diagram showing a comparative example of the follow-up test completion rate and score change for each group, A to C. FIG. 10 is a diagram showing a comparison example of the execution rate of "specific actions to undertake starting tomorrow" and the change in score for each group, A to E. FIG. 10 is a diagram showing a comparative example of the average feedback score from others and the change in score for each group, A to E.

Embodiments of the present invention will be described below with reference to the drawings.

FIG. 1 shows the overall configuration of an information processing system 1 according to an embodiment of the present invention.
The information processing system 1 shown in FIG. 1 is configured by connecting a server 10 and n user terminals 20-1 to 20-n (n is any integer value greater than or equal to 1) to each other via a predetermined network N such as the Internet.
In the following description, when there is no need to distinguish between the user terminals 20-1 to 20-n, they will be collectively referred to as "user terminal 20."

The user terminal 20 is an information processing device managed for each user, and is configured, for example, by a smartphone.
The server 10 is a server that executes various processes to manage the operations of the user terminals 20-1 to 20-n.

Specifically, in this embodiment, the server 10 manages each operation of the user terminal 20 as follows.
That is, the server 10 first transmits a test consisting of questions that have been stored in advance in the server 10 or the like to the user terminal 20 .

The questions included in the test are created for each basic skill (hereinafter simply referred to as a "skill") in the user's business.
Here, skills refer to the basic abilities that are required across all occupations, industries, and positions, among the knowledge and skills necessary to continuously produce the results expected within an organization. No matter how highly specialized a person may be, what is needed to actually carry out their work are basic abilities such as "planning ability,""time management ability," and "communication ability."
Specifically, m skills (m is any integer value greater than or equal to 1) are defined, and p items (p is any integer value greater than or equal to 1, independent of m) are further defined for each skill, and questions related to each item are created for each item. Basic business skills refer to techniques or abilities that are useful in working as a member of society.
In this embodiment, the basic skills in business are divided into four categories: knowledge necessary for a business person, ability to plan and carry out work, communication ability, and thinking ability, and an evaluation is made for each category as well as an overall evaluation. Specific examples of skills and categories will be described later with reference to FIG. 4.

The user terminal 20 receives the test sent by the server 10. The user then operates the user terminal 20 to input answers to each of the questions that make up the test.
The user terminal 20 transmits the test answers (a collection of answers to each question) entered by the user to the server 10 .

The server 10 sequentially acquires and grades the test answers each time they are sent from each of the user terminals 20-1 through 20-n. The server 10 also normalizes the graded results for each item, and stores and manages them as scores for each user.

The server 10 sets and stores extraction conditions for extracting scores of a predetermined population from the scores managed for each user.
The predetermined population is not particularly limited, and various kinds of populations can be adopted, such as a group of users who match one or more predetermined pieces of attribute information among various attribute information related to the users, or a group of users whose scores are within a certain range, etc. It is assumed that the server 10 manages, for each user, a score indicating the scoring result and various attribute information of the user in association with each other.
In this case, extraction conditions for extracting scores from a predetermined population can be, for example, the same age, the same occupation, the same industry, the same position, the same year of joining the company, past score values or ranges, etc.

The server 10 extracts the score of a specific user and the score of a specific population that includes the specific user, and compares the two scores.
Specifically, for example, the score of the predetermined user can be compared with the average, maximum, or minimum score of a predetermined population that includes the predetermined user.

Furthermore, the server 10 can create a comment as information for supporting the predetermined user based on the result of the comparison.
The specific form of the comment to the predetermined user will be described later with reference to the test result sheet of FIG.

In addition, the server 10 can display, along with the comment, a graph plotting the score of the specified user and the score of a specified population that includes the specified user, on the screen of the user terminal 20 of the specified user.
The specific aspects of the graph will be described later with reference to FIG.

This allows the user to easily visually see the degree of growth of the user's current skills compared to past skills, as well as the effectiveness of the company's training, from the distribution of the user's own score for each item for each skill on the graph displayed on the screen of the user terminal 20 and the score of a specified population that includes the user.

Furthermore, by reading the comments displayed on the screen of the user terminal 20, the user can easily formulate specific action plans for improving his or her own skills.
The details of these processes executed by the server 10 will be described later with reference to FIG.

Figure 2 is a block diagram showing the hardware configuration of the server in the information processing system 1 of Figure 1.

The server 10 includes a CPU (Central Processing Unit) 101, a ROM (Read Only Memory) 102, a RAM (Random Access Memory) 103, a bus 104, an input/output interface 105, an output unit 106, an input unit 107, a memory unit 108, a communication unit 109, and a drive 110.

The CPU 101 executes various processes according to a program recorded in the ROM 102 or a program loaded from the storage unit 108 into the RAM 103 .
The RAM 103 also stores data and the like necessary for the CPU 101 to execute various processes.

The CPU 101, ROM 102, and RAM 103 are interconnected via a bus 104. The bus 104 is also connected to an input/output interface 105. The input/output interface 105 is connected to an output unit 106, an input unit 107, a memory unit 108, a communication unit 109, and a drive 110.

The output unit 106 is composed of a display, a speaker, etc., and outputs various information as images and sounds.
The input unit 107 is composed of a keyboard, a mouse, etc., and is used to input various information.

The storage unit 108 is configured with a hard disk, a DRAM (Dynamic Random Access Memory), etc., and stores various data.
The communication unit 109 communicates with other devices (user terminal 20 in the example of FIG. 1) via a network N including the Internet.

Removable media 120, such as a magnetic disk, optical disk, magneto-optical disk, or semiconductor memory, is appropriately loaded into the drive 110. A program read from the removable media 120 by the drive 110 is installed in the storage unit 108 as needed.
Furthermore, the removable media 120 can also store various data stored in the storage unit 108 in the same manner as the storage unit 108 .

Figure 3 is a functional block diagram showing the functional configuration of the server in the information processing system of Figure 1.

As shown in FIG. 3, the CPU 101 (FIG. 2) of the server 10 functions as a test creation unit 121, a test question setting unit 122, an answer acquisition unit 123, a scoring unit 124, a scoring unit 125, a score acquisition unit 126, a comment creation unit 127, a display control unit 128, a learning management unit 129, and a course recommendation unit 130.
In one area of the storage unit 108 (FIG. 2), a question DB 141, a marking result DB 142, a population DB 143, and a student DB 144 are provided.

The question DB 141 stores questions for evaluating the user's skills, predetermined scoring criteria for the questions, and sets of correct answers.
The scoring result DB 142 stores the scoring results for each question in the question DB 141 as a score for each user after normalizing (scoring) the results for each theme in each field.
Population DB143 stores the score of a specific user, the score of a specific population that includes the specific user, and specific extraction conditions for extracting the score of the population based on the attributes of the specific user (e.g., the same industry, the same occupation, the same age, etc.).
The attendance DB 144 stores training videos and the like for courses reserved by users. Courses are not limited to videos; some courses are actually taught by instructors at venues, and information on reservations to participate in the courses is also stored in the attendance DB 144.
In addition, the attendance DB 144 stores information about the user who is the target of taking the course, information about multiple courses as educational venues, the attendance history of the user who took the course, the learning history of the user's learning behavior after taking the course, comments and feedback scores and their average scores to the user from the course manager or superior, and suggested information regarding future course plans created by the course recommendation unit 130.
Information about the user who is to take the course includes, for example, the user's name, age, user ID, password, email address (hereinafter referred to as the "registered address"), and information about the organization to which the user belongs (for example, company name, company industry, department, job type, date of joining the company), etc.
A course is, for example, a training session or seminar that implements a training program, as well as a remote course or remote learning class via the Internet. A course also includes multiple users participating in multiple courses, or one-on-one sessions between a teacher and a student. A single user may also take multiple courses as long as the courses do not overlap.
The attendance DB 144 also stores follow-up test questions, predetermined grading criteria for the questions, and sets of correct answers in association with each other.

Here, the difference between the follow-up test and the usual diagnostic test for business fundamentals, which gives a score as the evaluation result, will be explained.
While regular diagnostic tests for business fundamentals are designed to comprehensively assess the extent to which a wide range of knowledge and skills have been acquired, follow-up tests are designed to assess the extent to which knowledge related to the training content has been acquired after each training session. For this reason, follow-up tests are designed with relatively simple questions, such as a question-and-answer format. Also, while regular tests have a total of 100 questions and the questions are uniform, follow-up tests have questions that are individually set according to the training content, and the number of questions is around 10 (for example, 5 to 6 questions).
For example, as shown in screen 221 of FIG. 10, the follow-up test question to be taken after taking the basic training in "logical thinking" is, "Logical thinking that is useful in the workplace is 'thinking by formulating ( )'. Please choose one appropriate word from the following to fill in the blank." The answer options for this question are, for example, logic, hypothesis, logic, evidence, etc.

