KR20230172116A - Server for analyzing the user's learning characteristics using log data of electronic pen - Google Patents

Abstract

One embodiment is an electronic device that photographs a dot image printed in a size that is not visually recognizable on a printed matter, analyzes the pattern of the dot image, identifies a dot code corresponding to the pattern, and performs an operation corresponding to the dot code. a communication unit that receives log data recording the dot code together with a time value from the pen; a storage unit that stores the log data for each user identifier; and an analysis unit that analyzes the log data to generate user learning data.

Description

A server that analyzes the user's learning characteristics using log data from the electronic pen {SERVER FOR ANALYZING THE USER'S LEARNING CHARACTERISTICS USING LOG DATA OF ELECTRONIC PEN}

This embodiment relates to a learning management server.

There is a technology called a learning management system. This technology is widely known as LMS (Learning Management System).

Learning management systems were mainly developed to allow educators to easily upload learning content when a curriculum is opened in an online space or to facilitate learners' accessibility to the content.

As learning management systems have recently developed further, they are developing to provide customized learning for individual learners by tracking the learner's learning process and managing the learning history.

Since learning in a learning management system is mainly carried out in an online space, the operation signals input by the learner - mainly click signals for content or text signals entered on the keyboard (text signals for entering the correct answer) - are the data to be analyzed. It becomes.

The learning management system evaluates the playback time of the content started and ended by the learner as the learning progress rate or evaluates the learner's achievement using the correct rate of the answers entered by the learner.

When the learning management system was released to the market, the response from users was enthusiastic. Learners believed that by using the learning management system, they could analyze their own learning patterns and easily identify what needs to be improved and what needs to be strengthened in learning. However, recently the response has become much colder. As the accuracy of learning data provided by learning management systems decreases, users no longer trust the analysis results provided by learning management systems.

The cause lies in the source of the data that the learning management system uses for analysis. The learning management system uses user manipulation signals directly entered by users in the online space as the analysis object. Unlike the offline space, the online space is less intuitive and convenient, so the analysis object lacks consistency and may distort the analysis. Arbitrary manipulation may also be included. Because the original source of analysis is unreliable data, the analysis results also become unreliable.

As a specific example, offline, you can accurately determine the rate of learning progress by checking that the pages of a book are turning, but online, you have to estimate whether the book's pages are turning based solely on the user's operation signals, but this estimation is not intuitive and therefore not accurate. It is not. In this respect, online learning management systems can be judged to be less intuitive than offline ones.

As another example, an online learning management system requires users to connect to a personal computer (e.g., a laptop) and then search for the relevant content one by one from a hierarchical list, which is different from the offline method where users only have to search for books on the bookshelf. It is less convenient. Additionally, entering answers using a device such as a keyboard can also be considered less convenient than entering answers using a pen. Because online learning management systems are less convenient than offline ones, the input of data subject to analysis is often interrupted midway, resulting in distortion of analysis results.

Against this background, we would like to consider introducing a technology that uses data from offline devices, which are highly intuitive and convenient, as the subject of analysis in a learning management system. We believe that this attempt is unprecedented and goes beyond the limitations of previous online learning management systems.

In this embodiment, as an offline device with high intuitiveness and convenience, data from an electronic pen is used as an analysis target for a learning management system.

An electronic pen is a device that recognizes printed matter using an image sensor.

Electronic pens often function as a device for reading books. This function allows the electronic pen to read the contents of the book when you touch it to the book.

The book does not have any electronic devices - for example, RFID (radio frequency identification, etc.) - but has invisible dot images printed on it. The electronic pen recognizes these dot images and plays the sound file corresponding to the dot image. By giving it to you, it can perform the function of reading a book.

Because the dot image is printed in a size that is invisible to the general eye, users have a mystifying feeling that the electronic pen recognizes the book itself and reads the book.

Devices other than electronic pens can also perform the function of reading books. Audiobooks are a representative example. A personal computer or smartphone can read a book to you by playing an audiobook.

However, because electronic pens have different advantages than these devices, they are attracting attention from many users.

The electronic pen provides intuitiveness and convenience to users who want to read books.

