Learning support systems, methods, and programs

Abstract

This enables the suggestion of appropriate learning functions at the appropriate time for learners in online learning. [Solution] The learning support system includes a monitoring unit that measures the learning progress and learning behavior of a learner in online learning, a determination unit that identifies the learning functions that the learner should use as recommended learning functions based on the measured learning progress and learning behavior of the learner, and a recommendation unit that proposes the recommended learning functions to the learner when the learner's learning behavior meets predetermined conditions.

Description

Technical Field

[0001] This disclosure relates to a technology for assisting learning.

Background Art

[0002] In recent years, the number of people studying to obtain qualifications among students and working adults has been increasing. However, students are busy with schoolwork and part-time jobs, and working adults are overwhelmed by their daily work. It is difficult for both students and working adults to secure learning time for qualification acquisition. Therefore, e-learning, in which learners can take lectures or perform exercises using their personal computers (PCs) or smartphones during their spare time, has been spreading. In an e-learning system, lecture videos are distributed from a server to the learner's PC or smartphone via the Internet (see, for example, Patent Document 1). Various functions for improving the learning efficiency of users are provided in the e-learning system.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, as the e-learning system becomes more multifunctional, the user interface becomes complex and difficult for learners to use. Even if a detailed manual is prepared, learners find it troublesome to read the manual.

[0005] One object included in this disclosure is to provide a learning support system and a learning support method that enable the proposal of a suitable learning function at a suitable timing for a learner in online learning.

Means for Solving the Problems

[0006] A learning support system in one aspect included in this disclosure comprises: a monitoring unit that measures the learning progress and learning behavior of a learner in online learning; a determination unit that identifies learning functions that the learner should use as recommended learning functions based on the measured learning progress and learning behavior of the learner; and a recommendation unit that proposes the recommended learning functions to the learner when the learner's learning behavior meets predetermined conditions. [Effects of the Invention]

[0007] According to one aspect of this disclosure, it becomes possible to suggest suitable learning functions to learners at a suitable time in online learning. [Brief explanation of the drawing]

[0008] [Figure 1] This is a block diagram showing one example configuration of the overall system. [Figure 2] This is an example of a learning support system configuration. [Figure 3] This is an example of a hardware configuration for a learning support system. [Figure 4] This is a diagram to explain the learning progress-based course function. [Figure 5] This is a diagram illustrating additional functions for different learning behaviors. [Figure 6] This is a diagram illustrating additional features based on environmental preferences. [Figure 7] This figure shows an example of learning function management information. [Figure 8] This figure shows an example of user information. [Figure 9] This is a flowchart showing an example of the course proposal process. [Figure 10] This is a sequence diagram showing an example of the process of releasing the learning function. [Figure 11] This figure shows an example of the screen display for proposed method 1. [Figure 12] This figure shows an example of the display of screen (1) of proposed method 2. [Figure 13] It is a diagram showing an example of the display of the screen (2) of Proposal Method 2. [Figure 14] It is a diagram showing an example of the display of the screen (3) of Proposal Method 2. [Figure 15] It is a flowchart showing an example of the high-speed playback function proposal process. [Figure 16] It is a flowchart showing an example of the problem exercise strengthening function proposal process. [Figure 17] It is a flowchart showing an example of the flashcard automatic presentation function proposal process. [Figure 18] It is a flowchart showing an example of the action promotion function proposal process. [Figure 19] It is a flowchart showing an example of the learning management function proposal process. <00000�2>It is a flowchart showing an example of the additional function proposal process according to environmental preferences.

Embodiments for Carrying Out the Invention

[0009] An example of the learning support system of this embodiment will be described.

[0010] The learning support system is a system that supports e-learning (online learning) for providing various learning contents to learners online.

[0011] The learning contents are, for example, learning contents for learning targets of national qualifications such as real estate brokers, FP (Financial Planner), and administrative scriveners. Generally, in order to pass the national qualification examination, learners need to learn a huge amount, not only basic knowledge but also examination countermeasures for this examination. However, if learners start by looking at a huge amount of learning contents, there is a risk that their learning motivation will decrease. Therefore, the learning support system of this embodiment divides the learning contents and additional functions into a plurality of learning functions and sequentially releases the learning functions according to the learning progress and learning behavior of the learners. As a result, it is expected that learners will steadily level up and improve their academic ability efficiently.

[0012] <<System Configuration>>

[0013] FIG. 1 is a block diagram showing an example of the configuration of the entire system.

[0014] As shown in FIG. 1, the learning support system 1 is connected to the user terminal 2 via the network 100. The learning support system 1 may be, for example, a computer such as a server or a PC (Personal Computer), or a configuration combining these. The user terminal 2 is an information processing terminal operated by a learner who uses the learning content provided by the learning support system 1. The user terminal 2 is a smartphone, a tablet, or a PC. The network 100 is, for example, the Internet. Hereinafter, the learner may also be referred to as a user. FIG. 1 shows the case where there is one user terminal 1 connected to the learning support system 1, but a plurality of user terminals 1 are connected to the learning support system 1.

[0015] FIG. 2 is a block diagram showing an example of the configuration of the learning support system.

[0016] The learning support system 1 includes a storage device 11, a monitoring unit 12, a determination unit 13, a recommendation unit 14, a qualification management unit 15, and a billing processing unit 16.

[0017] The storage device 11 stores learning content D11, learning function management information D12, and user information D13. The learning content D11 is data such as text lectures and videos of various lectures. The learning function management information D12 is various management information regarding various learning functions. The learning functions include a lecture function for providing various lectures and additional functions for supporting learning. The learning functions are not initially open to the user, but learning functions that the user satisfies a predetermined acquisition condition are sequentially proposed and released by the user's judgment. The details of the learning functions and the learning function management information D12 will be described later. The user information D13 is various management information of each user 90. The details of the user information D13 will be described later.

[0018] The monitoring unit 12 measures the learning progress and learning behavior based on the records of course attendance and problem-solving practice performed by users 90 who utilize online learning content.

[0019] The determination unit 13 determines that a learning function whose learning progress or learning behavior meets the acquisition conditions is a recommended learning function that the user 90 should use. The acquisition conditions and the determination process will be described later.

[0020] The recommendation unit 14 proposes to user 90 a learning function that it has determined to be useful for the user 90. For example, the learning function and its usage fee are presented.