The information on multiple courses stored in the course attendance DB 144 is information in which one or more evaluation elements (hereinafter referred to as "theme" or "sub-theme") correspond to each of the multiple courses. One theme or sub-theme may be associated with one course. A sub-theme is a small theme included in a theme, and courses with only a small theme may also be set.
The theme is one of the evaluation elements for measuring basic business skills, which are divided into four areas, such as business knowledge, planning and control, thinking, and communication, as shown in the graph in Figure 4. Each divided area has courses that include one or more themes.

For example, themes that assess basic business skills in the field of business knowledge include current affairs, legal affairs, human resources, and labor, financial management, marketing, and management. Although not shown in the figure, the legal affairs, human resources, and labor theme includes subthemes such as human resources and labor and compliance.
The themes that assess basic business skills in the field of planning and control include objectives and goals, planning, business management, review and evaluation, and improvement. Although not shown, the objectives and goals theme includes a subtheme called goal-based thinking. Furthermore, the planning theme includes a subtheme called action plan creation.
The themes for assessing basic business skills in the thinking field include numerical processing, application of thinking methods, information gathering, problem setting, solution planning, etc. Although not shown in the figure, the theme of application of thinking methods includes a sub-theme called the ability to decompose into elements.
Themes for assessing basic business skills in the field of communication include negotiation, written communication, oral communication, listening, business etiquette, etc. Although not shown, the theme of written communication includes a subtheme of slide creation ability.
The business fundamentals assessed by this information processing system are intended to improve the business skills of the students by having them take one or more courses set for each theme or for multiple themes.
Before taking the course, participants will be given a diagnostic test on their basic business skills before, during and after the course.
The diagnostic test is a test that encourages correct self-awareness and comprehensively supports employee growth. Employees can not only take the test, but also self-recognize issues from the test results and set goals that prompt them to take the next action. In other words, by repeating the cycle of Plan → Do → Check → Action, employees can achieve continuous growth.
Furthermore, the diagnostic test is not something that can be taken once and then left alone; by periodically checking whether students are properly learning and moving towards their desired goals, it can also serve as a guide for course corrections. It can also help to maintain students' motivation to learn.

In the server 10, the test creation unit 121 creates questions for each item of each skill from among questions for evaluating the user's skills that are stored in advance in the question DB 141. The collection of questions for each item of each skill created in this way is a test.
The test setting unit 122 sets the test to the user by displaying the test created by the test creation unit 121 on the user terminal 20 via the communication unit 109.

The user operates the user terminal 20 to input answers (answers for each question) to the tests set by the test question setting unit 122. The answers entered by the user are transmitted from the user terminal 20 to the server 10.

The answer acquisition unit 123 of the server 10 receives the test answers (a collection of answers for each question) sent from the user terminal 20 via the communication unit 109.
The marking unit 124 marks the test answers acquired by the answer acquisition unit 123 for each question based on predetermined marking criteria.

The scoring unit 125 normalizes (scores) the results of scoring for each question by the scoring unit 124 for each theme in each field, and stores the scores in the scoring result DB 142 and manages them for each user.

The score acquisition unit 126 acquires the score of a predetermined user and the score of a predetermined population that includes the predetermined user from the scores of each user managed in the scoring result DB 142. The predetermined user may also be referred to as the first user.
The predetermined population is extracted according to predetermined extraction conditions pre-stored in the population DB 143. Specifically, as described above, a population can be extracted using predetermined extraction conditions that include any combination of any number (including 1) of the same age, same occupation, same industry, same job title, same year of joining the company, or the past scores of the predetermined user.

The comment creation unit 127 compares the score of a specific user acquired by the score acquisition unit 126 with the scores of a specific population that includes the specific user, and creates a comment as information to support the specific user from a combination of pre-set character strings based on the results of the comparison.

The comments may include comments regarding the user's suitability for at least one of the user's occupation, industry, and job title, as well as the correspondence between the occupation and each of the skills and items, comments regarding recommended actions to enhance the strengths of the specified user's occupation, and comments regarding recommended actions to overcome the weaknesses of the specified user's occupation.

The learning management unit 129 displays each user's personal page (see FIG. 7) to the user. The learning management unit 129 manages the learning behavior of the user after attending a course on the personal page.
Specifically, the learning management unit 129 manages the course attendance status of the user in the course plan based on the information in the attendance DB 144 (the attendance history of the user who attended the course, the learning history of the user's learning behavior after attending the course, comments to the user from others such as the course administrator or superior, feedback scores from others, etc.), manages the progress of actions in response to the user's course attendance behavior report, conducts follow-up tests, manages feedback information (comments, scores, etc.) from the course administrator or superior, etc., and uploads this information to the user's My Page, etc. Specific operations will be described later with reference to the drawings.

The course recommendation unit 130 suggests future course plans to improve a user's business fundamentals based on the correlation (correspondence) between the course attendance history of a user who has taken a course as one of the educational opportunities for improving business fundamentals, the user's behavior after taking the course, and the evaluation results of the user's business fundamentals after taking one or more courses multiple times (for example, the average scores in all areas of the previous and current tests).

The course recommendation unit 130 includes a course plan creation unit 151 , a proposal unit 152 , and an alert unit 153 .
Based on the information read from the attendance DB 144 and the information read from the scoring result DB 142, the attendance plan creation unit 151 creates a future attendance plan for the user, including a combination of courses suitable for improving the user's skills (simultaneous course themes and number of courses, taking this course first and then this course, etc.), the number of courses to be taken, the interval between courses, the current situation, etc., and stores the plan in the attendance DB 144 while also outputting it to the suggestion unit 152.

The suggestion unit 152 uploads the future course plan created by the course plan creation unit 151 to My Page and suggests it to the user via the display control unit 128.

The alert unit 153 outputs an alert when the user's current status in the attendance DB 144 (number of attendances, attendance interval, action completion rate after attendance, follow-up test completion rate after attendance, execution rate of specific actions to be undertaken starting tomorrow, average score of feedback from others, etc.) does not match the judgment conditions (recommended number of attendances, recommended attendance interval, each completion rate, execution rate, average score threshold, etc.) derived in advance from case studies (see Figures 19 to 21, etc.).

For example, when a user attempts to reserve a course for more than the recommended number of times per year (threshold), the alert unit 153 displays an alert on the course reservation screen to the effect that the number of times is too many.
When a user books a course that exceeds the recommended number of times per year (threshold), the alert unit 153 displays information (such as an alert message or an alert object) within the course plan proposed on My Page 201 indicating a caution or warning that the number of courses is too high.

When a user attempts to book a course before the recommended course interval (threshold) has elapsed, the course recommendation unit 130 displays an alert on the course booking screen to the effect that the course is booked too early.
When a user makes a reservation for a course before the recommended attendance interval (threshold) has elapsed, the alert unit 153 displays information (such as an alert message or an alert object) indicating a caution or warning to cancel the reservation within the course plan proposed on My Page 201.

If the user's action completion rate after taking the course does not reach a threshold value of, for example, 100%, the alert unit 153 sends an email (alert email) to the user's registered address containing a message urging the user to proceed with the action after taking the current course without making a reservation for the next course.
If the user's action completion rate after taking the course does not reach a threshold value of, for example, 100%, the alert unit 153 displays information (such as an alert message or an alert object) indicating a caution or warning urging the user to proceed with post-course actions for the current course without booking the next course within the course plan proposed on My Page 201.

If the user's follow-up test completion rate after taking the course does not reach a threshold value of, for example, 100%, the alert unit 153 sends an email (alert email) to the user's registered address containing a message urging the user to take specific action starting tomorrow to complete the remaining part of the current course without making a reservation for the next course.
If the user's completion rate of the follow-up test after taking the course does not reach a threshold value of, for example, 100%, the alert unit 153 displays information (such as an alert message or an alert object) indicating a caution or warning urging the user to take the follow-up test after taking the current course without booking the next course within the course plan proposed on the My Page 201.

If the execution rate of specific actions to be taken starting tomorrow is below a threshold value of, for example, 75%, the alert unit 153 sends an email (alert email) to the user's registered address containing a message urging the user to take the remaining "specific actions to be taken starting tomorrow" for the current course without making a reservation for the next course.
If the execution rate of the specific actions to be taken from tomorrow is, for example, below a threshold value of 75%, when an attempt is made to reserve the next course from My Page 201, the alert unit 153 displays information (such as an alert message or an alert object) indicating a caution or warning urging the user to take the remaining "specific actions to be taken from tomorrow."