Users can read the contents of a page by simply touching the electronic pen to the page of the book they want to read. However, other devices can only read the contents by finding and playing the file location or page of the sound source one by one using a controller such as a keyboard or mouse. This characteristic of the electronic pen can be called intuitive in that the user can directly play the content he or she is looking at without entering indirect identifiers - file names, page numbers, etc. - into the device.

The electronic pen has a similar appearance to a regular pen and has a sound source file in its internal memory, making it highly convenient to carry. Users can use the electronic pen with the same feeling as if they were holding a pencil. It is true that smartphones are much smaller in size and weight than personal computers, but they do not provide the convenience of portability like an electronic pen.

Because of these advantages, many users are using electronic pens. In particular, the use of electronic pens is very high among infants who do not know how to read or whose reading skills are not perfect.

This embodiment seeks to provide a technology for managing learning using data generated by an electronic pen, which is an offline device with high intuitiveness and convenience. This attempt may be a new technology that can solve the problem of distortion of analysis results in online learning management systems.

The purpose of this embodiment is, in one aspect, to provide technology for managing learning using data generated by an electronic pen. In another aspect, the purpose of this example is to provide technology for converting dot images recognized by an electronic pen into log data and analyzing users' learning patterns using such log data.

In order to achieve the above-mentioned purpose, one embodiment is to photograph a dot image printed in a size that is not visually recognizable on a printed matter, analyze the pattern of the dot image, check the dot code corresponding to the pattern, and determine the dot code. a communication unit that receives log data recording the dot code together with a time value from electronic pens that perform operations corresponding to; a storage unit that stores the log data for each user identifier; and an analysis unit that analyzes the log data to generate user learning data.

The printed material is a booklet, and the booklet consists of a plurality of pages. Dot images of different patterns are printed on each page, and the analysis unit determines the log data among the dot codes corresponding to the dot images for one user. The reading rate for the booklet can be calculated based on the ratio of dot codes received.

The storage unit further stores user characteristic values representing the biological or environmental characteristics of users, and the analysis unit compares the reading rate of one user with users with similar biological characteristics or with users with similar environmental characteristics. Comparative analysis data can be calculated.

The storage unit may further store user characteristic values representing biological or environmental characteristics of users, and perform statistical analysis on learning data of users with similar biological characteristics or users with similar environmental characteristics.

The printed material is a booklet, and the booklet consists of a plurality of pages, and each page has dot images of different patterns printed on it. The analysis unit analyzes each page at time intervals of the log data that is continuously received for one user. It is possible to estimate the residence time of and use the residence time to calculate the reading rate of the booklet by the user.

As described above, according to this embodiment, it is possible to provide a technology for managing learning using data generated by an electronic pen as an offline device with high intuitiveness and convenience. And, according to this embodiment, it is possible to provide a technology for converting the dot image recognized by the electronic pen into log data and analyzing users' learning patterns using this log data.

Figure 1 is a configuration diagram of an electronic pen learning analysis system according to an embodiment.
Figure 2 is a configuration diagram of a server according to one embodiment.
Figure 3 is a diagram illustrating an example of a process in which log data is generated in one embodiment.
Figure 4 is an example diagram showing a storage form of log data in one embodiment.
Figure 5 is a diagram showing an example of a detailed configuration for generating learning data in the analysis unit of the server according to an embodiment.
Figure 6 is a diagram illustrating an example of a detailed configuration for generating statistical data in an analysis unit of a server according to an embodiment.
Figure 7 is a diagram showing a first example of a learning data analysis screen according to an embodiment.
Figure 8 is a second example diagram of a learning data analysis screen according to an embodiment.
Figure 9 is a configuration diagram of a network according to one embodiment.
Figure 10 is a diagram showing a dot image of a printed product according to one embodiment.
Figure 11 is a diagram showing an example of a dot code data mapping table according to an embodiment.
12A to 12C are diagrams showing a first example of an analysis result screen in a UI device according to an embodiment.
13A to 13C are diagrams of a second example of an analysis result screen in a UI device according to an embodiment.
14A and 14B are diagrams of a third example of an analysis result screen in a UI device according to an embodiment.
15A and 15B are diagrams of a fourth example of an analysis result screen in a UI device according to an embodiment.
16A to 16C are diagrams showing a fifth example of an analysis result screen in a UI device according to an embodiment.

