KR20160087478A - Method for planning portfolio using learner analysis data on the basis of mobile terminal and service - Google Patents

Abstract

The present invention relates to a method and a service of designing a portfolio using learning analysis data based on a mobile terminal. A system of providing a learning portfolio related to an embodiment of the present invention comprises: a memory which stores education progress information and content information for education; a mobile terminal which provides learning to a user by using the education progress information and the content information for education; a wireless communication unit which receives feedback information of the user which is related to the learning from the mobile terminal; and a control unit which generates analysis data by using the education progress information, the content information for education, and the feedback information. The control unit can determine learning guidance information specified for the user by using the analysis data, and control the wireless communication unit to transmit the determined learning guidance information to the mobile terminal.

Description

BACKGROUND OF THE INVENTION Field of the Invention [0001] The present invention relates to a method and a service for designing a portfolio using learning analysis data based on a mobile terminal,

The present invention relates to a method and a service for designing a portfolio using learning analysis data based on a mobile terminal.

A terminal such as a personal computer, a notebook computer, a mobile phone, or the like can be configured to perform various functions. Examples of such various functions include a data and voice communication function, a function of photographing a video or a moving image through a camera, a voice storage function, a music file playback function through a speaker system, and an image or video display function. Some terminals include additional functions to execute games, and some other terminals are also implemented as multimedia devices. Moreover, recent terminals can receive a broadcast or multicast signal to view a video or television program.

In general, a terminal can be divided into a mobile terminal (mobile / portable terminal) and a stationary terminal according to whether the terminal can be moved. The mobile terminal can be divided into a handheld terminal and a vehicle mount terminal according to whether the user can directly carry the mobile terminal.

Such a terminal has various functions, for example, in the form of a multimedia device having multiple functions such as photographing and photographing of a moving picture, reproduction of a music or video file, reception of a game and broadcasting, etc. .

In order to support and enhance the functionality of such terminals, it may be considered to improve the structural and / or software parts of the terminal.

On the other hand, as smartphones and social network services (SNS) become common, the types and amounts of data generated by billions of users around the world are increasing at an explosive rate, and the awake leaders of government, We are paying attention to data utilization.

The government is also in line with the global trend by introducing public data as a government 3.0 policy and fostering data-based new industries as a new government operating paradigm.

In particular, Big Data is more like a picture that expresses the needs and behaviors of individuals rather than data representing the group, so it is expected to be very useful in all fields that are oriented toward personalized personalized services.

However, the education sector is slow to prepare for data use rather than the public information openness or private business intelligence (Business Intelligence) field.

This does not motivate interested stakeholders and educational services agencies to share data, and the lack of a service model is also a major cause.

Generally, meaningful data is generated by various learning activities using ICT (Information and Communication Technology) in the classroom and online, but these data are discarded or only partially extracted and recorded when the activity or process ends.

Therefore, it is not easy to provide a personalized learning environment or to support level-level learning because it requires data and follow-up activities at the average level in situations where the learner does not understand the level of understanding and process correctly.

For example, in the existing offline education, only the final evaluation data such as the test results are manually recorded, and the meaningful activity record in the learning process is not accumulated, so that it faces the limit for level-specific learning guidance and individual learning .

Moreover, it is difficult to provide personalized feedback, such as learning habits and cognitive level, because it only measures the academic level of students through formal tests.

Therefore, there is a need for new data - based services to overcome these limitations and to provide support and synchronization for individual learners.

This specification proposes a use case that is expected to be provided as a learning analysis service.

In particular, the International Organization for Standardization has initiated efforts to establish the concept of learning analysis and to identify stakeholders in a concrete way, while the private organizations participating in the organizations are making practical efforts such as data collection system, Considering the characteristics of these two approaches, we propose a model to complete personalized learning services using learning analysis techniques.

Korean Intellectual Property Office Publication No. 10-2011-0122267

It is an object of the present invention to provide a method and a service for designing a portfolio using learning analysis data based on a mobile terminal.

Specifically, it is an object of the present invention to overcome a limited situation and to provide a new service or use case based on data for support and motivation for individual learners.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory and are not restrictive of the invention, unless further departing from the spirit and scope of the invention as defined by the appended claims. It will be possible.