If the average score of feedback from others is, for example, a threshold value of 3 points or less, the alert unit 153 causes the course recommendation unit 130 to send an email (alert email) to the user's registered address containing a message encouraging the user to review the training content of the current course without making a reservation for the next course.
If the average score of feedback from others is, for example, below a threshold value of 3 points, when the user tries to book the next course, the alert unit 153 displays information (such as an alert message or an alert object) indicating a caution or warning urging the user to review the training content that has already been taken.

Specifically, the course recommendation unit 130 reads the above-mentioned course information (course history, behavioral status) from the course DB 144, information to be compared with the user (population score) from the population DB 143, and multiple assessment results (scores) for each field from the scoring result DB 142, and based on this information, creates a future course plan for the user to improve their basic business skills, uploads the created future course plan to the user's My Page, and proposes it to the user.

The course history includes, for example, concurrently taken courses, the number of courses taken in a specified period (yearly, six months, three months, etc.) (once a year, once every six months (twice a year), once every three months (four times a year), etc.), and the interval between courses (one year (12 months), six months, three months, etc.).
The behavioral status includes at least one of the following: behavior completion rate after taking the course, follow-up test (additional assessment) completion rate, number of course behavior reports after taking the course, and average score given as feedback by the administrator who manages the user (advisor in charge, course manager, supervisor, etc.) based on the user's learning status.
The evaluation results for each subject area obtained multiple times are, for example, the average score for each subject area in the test one year ago and the average score for the current test (the average score for each subject area in the test one year ago and one year from now).

The display control unit 128 controls the display on the screen of the user terminal 20 via the communication unit 109 of a graph plotting the score of a specific user acquired by the score acquisition unit 126 and the score of the population that includes the specific user in a specific display area.

Furthermore, the display control unit 128 controls the display of the comment created by the comment creating unit 127 on the screen of the user terminal 20 via the communication unit 109 .
Specific examples of comments displayed on the screen of the user terminal 20 will be described later with reference to the test result sheet of FIG.

Furthermore, the display control unit 128 controls the transfer and display of a user's My Page, which is managed by the learning management unit 129, to the user terminal 20 of the user who logs in to the user's My Page.
On their own My Page, users can take follow-up tests administered by the learning management unit 129 and can also view future course plans and the like output by the course recommendation unit 130.

Conventional training services typically focus on issuing recommendations and alerts to encourage users to take the course, but this information processing system not only encourages users to take the course but also has the function of preventing users from taking too many courses, thereby achieving the following effects:
First, from the perspective of the user's business knowledge and learning, by providing recommendations and alerts on the number of classes and intervals recommended when proposing a course plan from the information processing system side, the number of classes and intervals recommended can be imprinted in the user's mind, and the user will then book classes at those numbers and intervals, thereby maintaining an appropriate learning situation. This can be highly effective in terms of the user's knowledge acquisition and growth.
Furthermore, training service providers can provide users with recommendations and alerts on the number of courses to take and the intervals between courses when proposing a course plan that includes a good combination of courses (such as simultaneous courses), which not only encourages users to take courses but also discourages excessive course attendance or frequent courses in a short period of time from the perspective of stable operation, thereby promoting continued use and realizing stable operation of the subscription model.

Figure 4 shows an example of the graph display area before the score values are plotted.

As shown in FIG. 4, skills can be defined in four areas as the user's basic business skills (hereinafter referred to as "basic business skills"), and items can be set for each area under six themes.
Specifically, the four areas of business fundamentals can be defined as business knowledge, planning and control, communication, and thinking.

Furthermore, there are five themes set for each field. For example, the skills in the field of "business knowledge" can be set up under the themes of current affairs, legal affairs, human resources, and labor, financial management, marketing, and management. The legal affairs, human resources, and labor theme includes sub-themes such as human resources and labor and compliance.
The skills in the "Planning and Control" field can be set up under the themes of purpose and goals, planning, work management, review and evaluation, and improvement. The theme of purpose and goals includes a subtheme of goal-based thinking. The theme of planning also includes a subtheme of action plan creation.
The skills in the "communication" category can be set up under the themes of negotiation, written communication, oral communication, listening, and business etiquette. The written communication theme includes the subtheme of slide creation skills.
In the "thinking" category, skills can be set up under the themes of numerical processing, application of thinking methods, information gathering, problem setting, and solution planning. The theme of application of thinking methods includes the sub-theme of the ability to decompose into elements.

The server 10 then administers individual tests to the user for each item set for each skill, obtains the test results, scores the results based on the predetermined scoring criteria for each item for each skill, normalizes (scores) the results, obtains the scores, and displays a graph on the user terminal 20 plotting the scores in a predetermined display area.

Specifically, in the concentric display area shown in Figure 4, four skills are evenly allocated to the periphery of the display area, and each item set for each skill is placed at equal intervals on the periphery. The lowest score obtained by normalization (0 (zero)) is assigned to the center of the concentric circle, and the highest score (5) is assigned to the periphery. In addition, concentric circles are placed in the display area for each possible score value (1 to 5).

The server 10 then displays on the user terminal 20 a graph in a display area plotting one or more combinations of a specific user's score from the scores managed for each user and the scores of a specific population that includes the specific user, such as people of the same age, occupation, industry, position, year of employment, or the user's past results.

This makes it possible to visualize the distribution of score values for each item for each skill, allowing the specified user to easily see their current skills, the degree of growth compared to past skills, and the effectiveness of the company's training.
A graph in which the scores of each item for each skill are actually plotted will be described with reference to FIG.

Figure 5 shows an example of a test result diagnostic sheet (hereinafter referred to as the "test result sheet") that summarizes graphs and comments displayed on a user terminal.

The server 10 displays the graphs and comments created by each user on each of the user terminals 20-1 to 20-n.
Specifically, as illustrated in Figure 5, a test result sheet containing graphs and comments of a specific target user (hereinafter referred to as the "target user") can be displayed on the user terminal 20 operated by the target user.

Furthermore, the score values plotted on the graph on the test result sheet are not limited to the score values of the target user for each item, but can also be plotted for scores of users of the same age, occupation, industry, position, and year of employment as the target user, or the population of the person's past results. In the example of Figure 5, the average scores of users of the same age as the target user, and the average scores of users of the same occupation and age as the target user are plotted.

This allows the target user to easily see the level of their own business skills, as well as the level of business skills of users of the same age as the target user and users of the same occupation and age as the target user, thereby allowing the target user to understand the level of their own business skills in relative terms.
Therefore, the target user can easily understand the skills that should be improved as the target user's own strengths and the skills that should be improved as the target user's own weaknesses.

Furthermore, as shown in Figure 5, the comments written on the test result sheet can consist of comments at each item level, comments on strengths and weaknesses, and summary comments.

Specifically, in the example of Figure 5, for the item "Problem Setting" set for the skill "Thinking," the summary is written as "Basic knowledge of problem setting required of business people," and the score for the specified user is written as "2."
Furthermore, the average score of other users for the same item is recorded as "3," which indicates that the skill of the specified user is inferior to that of other users.
Then, a comment about the item in question will be written, such as, "You lack the basic knowledge of problem setting required of business people. Please make sure to acquire this knowledge in your future studies."

In addition, for the item "business etiquette" set under the skill "communication," the summary is written as "basic business etiquette for leaving a good impression on others," and the score is written as "5."
Furthermore, the average score of other users for the same item is recorded as "3," which indicates that the skill of the specified user is superior to that of other users.

For example, if the server 10 determines that a person has sufficient knowledge of business etiquette but is slightly lacking in consideration for others, it will post a comment related to that item, such as, "Business etiquette is the basis for building relationships, and consideration for others is the most important thing. You have acquired the knowledge, so please remember to continue to be considerate."

In this way, comments are written as information to support the user based on the user's answers to the tests given to them.

In addition, comments about strengths and weaknesses are provided based on the results of comparing the target user's score with the scores of the population to which the target user belongs, and include recommended actions to enhance the strengths of the target user's occupation and recommended actions to overcome the weaknesses of the target user's occupation.

Specifically, as shown in the test result sheet in Figure 5, strengths and weaknesses are listed, along with comments on recommended actions. For example, if a candidate has strengths in the areas of legal and labor affairs, a recommended action might be something like, "To further develop your strength, we recommend learning through actual work. If your job is in the XX category, you will likely learn by taking on a task like XX."