Hereinafter, some embodiments of the present invention will be described in detail through illustrative drawings. When adding reference numerals to components in each drawing, it should be noted that identical components are given the same reference numerals as much as possible even if they are shown in different drawings. Additionally, in describing the present invention, if it is determined that a detailed description of a related known configuration or function may obscure the gist of the present invention, the detailed description will be omitted.

Additionally, when describing the components of the present invention, terms such as first, second, A, B, (a), and (b) may be used. These terms are only used to distinguish the component from other components, and the nature, sequence, or order of the component is not limited by the term. When a component is described as being “connected,” “coupled,” or “connected” to another component, that component may be directly connected or connected to that other component, but there is another component between each component. It will be understood that elements may be “connected,” “combined,” or “connected.”

Figure 1 is a configuration diagram of an electronic pen learning analysis system according to an embodiment.

Referring to FIG. 1, the electronic pen learning analysis system 100 may include an electronic pen 110, a server 120, and a user interface (UI) device 130. In addition, the electronic pen learning analysis system 100 may further include a printed matter 10 and a network 20.

The electronic pen 110 can capture a dot image printed on the printed matter 10 in a size that is not visually recognizable.

Visually recognized (visible) content may be printed on the printed material 10. Visible content may include text or illustrations, for example. In addition, content that an average person can recognize with his or her eyes can be defined as visible content. The smallest size that the human eye can see is usually known to be 0.1 mm. Because the visible content is in a meaningful shape, it can actually have a size larger than 0.1 mm. People can understand the intention of the printed matter 10 by looking at the visible content printed on the printed matter 10.

A dot image may be printed on the printed material 10 in a size that is not visually recognized (invisible). The invisible dot image may be printed in the same area as the visible content. For this reason, users may only recognize visible content and not recognize invisible dot images.

Dot images can form various patterns. And, the pattern can be matched with one dot code. The pattern can be determined by the position of the dots placed in the dot image. In a dot image, dots may be placed in specific positions, and the positions of these dots can be viewed as patterns. A dot image may be composed of a plurality of dot cells, and each dot cell may represent a binary or quaternary number. For example, in a dot cell, a dot can be interpreted as 0 if it is located in the upper left corner, 1 if it is located in the upper right corner, 2 if it is located in the lower left corner, and 3 if it is located in the lower right corner. When these dot cells form a dot image, the dot image can be matched to a dot code from 0 to 65535, and can be matched to a larger number of dot codes.

The electronic pen 110 can capture the dot image printed on the printed matter 10 and analyze the pattern of the dot image to check the dot code corresponding to the dot image. And, the electronic pen 110 can perform operations corresponding to the confirmed dot code.

The electronic pen 110 can match a specific code to a specific operation. For example, if the dot code is A, the electronic pen 110 can play the sound source file of content A through the speaker, and if the dot code is B, the electronic pen 110 can play the sound source file of content B through the speaker. You can play it through . In addition, the electronic pen 110 may perform an operation to recognize alphabets or letters according to a dot code, and may also perform an operation to record a voice.

These matching rules may be defined in advance and stored inside the electronic pen 110. Accordingly, when the user simply touches the electronic pen 110 to the printed matter 10, the electronic pen 110 can perform the operation of playing back the visible content displayed on the printed matter 10 as a sound source file. will be.

Meanwhile, in this embodiment, the electronic pen 110 may store the dot codes recognized by the user on the electronic pen 110 together with the time value as log data. For example, if the printed material 10 is a booklet consisting of a plurality of pages, and the user reads each page sequentially using the electronic pen 110, the electronic pen 110 reads each page along with a dot code corresponding to each page. The time value for which the electronic pen 110 is in contact with each page can be stored as log data.

Log data may include dot codes and time values. Here, the time value may be the time value at the moment the dot code is recognized, or it may be the time value at the moment the log data is saved. The time from when a dot code is recognized to when log data is stored may be significantly shorter than the time from when the electronic pen 110 recognizes one dot code to the next dot code.

The electronic pen 110 can transmit stored log data to the server 120 regularly or irregularly.

The electronic pen 110 may be connected to the server 120 through the network 20. Considering portability, the electronic pen 110 may be connected to the network 20 through a wireless connection, but considering irregular transmission, it may be connected to the server 120 through a wired connection.