A system for providing a learning portfolio related to an example of the present invention for realizing the above-mentioned problems, comprising: a memory for storing training course information and training content information; A mobile terminal for providing learning to a user using the training course information and the training content information; A wireless communication unit for receiving feedback information of the user related to the learning from the mobile terminal; And a controller for generating analysis data using the training course information, the training content information, and the feedback information, wherein the controller determines learning guidance information specific to the user using the analysis data, And the communication unit can control to transmit the determined learning guidance information to the mobile terminal.

In addition, the training course information and the training content information can be changed, and the wireless communication unit can additionally receive the changed training course information and training content information from the outside.

In addition, the curriculum information may include an elementary school, a middle school and a high school curriculum, a vocational training curriculum, a higher education curriculum, and an overseas curriculum.

In addition, the education content information may include academic database information, private database information, overseas education content information, and individual education content information provided by the institute.

The feedback information may include at least one of data information generated through the digital contents, learning activity data information generated through the learning platform, data information generated during the operation of the education program at the educational institution, data information about the user's career and connections, And may include data information that occurs during the profiling of the user.

The criteria for generating analysis data using the training course information, the training content information, and the feedback information may include a learning activity measurement standard, a context standard, a participation standard, and an achievement standard, Metrics can include readings, lectures, quizzes, projects, assignments, media, teaching, guidance, research, evaluation, collaboration, annotation, gaming, social, messaging, scheduling and discussion standards.

The method for generating analysis data using the training course information, the training content information, and the feedback information may include a learning analysis dashboard method, a prediction analysis method, an adaptive learning analysis method, a social network analysis method, An analysis method and an evaluation method using ICT.

The learning guidance information may be learning guidance information for supplementing weaknesses of the user determined using the analysis data.

According to another aspect of the present invention, there is provided a method of providing a learning portfolio associated with an exemplary embodiment of the present invention, the method comprising: storing training course information and training content information; Providing the user with learning using the training course information and the training content information; Receiving feedback information of the user associated with the learning from the mobile terminal; Generating analysis data using the training course information, the training content information, and the feedback information; Determining learning guidance information specific to the user using the analysis data; And transmitting the determined learning guidance information to the mobile terminal.

In addition, the training course information and the training content information may be changed, and the wireless communication unit may additionally receive the changed training course information and the training content information from the outside.

In addition, the curriculum information may include an elementary school, a middle school and a high school curriculum, a vocational training curriculum, a higher education curriculum, and an overseas curriculum.

In addition, the education content information may include academic database information, private database information, overseas education content information, and individual education content information provided by the institute.

The feedback information may include at least one of data information generated through the digital contents, learning activity data information generated through the learning platform, data information generated during the operation of the education program at the educational institution, data information about the user's career and connections, And may include data information that occurs during the profiling of the user.

The criterion for generating the analysis data using the training course information, the training content information, and the feedback information includes a learning activity measurement standard, a context standard, a participation standard, and an achievement standard, , Reading, lectures, quizzes, projects, assignments, media, teaching, guidance, research, evaluation, collaboration, annotation, gaming, social, messaging, scheduling and discussion criteria.

The method for generating analysis data using the training course information, the training content information, and the feedback information may include a learning analysis dashboard method, a prediction analysis method, an adaptive learning analysis method, a social network analysis method, It can include evaluation methods using ICT.

The learning guidance information may be learning guidance information for supplementing weaknesses of the user determined using the analysis data.

On the other hand, a program of instructions executable by a digital processing apparatus is implemented tangibly to perform a method of providing a learning portfolio related to an example of the present invention for realizing the above-mentioned problems, Wherein the learning portfolio providing method comprises: storing training course information and training content information; Providing the user with learning using the training course information and the training content information; Receiving feedback information of the user associated with the learning from the mobile terminal; Generating analysis data using the training course information, the training content information, and the feedback information; Determining learning guidance information specific to the user using the analysis data; And transmitting the determined learning guidance information to the mobile terminal.

The mobile terminal according to at least one embodiment of the present invention configured as described above can provide a method and a service for designing a portfolio using learning analysis data.

Specifically, the present invention overcomes a limited situation and provides a new service based on data, that is, a use case, to a user for support and motivation for individual learners.

The effects obtained by the present invention are not limited to the above-mentioned effects, and other effects not mentioned can be clearly understood by those skilled in the art from the following description will be.

