KR20130082839A - Apparatus and method for providing user customised cotent - Google Patents

Apparatus and method for providing user customised cotent Download PDF

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Publication number
KR20130082839A
KR20130082839A KR1020110138531A KR20110138531A KR20130082839A KR 20130082839 A KR20130082839 A KR 20130082839A KR 1020110138531 A KR1020110138531 A KR 1020110138531A KR 20110138531 A KR20110138531 A KR 20110138531A KR 20130082839 A KR20130082839 A KR 20130082839A
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South Korea
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learning
user
content
concentration
area
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KR1020110138531A
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Korean (ko)
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손은진
황선홍
홍승표
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두산동아 주식회사
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Publication of KR20130082839A publication Critical patent/KR20130082839A/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/20—Education
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B7/00—Electrically-operated teaching apparatus or devices working with questions and answers
    • G09B7/06—Electrically-operated teaching apparatus or devices working with questions and answers of the multiple-choice answer-type, i.e. where a given question is provided with a series of answers and a choice has to be made from the answers

Abstract

PURPOSE: User customized contents providing device and method thereof are provided to accurately understand learning concentration by collecting user reaction result generated while learning contents and to provide contents according to the learning concentration. CONSTITUTION: A system consists of a contents providing unit (110), a user reaction collection unit (120), a learning concentration analysis unit (130), a contents modification unit (140) and a test question providing unit (150). A contents providing device (100) provides learning contents to users by connecting with a user terminal through a communication network and collects user reaction. The collected user reaction is capable of modifying contents provided to the user through learning concentration analysis or providing test questions reflecting the learning level. [Reference numerals] (100) Contents providing device; (110) Contents providing unit; (120) User reaction collection unit; (130) Learning concentration analysis unit; (140) Contents modification unit; (150) Test question providing unit; (AA) Learning contents; (BB) User reaction; (CC) Test questions

Description

Device and method for providing user-customized content {APPARATUS AND METHOD FOR PROVIDING USER CUSTOMISED COTENT}

The present invention relates to a user-customized content providing apparatus and method thereof, and specifically, collects user response results to accurately check the learning concentration according to the learning area and the system of the learning object, and adds it to the user according to the identified learning concentration. The present invention relates to a user-customizable content providing device and a method for enhancing learning concentration through inducing learning or calling attention.

Learners learn about learning content in their desired direction. For example, learners look closely at areas of interest. However, learners may learn about the subjects that they are not interested in, even if they go through the contents of the outline or skip some contents without learning.

At this time, the authors want to know what is the content of the learning content that the learner learns, and what is not learned. In addition, authors want to know not only whether they learn, but also how much they focus on learning. This may be useful when the authors modify the pre-produced learning content or develop new learning content.

However, since books are purchased offline, authors are not only able to grasp the learning area that learners are learning in real time, but also hard to know how high the concentration of learning is. In addition, authors cannot further induce learning to learners even if their learning progress is different from the intended learning direction. It is not possible to quickly change the composition or style of a book because the books are produced and distributed offline.

To compensate for this, authors first produce sample books and distribute them offline. And learners' interest in learning contents can be collected through surveys on distributed sample books. In addition, the method for checking the learning direction of the learners may include a learning test performed by hand writing or drawing with writing instruments while learning the book through offline.

Such surveys or offline inspections can collect learners' simple grading or opinions about the composition of content. If such a questionnaire is made of simple repetition, interest of the questionnaire may be deteriorated. In addition, an error between the actual learning pattern and the answer may occur due to the response tendency of the questionnaire and internal and external factors at the time of the questionnaire. That is, when collecting feedback on the composition of the learning content around the answerer's answer, there may be an error between the actual learning pattern and the questionnaire answer. And since the questionnaire must check the questionnaire one by one, there is a problem that it takes additional time to record and quantify the individual learner's learning direction.

The present invention has been made to solve the above problems, by collecting the user response results occurring in the middle of the user learning the learning content to accurately check the learning concentration according to the area of learning and the structure of the learning, According to the concentration of learning, the user can induce additional learning or increase the concentration of learning through attention, and provide a user-customized content providing device and method that can further enhance the learning effect through an evaluation problem that matches the learning concentration of the user. It aims to do it.