[0021] When the user 90 accepts the proposed learning function, the qualification management unit 15 makes the learning function available to the user 90 and updates the user information D13.

[0022] The billing unit 16 charges user 90 for the learning function made available to the user 90.

[0023] Figure 3 is a block diagram showing an example of the hardware configuration of a learning support system. The hardware of learning support system 1 is configured as a computer, as an example. Learning support system 1 comprises a processor 21, main memory 22, auxiliary memory 23, communication device 24, input device 25, and output device 26, which are interconnected via an internal bus 27.

[0024] The processor 21 is an arithmetic processing unit such as a CPU (Central Processing Unit), and functions as one of the components of the learning support system 1 according to this embodiment by executing software programs stored in the main memory 22 or auxiliary memory 23. For example, by the processor 21 executing software programs, some or all of the monitoring unit 12, determination unit 13, recommendation unit 14, qualification management unit 15, and billing processing unit 16 are realized. However, some or all of these components may be realized by dedicated circuits such as ASICs (Application Specific Integrated Circuits).

[0025] The main memory 22 is a volatile memory such as RAM (Random Access Memory) that temporarily stores the software program executed by the processor 21 and the data necessary for its processing.

[0026] The auxiliary storage device 23 is a non-volatile memory such as an HDD (Hard Disk Drive), SSD (Solid State Drive), or ROM (Read Only Memory), and it semi-permanently stores software programs and various data. In the learning support system 1, input data, used data, and generated data are recorded in the main memory device 22 and / or the auxiliary storage device 23.

[0027] The communication device 24 is a device that enables communication with external devices and services via a communication network (not shown). In this embodiment, for example, in the learning support system 1, the communication device 24 connects to the user terminal 2 via the network 100 and enables communication. When the learning support system 1 uses a generative artificial intelligence model as an external service, it uses the generative artificial intelligence model through communication via the communication device 24.

[0028] The input device 25 is an input device such as a keyboard, mouse, and touch panel operated by the user 90. In this embodiment, when an administrator (not shown) operates the learning support system 1, information from the administrator is input to the input device 25. The output device 26 is a display device that displays video, images, and text, such as a liquid crystal display. When the administrator operates the learning support system 1, information is displayed to the administrator on the output device 26. The input device 25 and output device 26 do not need to be provided unless the administrator directly operates the learning support system.

[0029] Furthermore, the learning support system 1 may be configured not only as a single computer, but also as a distributed system in which multiple computers work in cooperation. Additionally, part or all of the learning support system 1 may be built on the cloud.

[0030] Furthermore, the hardware configuration of user terminal 2 is basically the same as the configuration example described with reference to Figure 3, so a detailed explanation will be omitted.

[0031] <Learning Function>

[0032] The following explains the details of the learning function.

[0033] The learning functions include course functions, additional functions tailored to learning behaviors, and additional functions tailored to environmental preferences.

[0034] <Course Function>

[0035] Figure 4 is a diagram illustrating the course function based on learning progress.

[0036] As shown in Figure 4, the course function based on learning progress includes four functions: introductory course, basic course, past exam question course, and last-minute preparation course. Each course function consists of text, lectures, and tests.

[0037] The introductory course includes an introductory course textbook, video lectures, and a check test (true / false format). The introductory course is the first course that learners take when they begin studying for the qualification, and its purpose is to acquire basic knowledge.

[0038] The Basic Course includes a Basic Course Textbook, video lectures, and quizzes (true / false format) and past exam questions (in the format of the actual exam). The Basic Course is designed to deepen the knowledge acquired in the Introductory Course and to cultivate the fundamental skills necessary to answer questions on the actual exam.

[0039] The Past Exam Questions Course includes a textbook, video lectures on past exam questions, and quizzes (true / false format) and past exam questions (in the format of the actual exam). The Past Exam Questions Course uses questions from actual exams to help students learn about exam question trends and answering techniques.

[0040] The last-minute preparation course includes a textbook, video lectures, and practice questions (in the format of the actual exam). This course is taken in the period immediately before the actual exam and provides a final preparation for the exam.

[0041] Learning support system 1 provides courses in stages, from introductory courses to last-minute preparation courses, according to the learner's progress. Learning progress is determined from records of online lecture attendance and problem-solving practice for each course. This allows learners to progress at their own pace, according to their understanding and proficiency, enabling efficient improvement of their academic abilities.

[0042] <Additional functions based on learning behavior>

[0043] Figure 5 is a diagram illustrating additional functions for different learning behaviors.

[0044] As shown in Figure 5, additional functions for each learning behavior include a high-speed playback function, a new problem practice function, a practice time limit function, an automatic flashcard presentation function, a learning report function, a behavior promotion notification function, and an individualized instruction function.

[0045] The high-speed playback function allows for faster playback of subsequent lectures, improving the time efficiency of lecture viewing. When learners repeatedly watch the same lecture video, they already understand the content, so high-speed playback allows for more efficient review.

[0046] The new problem practice feature provides new problems to learners who have repeatedly practiced with past exam questions. These new problems are not past questions, but are separately created. Even if learners have memorized the answer patterns of past questions, the new problems allow for a proper assessment of their abilities and the development of their applied skills.

[0047] The practice time limit function sets a time limit for problem-solving exercises. This allows users to practice solving problems at a speed equivalent to that of the actual exam. However, for the first attempt, this function should not be used, as accuracy should be prioritized over speed. This allows learners to gradually develop time management skills for the actual exam.

[0048] The automatic flashcard presentation function automatically presents flashcards for information that the user is having trouble remembering, at timings based on the forgetting curve. These flashcards are learning content used in online learning, displaying questions and answers alternately for information to be memorized. By reviewing memorized information at the optimal timing according to the learner's level of retention, efficient memory retention can be achieved.

[0049] The learning report function automatically notifies learners of their learning progress from lecture videos and their performance on practice problems. This allows learners to objectively understand their own learning status and use it to reflect on their studies and plan for the future.

[0050] The action-prompting notification feature automatically notifies users of assignment deadlines, scheduled live lectures, recommended review times, and other important information. Recommended review times are determined based on, for example, the Spaced Repetition System (SRS). SRS is a method that gradually widens the intervals between reviews, allowing users to recall information at the optimal time just as they are beginning to forget, thus transferring it to long-term memory. It may also send reminders to encourage learning, such as, "You haven't reached your study time goal this week." This helps learners develop good study habits and promotes continuous learning.