1 is a block diagram illustrating a portable terminal according to an embodiment of the present invention.
2A is a perspective view of a portable terminal according to an embodiment of the present invention.
FIG. 2B is a rear perspective view of the portable terminal shown in FIG. 2A.
3 shows a specific example of a data model of the education field in connection with the present invention.
4 shows a concrete example of a data matrix for learning analysis in connection with the present invention.
5 shows a concrete example of the concept of fusion between learning analysis levels in connection with the present invention.
6A shows a specific example of a main workflow for a learning analysis service related to the present invention.
6B is a diagram for explaining a foreign case related to learning analysis in connection with the present invention.
Fig. 7 is a concrete example showing a topic unit connection of a mathematics subject in the ASN Framework.
FIG. 8 shows a specific example of a learning path that links learning analysis and linked data technology related to the present invention.
9 shows an example of a conceptual configuration of a learning portfolio related to the present invention.
FIG. 10 shows a specific example of a circulation model of a learning portfolio linked with the learning analysis proposed by the present invention.

Hereinafter, a portable terminal related to the present invention will be described in detail with reference to the drawings. The suffix "module" and " part "for the components used in the following description are given or mixed in consideration of ease of specification, and do not have their own meaning or role.

The portable terminal described in this specification may include a mobile phone, a smart phone, a laptop computer, a digital broadcasting terminal, a PDA (Personal Digital Assistants), a PMP (Portable Multimedia Player), and a navigation device. However, it will be easily understood by those skilled in the art that the configuration according to the embodiments described herein may be applied to fixed terminals such as a digital TV, a desktop computer, and the like, unless the configuration is applicable only to a portable terminal.

Prior to a specific description of a service proposed by the present invention, a portable terminal applicable to the present invention will be described in detail.

1 is a block diagram of a portable terminal according to an embodiment of the present invention.

The portable terminal 100 includes a wireless communication unit 110, an A / V input unit 120, a user input unit 130, a sensing unit 140, an output unit 150, a memory 160, A controller 170, a controller 180, a battery 190, and the like. The components shown in Fig. 1 are not essential, and a portable terminal having more or fewer components may be implemented.

Hereinafter, the components will be described in order.

The wireless communication unit 110 may include one or more modules that enable wireless communication between the wireless terminal 100 and the wireless communication system or between the wireless terminal 100 and a network in which the wireless terminal 100 is located. For example, the wireless communication unit 110 may include a broadcast receiving module 111, a mobile communication module 112, a wireless Internet module 113, a short range communication module 114, and a location information module 115 .

The broadcast receiving module 111 receives broadcast signals and / or broadcast-related information from an external broadcast management server through a broadcast channel.

The broadcast channel may include a satellite channel and a terrestrial channel. The broadcast management server may refer to a server for generating and transmitting broadcast signals and / or broadcast related information, or a server for receiving broadcast signals and / or broadcast related information generated by the broadcast management server and transmitting the generated broadcast signals and / or broadcast related information. The broadcast signal may include a TV broadcast signal, a radio broadcast signal, a data broadcast signal, and a broadcast signal in which a data broadcast signal is combined with a TV broadcast signal or a radio broadcast signal.

The broadcast-related information may refer to a broadcast channel, a broadcast program, or information related to a broadcast service provider. The broadcast-related information may also be provided through a mobile communication network. In this case, it may be received by the mobile communication module 112.

The broadcast-related information may exist in various forms. For example, an EPG (Electronic Program Guide) of DMB (Digital Multimedia Broadcasting) or an ESG (Electronic Service Guide) of Digital Video Broadcast-Handheld (DVB-H).

For example, the broadcast receiving module 111 may be a Digital Multimedia Broadcasting-Terrestrial (DMB-T), a Digital Multimedia Broadcasting-Satellite (DMB-S), a Media Forward Link Only (DVF-H) A digital broadcasting system such as DVB-CB, OMA-BCAST, or Integrated Services Digital Broadcast-Terrestrial (ISDB-T). Of course, the broadcast receiving module 111 may be adapted to other broadcasting systems as well as the digital broadcasting system described above.

The broadcast signal and / or broadcast related information received through the broadcast receiving module 111 may be stored in the memory 160.

The mobile communication module 112 transmits and receives radio signals to at least one of a base station, an external terminal, and a server on a mobile communication network. The wireless signal may include various types of data depending on a voice call signal, a video call signal or a text / multimedia message transmission / reception. The mobile communication module 112 connects the communication with the 3D web providing server 700 under the control of the controller 180 and transmits a signal requesting the 3D web page selected by the user to the 3D web providing server 700. [ (700), and receives a signal including the 3D web page according to the request from the 3D web providing server (700).