For example, if a person has weaknesses in the area of objectives and goals, a recommended action might include a comment such as, "To overcome this, it would be good to solidify your knowledge through discussions in addition to self-study such as reading. We recommend that you talk to experts or participate in workshops at seminars."

This allows target users to easily understand what they need to do specifically to work in their current job position.

In addition, the summary comment includes the target user's suitability for the job type and the correspondence between the job type and each skill, based on the results of comparing the target user's score with the scores of the population to which the target user belongs.

Specifically, as shown in the test result sheet in Figure 5, the summary comments include phrases such as "This will broaden your possibilities as a sales professional" to indicate the user's suitability for the job type, and the summary comments include phrases such as "You seem to excel in business etiquette and written communication. By further developing your strengths," and "You appear to have issues with your objectives, goals, and basic reasoning skills. These are generally required elements for sales positions," to indicate the correspondence between the job type and each skill.

By reading the comments, users can easily plan specific actions to improve their skills. Furthermore, by learning about their current suitability for their job, they can easily learn which skills and which aspects of their skills are their strengths in that job, and conversely, what is needed to improve their suitability for that job.

In addition to the graphs and comments, the test result diagnostic sheet can also include the test date, test area, company name, user name, occupation, age, and total score.
This allows information about the target user's score to be easily viewed.

Next, the course recommendation operation of the server 10 in this information processing system will be described with reference to Fig. 6. Fig. 6 is a flowchart showing the course recommendation operation of the server 10.
In this case, the course recommendation unit 130 suggests to the user a future course plan to improve their basic business skills based on the correlation (correspondence) between the educational history of the user who took the course to improve their basic business skills, the user's behavior after taking the course, and the average values of the user's test results in all areas after taking the course.

Specifically, in step S11 of FIG. 6, the course recommendation unit 130 reads the test results and the learning history from the course DB 144.
Next, in step S12, the course recommendation unit 130 creates a future course plan for the user to improve their basic business skills based on the correlation (correspondence) between the course history, the user's behavior after taking the course, and the evaluation results of the basic business skills after taking one or more courses multiple times (e.g., the average values of all areas in the previous and current tests).
Then, in step S13, the course recommendation unit 130 uploads the created future course plan to the user's personal page and proposes the future course plan to the user.

The operation of the learning management unit of the server will be described below with reference to FIGS.
FIG. 7 is a diagram showing an example of a My Page disclosed to a user.
FIG. 8 is a diagram showing an example of a course completion screen displayed on the My Page.

As shown in FIG. 7, My Page 201 has columns for a course status summary, a training course plan, a course history summary, a course history detail, and the like.
In the attendance status summary column, numerical values such as the number of attendances, attendance interval, action completion rate after attendance, follow-up test completion rate, execution rate of specific actions to be undertaken from tomorrow, and average score of feedback from others are displayed in respective boxes, all read from attendance DB 144.

The number of times taken box displays the recommended number of times derived from the score in the scoring result DB142 and the number of times the user has actually taken the course this year. In the example in Figure 7, the recommended number of times is clearly displayed as 2 times, and the number of times the user has taken the course this year is displayed as 1 time.

The course interval box displays the recommended interval derived from the score in the scoring result DB142 and the interval since the user last took the course. In the example in Figure 7, the recommended interval is clearly displayed as 6 months, and the interval since the user last took the course is displayed as 8 months.

The post-learning action completion rate box displays the user's current status. In the example in Figure 7, the action completion rate is displayed as 50%.

The follow-up test completion rate box displays the user's current status. In the example in Figure 7, the follow-up test completion rate is displayed as 50%.

The execution rate of specific actions to be undertaken starting tomorrow box displays the user's current status. In the example in Figure 7, the execution rate of specific actions to be undertaken starting tomorrow is displayed as 75%.

The average score box for feedback from others displays the user's current status. In the example in Figure 7, the average score for feedback from others is displayed as 3 points.

The training attendance plan field displays the training attendance plan (future attendance plan) created by the attendance recommendation unit 130 .
For example, if the job type is sales and the employee is junior, a three-year training plan covering the fourth to sixth year after joining the company is presented. The goal is, for example, to become a person who can mentor junior employees, based on the test results and learning history, and the trainee's name is entered as the trainee's name. The three-year plan is divided into six-month periods for the first, second, and third years, and the names of courses recommended for attendance are presented for April-September and October-March, respectively.

The course status summary section also displays a table of the training plan for the course the user is taking.

The course history summary column displays a list of courses (training) that the user has already taken. The list has columns for the year, number of courses taken that year, course date, training name, comments, etc., and data from the course DB 144 is entered into these columns. The comments column displays alert messages such as "The recommended number of courses has not been reached" or "The recommended course interval is six months."

The column for course history details has columns for, for example, elements necessary for developing subordinates, logical thinking, behavior tests, and training content explanation videos, in the order of the courses taken.
The column for elements necessary for developing subordinates is intended for managers, and a reservation button allows them to make reservations for courses on elements necessary for developing subordinates.
The Logical Thinking column is a column for scheduled courses in the field of logical thinking, as an example of courses to be taken in the future, and displays the training dates. The Behavior Test shows the results of testing the operation of the settings on this page. If the operation is normal, the word "Complete" and a check mark will be displayed.
The training content explanation video section allows you to play videos that explain the training content for new and young employees. The video can be played by clicking the "Watch" button.

Now, with reference to FIG. 8, the learning steps that a user must complete after taking one course will be described.
When a user takes a course (watches a video seminar), a learning progress column 202 is provided for the name of the course on My Page 201, as shown in Fig. 8. By clicking a button 203 for checking the number of completed steps in column 202, a status screen 204 for each step is displayed. By viewing this status screen 204, the user can check how far along they are in their learning.

In this example, the number of learning steps, that is, the number of completed steps, is eight.
Specifically, there are eight steps in total: bookmark (step 1), reservation (step 2), first video (step 3), first report/attendance report (step 4), viewing comments in the first report (step 5), first report/action report (step 6), first report/view comments (step 7), and first test (step 8).
For this reason, the status screen 204 has rows for each step arranged in the order of learning, and each row for each step is provided with the date of completion.
When all steps are completed, a check mark and the word "Completed" are displayed in the learning progress column 202, indicating that the learning steps after taking one course have been completed.

In this example, all eight steps have been completed, so button 203 displays "Complete Step 8 of 8." Column 202 also displays the word "Complete" and a check mark. By viewing column 202, the user can see that they have completed all learning related to this course.

Next, a review test (follow-up test) after taking a course, which is carried out by the learning management unit, will be described with reference to FIGS.
FIG. 9 is a diagram showing an example of a start screen when taking a follow-up test on a user's My Page.
FIG. 10 is a diagram showing an example of a question screen that is displayed following the start screen of FIG.
FIG. 11 is a diagram showing an example of a screen that is displayed when all questions have been answered by answering the questions in order starting from the question screen of FIG.
FIG. 12 is a diagram showing an example of a confirmation screen displayed following the screen of FIG.
FIG. 13 is a diagram showing an example of a test result screen that is displayed following the marking start screen of FIG.

After a user has taken the logical thinking course (training) that was reserved in the logical thinking column on My Page 201 in Figure 7, a "Report" button 211 and a "Take the Exam" button 212 are provided in the logical thinking column on My Page 201, as shown in Figure 9.
The user can take a review test (follow-up test) by clicking button 212.
In this case, when the Take Exam button 212 in FIG. 9 is clicked, the learning management unit 129 displays a question screen 221 shown in FIG.
The question screen 221 has questions on the theme of logical thinking, a field of answer options for the questions, a "Next Question" button 222, and a "Check Score" button 223.
The "Next Question" button 222 is a link button linked to the next question, and clicking it displays the next question screen.

The "Check Scoring" button 223 is a button for displaying current scoring information; clicking it will display the current scoring information.

From the question screen 221 in Figure 10, proceed through the answering operations for the questions in order. When all questions have been answered, the screen will change to 231 as shown in Figure 11.

The screen 231 in FIG. 11 has a "Return to Questions" button 232 and a "Score" button 233.
When the user clicks on the "Score" button 233, the learning management unit 129 displays a confirmation screen 241 shown in FIG.

The confirmation screen 241 is a screen that prompts (confirms) the user to grade. The confirmation screen 241 displays a message such as "We will grade you. Are you sure?" and also provides an "OK" button 242 and a "Cancel" button 243 as options.