To this end, the apparatus according to the first aspect of the present invention, the content providing unit for generating a learning content divided into the learning area to provide to the user; A user response collector configured to collect a user response result generated in the middle of learning the provided learning content; A learning concentration analysis unit configured to calculate a learning concentration using the collected user response results and to analyze the calculated learning concentration of each user for each learning area; And calculating a learning area in which the analyzed learning concentration of the user is equal to or less than a preset learning concentration, and changing the provided learning content so that the calculated learning concentration exceeds the preset learning concentration. And a content changer provided to the user.

According to a second aspect of the present invention, there is provided a method comprising providing content to a user by generating learning content divided into learning areas; A user response collection step of collecting a user response result occurring in the middle of learning the provided learning content; A learning concentration analysis step of calculating a learning concentration using the collected user response results and analyzing the calculated learning concentration of each user for each learning region; A learning area calculating step of calculating a learning area in which the analyzed learning concentration of the user is equal to or less than a preset learning concentration; And a content change step of changing the provided learning content to the user so that the calculated learning concentration of the learning area exceeds the preset learning concentration.

The present invention collects user reaction results (eg, eye tracking data, user brain wave measurement data, user input data, etc.) generated while a user learns the learning content, and the learning concentration according to the learning area and the learning object system. Exactly, and according to the identified learning concentration has the effect of inducing additional learning to the user or increase the learning concentration through attention.

In addition, the present invention, by adjusting the difficulty of the evaluation problem in accordance with the learning concentration of the user has an effect that can further increase the learning effect through the evaluation problem suitable for the user's learning concentration.

In addition, the present invention has an effect of increasing the concentration of learning by providing additional learning content in the learning area that the user has not learned to induce additional learning or call attention to the user.

1 is a configuration diagram of an embodiment of a user-customized content providing device according to the present invention;
2 is a diagram illustrating an embodiment of a region definition process of learning content according to the present invention;
3 and 4 illustrate an embodiment of a user's eye tracking process according to the present invention;
5 is a flowchart illustrating a method for providing user-customized content according to the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. The configuration of the present invention and the operation and effect thereof will be clearly understood through the following detailed description. Prior to the detailed description of the present invention, the same components will be denoted by the same reference numerals even if they are displayed on different drawings, and the detailed description will be omitted when it is determined that the well-known configuration may obscure the gist of the present invention. do.

1 is a configuration diagram of an embodiment of a user-customized content providing apparatus according to the present invention.

As shown in FIG. 1, the content providing device 100 includes a content providing unit 110, a user response collecting unit 120, a learning concentration analysis unit 130, a content changing unit 140, and an evaluation problem providing unit ( 150). Herein, the content providing device 100 may be connected to the user terminal 101 through a communication network in order to provide content to a plurality of users using the user terminal 101 and collect user responses. The content providing device 100 may provide learning content to the user terminal 101, and receive a user response result through a communication network.

Hereinafter, each component of the content providing apparatus 100 according to the present invention will be described.

The content provider 110 generates learning content divided into learning areas and provides them to the user through the user terminal 101. Here, the learning content is defined in the learning area and the characteristics of each area. For example, focus factors are defined for important concepts. The central element may be designated as an element that the user must learn. In addition, the content providing unit 110 may generate learning content divided into some learning areas from among a plurality of learning areas such as a language field, a logic field, an interpersonal relationship field, a music field, and a space field.

In addition, the user response collector 120 collects a user response result generated while the user learns the learning content provided by the content provider 110. For example, the user response collector 120 may collect at least one of user gaze tracking data, user brain wave measurement data, and user input data as a user response result. In this case, since the user response collection unit 120 is performed at the user terminal, the user response collection unit 120 may collect the user response result generated while the user actually uses the test in a specific test environment.

Here, looking at an example related to the user's motion recognition, the user response collector 120 is a user gaze on which area of the learning content the user looks through the user terminal 101 equipped with the eye tracker (Eye Tracker) Trace data can be collected. Referring to an example of tracking the gaze of a user, the user response collector 120 may request at least one of a user's content immersion time, a gaze movement path, and a gaze position currently viewed by the user terminal 101 to measure the information. Can be. In addition, the user response collection unit 120 may collect the responsiveness or concentration for each learning time or area of the learning content while the user learns the learning content through the user terminal 101 equipped with the EEG measuring apparatus. In addition, the user response collector 120 may collect user input data including a finger gesture such as a user writing on the learning content or clicking a mouse through the user terminal 101. Specifically, the user response collector 120 may include data input when the user touches the touch panel, data input by the user through a mouse, pen mouse, touch fan, motion recognition, augmented reality, and voice spoken by the user. Data can be collected.