The wireless Internet module 113 refers to a module for wireless Internet access, and may be built in or externally mounted in the mobile terminal 100. The wireless Internet module 113 connects the communication with the 3D web providing server 700 under the control of the controller 180 and transmits a signal requesting the 3D web page selected by the user to the 3D web providing server 700. [ (700), and receives a signal including the 3D web page according to the request from the 3D web providing server (700). WLAN (Wi-Fi), Wibro (Wireless broadband), Wimax (World Interoperability for Microwave Access), HSDPA (High Speed Downlink Packet Access) and the like can be used as the technology of the wireless Internet.

The short-range communication module 114 refers to a module for short-range communication. In accordance with the control of the control unit 180, the short-range communication module 114 connects a communication with the 3D web providing server 700 and transmits a signal requesting the provision of the 3D web page selected by the user to the 3D web providing server 700. [ (700), and receives a signal including the 3D web page according to the request from the 3D web providing server (700). Bluetooth, Radio Frequency Identification (RFID), Infrared Data Association (IrDA), Ultra Wideband (UWB), ZigBee, and the like can be used as the short range communication technology.

The position information module 115 is a module for obtaining the position of the portable terminal 100, and a representative example thereof is a Global Position System (GPS) module. According to the current technology, the GPS module 115 calculates distance information and accurate time information from three or more satellites, and then applies trigonometry to the calculated information to obtain a three-dimensional string of latitude, longitude, The location information can be accurately calculated. At present, a method of calculating position and time information using three satellites and correcting an error of the calculated position and time information using another satellite is widely used. In addition, the GPS module 115 can calculate speed information by continuously calculating the current position in real time.

Referring to FIG. 1, an A / V (Audio / Video) input unit 120 is for inputting an audio signal or a video signal, and may include a camera 121 and a microphone 122. The camera 121 processes image frames such as still images or moving images obtained by the image sensor in the video communication mode or the photographing mode. The processed image frame can be displayed on the display unit 151. [

The image frame processed by the camera 121 may be stored in the memory 160 or transmitted to the outside through the wireless communication unit 110. [

At this time, two or more cameras 121 may be provided depending on the use environment.

For example, the camera 121 may include first and second cameras 121a and 121b for capturing 3D images on the opposite side of the display unit 151 of the portable terminal 100, A third camera 121c for self-photographing the user may be provided in a part of the surface of the display unit 151 of the terminal 100. [

In this case, the first camera 121a is for capturing the left eye image, which is the source image of the 3D image, and the second camera 121b, for the right eye image capturing.

The microphone 122 receives an external sound signal through a microphone in a communication mode, a recording mode, a voice recognition mode, or the like, and processes it as electrical voice data. The processed voice data can be converted into a form that can be transmitted to the mobile communication base station through the mobile communication module 112 when the voice data is in the call mode, and output. Various noise reduction algorithms may be implemented in the microphone 122 to remove noise generated in receiving an external sound signal.

The user input unit 130 generates input data for a user to control the operation of the terminal.

The user input unit 130 may receive from the user a signal designating two or more contents among the contents to be displayed according to the present invention. And a signal designating two or more contents may be received via a touch input or via a hard key and a soft key input.

The user input unit 130 may receive an input from the user for selecting the one or more contents. In addition, an input for generating an icon related to a function that the portable terminal 100 can perform can be received from the user.

The user input unit 130 may include a directional keypad, a keypad, a dome switch, a touchpad (static / static), a jog wheel, a jog switch, and the like.

The sensing unit 140 senses the current state of the portable terminal 100 such as the open / close state of the portable terminal 100, the position of the portable terminal 100, the presence of the user, the orientation of the portable terminal, And generates a sensing signal for controlling the operation of the portable terminal 100. For example, when the portable terminal 100 is in the form of a slide phone, it is possible to sense whether the slide phone is opened or closed. It is also possible to sense whether the battery 190 is powered on, whether the interface unit 170 is connected to an external device, and the like. Meanwhile, the sensing unit 140 may include a proximity sensor 141. The proximity sensor 141 will be described later in relation to the touch screen.