[0051] The individualized instruction function manages learning progress and performance, and provides guidance on how to proceed with future learning. By suggesting optimal learning plans and areas to focus on based on each learner's level of understanding and progress, it enables efficient learning.

[0052] <Additional features based on environmental preferences>

[0053] Figure 6 is a diagram illustrating additional functions based on environmental preferences.

[0054] As shown in Figure 6, additional features based on environmental preferences include offline learning functions, avatar instructor functions, gamification functions, and community functions.

[0055] The offline learning function allows students to take courses without connecting to the learning system. This makes learning possible in locations with poor internet connectivity (such as trains or buses). By downloading lecture videos and learning materials in advance, learners can continue their studies even in environments without internet access.

[0056] The avatar instructor feature allows virtual instructors to deliver video lectures. Learners can select avatar instructors according to their preferences, providing a more user-friendly learning environment.

[0057] Gamification features incorporate game elements into learning. These include point and badge features, leaderboard features, and reward features. The point and badge feature awards points or badges for completing specific tasks (e.g., "scoring 80% or higher on a practice test" or "studying for 7 consecutive days"). The leaderboard feature ranks learners based on study time or points earned. The reward feature allows learners to exchange earned points for special lecture videos or learning materials. These game elements can increase learner motivation and encourage continuous learning.

[0058] The community function allows learners to form communities on social networking services (SNS) and exchange opinions with each other. By sharing questions and learning methods with other learners, feelings of isolation can be reduced and motivation for learning can be maintained.

[0059] <Managing Learning Functions>

[0060] The learning support system 1 manages each learning function using learning function management information D12 and proposes learning functions to learners for which the learner has met the acquisition conditions.

[0061] Figure 7 shows an example of learning function management information D12.

[0062] As shown in Figure 7, the learning function management information D12 includes the following items: function ID, function name, acquisition conditions, and fee (yen). The function ID is an identifier that uniquely identifies each learning function. The function name is the name of each learning function. The acquisition conditions are the conditions that user 90 must meet in order to receive a proposal for the learning function. The fee (yen) is the usage fee for the learning function.

[0063] The learning functions with function IDs FT01-1 to FT01-4 are learning progress-based course functions. The introductory course (FT01-1) has no acquisition conditions set and is available from the start when user 90 begins learning. The basic course (FT01-2) is suggested when the completion rate of the introductory course reaches 70% or higher. The past exam questions course (FT01-3) is suggested when the completion rate of the basic course reaches 70% or higher. The last-minute preparation course (FT01-4) is suggested when the completion rate of the past exam questions course reaches 80% or higher. In this way, the learning progress-based course functions are suggested in stages according to user 90's learning progress. Note that this example shows how to define acquisition conditions by completion rate, but acquisition conditions may be defined by other indicators. For example, acquisition conditions may be defined by the amount of learning content taken or the score of tests taken. The same applies below.

[0064] The learning functions with function IDs FT02-1 to FT02-7 are additional functions based on learning behavior. The high-speed playback function (FT02-1) requires that the course has been taken at normal speed as a condition for acquisition. The new problem practice function (FT02-2) requires that the problem practice has been completed n times as a condition for acquisition. n should be set to an appropriate value depending on how many times the practice problems need to be completed for them to be retained in memory. For example, it may be possible to enable practice with new problems after completing past problem practice 3 times. The practice time limit function (FT02-3) requires that the problem practice has been completed m times as a condition for acquisition. m should be set to an appropriate value depending on how many times the practice problems need to be completed before moving on to practicing under the same time constraints as the actual exam. For example, it may be possible to enable setting a time limit after completing past problem practice 3 times. The automatic flashcard presentation function (FT02-4) requires, as an example, that the correct answer rate for memorization questions is less than 70% as a condition for acquisition. The learning report function (FT02-5) requires that learning progress is behind schedule. The behavioral promotion notification function (FT02-6) requires that the user's performance rate for a given learning behavior be 90% or higher to be activated. The individualized instruction function (FT02-7) requires that the user's learning progress is behind schedule. In this way, additional functions for each learning behavior are suggested according to the user's learning behavior.

[0065] The learning functions with function IDs FT03-1 to FT03-4 are environment-specific add-on functions. The offline learning function (FT03-1), avatar instructor function (FT03-2), gamification function (FT03-3), and community function (FT03-4) do not have any acquisition conditions set and can be used according to the user's wishes.

[0066] <User Information Management>

[0067] The learning support system 1 manages the learning functions used by each user 90 and their learning progress based on user information D13.

[0068] Figure 8 shows an example of user information D13.

[0069] As shown in Figure 8, user information D13 includes the following items: learning course, user ID, name, available learning functions, start date, learning progress, and payment method. The learning course indicates the type of qualification exam. In the example in Figure 8, the learning course is listed as Real Estate Transaction Specialist. The user ID is an identifier that uniquely identifies each user 90. The name is the name of user 90. Available learning functions are the function IDs of the learning functions that have already been made available to user 90. The start date is the date when user 90 started learning. Learning progress indicates the progress of user 90 in each course. The payment method is how user 90 pays for the learning functions.

[0070] The first row of Figure 8 shows an example for Ichiro Suzuki, whose user ID is UTID01. FT01 is recorded as an available learning function. The course start date is January 3, 2026. The learning progress is recorded as 50% completion of the introductory course.

[0071] The second row of Figure 8 shows an example for Jiro Tanaka, whose user ID is UTID02. FT01-1 and FT01-2 are recorded as available learning functions. The course start date is November 30, 2025. Learning progress is recorded as 80% completion of the introductory course and 10% completion of the basic course.

[0072] In this embodiment, although not shown in Figure 8, user information D13 manages the number of times each user 90 has taken video lectures for each course, the number of times they have completed problem-solving exercises for problem-solving courses, the analysis results of the learning and problem-solving exercises, and the number of times they have taken the actual exam (or whether they are a beginner or not).

[0073] Thus, user information D13 manages the unlock status of learning functions for each user 90, indicating whether or not they are unlocked, and the learning progress, indicating how far the user has progressed in completing unlocked courses. In addition, the unlock status of additional functions is also managed. By referring to user information D13, the learning support system 1 can understand the learning status of each user 90 and suggest appropriate learning functions at the appropriate time.