Here, when the user clicks on the "OK" button 242, the learning management unit 129 executes the grading process and displays a test result (grading result) screen 251 shown in FIG.
The percentage of correct answers can be confirmed as test results on this screen 251. In this example, all answers are correct, so the percentage of correct answers is displayed as 100%.
If there is a question that is not answered correctly, a back button (not shown) is displayed on the screen 251 for each question, allowing the user to return to the question and answer it again. This process continues until all questions are answered correctly.

Next, a course attendance behavior report that should be made after a user attends a course will be described with reference to FIGS.
FIG. 14 is a diagram showing an example of an input screen for future actions when reporting class actions.
FIG. 15 is a diagram showing an example of a check screen for checking the user's behavior after a certain period from the class behavior report.

After the user has attended the course, he or she reports the course attendance behavior on the My Page 201 shown in FIG. 7 as part of the learning step.
At this time, an input screen 261 is displayed on the My Page 201 as shown in FIG.

The input screen 261 displays, for example, three fields 262 for the user to write down the details of specific actions to be taken starting tomorrow, a field 263 for the scheduled check date, and a message 264 indicating what to write in each field.
The user writes down what he or she needs to do in at least one of the three columns 262, and then completes the class activity report.

The scheduled check date field 263 is set to a date three months from today by default, and the user will check the completion rate (achievement level) of the tasks to be done on the scheduled check date.
By entering a date three months from today as the default setting, the user can remember that the tasks that need to be completed in approximately three months. The date in the scheduled check date column 263 can be changed from the default date by user operation.

After a certain period of time (for example, three months) has passed since the class behavior report was submitted, an alert will be output to the user's My Page or via email to inform them that it is time to check.
When a user who has seen the alert logs into his/her personal page, a check screen 271 shown in FIG. 15 is displayed.
The check screen 271 has details 272 of specific actions to be taken from tomorrow, which the user inputs when reporting the course activity, an input field 273 for the execution rate, and an input field 274 for "Did you do what you should have done?" for each of the details.
In each field of this check screen 271, the user inputs his/her own idea of the execution rate (how much was done or not done) and the reason for it.

By allowing users to self-evaluate their post-course behavior, they can reconsider and reaffirm their behavior in the post-course period and how they will approach their goals (what they need to do).

In this way, the My Page provided to users has a default post-course action period (three months) and course interval (once every six months) set as their future course plan. Users who receive a course plan recommendation will be able to follow the course plan and take courses at a frequency appropriate for acquiring the skills they need and are satisfied with, unless they wish to change it themselves.

Next, feedback from others will be described with reference to FIGS.
FIG. 16 shows a part of the screen of My Page.
FIG. 17 is a diagram showing an example of a screen displaying comments fed back from the course administrator.
FIG. 18 is a diagram showing an example of display of feedback points from the course manager.

When the user completes the check step by entering the execution rate on the check screen 271 and the reason for whether or not they did what they should have done, comments will then be returned from the user's superior or course administrator regarding the results of the user's own behavior check (execution rate, reasons, etc.).
When a comment is entered into a user's My Page, an alarm is sent to the user as described above.

When a user who has seen the alert logs into My Page, a "View Comments" button 281 is provided in the Logical Thinking section of the course history details on My Page 201 shown in FIG.
When the user clicks on the "View Comments" button 281, a comment screen 291 is displayed. Comments from superiors, course managers, etc. are displayed on the comment screen 291.

By reading the comments from the course administrator on this comment screen 291, the user can learn objective opinions based on the criteria of others, rather than just the user's own assessment of whether or not they were able to complete the course.

Furthermore, as shown in Figure 18, the comment screen 291 displays feedback points from the supervisor as a graded evaluation, allowing the user to check the supervisor's evaluation from these points as well. The example in Figure 18 shows a case where the supervisor has given the user a feedback point of "3" out of a five-point evaluation.

Based on the idea that a user's behavior is only acquired when it is recognized by others, taking into account feedback from others provides confirmation that the user has acquired skills.
This verification is based on data showing that feedback from others is also correlated with an increase in score, and comments from others, such as that knowledge has been acquired or that the user's behavior has clearly changed, prove that the user was able to achieve the specific behavioral goals they set after taking the course.

Next, we will explain an example of how having users take courses at an appropriate frequency and timing can improve users' skills by using the fact that users tend to take courses consistently as a basis for making judgments. First, with reference to Figure 19, we will explain a case study in which participants were divided into groups based on the number of courses taken per year, and the changes in the number of courses taken and the scores were compared and verified.

FIG. 19 is a diagram showing a comparative example of the number of times each group, A to E, attended the class and the change in their scores.
The verification data is the trend of scores (average scores for each field), which are evaluation values derived from the results of the diagnostic tests on business fundamentals stored in the scoring result DB 142, versus the number of times each test is taken per year. The comparison targets are user groups divided into groups A, B, C, D, and E based on the number of times each user took a course per year. Each user has the same attributes, such as the same industry, occupation, and age, and the industry is manufacturing, the occupation is sales, and the age is in their 30s.

Table 311 shown in Figure 19 compares the average score for each subject area, the number of courses taken per year, and the average score for each subject area one year later for each user group divided into Group A (0 times), Group B (1 time), Group C (2 times), Group D (3 times), and Group E (4 times) based on the number of courses taken. Note that the number of courses taken per year is the number of times an individual user took a course in a year, regardless of the course field.

According to table 311 shown in FIG. 19, under the same conditions, it is clear that Group C showed the greatest change (increase) in the average score for each field one year later compared to the score one year earlier.
From this result, it is concluded that the recommended number of times per year to take the course for this attribute is two.
In the server 10, the course recommendation unit 130 creates a course plan based on the recommended number of courses per year derived from the above verification data, and proposes the created course plan to the user, thereby encouraging participation and preventing excessive participation.

First, we will explain some mechanisms for encouraging attendance based on the recommended number of annual attendances.
First, the course recommendation unit 130 displays on the user's personal page 201 a course plan based on the recommended number of courses per year derived based on the scores of the business fundamentals diagnostic test in the course DB 144, and proposes the plan to the user.
Second, if the attendance status of a user in the attendance DB 144 does not meet the recommended number of attendances per year, the attendance recommendation unit 130 sends an email (alert email) to the registered address of the user.
Third, if the number of courses to be taken per year recommended in the course DB 144 is not met, the course recommendation unit 130 displays information indicating cautions or warnings (such as alert messages or alert objects) within the course plan proposed on the My Page 201.

Next, we will explain some mechanisms for restricting attendance based on the recommended number of annual attendances.
First, the course recommendation unit 130 displays on the My Page 201 (see FIG. 7) the recommended number of courses to take per year, derived based on the scores of the diagnostic test for business fundamentals in the course DB 144 and the user's attributes.
Second, when a user attempts to reserve a course in excess of the recommended number of times per year, the course recommendation unit 130 displays an alert on the course reservation screen.
Third, when a user books a course for more than the recommended number of times per year, the course recommendation unit 130 displays information indicating cautions or warnings (such as alert messages or alert objects) within the course plan proposed on the My Page 201.

Next, referring to Figure 20, we will explain the sequence in which participants were divided into groups based on the annual interval between classes and the changes in scores.

FIG. 20 is a diagram showing a comparative example of the change in score and the interval between classes for each of groups A to E.
The verification data is the transition of scores (average scores for each field), which are evaluation values derived from the results of the diagnostic test on business fundamentals stored in the scoring result DB 142, per year's interval between courses. The comparison targets are groups of users divided into groups A, B, C, D, and E based on the interval between taking a course and the next course over the course of a year. Each user has the same attributes, such as the same industry, occupation, and age, and is in the manufacturing industry, sales, and 30s.

Table 312 shown in Figure 20 compares the average score for each subject area, the course interval, and the average score for each subject area one year later for each user group divided into group A (every month), group B (every three months), group C (every six months), group D (every nine months), and group E (every 12 months) based on the course interval. Note that the course interval is the interval between when an individual user takes a course and when they take the next course, regardless of the course field.

According to table 312 shown in FIG. 20, under the same conditions, it is clear that Group C showed the greatest change (increase) in the average score for each field one year later compared to the score one year earlier.
From these results, it can be concluded that the recommended annual interval for this attribute is six months.
In the server 10, the course recommendation unit 130 creates a course plan based on the recommended course interval derived from the above verification data, and proposes the created course plan to the user, thereby encouraging attendance and preventing excessive attendance.