The server 120 may generate learning data using log data received from the electronic pen 110. The server 120 may recognize the user of the electronic pen 110 and generate learning data for the user.

The electronic pen 110 may be matched to a specific user. The electronic pen 110 may have one identifier, and this identifier may be a communication address generally assigned to a communication device. The identifier of the electronic pen 110 may be matched to the user's ID.

The server 120 may recognize the user who is generating log data using the identifier of the electronic pen 110, and generate log data using the user ID that matches the identifier of the electronic pen 110. Users can be recognized. In the latter example, a component included in the network 20 may convert the identifier of the electronic pen 110 into a user ID and transmit it to the server 120.

The server 120 can generate various learning data using log data. The server 120 can use log data to calculate a reading rate indicating how much one booklet has been read. Additionally, the server 120 can use log data to calculate a reading rate that indicates how accurately one booklet has been read. In addition, the server 120 can calculate a complete reading rate indicating the extent to which a plurality of books consisting of complete books have been read.

The server 120 can collect log data for a plurality of users from a plurality of electronic pens 110 and calculate statistical learning data. For example, the server 120 may calculate statistics on learning data according to biological characteristics. The server 120 can calculate statistics on learning data by age, which is one of the biological characteristics, and can calculate statistics on learning data by gender. As another example, the server 120 may calculate statistics on learning data according to environmental characteristics. The server 120 can calculate statistics on learning data by region, which is one of the environmental characteristics, and can calculate statistics on learning data by household environment, such as presence or absence of siblings.

The server 120 may collect information about biological characteristics or environmental characteristics of each user to calculate such statistical data. The server 120 may collect information about the user's biological or environmental characteristics at the user's ID creation stage, and may collect such information while providing a reward to the user at a later stage.

The server 120 can analyze the user's learning characteristics using log data. For example, the server 120 can use log data to calculate the time spent on each page and use the stay time to analyze the user's learning concentration and study attitude toward reading. Furthermore, the server 120 can use log data to analyze the user's personality and the possibility of psychological problems. At this time, the server 120 can analyze not only the log data but also the contents of the content confirmed through the dot code.

The analysis results of the server 120 may be displayed to the user through the UI device 130.

The UI device 130 can be connected to the server 120 through the network 20 and includes a display device, so that information received from the server 120 can be displayed on the display device. The UI device 130 may also perform the function of a repeater.

Figure 2 is a configuration diagram of a server according to one embodiment.

Referring to FIG. 2, the server 120 may include a communication unit 1210, a storage unit 1220, and an analysis unit 1230.

The communication unit 1210 can communicate with the electronic pen through a network. The communication unit 1210 can receive log data in which a dot code is recorded along with a time value from the electronic pen.

The communication unit 1210 can communicate with multiple electronic pens through a network. The communication unit 1210 can calculate statistics on learning data by analyzing log data received from a plurality of electronic pens.

The communication unit 1210 can communicate with the UI device through a network. The communication unit 1210 may transmit analysis results of log data to the UI device.

The storage unit 1220 can store log data received from electronic pens. The storage unit 1220 may store log data for each user's identifier. Each log data may be received with the identifier of the electronic pen attached or may be received with the user's identifier attached.

The analysis unit 1230 may analyze log data to generate user learning data. Hereinafter, the content described as the analysis function of the server 120 can be understood as being performed by the analysis unit 1230 unless otherwise specified.

In order to understand the analysis function in the server 120, we will first look at the creation process of log data subject to analysis and the form of log data.

Figure 3 is a diagram illustrating an example of a process in which log data is generated in one embodiment.

Referring to Figure 3, the user can play back the contents of each page in voice using an electronic pen.

Different dot images are printed on each page of the printed matter, and the electronic pen can recognize the different dot images by converting them into different dot codes.

The time the user touches the electronic pen to each page is bound to be physically different, and the electronic pen can store this time as log data along with the dot code.

For example, the user played page 1 with voice at 10:13:02 on May 1, 2022, and page 2 with voice at 10:15:17 on May 1, 2022. The pen can save the dot code and time of the reproduced page as log data.

Figure 4 is an example diagram showing a storage form of log data in one embodiment.

Referring to FIG. 4, the electronic pen can create a dot code history table in the memory and sequentially store time values along with the dot code in this table. At this time, each row of the table can be log data.