[0074] <<System Operation>>

[0075] <Course proposal>

[0076] This section describes the operation of each process in the learning support system 1.

[0077] Figure 9 is a flowchart showing an example of the course suggestion process. The course suggestion process is in which the learning support system 1 suggests appropriate courses according to the user 90's learning progress.

[0078] First, the determination unit 13 refers to user information D13 to determine whether the user 90 is a beginner (step S101). A beginner is defined as a user 90 who is studying for the qualification for the first time. Beginners need to have functions added in stages as their learning progresses. On the other hand, students in their second year or later have exam experience, so they do not need to have courses added in stages, and all courses can be unlocked from the beginning.

[0079] If it is determined in step S101 that the user is a beginner (S101: Yes), the determination unit 13 determines whether the only unlocked courses are introductory courses (step S102). If the only unlocked courses are introductory courses (S102: only introductory courses), the determination unit 13 determines whether the enrollment rate for introductory lectures is 70% or higher (step S103). If the enrollment rate for introductory lectures is 70% or higher (S103: Yes), the recommendation unit 14 suggests a basic course (step S104). This allows learners to easily find out when and which courses to take, enabling them to learn efficiently. If the enrollment rate for introductory lectures is less than 70% (S103: No), the process ends.

[0080] If the unlocked courses in step S102 are the introductory course and the basic course (S102: introductory course + basic course), the determination unit 13 determines whether the attendance rate for the basic course is 70% or higher (step S105). If the attendance rate for the basic course is 70% or higher (S105: Yes), the recommendation unit 14 suggests the past exam questions course (step S106). If the attendance rate for the basic course is less than 70% (S105: No), the process ends.

[0081] If the unlocked courses in step S102 are the introductory course, the basic course, and the past exam questions course (S102: introductory course + basic course + past exam questions course), the judgment unit 13 determines whether the attendance rate for the past exam questions lecture is 80% or higher (step S107). If the attendance rate for the past exam questions lecture is 80% or higher (S107: Yes), the recommendation unit 14 suggests the last-minute course (step S108). If the attendance rate for the past exam questions lecture is less than 80% (S107: No), the process ends.

[0082] On the other hand, if it is determined in step S101 that user 90 is not a beginner (S101: No), then because user 90 has experience taking the exam, all courses are released and the process ends without providing step-by-step suggestions.

[0083] In this way, the course suggestion process sequentially suggests courses in multiple stages according to the learner's progress. This allows learners to select the next course to use at the appropriate time, enabling them to proceed with efficient learning.

[0084] <Release of learning function>

[0085] Figure 10 is a sequence diagram showing an example of the learning function release process. The learning function release process is a process in which the learning support system 1 proposes a learning function to the user 90, obtains the user 90's consent, and releases the learning function.

[0086] First, the learning support system 1 sends a suggestion of learning functions to the user terminal 2 (step S201). This suggestion includes information about recommended learning functions that the user 90 should use, which has been determined by the aforementioned course suggestion process and high-speed playback function suggestion process.

[0087] Next, user terminal 2 displays the learning function and its cost (step S202). The screen of user terminal 2 displays the content of the proposed learning function along with the usage fee for that learning function. This allows user 90 to confirm the details and cost of the proposed learning function.

[0088] If user 90 wishes to use the proposed learning function, user terminal 2 sends information to learning support system 1 indicating that it accepts the release of the learning function (step S203).

[0089] When the qualification management unit 15 of the learning support system 1 receives the acceptance information, it releases the learning function to the user 90 (step S204). Subsequently, the qualification management unit 15 updates the user's function information (S205). Specifically, the function ID of the newly released learning function is added to the item of released learning functions for the user 90 in the user information D13.

[0090] Subsequently, a process utilizing the learning function is executed between the user terminal 2 and the user support system 1 (step S206). User 90 can then perform learning using the now-available learning function.

[0091] Finally, the billing processing unit 16 of the learning support system 1 executes the billing process for the learning function (step S207). The billing processing unit 16 charges the user 90 for the fee of the unlocked learning function.

[0092] Thus, in the learning function release process, when user 90 accepts the proposed learning function, the learning function is released to user 90 and user information D13 is updated. This makes it possible to propose the use of a suitable learning function to the learner at an appropriate time identified based on the learner's learning behavior, and based on the learning progress and learning behavior, making it possible to propose a suitable learning function to the learner at an appropriate time in online learning.

[0093] <Screen display example 1>

[0094] Figure 11 shows an example of the screen display for proposed method 1. Proposed method 1 is a method of suggesting learning functions via a pop-up screen.

[0095] As shown in Figure 11, the screen of user terminal 2 displays Mr. Tanaka's My Page for the ○○ Qualification Correspondence Course. A logout button is located at the top of the screen. On the left side of the screen, there are buttons indicating the course status and completion rate bars for each course: Introductory, Basic, Past Questions, and Direct Preparation. In the example in Figure 11, the completion rate bar for the Introductory course is hatched with diagonal lines, visually indicating that the completion rate is approximately 70%. Here, as shown in Figure 7, the acquisition requirement for the Basic course is set to a completion rate of 70% or higher for the Introductory lectures, so the acquisition requirement for the Basic course has been met. The completion rate bars for Basic, Past Questions, and Direct Preparation are blank, indicating that these courses have not yet been taken. A back button is located at the bottom of the screen.

[0096] A pop-up window is displayed in the center of the screen. As mentioned above, the conditions for obtaining the basic course have been met, so the pop-up window displays the heading "Recommended features for Tanaka" along with the suggestion "Basic course (¥xxxx)". An "x" button is located in the upper right corner of the pop-up window, allowing user 90 to close the pop-up window without accepting the basic course. An "accept" button is located in the lower right corner of the pop-up window. When user 90 presses the accept button, the process of accepting the release of the learning function, as shown in step S203 of Figure 10 above, is executed.

[0097] Thus, in Proposal Method 1, when user 90 is browsing their My Page, if there is a recommended learning function to suggest, the learning function and its fee will be displayed via a pop-up screen. This allows user 90 to check their own learning progress, understand the content and cost of the suggested learning function, and decide whether or not to use it.

[0098] <Screen display example 2>

[0099] Figures 12 to 14 show examples of screen displays for proposed method 2. Proposed method 2 is a method in which learning functions recommended to user 90 are displayed step by step on the My Page screen of user terminal 2, and users 90 are made to accept and accept the proposed learning functions according to their actions.