First, we will explain some mechanisms for encouraging attendance based on recommended attendance intervals.
First, the course recommendation unit 130 displays on the My Page 201 a course plan based on a recommended course interval derived based on the scores of the business fundamentals diagnostic test in the course DB 144 and proposes it to the user.
Second, if a course is not booked even after the recommended course interval has elapsed based on the user's course status in the course DB 144, the course recommendation unit 130 sends an email (alert email) to the user's registered address urging the user to book the course.
Third, if a course is not booked even after the recommended course interval in the course DB 144 has elapsed, the course recommendation unit 130 displays information (such as an alert message or an alert object) within the course plan proposed on the My Page 201 to encourage the user to book the course.

Next, we will explain several mechanisms for restricting attendance based on the recommended attendance interval.
First, the course recommendation unit 130 displays on the My Page 201 (see FIG. 7) the recommended course interval derived based on the scores of the business fundamentals diagnostic test in the course DB 144 and the user's attributes as described above.
Second, if a user attempts to book a course before the recommended course interval has elapsed, the course recommendation unit 130 displays an alert on the course booking screen to the effect that the course is booked too early.
Third, if a user books a course before the recommended course interval has elapsed, the course recommendation unit 130 displays information (such as an alert message or an alert object) indicating a caution or warning to cancel the reservation within the course plan proposed on the My Page 201.

In this way, if a user is taking too many or too few courses relative to the recommended number of courses per year or the recommended interval between courses, an alert will be issued to warn the user, allowing for the optimization of course opportunities.

Next, referring to Figure 21, we will explain the sequence in which users were grouped based on their action completion rate after taking the course, and the changes in action completion rate and score were compared and verified.

FIG. 21 is a diagram showing a comparative example of the action completion rate and the change in score for each of groups A to C.
The verification data is data comparing the progress of scores (average scores for each field), which are evaluation values derived from the results of the diagnostic tests for business fundamentals stored in the scoring result DB 142, with the action completion rate. The comparison targets are user groups divided into Group A (e.g., 0%), Group B (e.g., 1-50%), and Group C (e.g., 51-100%) according to their action completion rates after taking the course. Each user has the same attributes, such as the same industry, occupation, and age, and the industry is manufacturing, the occupation is sales, and the age is in their 30s.

Table 313 shown in Figure 21 compares the average score for each subject area, the action completion rate after taking the course, and the average score for each subject area one year later for each user group divided into Groups A, B, and C based on the action completion rate after taking the course.

According to table 312 shown in FIG. 21, it can be seen that under the same conditions, Group C had the greatest change (increase) in the average score for each field one year later compared to the score one year earlier.
From these results, it can be concluded that there is a correlation between the rate at which actions are completed after taking the course for that attribute and the rate at which scores increase, and that aiming for a 100% rate at which actions are completed after taking the course will lead to an increase in scores.
In the server 10, the course recommendation unit 130 creates a course plan based on the post-course action completion rate derived from the above-mentioned verification data, and proposes the created course plan to the user, thereby encouraging participation and preventing excessive participation.

First, we will explain some mechanisms for encouraging participation based on the rate of action completion after participation.
First, the course recommendation unit 130 displays the action completion rate after the course, derived based on the score of the business basic skills diagnostic test in the course DB 144, on the user's personal page 201 (see Figure 7), allowing the user to understand the current situation.
Second, if the user's course status in the course DB 144 shows that the post-course action completion rate has reached 100%, the course recommendation unit 130 sends an email (alert email) to the user's registered address containing a message encouraging the user to make a reservation for the next course.
Third, if the post-course action completion rate in the course DB 144 reaches 100%, the course recommendation unit 130 displays information (such as an alert message or an alert object) encouraging the course to be taken within the proposed course plan on the My Page 201.

Next, we will explain several mechanisms for restricting attendance based on the action completion rate after attendance.
First, the course recommendation unit 130 displays on the My Page 201 (see FIG. 7) the action completion rate after the course, which is derived based on the score of the business fundamentals diagnostic test in the course DB 144 and the user's attributes.
Second, if the user's action completion rate after taking the course does not reach 100%, the course recommendation unit 130 sends an email (alert email) to the user's registered address containing a message encouraging the user to proceed with post-course actions for the current course without making a reservation for the next course.
Third, if the user's action completion rate after taking the course does not reach 100%, the course recommendation unit 130 displays information (such as an alert message or an alert object) indicating a caution or warning urging the user to proceed with the action after taking the current course without booking the next course within the course plan proposed on the My Page 201.

In this way, by creating a course plan or issuing alerts to users based on the correlation between the rate of increase in test scores and the rate at which users complete actions after taking a course, it is possible to provide users with a stable opportunity to take courses and optimize course attendance.

Next, referring to Figure 22, we will explain the sequence in which users were divided into groups based on their follow-up test completion rate after taking the course, and the follow-up test completion rate and score changes were compared and verified.

FIG. 22 is a diagram showing a comparative example of the follow-up test completion rate and score change for each group, A to C.
The verification data is data comparing the progress of scores (average scores for each field), which are evaluation values derived from the results of the diagnostic tests for business fundamentals stored in the scoring result DB 142, with the follow-up test completion rate. The comparison targets are user groups divided into Group A (e.g., 0%), Group B (e.g., 1-50%), and Group C (e.g., 51-100%) according to the follow-up test completion rate after taking the course. Each user has the same attributes, such as the same industry, occupation, and age, and the industry is manufacturing, the occupation is sales, and the age is in their 30s.

Table 314 shown in Figure 22 compares the average score for each subject area, the follow-up test completion rate after taking the course, and the average score for each subject area one year later for each user group divided into Groups A, B, and C based on the follow-up test completion rate after taking the course.

According to table 314 shown in FIG. 22, under the same conditions, it is clear that Group C showed the greatest change (increase) in the average score for each field one year later compared to the score one year earlier.
From these results, it can be concluded that there is a correlation between the rate at which the follow-up test is completed after taking the course and the rate at which scores increase for the relevant attributes, and that aiming for a 100% completion rate for the follow-up test after taking the course will lead to an increase in scores.
In the server 10, the course recommendation unit 130 creates a course plan based on the post-course follow-up test completion rate derived from the above-mentioned verification data, and proposes the created course plan to the user, thereby encouraging participation in the course and preventing excessive participation.

First, we will explain some mechanisms for encouraging participation based on the completion rate of follow-up tests after participation.
First, the course recommendation unit 130 displays the completion rate of the follow-up test after the course, which is derived based on the score of the business basic skills diagnostic test in the course DB 144, on the user's personal page 201 (see Figure 7), allowing the user to understand the current situation.
Second, if the user's attendance status in the attendance DB 144 shows that the completion rate of the follow-up test after attendance has reached 100%, the attendance recommendation unit 130 sends an email (alert email) to the user's registered address containing a message urging the user to make a reservation for the next course.
Third, if the completion rate of the follow-up test after taking the course in the course DB 144 reaches 100%, the course recommendation unit 130 displays information (such as an alert message or an alert object) encouraging the course to be taken within the proposed course plan on the My Page 201.

Next, we will explain several mechanisms for restricting attendance based on the completion rate of follow-up tests after attendance.
First, the course recommendation unit 130 displays on the My Page 201 (see FIG. 7) the score of the business fundamentals diagnostic test in the course DB 144 and the completion rate of the follow-up test after the course, which is derived based on the user's attributes.
Second, if the user's follow-up test completion rate after taking a course does not reach 100%, the course recommendation unit 130 sends an email (alert email) to the user's registered address containing a message encouraging the user to take the follow-up test after taking the current course without making a reservation for the next course.
Third, if the user's completion rate of the follow-up test after taking the course does not reach 100%, the course recommendation unit 130 displays information (such as an alert message or an alert object) indicating a caution or warning urging the user to take the follow-up test after taking the current course without making a reservation for the next course within the course plan proposed on the My Page 201.

In this way, by creating a course plan or issuing alerts to users based on the correlation between the rate of increase in test scores and the rate at which users complete follow-up tests after taking the course, it is possible to provide users with a stable opportunity to take the course and optimize their course attendance.

Next, referring to Figure 23, we will explain the sequence in which participants were divided into groups based on the execution rate of the "specific actions to take starting tomorrow" in their course behavior reports, and the execution rate of "specific actions to take starting tomorrow" and changes in scores were compared and verified.

FIG. 23 is a diagram showing a comparative example of the execution rate of "specific actions to be undertaken from tomorrow" and the change in score for each of groups A to E.
The verification data is the progress of scores (average scores for each field), which are evaluation values derived from the results of the business fundamentals diagnostic tests stored in the scoring result DB 142, divided by the execution rate of "specific actions to be taken starting tomorrow." The comparison targets are user groups divided into Group A (0), Group B (1-25%), Group C (25-50%), Group D (50-75%), and Group E (75-100%) based on the execution rate of "specific actions to be taken starting tomorrow" in the course behavior report. Each user has the same attributes, such as the same industry, occupation, and age, and the industry is manufacturing, the occupation is sales, and the age is in their 30s.