Through this, the learning concentration analysis unit 130 calculates the learning concentration using the user response result collected by the user response collecting unit 120, and analyzes the calculated learning concentration of the user for each learning area. At this time, the learning concentration analysis unit 130 calculates the learning concentration by substituting a preset immersion calculation formula and checks whether the learning concentration of the user exceeds a predetermined value. For example, when the predetermined learning concentration is 70%, the learning concentration analyzer 130 checks whether the learning concentration of the user exceeds 70%.

Looking at the learning concentration in detail, the learning concentration analysis unit 130, when the user passes the learning area of the learning content and does not learn, the user is a learning time preset learning of the learning area other than the central element of the learning content When exceeding or when the user's eyes stay in a certain area in contradiction with the predefined learning flow, the number of times of reading a part of the learning content repeatedly, the time the eyes stay, etc. are comprehensively measured and substituted into the immersion calculation formula. If the immersion degree obtained is lower than the reference value, it is determined that the learning concentration is low. For example, the learning concentration analysis unit 130 reflects the learning concentration as low if the unlearned learning region is 60% among the learning regions of the entire learning content. Here, if the user viewing the learning area is less than a predetermined time, the learning concentration analyzer 130 may determine the learning area as an unlearned area.

On the other hand, the learning concentration analysis unit 130 repeats any one learning area when the user learns the entire learning content while learning all the learning areas designated as the central elements based on the user's eye tracking data at a predetermined learning time. Even when learning according to a predetermined learning direction without reading, it can be determined that the learning concentration is high. In addition, the learning concentration analysis unit 130 determines that the learning concentration is high when the brain wave associated with the learning concentration from the EEG measurement data is measured above a predetermined threshold. For example, the learning concentration analyzer 130 may determine that the learning concentration is high when an alpha wave or a SMR (Sensory Motor Rhythm) wave, which is related to learning concentration, is measured. In addition, the learning concentration analysis unit 130 measures the learning concentration that is concentrated on the learning content through the user input data. For example, the learning concentration analyzer 130 may input data when the user touches the touch panel, data input by the user through a mouse, a pen mouse, a touch fan, motion recognition, augmented reality, and the voice spoken by the user. The concentration of learning of the user may be measured using data. The learning concentration analysis unit 130 may check the learning concentration of each learning field by checking the learning time and the learning score of the learning content for each learning field. For example, when the learning content is composed of the content of the first field and the second field, the learning concentration analyzer 130 learns the time of learning the content of the first field, the learning score, and the content of the second field. An hour and its learning score can be checked by field of study. The results of learning concentration by learning area can be used as a reference for generating assessment questions. Further, the learning concentration analysis unit 130 may calculate and calculate the learning concentration and learning fatigue of the user for each learning area.

Meanwhile, the content change unit 140 calculates a learning area in which the user's learning concentration is less than or equal to the predetermined learning concentration using the learning concentration analysis result of the learning concentration analysis unit 130. In addition, the content change unit 140 changes the learning content and provides the content to the user through the content providing unit 110 such that the calculated learning concentration of the learning area exceeds a preset learning concentration.

In this case, when the learning concentration of the user analyzed by the learning concentration analysis unit 130 is less than or equal to the predetermined learning concentration, the content change unit 140 provides the user with an unlearning identification effect for alerting the identified unlearned area. can do. For example, if the learning concentration is insufficient, the content change unit 140 may increase the learning concentration by inducing additional learning or calling attention to the user through the sparkling effect or the enlargement of the pop-up.

In addition, when the learning concentration of the learning area calculated by the learning concentration analyzer 130 is identified as the unlearned area, the content change unit 140 generates additional learning content for the identified unlearned area and provides the user to the user. do. When it is confirmed in the learning concentration analysis unit 130 that the user skips without reading a specific row, picture, or chart, the content change unit 140 generates additional learning content for the concept and provides the same to the user. In addition, even if the user reads and skips only a title of a specific row, the content change unit 140 may generate additional learning content including a learning area for the specific row and provide the same to the user.

Meanwhile, the evaluation problem providing unit 150 adjusts the difficulty level of the evaluation problem of the learning content according to the learning concentration analyzed by the learning concentration analysis unit 130 and provides it to the user. For example, the evaluation problem provider 150 adjusts the difficulty level of the evaluation problem with respect to the learning area having a high learning concentration. This may lead to a deeper learning effect for the user. In addition, the evaluation problem providing unit 150 may generate an evaluation problem for the unlearned area. In this way, the evaluation problem providing unit 150 may help the user to learn the unlearned learning area. And the evaluation problem providing unit 150 provides an evaluation problem to the user.