The output unit 150 is for generating an output relating to visual, auditory or tactile sense and includes a display unit 151, an acoustic output module 152, an alarm unit 153, a haptic module 154, 155, and the like.

The display unit 151 displays (outputs) the information processed in the portable terminal 100. For example, when the portable terminal is in the call mode, a UI (User Interface) or a GUI (Graphic User Interface) associated with a call is displayed. When the portable terminal 100 is in the video communication mode or the photographing mode, the photographed and / or received image, UI, or GUI is displayed.

In addition, the display unit 151 according to the present invention supports 2D and 3D display modes.

That is, the display unit 151 according to the present invention may have a configuration in which the switch liquid crystal 151b is combined with a general display device 151a as shown in FIG. 5 below. 5 (a), the optical parallax barriers 50 are operated by using the switch liquid crystal 151b to control the traveling direction of the light, so that different lights can be separated from the left and right eyes. Therefore, when a combined image of the right eye image and the left eye image is displayed on the display device 151a, the user can see the image corresponding to each eye and feel as if it is displayed in three-dimensional form.

That is, under the control of the control unit 180, the display unit 151 drives only the display device 151a without driving the switch liquid crystal 151b and the optical parallax barrier 50 in the 2D display mode Performs normal 2D display operation.

The display unit 151 drives the switch liquid crystal 151b and the optical parallax barrier 50 and the display device 151a under the control of the controller 180 to display the display liquid crystal 151b, 151a to perform the 3D display operation.

The 3D display process of the display unit 151 will be described later in detail with reference to FIGS. 3 to 5.

The display unit 151 may be a liquid crystal display (LCD), a thin film transistor-liquid crystal display (TFT LCD), an organic light-emitting diode (OLED) A flexible display, and a three-dimensional display (3D display).

Some of these displays may be transparent or light transmissive so that they can be seen through. This can be referred to as a transparent display, and a typical example of the transparent display is TOLED (Transparent OLED) and the like. The rear structure of the display unit 151 may also be of a light transmission type. With this structure, the user can see an object located behind the terminal body through the area occupied by the display unit 151 of the terminal body.

There may be two or more display units 151 according to the embodiment of the portable terminal 100. For example, in the portable terminal 100, a plurality of display units may be spaced apart from one another or may be disposed integrally with each other, or may be disposed on different surfaces.

(Hereinafter, referred to as a 'touch screen') in which a display unit 151 and a sensor for sensing a touch operation (hereinafter, referred to as 'touch sensor') form a mutual layer structure, It can also be used as an input device. The touch sensor may have the form of, for example, a touch film, a touch sheet, a touch pad, or the like.

The touch sensor may be configured to convert a change in a pressure applied to a specific portion of the display unit 151 or a capacitance generated in a specific portion of the display unit 151 into an electrical input signal. The touch sensor can be configured to detect not only the position and area to be touched but also the pressure at the time of touch.

If there is a touch input to the touch sensor, the corresponding signal (s) is sent to the touch controller (not shown). The touch controller processes the signal (s) and transmits the corresponding data to the controller 180. Thus, the control unit 180 can know which area of the display unit 151 is touched or the like.

The proximity sensor 141 may be disposed in an inner area of the portable terminal or in the vicinity of the touch screen, which is enclosed by the touch screen. The proximity sensor refers to a sensor that detects the presence or absence of an object approaching a predetermined detection surface or a nearby object without mechanical contact using the force of an electromagnetic field or infrared rays. The proximity sensor has a longer life span than the contact sensor and its utilization is also high.

Examples of the proximity sensor include a transmission type photoelectric sensor, a direct reflection type photoelectric sensor, a mirror reflection type photoelectric sensor, a high frequency oscillation type proximity sensor, a capacitive proximity sensor, a magnetic proximity sensor, and an infrared proximity sensor. And to detect the proximity of the pointer by the change of the electric field along the proximity of the pointer when the touch screen is electrostatic. In this case, the touch screen (touch sensor) may be classified as a proximity sensor.

Hereinafter, for convenience of explanation, the act of recognizing that the pointer is positioned on the touch screen while the pointer is not in contact with the touch screen is referred to as "proximity touch & The act of actually touching the pointer on the screen is called "contact touch. &Quot; The position where the pointer is proximately touched on the touch screen means a position where the pointer is vertically corresponding to the touch screen when the pointer is touched.