[0100] First, Figure 12 shows an example of the initial screen display in proposed method 2. As shown in Figure 12, the screen of user terminal 2 displays Mr. Tanaka's My Page for the ○○ Qualification Correspondence Course. At the top of the screen are the course name display area and the logout button. On the left side of the screen, there are buttons to take the course and attendance rate bars showing the attendance rate for each course: Introductory, Basic, Past Questions, and Last-Minute Preparation. In the example in Figure 12, the attendance rate bar for the Introductory course is hatched with diagonal lines, indicating that the attendance rate for the Introductory course is about 60%. Therefore, although the requirements for obtaining the Basic course have not been met, it can be said that the attendance rate for the Introductory course is approaching the requirements for obtaining the Basic course. On the other hand, the attendance rate bars for the Basic course, Past Questions course, and Last-Minute Preparation course are blank, indicating that the courses have not yet started.

[0101] At the bottom of the screen in Figure 12, there is a display area for recommended learning functions for user 90, labeled "Recommended functions for Tanaka." At this stage, the basic course is the recommended option, but it is enclosed in a dashed frame because the acquisition conditions have not yet been met. This display appears as a result of the recommendation unit 14 notifying user terminal 2 of learning functions for which user 90's learning progress is approaching the acquisition conditions.

[0102] Next, Figure 13 shows an example of the screen display after further progress in the introductory course from the state shown in Figure 12. The completion rate bar for the introductory course is hatched with diagonal lines, indicating that the completion rate for the introductory course is approximately 70%. Therefore, the conditions for obtaining the basic course have been met. As a result, the basic course is recommended and, since the conditions for obtaining it have been met, it is displayed surrounded by a solid line frame. User 90 can select the basic course displayed in the recommendation display area. When User 90 selects the displayed basic course, the display changes to the one shown in Figure 14.

[0103] Figure 14 shows an example of a pop-up screen displaying detailed suggestions for a basic course. As shown in Figure 14, a pop-up screen is displayed in the center of the screen with the heading "Recommended features for Mr. / Ms. Tanaka," along with the name of the basic course and the usage fee for that course. This pop-up screen has an accept button and a button to close it. When user 90 presses the accept button, the processes from step S203 onwards in the learning function release process shown in Figure 10 are executed, and the qualification management unit 15 releases the basic course to user 90.

[0104] Thus, in proposal method 2, recommended learning functions are displayed on the user's My Page screen according to the user's learning progress, and detailed suggestions and acceptance operations are performed step by step according to the user's actions. This allows user 90 to check the suggested learning functions and their costs at a time that suits them, without interrupting the learning process, and to decide whether or not to use them.

[0105] <High-speed playback function proposal>

[0106] Figure 15 is a flowchart showing an example of the process for suggesting the high-speed playback function. The high-speed playback function suggestion process is a process in which the learning support system 1 focuses on the user 90's behavior when taking lecture videos and suggests the use of the high-speed playback function at a time when it is determined that using the high-speed playback function would be beneficial for the user 90.

[0107] First, the learning support system 1 detects that user 90 has performed an operation to begin watching a lecture video (step S301). For example, this action of starting to watch a lecture video is detected when the user terminal 2 performs an operation to play the lecture video.

[0108] Next, the determination unit 13 determines whether or not the user is taking the lecture video for the second time or later (step S302). Here, taking the lecture for the second time or later means that, based on the attendance history recorded in user information D13, the user has taken the same lecture video at least once in the past. If it is the first time taking the lecture, the high-speed playback function is not suggested, as understanding the learning content should be prioritized, and this process ends.

[0109] If it is determined in step S302 that this is the user's second or subsequent course, the determination unit 13 determines whether the high-speed playback function has already been made available to the user 90 (step S303). If the high-speed playback function has already been made available, the user 90 can use the function, so no further suggestions are made, and this process ends.

[0110] On the other hand, if it is determined in step S303 that the high-speed playback function is not enabled, the recommendation unit 14 proposes to the user 90 that they use the high-speed playback function (step S304). This proposal is made, for example, by displaying the details of the high-speed playback function and the usage fee on the screen of the user terminal 2 using the proposal method 1 described above.

[0111] Thus, the high-speed playback function proposal process focuses on the timing of the learner's action, namely the start of viewing a lecture video, and proposes the high-speed playback function only when the same lecture video is being viewed repeatedly. This allows the high-speed playback function to be presented at an appropriate time to learners who have already grasped the learning content, enabling them to efficiently review the lecture. As a result, learners can reduce the time required for review and continue learning while effectively utilizing their study time.

[0112] Furthermore, since the system is designed not to suggest the high-speed playback function during the first lesson, it can provide appropriate learning support according to the learner's stage of learning without hindering their understanding.

[0113] <Proposal for problem practice enhancement function>

[0114] Figure 16 is a flowchart showing an example of the process for suggesting the problem-solving practice enhancement function. The problem-solving practice enhancement function suggestion process is a process in which the learning support system 1 focuses on the user 90's progress in solving problems and suggests the use of the problem-solving practice enhancement function when it is determined that enhancing the problem-solving practice would be effective for the user 90.

[0115] First, the learning support system 1 detects that user 90 has performed an operation to start the problem exercise (step S401). For example, the action of starting the problem exercise is detected when the operation to start the problem exercise is performed on user terminal 2.

[0116] Next, the determination unit 13 determines whether or not the problem practice has been performed for the nth time or later (step S402). Here, whether or not it has been performed for the nth time or later is determined based on the number of times the problem practice has been performed recorded in user information D13. If the number of times the problem practice has been performed is less than n, the learner should first prioritize basic practice using past questions, so the problem practice enhancement function is not suggested, and this process ends.

[0117] If it is determined in step S402 that it is the nth time or later, the determination unit 13 determines whether the new problem practice function has already been made available to the user 90 (step S403). If the new problem practice function has not been made available, the recommendation unit 14 proposes to the user 90 that they be provided with problem practice using new problems that are different from past questions (step S404). These new problems are not questions that have been asked in past exams, but are questions that have been created separately.

[0118] Next, the determination unit 13 determines whether the exercise time limit function has already been released for the user 90 (step S405). If the exercise time limit function has not been released, the recommendation unit 14 suggests to the user 90 that a time limit be set for the exercises (step S406). This suggestion is displayed on the screen of the user terminal 2, for example, by suggestion method 1 described above.