Table 315 shown in Figure 23 is a table that compares the average score for each subject area, the implementation rate of "specific actions to undertake starting tomorrow," and the average score for each subject area one year later for each user group divided into groups A, B, C, D, and E based on the implementation rate of "specific actions to undertake starting tomorrow" in the course behavior report.

According to table 315 shown in FIG. 23, under the same conditions, it is clear that Group E showed the greatest change (increase) in the average score for each field one year later compared to the score one year earlier.
From these results, it can be concluded that there is a correlation between the execution rate of "specific actions to take starting tomorrow" for the attribute in question and an increase in score, and that aiming for an execution rate of 76% or more for "Did you do what you needed to do?" will lead to an increase in score.
In the server 10, the course recommendation unit 130 creates a course plan based on the recommended course interval derived from the above verification data, and proposes the created course plan to the user, thereby encouraging attendance and preventing excessive attendance.

First, we will explain some mechanisms for encouraging participation based on the rate of implementation of "specific actions to take starting tomorrow."
First, the course recommendation unit 130 displays on the user's personal page 201 a course plan based on the execution rate of "specific actions to be taken starting tomorrow" derived from the scores of the business basics diagnostic test in the course DB 144, and suggests it to the user.
Second, if the execution rate of "specific actions to be taken starting tomorrow" based on the user's attendance status in the attendance DB 144 reaches 76% or more, the course recommendation unit 130 sends an email (alert email) to the user's registered address containing a message urging the user to make a reservation for the next course.
Third, if the execution rate of the "specific actions to be taken starting tomorrow" in the course DB 144 reaches 76% or more, the course recommendation unit 130 displays information encouraging the course (such as an alert message or an alert object) within the course plan proposed on the My Page 201.

Next, we will explain some mechanisms for restricting attendance based on the execution rate of "specific actions to take starting tomorrow."
First, the course recommendation unit 130 displays on the My Page 201 (see Figure 7) the execution rate of "specific actions to be taken starting tomorrow" derived based on the scores of the business basics diagnostic test in the course DB 144 and the user's attributes.
Second, if the user's follow-up test completion rate after taking the course is 75% or less, the course recommendation unit 130 sends an email (alert email) to the user's registered address containing a message encouraging the user to take the remaining ``concrete actions to start tomorrow'' for the current course without making a reservation for the next course.
Third, if the execution rate of the "specific actions to be taken starting tomorrow" is 75% or less, when you try to book the next course from My Page 201, the course recommendation unit 130 will display information (such as an alert message or an alert object) indicating a caution or warning to encourage you to take the remaining "specific actions to be taken starting tomorrow."
The act of making a reservation for the next course may involve operating the course reservation button or inputting reservation information (course name, reservation date, etc.) into the reservation field.

In this way, by creating a course plan and issuing alerts to users based on the correlation between the rate of increase in test scores and the rate at which they take "specific actions to undertake starting tomorrow," it is possible to provide users with a stable opportunity to take courses and optimize course attendance.

In addition, the course behavior report screen or behavior report check screen has a date field for setting the timing for checking whether the "specific actions to be taken starting tomorrow" that the user has set has been completed. The user can set any date by entering it in this date field, but the date "three months from now" is preset in the date field so that the user will always see it.
This suggests that it takes three months for behavioral change to occur after attending one course, and has the indirect effect of informing users taking a course that it is more effective to wait at least three months before attending the next training session.

Next, referring to Figure 24, we will explain the sequence in which participants were divided into groups based on the average score of feedback from others, and the execution rate of "specific actions to take starting tomorrow" and changes in scores were compared and verified.

FIG. 24 is a diagram showing a comparative example of the average points of feedback from others and the change in score for each of the groups A to E.
The verification data is the transition of scores (average scores for each field), which are evaluation values derived from the results of the diagnostic tests on business fundamentals stored in the scoring result DB 142, and the average score of feedback from others. The comparison targets are user groups divided into Group A (1 or less), Group B (2), Group C (3), Group D (4), and Group E (5) based on the average score of feedback from others. Each user has the same attributes, such as the same industry, occupation, and age, and the industry is manufacturing, the occupation is sales, and the age is in their 30s.

Table 316 shown in Figure 24 is a table that compares the average score for each category, the average score for feedback from others, and the average score for each category one year later for each user group divided into groups A, B, C, D, and E based on the average score of feedback from others.

According to table 316 shown in Figure 24, under the same conditions, it can be seen that Group D (4) and Group E (5) showed a large change (increase) in their average scores for each field one year later compared to their scores one year earlier, meaning that the average score for feedback from others was 4 points or more.
From these results, it can be concluded that there is a correlation between the average score of feedback from others for a given attribute and an increase in score, and that aiming for an average score of 5 in feedback from others will lead to an increase in score.
In the server 10, the course recommendation unit 130 creates a course plan based on the average score of feedback from others derived from the above verification data, and proposes the created course plan to the user, thereby encouraging participation in courses and preventing excessive participation.

First, we will explain some mechanisms for encouraging students to take courses based on the average score of feedback from others.
First, the course recommendation unit 130 displays on the user's personal page 201 a course plan based on the average score of feedback from others derived from the scores of the business basic skills diagnostic test in the course DB 144, and suggests the plan to the user.
Second, if the average score of feedback from others in the course DB 144 is 4 points or higher, the course recommendation unit 130 displays information (such as an alert message or an alert object) on the My Page 201 encouraging the user to book the course.
Third, if the average score of feedback from others based on the user's attendance status in the attendance DB 144 is 4 points or higher, the course recommendation unit 130 sends an email (alert email) to the user's registered address containing a message urging the user to make a reservation for the next course.

Next, we will explain some mechanisms for restricting attendance based on the average score of feedback from others.
First, the course recommendation unit 130 displays on the My Page 201 (see FIG. 7) the average score of the business fundamentals diagnostic test in the course DB 144 and feedback from others derived based on the user's attributes.
Second, if the average score of feedback from others is 3 points or less, the course recommendation unit 130 sends an email (alert email) to the user's registered address containing a message encouraging the user to review the training content of the current course without making a reservation for the next course.
Third, if the average score of feedback from others is 3 points or less, the course recommendation unit 130 will display information (such as an alert message or an alert object) indicating a caution or warning urging the user to review the training content that has already been taken when the user tries to book the next course.

In this way, by creating a course plan or issuing alerts to users based on the correlation between the rate of increase in test scores and the average score from feedback from others, it is possible to provide users with a stable opportunity to take courses and optimize course attendance.

In the above example, artificial intelligence or a machine learning engine determines the appropriate frequency and timing for taking a course (a certain period of time after taking the course when not taking the course).
People who select and take courses at their own pace tend to find it difficult to feel the benefits of their learning and their learning pace slows down.

In this example, an AI or machine learning engine determines the appropriate concurrent courses, course duration, and course intervals for the student based on the student's progress in their ability development to date (course attendance status, test results such as follow-up tests taken after the course, changes in scores between previous and current courses, workplace evaluations, etc.) and other similar examples from the past.
In this way, people who take courses with appropriate simultaneous study topics, course duration, and course intervals determined by AI or machine learning tend to continue taking courses at an appropriate frequency and timing even after taking the course, making it easier to improve their skills.

The above describes one embodiment of the present invention, but the present invention is not limited to the above embodiment, and includes modifications and improvements within the scope of achieving the objectives of the present invention.

For example, the hardware configuration shown in Figure 2 is merely an example for achieving the objectives of the present invention and is not particularly limited.

Furthermore, the functional block diagram shown in Figure 3 is merely an example and is not particularly limited. In other words, it is sufficient for the information processing device to be equipped with the functionality to execute the above-described series of processes as a whole, and the functional blocks and databases used to realize this functionality are not particularly limited to the example in Figure 3.

Furthermore, the locations of the functional blocks are not limited to those shown in FIG. 3 and may be arbitrary.
Furthermore, one functional block and database may be configured as a single piece of hardware, a single piece of software, or a combination thereof.

When the processing of each functional block is performed by software, the program that constitutes the software is installed into a computer or the like from a network or a recording medium.
The computer may be a computer built into dedicated hardware, or may be a computer capable of executing various functions by installing various programs, such as a server, a general-purpose smartphone, or a personal computer.