Log data stored in the electronic pen can be transmitted to the server regularly or irregularly, and the server can analyze the received log data to generate learning data for the user.

Log data contains various information. First, the dot code contains information about the content. Although the dot code itself does not contain information, the server can check the contents of the content through the dot code. Log data includes time values, and the server can use the time values to check the stay time for each page and check the patterns of time values.

Figure 5 is a diagram showing an example of a detailed configuration for generating learning data in the analysis unit of the server according to an embodiment.

Referring to FIG. 5, the analysis unit 1230 may include a content analysis unit 1510, a content DB 1512, a time analysis unit 1520, and a learning analysis unit 1530.

The content analysis unit 1510 can analyze the content of the dot code. Once the dot code is confirmed, the content analysis unit 1510 can confirm the content by substituting the dot code into the content DB 1512.

Content content may include content title, content classification value, content language value, content target age value, content publisher value, upper group to which the content belongs (e.g., collection-value, etc.), content difficulty, content length, etc. Additional content characteristic values may be included.

The content analysis unit 1510 can check the content through the dot code, generate a content analysis value, and transmit it to the learning analysis unit 1530.

The time analysis unit 1520 can analyze the time value of log data.

The time analysis unit 1520 may generate a time analysis value including the time value itself and a time difference value corresponding to the difference between the previous time and the later time, and transmit it to the learning analysis unit 1530.

Additionally, the learning analysis unit 1530 can generate learning data by combining content analysis values and time analysis values.

Figure 6 is a diagram illustrating an example of a detailed configuration for generating statistical data in an analysis unit of a server according to an embodiment.

Referring to FIG. 6, the analysis unit 1230 may further include a statistical analysis unit 1610.

The server can receive log data from multiple electronic pens and analyze the log data to generate statistical data.

The statistical analysis unit 1610 may receive learning data for multiple users from the learning analysis unit 1530. Additionally, the statistical analysis unit 1610 can generate statistical data using learning data for multiple users.

Figure 7 is a diagram showing a first example of a learning data analysis screen according to an embodiment.

Referring to FIG. 7, the server can calculate the reading rate for one printed matter.

The server can use the dot code to identify a printed matter - for example, a booklet - to which the dot code belongs. Additionally, the server can confirm that the printed matter consists of multiple pages and check the total number of dot codes for the total pages. Additionally, the server can calculate the reading rate for the printed matter as a ratio of the number of dot codes received as log data to the total number of dot codes.

The server - the storage unit of the server - may further store user characteristic values representing biological or environmental characteristics of users. Additionally, the server can calculate similar group comparative analysis data by comparing one user's learning data with users with similar biological characteristics or with users with similar environmental characteristics.

For example, as shown in FIG. 7, the server may compare reading rates among all users who have read books, or it may compare reading rates among users with the same age, which is an example of a biological characteristic.

Figure 8 is a second example diagram of a learning data analysis screen according to an embodiment.

Referring to FIG. 8, the server can use the biological or environmental characteristics of users to statistically analyze learning data of users with similar biological characteristics or users with similar environmental characteristics.

For one user, the server can estimate the residence time on each page based on the time interval of continuously received log data, and use the residence time to calculate the reading rate of the booklet for each user, as shown in Figure 8. The diagram lists the books with the highest reading rates according to biological characteristics (e.g., age) and environmental characteristics (e.g., region).

Users can use this statistical data to select a booklet that is suitable for them, and publishers can use this statistical data to specify marketing targets.

In the above, an embodiment has been described focusing on the server, and below, the operation of the electronic pen and its peripheral devices will be described to help understand the embodiment.

Figure 9 is a configuration diagram of a network according to one embodiment.

Referring to FIG. 9, the network 20 may include a repeater 22 and a network device 24.

The repeater 22 can be wirelessly connected to the electronic pen. The wireless connection may be, for example, a Bluetooth connection or a Wi-Fi connection. The repeater 22 can transmit log data received from the electronic pen to the server through the network device 24 through a wireless connection.

The repeater 22 can transmit time synchronization information using an electronic pen. And, the electronic pen can synchronize time using this time synchronization information. Here, synchronization may refer to synchronization with the repeater 22 time or synchronization with the server time.