[0119] Thus, the problem-solving practice enhancement function proposal process focuses on the timing of the learner's action, namely the start of problem-solving practice, and progressively proposes new problem-solving practice functions and practice time limit functions to learners who have repeatedly performed problem-solving practice more than a predetermined number of times. This allows learners who have memorized the answer patterns of past questions to have their abilities assessed with new questions, and furthermore, practice with a time limit allows them to practice under conditions similar to the actual exam.

[0120] As a result, it becomes possible to provide practice problems tailored to the learner's level of understanding and proficiency, thereby enhancing the learning effect of practice problems and gradually improving their ability to cope with the actual exam.

[0121] <Proposal for an automatic flashcard presentation function>

[0122] Figure 17 is a flowchart showing an example of the process for suggesting the automatic flashcard presentation function. The automatic flashcard presentation function suggestion process is a process in which the learning support system 1 determines whether there are any areas where the user 90 has difficulty memorizing based on the results of the problem practice exercises, and suggests the use of the automatic flashcard presentation function if it is determined that memorization support would be effective.

[0123] First, the learning support system 1 detects that user 90 has performed an operation to end the problem exercise (step S501). For example, the termination of this problem exercise is detected when the user terminal 2 performs an operation to end the problem exercise.

[0124] Next, the determination unit 13 determines whether or not there are areas in the practice problems where the user has difficulty memorizing (step S502). Here, whether or not the user has difficulty memorizing is determined based on the correct answer rate of questions that can be answered correctly if the memorized items are memorized. If the correct answer rate of the memorization questions is below a predetermined standard, the user 90 is determined to have difficulty memorizing.

[0125] If it is determined in step S502 that the user has difficulty memorizing, the determination unit 13 determines whether the automatic flashcard presentation function has already been made available to the user 90 (step S503). If the automatic flashcard presentation function has already been made available, the user 90 can use the function, so no further suggestions are made, and this process ends.

[0126] On the other hand, if it is determined in step S503 that the automatic flashcard presentation function is not enabled, the recommendation unit 14 suggests to the user 90 that they use the automatic flashcard presentation function, which automatically presents flashcards based on the forgetting curve (step S504). This suggestion is made by displaying the details of the automatic flashcard presentation function and its usage fee on the screen of the user terminal 2 using either suggestion method 1 or suggestion method 2 described above.

[0127] Thus, the process for proposing the automatic flashcard presentation function focuses on a natural stopping point for learners, such as the end of a problem-solving exercise, and proposes the automatic flashcard presentation function only when the correct answer rate for memorized items is low. This allows learners to review items they struggle with at an optimal timing based on the forgetting curve.

[0128] As a result, learners can efficiently review memorized information, promoting knowledge retention while naturally continuing review behavior without disrupting the learning process.

[0129] <Proposal for action promotion notification function>

[0130] Figure 18 is a flowchart showing an example of the process for suggesting the behavioral guidance notification function. The behavioral guidance notification function suggestion process is a process in which the learning support system 1 focuses on the user 90's daily learning activities and suggests the use of the behavioral guidance notification function when it determines that the learning activities are not being performed at the appropriate time.

[0131] First, the learning support system 1 detects that user 90 has performed an operation to end the day's learning (step S601). For example, this action of ending the day's learning is detected when an operation to end the day's learning is performed on user terminal 2.

[0132] Next, the determination unit 13 determines whether the user 90 is performing learning activities in a timely manner (step S602). Here, whether or not learning activities are performed in a timely manner is determined based on whether the submission of assignments, attendance at live lectures, and review are each performed at appropriate times within the predetermined time.

[0133] If it is determined in step S602 that the learning behavior was not performed in a timely manner, the determination unit 13 determines whether the behavior-promoting notification function has already been made available to the user 90 (step S603). If the behavior-promoting notification function has already been made available, the user 90 can use the function, no further suggestions are made, and this process ends.

[0134] On the other hand, if it is determined in step S603 that the action prompt notification function is not enabled, the recommendation unit 14 proposes to the user 90 that they use the action prompt notification function (step S604). This proposal is made, for example, by displaying the details of the action prompt notification function and its usage fee on the screen of the user terminal 2 using the proposal method 1 described above.

[0135] Thus, the action-promoting notification function proposal process focuses on the natural timing of completing a day's learning, and proposes the action-promoting notification function only if the learning behavior is not being performed at the appropriate time. This allows for the identification of learning delays or interruptions without excessive notifications to the learner, and effectively promotes future learning behavior.

[0136] As a result, learners can more easily review their own learning rhythms, which helps support them in continuing their learning.

[0137] <Proposed Learning Management Function>

[0138] Figure 19 is a flowchart showing an example of the learning management function suggestion process. The learning management function suggestion process is a process in which the learning support system 1 focuses on the learning progress of user 90 and suggests the use of the learning management function if it determines that the learning is not progressing according to plan.

[0139] First, the learning support system 1 detects that user 90 has performed an operation to end the day's learning (step S701). For example, this action of ending the day's learning is detected when an operation to end the day's learning is performed on user terminal 2.

[0140] Next, the determination unit 13 determines whether the user 90's learning is progressing according to plan (step S702). Here, whether the learning is progressing according to plan is determined based on whether the discrepancy between the learning schedule set as the target and the actual learning progress is within a predetermined range.

[0141] If it is determined in step S702 that the learning is not progressing according to plan, the determination unit 13 determines whether the learning report function has already been made available to the user 90 (step S703). If the learning report function has not been made available, the recommendation unit 14 suggests to the user 90 that they use the learning report function (step S704).

[0142] The learning report function presents learning records, including information on the date each lecture video in a lecture course (which consists of multiple lecture videos) was taken, and learning notifications, including the results for each session of a practice course (which consists of multiple practice exercises), at predetermined times. This allows learners to objectively understand their own learning progress and reflect on their learning.

[0143] Next, the determination unit 13 determines whether the individual tutoring function has already been made available to the user 90 (step S705). If the individual tutoring function has not been made available, the recommendation unit 14 suggests to the user 90 that they use the individual tutoring function (step S706).