Thereafter, the evaluation problem providing unit 150 collects the user's evaluation problem performance result. Collected assessment problem performance results can be used for learning concentration analysis.

2 is a diagram illustrating an embodiment of a process of defining a region of learning content according to the present invention.

As illustrated in FIG. 2, the content providing unit 110 sets the respective content areas by dividing the learning content into the first to fourth areas 210 to 240. The content providing unit 110 defines the content characteristics of each area. In addition, the content providing unit 110 defines the system of each area and the characteristics of the system. For example, the content providing unit 110 defines red item ① as the publisher. In addition, the content providing unit 110 defines an item for the details and matches the defined item with the database. For example, the content providing unit 110 matches the items corresponding to the blue ① and ② items 222 and 223 with the database.

Meanwhile, a user response pattern to be fetched according to an input characteristic of the user terminal 101 may be defined as enable / disable. For example, when the front terminal is absent in the user terminal 101, the user's motion may be defined using a method other than the eye tracker.

3 and 4 illustrate one embodiment of a user's eye tracking process according to the present invention.

As illustrated in FIG. 3, the user response collection unit 120 collects user gaze tracking data 310 while the user learns each area of the learning content displayed on the screen of the user terminal 101. The user's gaze tracking data 310 may display a path in which a user's eyes move.

For example, the user gaze tracking data 310 may include the following contents. The user learns from the first area 210 including the table title and learns up to the red ① item 221 of the second area 220 including the learning content. The user reads the third region 230 for a while and reads the blue ① item 222 of the second region 220 again. Thereafter, the user reads the fourth area 240 and finishes learning without reading the "self-determination of Min Young-hwan" below.

The user response collection unit 120 collects the user response result according to the input characteristics of each terminal for the predefined content such as a tablet, a mobile phone, a web-based asset, and the like. In addition, the learning concentration analysis unit 130 may analyze the learning concentration using the user response result. An example of extraction of user gaze tracking data is shown in FIG. 4.

The user reads the table title-descriptions (401) and reads the red item ① (221) of the second area 220 for 35 seconds per row (402). It is confirmed that the user repeatedly reads the red ① item 221 through the read time per row (403).

In addition, the learning concentration analysis unit 130 may confirm that the predefined learning direction is different from the actual reading order. Subsequently, the learning concentration analyzer 130 may determine that the user does not read the blue ② item 223 in detail about the short reading time of the blue item ② of the second area 220 (404). ). The learning concentration analysis unit 130 may confirm that the portion of “Min Young-hwan's self-determination” is not read (405).

Through this, first, the learning concentration analysis unit 130 may check the negligence of the user when the user passes a specific area without reading, such as the "self-determination of Min-hwan". Second, the learning concentration analysis unit 130, as shown in the red ① item 221 is longer than the predetermined time for reading the line, or if it takes longer for the gaze to stay in a non-critical area of the learning content of the learning content. This can be confirmed by a design error. Third, the learning concentration analysis unit 130 may confirm that the user lacks understanding when reading a single content several times.

In addition, the learning concentration analysis unit 130 may calculate the learning concentration of the user according to a preset calculation formula and sort them in chronological order.

5 is a flowchart illustrating a method for providing user-customized content according to the present invention.

The content provider 110 generates learning content divided into learning areas (S502).

The content providing unit 110 provides the generated learning content to the user (S504).

The user response collection unit 120 collects a user response result generated in the middle of learning the learning content (S506).

The learning concentration analysis unit 130 analyzes the learning concentration for each learning area using the user response result collected by the user response collection unit 120 (S508).

The learning concentration analysis unit 130 checks whether there is an unlearned learning area (S510).

As a result of the check (S510), if there is an unlearned learning element, the content change unit 140 changes the learning content of the unlearned learning element and provides it to the user so as to further learn and pay attention (S512). In this case, the content change unit 140 may increase the concentration of learning by inducing additional learning or calling attention to the user through the content providing unit 110 through the sparkling effect or the enlargement of the popup. On the other hand, if there is no learning element (S510), the unlearned learning element, the content change unit 140 performs the process "S514".