The repeater 22 may include a device capable of receiving standardized time, such as a Global Positioning System (GPS) receiver. And, the repeater 22 can include this standardized time in time synchronization information and transmit it to the electronic pen.

The electronic pen may include a timer inside. When the electronic pen is not communicating with the repeater 22, it can count time using an internal timer, and when it receives time synchronization information from the repeater 22, it resets the internal timer to the time included in the time synchronization information. Or you can compensate for that time.

The repeater 22 may further perform the function of a UI device.

The repeater 22 is a UI device that manages user information and can transmit user information to the server when communicating with the server.

The repeater 22 can transmit the identifier of the electronic pen - for example, a communication address - to the server to indicate the source of the log data, and can transmit the user ID matching the identifier of the electronic pen to the server. .

The repeater 22 can manage user information. The repeater 22 can manage user ID, user password, user's biological information, user's environmental information, etc. The repeater 22 can manage user information through its own memory, store user information on a server, and receive and manage user information through communication.

The repeater 22 can regularly or irregularly connect to the electronic pen and receive log data from the electronic pen. When the repeater 22 is connected to the electronic pen irregularly, the electronic pen may generate an alarm signal when accumulated log data exceeds a certain standard to manage the internal memory.

The electronic pen can record whether accumulated log data is transmitted to the server. Also, when the electronic pen is connected to communication with the repeater 22, it can transmit untransmitted log data to the repeater 22.

The electronic pen can generate an alarm signal so that the user can recognize it when the amount of log data that has not been transmitted among the accumulated log data exceeds a certain standard amount. Additionally, when the period of non-transmission of log data exceeds a certain standard period, the electronic pen can generate an alarm signal so that the user can recognize it.

The repeater 22 may include a processing chip and a display device to perform the above-described functions. In terms of form, the repeater 22 may be a personal computer such as a laptop or a portable communication terminal such as a smartphone. In addition, the repeater 22 may have a form such as an artificial intelligence speaker.

Figure 10 is a diagram showing a dot image of a printed product according to one embodiment.

Referring to FIG. 10, the printed matter 10 may have the form of a booklet. Also, the booklet may consist of multiple pages.

Dot images 10-1 of different patterns may be printed on each page. Additionally, the dot image 10-1 may include a plurality of dot cells 10-2 having the shape of a grid cell.

Dots are arranged in each dot cell 10-2, and the code value of each dot cell 10-2 may be interpreted differently depending on the position of the dot in each dot cell 10-2.

And, the electronic pen can generate a dot code using the code value of each dot cell 10-2 in the dot image 10-1.

After checking the dot code corresponding to the dot image 10-1, the electronic pen can check content data corresponding to each dot code using the dot code data mapping table stored in the memory.

Figure 11 is a diagram showing an example of a dot code data mapping table according to an embodiment.

Referring to FIG. 11, in the dot code data mapping table, dot code 1205625 may correspond to content data #64329_625, and dot code 1205628 may correspond to content data #64329_628.

The memory address value of content data may be stored in the dot code data mapping table. The electronic pen can check the memory address value of the content data corresponding to the dot code and play the content data at the corresponding memory address value through a speaker, etc.

Whenever a dot code is recognized, the electronic pen can save the dot code and time value as log data.

The learning data created by the operations on the electronic pen and server described above can be displayed to the user by the UI device.

12A to 12C are diagrams showing a first example of an analysis result screen in a UI device according to an embodiment.

Referring to FIGS. 12A to 12C, the UI device can display a calendar and display a read book on the calendar. Books read can be tallied by day, by month, or by year.

The values displayed by the UI device are values analyzed by the server, and the server can tally the books the user has read using the electronic pen by day/month/year. Aggregation can be done when a query from a UI device is sent, or it can be done periodically on the server.

When a specific date is clicked on the calendar, the UI device can display reading information for that day in detail. In reading information, the time spent reading a book can be displayed, and the reading rate can be displayed for each booklet.

When a booklet is clicked on a UI device, the total number of codes/number of instantaneous accesses/number of listening completions may be displayed, and the number of total pages/taken pages/read pages may be displayed. The total number of codes represents the number of dot codes corresponding to the entire page, and the instantaneous access number is the number of dot codes recognized by contact with the electronic pen and may correspond to the page taken. In addition, the number of listening completions may correspond to pages read when the electronic pen stays for a certain period of time after contact. This information can indicate which pages were touched by the electronic pen but were likely not actually read due to the short dwell time.