[0144] The individualized instruction function is a function that suggests to the user 90 how to proceed with future learning based on at least one of the learning record and the performance. This makes it possible to provide instruction that is tailored to each learner's level of understanding and progress. For example, if the learning record shows that the user is behind in attending lectures, the user terminal 2 may be notified with a suggestion to speed up the pace of attending lectures as a way to proceed with future learning. Also, if the user's performance in problem-solving exercises is poor in a particular area, the user terminal 2 may be notified with a suggestion to strengthen their learning in that area as a way to proceed with future learning.

[0145] In this way, the learning management function suggestion process focuses on the natural timing of completing a day's learning, and only suggests the learning report function and individual tutoring function in stages if learning is not progressing according to plan. This allows learners to visualize their own learning status and make appropriate reflections and revisions to their future learning plans.

[0146] As a result, learners will be able to maintain a planned learning approach, correct any learning delays early on, and progress through their studies efficiently.

[0147] <Proposals for additional functions tailored to environmental preferences>

[0148] Figure 20 is a flowchart showing an example of the process for suggesting additional functions based on environmental preferences. The process for suggesting additional functions based on environmental preferences is a process in which the learning support system 1 focuses on the usage status of user 90 and suggests the use of additional functions based on environmental preferences when it is determined that using additional functions according to the learning environment or preferences would be effective.

[0149] First, the learning support system 1 detects when user 90 starts using the learning support system 1, or when user 90 has continued using it for a certain period of time (step S801). This certain period of time is set, for example, when a predetermined number of days have passed since the start of learning, or when a predetermined number of logins have been made.

[0150] Next, the determination unit 13 determines whether or not the environment preference-based additional functions have already been made available to the user 90 (step S802). The environment preference-based additional functions include offline learning functions, avatar instructor functions, gamification functions, and community functions.

[0151] In step S802, if it is determined that none of the environment preference-based additional functions are available, the recommendation unit 14 proposes to the user 90 that they use that environment preference-based additional function (step S803). This proposal is made, for example, by displaying the content and usage fee of the environment preference-based additional function on the screen of the user terminal 2 using the proposal method 1 described above.

[0152] On the other hand, if it is determined in step S802 that all environmental preference-based additional functions have already been unlocked, no new suggestions will be made, and this process will terminate.

[0153] Thus, the process of suggesting additional features based on environmental preferences focuses on key learning milestones, such as the start of learning or after a certain period of use, and proposes the use of additional features based on environmental preferences. This makes it possible to flexibly arrange or enhance online learning according to the learner's learning environment and preferences.

[0154] As a result, learners can more easily continue their studies in a way that suits their living environment and learning style, enabling them to continue learning without undue strain and maintain their motivation.

[0155] The embodiments described above are illustrative for illustrating the present invention and are not intended to limit the present invention to those described herein. Those skilled in the art can implement the present invention in various other forms without departing from the scope of the present invention.

[0156] Furthermore, the embodiments described above include the following items. However, the items included in these embodiments are not limited to those listed below.

[0157] (Item 1)

[0158] The learning support system includes a monitoring unit that measures the learner's learning progress and learning behavior in online learning, a determination unit that identifies recommended learning functions based on the measured learning progress and learning behavior of the learner, and a recommendation unit that proposes the recommended learning functions to the learner when the learner's learning behavior meets predetermined conditions. This allows for learning support that proposes suitable learning functions to learners at suitable times in online learning, by suggesting the use of suitable learning functions identified based on learning progress and learning behavior at suitable timings identified based on the learner's learning behavior.

[0159] (Item 2)

[0160] In the learning support system described above, the learning function includes a course consisting of multiple lecture videos, and the determination unit determines which course to recommend based on the learner's learning progress. As a result, since courses are suggested based on the learning progress, learners can easily find out when and which courses to take, and can proceed with efficient learning.

[0161] (Item 3)

[0162] In the learning support system described above, the courses include multiple levels ranging from basic content to content geared towards exam preparation. The determination unit determines that the next level of course should be the recommended learning function course once the learner has completed a predetermined percentage or quantity of courses at a predetermined level. This allows the learner to sequentially suggest courses at multiple levels in accordance with their progress, enabling them to select the next course to use at an appropriate time and to proceed with efficient learning.

[0163] (Item 4)

[0164] In the learning support system described above, the learning function includes an additional function to improve the learner's learning efficiency, and the determination unit determines which additional function to recommend based on the learner's learning behavior. As a result, since the additional function is determined based on the learner's learning behavior, learning support can be provided according to the learner's learning style and learning situation, thereby improving learning efficiency.

[0165] (Item 5)

[0166] In the learning support system described above, the additional function is a high-speed playback function that plays lecture videos at high speed, and the determination unit determines that the high-speed playback function is an additional function that is a recommended learning function if the learner has taken the lecture video a predetermined number of times or more. According to this, the high-speed playback function is suggested according to the number of times the lecture video has been taken, so learners who have grasped the learning content can review efficiently and reduce learning time.

[0167] (Item 6)

[0168] In the learning support system described above, the recommendation unit suggests using the high-speed playback function at the moment the learner takes action to begin watching the lecture video. This means that the high-speed playback function is suggested in accordance with the learner's action of starting to watch the lecture video, making it easier for the learner to become aware of the function's existence and naturally encouraging its use.

[0169] (Item 7)

[0170] In the learning support system described above, the additional function is a problem-solving practice enhancement function, and the determination unit determines that the problem-solving practice enhancement function is an additional function designated as the recommended learning function if the learner has taken the problem-solving practice a predetermined number of times or more. According to this, since the problem-solving practice enhancement function is determined based on the progress of the problem-solving practice, it is possible to provide practice exercises that match the learner's level of understanding and proficiency, thereby improving the learning effect.

[0171] (Item 8)

[0172] In the learning support system described above, the problem practice enhancement function includes a new problem practice function that provides new problems to the problem practice. By providing new problems, learners can develop applied and practical skills without relying on memorizing past problems.

[0173] (Item 9)

[0174] In the learning support system described above, the problem practice enhancement function includes a time limit function that sets a time limit for problem practice. By setting a time limit for problem practice, it is possible to practice with a sense of tension similar to that of the actual exam, thereby improving the ability to cope with the actual exam.

[0175] (Item 10)

[0176] In the learning support system described above, the recommendation unit proposes the problem-solving practice enhancement function at the time the learner takes action to begin taking the problem-solving practice. As a result, since the problem-solving practice enhancement function is proposed in response to the learner's action of starting the problem-solving practice, it is possible to promote the use of the practice function at an appropriate time without hindering the learner's motivation.