The evaluation problem providing unit 150 adjusts the level of the evaluation problem based on the learning concentration analysis result analyzed by the learning concentration analysis unit 130 to generate an evaluation problem (S514).

The evaluation problem providing unit 150 provides the generated evaluation problem to the user (S516).

And the evaluation problem providing unit 150 collects the user's evaluation problem performance results (S518).

Meanwhile, the present invention can be applied to various playback apparatuses by implementing the above-described method for providing user-customized content by using a software program and recording it on a computer-readable predetermined recording medium.

The various playback apparatuses may be mobile terminals, PDAs, notebook computers, navigation systems, PMPs, smart phones, electronic dictionaries, and the like as the user terminals described above.

For example, the recording medium may be a hard disk, a flash memory, a RAM, a ROM, or the like embedded in each reproduction apparatus, or an external optical disk such as a CD-R or a CD-RW, a compact flash card, a smart media, have.

The foregoing description is merely illustrative of the present invention, and various modifications may be made by those skilled in the art without departing from the spirit of the present invention. Accordingly, the embodiments disclosed in the specification of the present invention are not intended to limit the present invention. The scope of the present invention should be construed according to the following claims, and all the techniques within the scope of equivalents should be construed as being included in the scope of the present invention.

The present invention collects the user response results occurring in the middle of the user learning the learning content to accurately determine the learner concentration according to the learning area and the system of the learning object, the user for the missing learning items according to the identified learning concentration You can increase the concentration of learning by providing additional learning to students or by calling attention. In this respect, the invention is a commercially available invention because the possibility of marketing or operating the applied device is not only sufficient for the use of the related technology, but also practically evident as it exceeds the limitation of the existing technology.

100: content providing device 110: content providing unit
120: user response collection unit 130: learning concentration analysis unit
140: content change unit 150: evaluation problem provider

Claims (10)

A content provider configured to generate learning content divided into learning areas and provide the same to a user;
A user response collector configured to collect a user response result generated in the middle of learning the provided learning content;
A learning concentration analysis unit configured to calculate a learning concentration using the collected user response results and to analyze the calculated learning concentration of each user for each learning area; And
Calculate a learning area whose learning concentration of the analyzed user is equal to or less than a predetermined learning concentration, change the provided learning content so that the calculated learning concentration exceeds the preset learning concentration, and provide the user with the content providing unit; Content change department provided to
Customizable content providing device comprising a. The method of claim 1,
An evaluation problem providing unit which provides the user with the difficulty of adjusting the evaluation problem difficulty of the learning content according to the analyzed learning concentration.
The user-customized content providing device further comprises. The method of claim 1,
The user response collector,
And collecting at least one of user gaze tracking data, user EEG measurement data, and user input data as a result of the user response. The method of claim 1,
The content change unit,
And when the analyzed user's learning concentration is less than or equal to a predetermined learning concentration, providing the user with an unlearned identification effect for alerting the identified unlearned area. The method of claim 1,
The content change unit,
And when the learning concentration of the calculated learning area is identified as the unlearning area, generating additional learning content for the identified unlearning area and providing the generated content to the user. A content providing step of generating learning content divided into a learning area and providing the same to a user;
A user response collection step of collecting a user response result occurring in the middle of learning the provided learning content;
A learning concentration analysis step of calculating a learning concentration using the collected user response results and analyzing the calculated learning concentration of each user for each learning region;
A learning area calculating step of calculating a learning area in which the analyzed learning concentration of the user is equal to or less than a preset learning concentration; And
A content changing step of changing the provided learning content to provide the user with the learning concentration of the calculated learning area exceeding the preset learning concentration;
User-tailored content providing method comprising a. The method according to claim 6,
A step of providing an evaluation problem provided to the user by adjusting the difficulty of the evaluation problem of the learning content according to the analyzed learning concentration
User-customized content providing method further comprising a. The method according to claim 6,
The user response collection step,
And collecting at least one of user gaze tracking data, user EEG measurement data, and user input data as a result of the user response. The method according to claim 6,
The content change step,
And when the analyzed user's learning concentration is less than or equal to a predetermined learning concentration, providing the user with an unlearned identification effect for alerting the identified unlearned area. The method according to claim 6,
The content change step,
And when the learning concentration of the calculated learning area is identified as the unlearning area, generating additional learning content for the identified unlearning area and providing the generated content to the user.
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JP2019215731A (en) * 2018-06-13 2019-12-19 富士通株式会社 Concentration evaluation program, device, and method
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