Recording media containing such programs may consist not only of removable media distributed separately from the device itself in order to provide the program to each user, but also of recording media provided to each user in a state where it is pre-installed in the device itself.

In this specification, the steps describing the program recorded on the recording medium include not only processes that are performed in chronological order, but also processes that are not necessarily performed chronologically but are executed in parallel or individually.

In addition, in this specification, the term "system" refers to an overall device consisting of multiple devices, multiple means, etc.

For example, in the above-described embodiment, there were four types of skills: business knowledge, planning and control, communication, and thinking skills, but this is merely an example. In other words, any m skills (m is an integer value of 1 or greater) related to basic business abilities can be adopted. In this case, the items provided for each skill are not particularly limited to the examples in the above-described embodiment, and any p items (p is an integer value of 1 or greater independent of m) can be adopted.

In the above embodiment, the total amount of courses (number of courses taken, intervals between courses, etc.) was restricted based on the average score for each of the four areas used to evaluate basic business skills, but the total amount may also be restricted by area, taking into account the balance between each area.
In the above embodiment, the course is intended to improve business skills, but it may simply be intended to improve practical skills and techniques in the user's daily life, and the term "skills" will be used to refer to business skills, practical skills, and techniques. The concept of a course also includes training sessions, workshops, lectures, seminars, etc.
In the above embodiment, lectures have been described as an example of a place where education is provided to improve basic business skills, but other educational opportunities include training, seminars, workshops, lectures, etc.
In the above embodiment, the history of attending a course is used as an example of the education history, but other history may be used as well, and it is sufficient if it is an education history of a user who has participated in an educational event.

In the above embodiment, the user is suggested on their personal page that the recommended number of courses per year is two and that the recommended interval between courses is six months, but in addition, for example, when the service is introduced, a consultant or the like may communicate that the recommended number of courses per year is two. By communicating that the most effective number of courses per year is two, and that excessive course attendance or taking multiple courses at once is unlikely to produce the desired effect, it is possible to indirectly prevent users from taking excessive courses.
The user's personal attributes may include the user's past experience, career history, adaptability to evaluation factors, and other attributes that are not directly related to the course, such as the user's hobbies, personality, physical characteristics, family structure, and lifestyle.

In summary, the information processing apparatus to which the present invention is applied is sufficient if it has the following configuration, and can take on a variety of different embodiments.
That is, an information processing device to which the present invention is applied (for example, the server 10 in FIG. 3)
a proposal unit (e.g., the course recommendation unit 130 in FIG. 3 ) that proposes a future educational plan (e.g., a course plan) to improve the user's (e.g., a student's) business fundamentals based on a correspondence relationship (e.g., correlation) between an educational history (e.g., course attendance history {simultaneous course themes, number of courses taken in a predetermined period (year), interval between courses, etc.}) of the user (e.g., a student) who has participated in (attended) an educational event (e.g., a course, training, seminar, workshop, etc.) to improve the user's business fundamentals, the user's behavior after participating in the event (e.g., a course, etc.), and the evaluation result of the user's business fundamentals after participating in the event (e.g., an average score in all areas of the scoring results);
Equipped with.
In this way, by proposing a future education plan (e.g., a course plan) based on the education history of a user who has attended an educational setting (e.g., a course), the user's behavior after attending the setting (e.g., a course), and the evaluation results of the user's basic business skills after attending the setting (e.g., a course) (e.g., a change in score between one year ago and the current time), the user can participate (e.g., take) a setting (e.g., a course) at a frequency (e.g., number of simultaneous courses, number of courses taken, interval between courses, etc.) that is appropriate for them to acquire the skills they need and are sufficient for.
As a result, users can maintain an appropriate learning situation. Furthermore, service providers offering this training service can not only encourage users to take courses, but also discourage excessive learning or frequent learning in a short period of time. Furthermore, by maintaining an appropriate learning pace, users can use the service for a long time. This also allows service providers to promote continued use and maintain stable operation of the subscription model.

The user's behavior after participating in the event (e.g., a course) is as follows:
The information includes at least one of the following: the action completion rate after participating in the event (e.g., a course, etc.) (e.g., the rate at which an action is completed after attending a class, etc.), the completion rate of an additional assessment (e.g., a follow-up test), the percentage at which the user has carried out the specific action that they declared they will take starting tomorrow after participating in the event (e.g., a course, etc.) (e.g., the rate at which the user has carried out the specific action that they will take starting tomorrow, etc.), and the average score given as feedback by the administrator (e.g., a supervisor) who manages the user based on the user's learning status (e.g., the average score of feedback from others, etc.).
In addition to the evaluation of the business fundamentals diagnostic test conducted after the course, the system takes into consideration the user's behavior after participating in the event (e.g., a course, etc.), the results of additional evaluations, and the average feedback score from others (e.g., course administrators, superiors, etc.), and determines the user's level of achievement in reflective learning for the event (e.g., a course, etc.), their motivation, and the evaluations of others of the user's behavior, and creates a future education plan, which can propose a future education plan with an appropriate quantity (number of courses and intervals between courses) and quality (e.g., course topics, etc.) for the user.

The suggestion means
An educational plan (e.g., a training attendance plan on the My Page in Figure 7) is proposed that includes at least one of the following: the subject of the event (e.g., a course, etc.) to be attended (e.g., a course theme or a concurrent course theme, etc.), the number of times to attend the event (e.g., a course, etc.) in a specified period (e.g., a year, etc.) (e.g., the number of times to attend), and the interval between participation (e.g., the interval between attendance).
In this way, by suggesting to the user the subject (the subject of the course or the subject of simultaneous courses), the recommended number of times (e.g., recommended number of times, etc.) to participate in the event (e.g., a course, etc.) in a specified period (year), and the recommended interval between participation (e.g., recommended interval, etc.), the user will be able to participate in the event (e.g., a course, etc.) at a frequency appropriate for acquiring the skills necessary and sufficient for them.

1: Information processing device, 10: Server, 20, 20-1, 20-n: User terminal, 101: CPU, 106: Output unit, 107: Input unit, 108: Memory unit, 109: Communication unit, 121: Test creation unit, 122: Test question setting unit, 123: Answer acquisition unit, 124: Grading unit, 125: Scoring unit, 126: Score acquisition unit, 127: Comment creation unit, 128: Display control unit, 129: Learning management unit, 130: Course recommendation unit, 141: Question DB, 142: Grading result DB, 143: Population DB, 144: Course DB, 151: Course plan creation unit, 152: Proposal unit, 153: Alert unit, N: Network

Claims (5)

a proposal means for proposing to the user a future educational plan for improving the basic business skills based on a correspondence relationship between an educational history of the user who has participated in an educational event for improving the basic business skills, a behavioral state of the user after participating in the event, and an evaluation result of the basic business skills after participating in the event ,
The behavioral status includes an execution rate of a specific behavior that the user has declared to be undertaken in the future after participating in the event,
The suggestion means recommends participation in the next event when the execution rate is equal to or greater than a predetermined threshold.
Information processing device. The behavioral situation further includes:
The information includes at least one of an action completion rate after participating in the event, an additional evaluation completion rate, the number of actions participated in the event, and an average score of points fed back from the user's administrator according to the user's learning status.
The information processing device according to claim 1 . The education plan proposed by the suggestion means includes:
The information includes at least one of the theme of the event to be attended, the recommended number of times to attend the event in a predetermined period, and the recommended interval between participations .
3. The information processing device according to claim 1 or 2. An information processing method executed by an information processing device,
and a step of proposing to the user a future educational plan for improving the basic business skills based on a correspondence relationship between an educational history of the user who has participated in an educational event for improving the basic business skills, a behavioral state of the user after participating in the event, and an evaluation result of the basic business skills after participating in the event ,
The behavioral status includes an execution rate of a specific behavior that the user has declared to be undertaken in the future after participating in the event,
The step of suggesting includes a step of recommending participation in the next event when the execution rate is equal to or greater than a predetermined threshold.
Information processing methods. A computer that controls an information processing device
execute a control process including a step of proposing to the user a future educational plan for improving the user's business fundamentals based on a correspondence relationship between an educational history of the user who has participated in an educational event for improving the user's business fundamentals, the user's behavioral status after participating in the event, and an evaluation result of the user's business fundamentals after participating in the event;
The behavioral status includes an execution rate of a specific behavior that the user has declared to be undertaken in the future after participating in the event,
the step of suggesting includes a step of recommending participation in the next event when the participation rate is equal to or greater than a predetermined threshold;
program.