[0177] (Item 11)

[0178] In the learning support system described above, the additional function is an automatic flashcard presentation function that presents items to be memorized to the learner at a predetermined time, and the judgment unit determines that the automatic flashcard presentation function is an additional function designated as the recommended learning function based on the correct answer rate of questions in the practice problems that can be answered correctly if the items to be memorized have been memorized. According to this, since the automatic flashcard presentation function is determined based on the correct answer rate of questions related to the items to be memorized, learners can efficiently review items they find difficult to memorize, and knowledge retention can be promoted.

[0179] (Item 12)

[0180] In the learning support system described above, the recommendation unit suggests using the automatic flashcard presentation function at the time the learner takes action to complete the problem-solving exercise. This suggests that the automatic flashcard presentation function is suggested at a natural stopping point, such as the completion of the problem-solving exercise, thus naturally encouraging review without disrupting the learning flow.

[0181] (Item 13)

[0182] In the learning support system described above, the additional function is an action-promoting notification function that gives learners notifications to encourage them to take action. The determination unit determines, based on the learner's learning behavior, whether the learner is taking learning actions at the appropriate time. If the learner is not taking learning actions at the appropriate time, the determination unit determines that the action-promoting notification function is an additional function that serves as the recommended learning function. This allows for the determination of whether the learner is taking learning actions at the appropriate time based on their learning behavior, thereby enabling early detection of learning delays or interruptions and supporting the continuation of learning.

[0183] (Item 14)

[0184] In the learning support system described above, the recommendation unit proposes the action-promoting notification function at the time the learner completes their daily learning. As a result, since the action-promoting notification function is proposed at the end of the day's learning, it is possible to effectively promote future learning activities without providing excessive notifications to the learner.

[0185] (Item 15)

[0186] In the learning support system described above, the additional function is a learning management function for managing the learner's planned learning. The determination unit determines whether the learning is progressing according to plan based on the learner's learning behavior, and if the learning is not progressing according to plan, it determines that the learning management function is an additional function that is the recommended learning function. As a result, since it determines whether the learning is progressing according to plan based on the learning behavior, it is possible to visualize the learner's learning status and support planned learning.

[0187] (Item 16)

[0188] In the learning support system described above, the learning management function includes a learning report function that presents learning notifications at predetermined times, which include at least one of the following: a learning record containing information on the date each lecture video in a lecture course consisting of multiple lecture videos was taken, and the grade for each session of a practice course consisting of multiple practice exercises. As a result, since learning notifications containing learning records and practice results are presented at predetermined times, learners can objectively grasp their own learning status and easily reflect on their learning.

[0189] (Item 17)

[0190] In the learning support system described above, the learning management function includes an individualized guidance function that suggests how to proceed with future learning based on at least one of the following: a learning record that includes information on the date each lecture video in a lecture course consisting of multiple lecture videos was taken, and the results of each session in a practice course consisting of multiple practice exercises. This allows for guidance tailored to each learner's level of understanding and progress, thereby improving learning efficiency, as the system suggests how to proceed with future learning based on the learning record and practice results.

[0191] (Item 18)

[0192] In the learning support system described above, the learning function includes an environment preference-based additional function that arranges or enhances the online learning to suit the learner's learning environment or preferences. This allows the learning to be arranged or enhanced according to the learner's learning environment and preferences, making it easier for learners to continue learning without difficulty and helping to maintain and improve their motivation to learn.

[0193] (Item 19)

[0194] The learning support method involves a computer measuring the learner's learning progress and learning behavior in online learning, identifying recommended learning functions based on the measured learning progress and learning behavior of the learner, and proposing the recommended learning functions to the learner when the learner's learning behavior meets predetermined conditions.

[0195] (Item 20)

[0196] The learning support program measures the learner's learning progress and learning behavior in online learning, identifies recommended learning functions based on the measured learning progress and learning behavior, and proposes these recommended learning functions to the learner when the learner's learning behavior meets predetermined conditions. [Explanation of Symbols]

[0197] 1…Learning support system 2…User terminal 11...Storage device 12...Monitoring Department 13…Judgment section 14…Recommendation Department 15…Qualification Management Department 16…Billing Processing Unit 21… Processor 22…Main memory 23…Auxiliary storage device 24...Communication equipment 25…Input device 26…Output device 27...Internal bus 90...User

Claims

1. A monitoring unit that measures the learning progress of learners in online learning and detects predetermined learning operations, A determination unit that identifies a learning function that the learner should use as a recommended learning function based on at least one of the measured learning progress of the learner and the detected learning operation, A recommendation unit proposes the recommended learning function to the learner at the timing triggered by the detection of the aforementioned learning operation, It has, As a learning function, there is a high-speed playback function that plays lecture videos at high speed. The determination unit determines that the high-speed playback function is the recommended learning function if the learner has taken the lecture video a predetermined number of times or more. Learning support system.

2. The recommendation unit suggests the use of the high-speed playback function at the time the learner takes action to begin watching the lecture video. The learning support system according to claim 1.

3. Computers It measures the learner's progress in online learning and detects predetermined learning actions. Based on at least one of the measured learning progress of the learner and the detected learning operations, the learning functions that the learner should use are identified as recommended learning functions. A learning support method that, at the timing triggered by the detection of the aforementioned learning operation, proposes the aforementioned recommended learning function to the learner, As a learning function, there is a high-speed playback function that plays lecture videos at high speed. The computer determines that the high-speed playback function is the recommended learning function if the learner has taken the lecture video a predetermined number of times or more. Learning support methods.

4. The computer proposes the use of the high-speed playback function at the time the learner takes action to begin watching the lecture video. The learning support method according to claim 3.

5. It measures the learner's progress in online learning and detects predetermined learning actions. Based on at least one of the measured learning progress of the learner and the detected learning operations, the learning functions that the learner should use are identified as recommended learning functions. A learning support program that causes a computer to perform the action of proposing the recommended learning function to the learner at a timing triggered by the detection of the aforementioned learning operation, As a learning function, there is a high-speed playback function that plays lecture videos at high speed. A learning support program that causes the computer to determine that the high-speed playback function is the recommended learning function if the learner has taken the lecture video from a predetermined number of times onward.

6. The computer is made to suggest the use of the high-speed playback function at the time the learner takes action to begin taking the lecture video. The learning support program according to claim 5.

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