13A to 13C are diagrams of a second example of an analysis result screen in a UI device according to an embodiment.

Referring to FIGS. 13A to 13C, the UI device can display pages with a high reading rate and pages with a low reading rate through analysis of each page on the server. And, when the UI device displays each page, it can enable specific pages to be intuitively recognized through thumbnails.

14A and 14B are diagrams of a third example of an analysis result screen in a UI device according to an embodiment.

Referring to Figures 14a and 14b, the UI device can display basic information about the book through communication with the server, and display statistics among users who have read the book or statistical values among users of the same age group. there is.

15A and 15B are diagrams of a fourth example of an analysis result screen in a UI device according to an embodiment.

Referring to FIGS. 15A and 15B, the UI device can check the reading rate of each booklet through communication with the server and display a certificate of completion as an award for the reading rate exceeding a certain value. Additionally, the UI device can encourage learning by displaying the accumulated number of certificates for compositions such as complete works.

16A to 16C are diagrams showing a fifth example of an analysis result screen in a UI device according to an embodiment.

Referring to FIGS. 16A to 16C, the UI device can display the number of books read in the user's entire collection of books, display books by publisher regardless of whether the user owns them or not, and display the number of books owned or read by the user. It can be used for marketing purposes.

As described above, according to this embodiment, it is possible to provide a technology for managing learning using data generated by an electronic pen as an offline device with high intuitiveness and convenience. And, according to this embodiment, it is possible to provide a technology for converting the dot image recognized by the electronic pen into log data and analyzing users' learning patterns using this log data.

Terms such as “include,” “comprise,” or “have,” as used above, mean that the corresponding component may be included, unless specifically stated to the contrary, and do not exclude other components. It should be interpreted that it may further include other components. All terms, including technical or scientific terms, unless otherwise defined, have the same meaning as generally understood by a person of ordinary skill in the technical field to which the present invention pertains. Commonly used terms, such as terms defined in a dictionary, should be interpreted as consistent with the meaning in the context of the related technology, and should not be interpreted in an idealized or overly formal sense unless explicitly defined in the present invention.

The above description is merely an illustrative explanation of the technical idea of the present invention, and various modifications and variations will be possible to those skilled in the art without departing from the essential characteristics of the present invention. Accordingly, the embodiments disclosed in the present invention are not intended to limit the technical idea of the present invention, but are for illustrative purposes, and the scope of the technical idea of the present invention is not limited by these embodiments. The scope of protection of the present invention should be interpreted in accordance with the claims below, and all technical ideas within the equivalent scope should be construed as being included in the scope of rights of the present invention.

Claims (5)

The dot image is captured from electronic pens that photograph a dot image printed in a size that is not visually recognizable on the printed matter, analyze the pattern of the dot image, check the dot code corresponding to the pattern, and perform operations corresponding to the dot code. A communication unit that receives log data recording a code with a time value;
a storage unit that stores the log data for each user identifier; and
Analysis unit that analyzes the log data and generates user learning data
Server containing . According to paragraph 1,
The printed material is a booklet, and the booklet consists of a plurality of pages, and each page has dot images of different patterns printed on it,
The analysis unit is a server that calculates, for one user, a reading rate for the booklet based on a ratio of dot codes received as the log data among dot codes corresponding to the dot images. According to paragraph 2,
The storage unit further stores user characteristic values representing biological or environmental characteristics of users,
The analysis unit is a server that calculates similar group comparative analysis data by comparing the reading rate of the user with users with similar biological characteristics or with users with similar environmental characteristics. According to paragraph 1,
The storage unit further stores user characteristic values representing biological or environmental characteristics of users,
A server that performs statistical analysis on learning data of users with similar biological characteristics or users with similar environmental characteristics. According to paragraph 1,
The printed material is a booklet, and the booklet consists of a plurality of pages, and each page has dot images of different patterns printed on it,
The analysis unit estimates a user's stay time on each page based on the time interval of the log data received continuously, and calculates the user's reading rate for the booklet using the stay time.

Images