The proximity sensor detects a proximity touch and a proximity touch pattern (e.g., a proximity touch distance, a proximity touch direction, a proximity touch speed, a proximity touch time, a proximity touch position, a proximity touch movement state, and the like). Information corresponding to the detected proximity touch operation and the proximity touch pattern may be output on the touch screen.

The audio output module 152 may output audio data received from the wireless communication unit 110 or stored in the memory 160 in a call signal reception mode, a call mode or a recording mode, a voice recognition mode, a broadcast reception mode, The sound output module 152 also outputs sound signals related to functions (e.g., call signal reception tones, message reception tones, etc.) performed in the portable terminal 100. The audio output module 152 may include a receiver, a speaker, a buzzer, and the like.

The alarm unit 153 outputs a signal for notifying the occurrence of an event of the portable terminal 100. Examples of events occurring in the portable terminal include receiving a call signal, receiving a message, inputting a key signal, and touch input. The alarm unit 153 may output a signal for notifying the occurrence of an event in a form other than the video signal or the audio signal, for example, vibration. In this case, the display unit 151 and the audio output module 152 may be a type of the alarm unit 153. The display unit 151 and the audio output module 152 may be connected to the display unit 151 or the audio output module 152, .

The haptic module 154 generates various tactile effects that the user can feel. A typical example of the haptic effect generated by the haptic module 154 is vibration. The intensity and pattern of the vibration generated by the hit module 154 can be controlled. For example, different vibrations may be synthesized and output or sequentially output.

In addition to the vibration, the haptic module 154 may include a pin arrangement vertically moving with respect to the contact skin surface, a spraying force or a suction force of the air through the injection port or the suction port, a touch on the skin surface, contact with an electrode, And various tactile effects such as an effect of reproducing a cold sensation using an endothermic or exothermic element can be generated.

The haptic module 154 can be implemented not only to transmit the tactile effect through the direct contact but also to allow the user to feel the tactile effect through the muscular sensation of the finger or arm. The haptic module 154 may include two or more haptic modules 154 according to the configuration of the portable terminal 100.

The projector module 155 is a component for performing an image project function using the portable terminal 100 and is similar to the image displayed on the display unit 151 in accordance with a control signal of the controller 180 Or at least partly display another image on an external screen or wall.

Specifically, the projector module 155 includes a light source (not shown) that generates light (for example, laser light) for outputting an image to the outside, a light source And a lens (not shown) for enlarging and outputting the image at a predetermined focal distance to the outside. Further, the projector module 155 may include a device (not shown) capable of mechanically moving the lens or the entire module to adjust the image projection direction.

The projector module 155 can be divided into a CRT (Cathode Ray Tube) module, an LCD (Liquid Crystal Display) module and a DLP (Digital Light Processing) module according to the type of the display means. In particular, the DLP module may be advantageous for miniaturization of the projector module 151 by enlarging and projecting an image generated by reflecting light generated from a light source on a DMD (Digital Micromirror Device) chip.

Preferably, the projector module 155 may be provided on the side surface, the front surface, or the back surface of the portable terminal 100 in the longitudinal direction. It goes without saying that the projector module 155 may be provided at any position of the portable terminal 100 as needed.

The memory 160 may store a program for processing and controlling the controller 180 and may store the input / output data (e.g., a telephone directory, a message, an audio, a still image, an electronic book, History, and the like). The memory 160 may also store the frequency of use of each of the data (for example, each telephone number, each message, and frequency of use for each multimedia). In addition, the memory unit 160 may store data on vibration and sound of various patterns output when the touch is input on the touch screen.

The memory 160 also stores a web browser displaying 3D or 2D web pages in accordance with the present invention. The web browser can be downloaded from the 3D web providing server 700 via the wireless communication unit 110 and stored.

The memory 160 may be a flash memory type, a hard disk type, a multimedia card micro type, a card type memory (for example, SD or XD memory, etc.) ), A random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read- A magnetic disk, an optical disk, a memory, a magnetic disk, or an optical disk. The portable terminal 100 may operate in association with a web storage that performs a storage function of the memory 160 on the Internet.

The interface unit 170 serves as a path for communication with all external devices connected to the portable terminal 100. The interface unit 170 receives data from an external device or receives power from the external device and transmits the data to each component in the portable terminal 100 or allows data in the portable terminal 100 to be transmitted to an external device. For example, a wired / wireless headset port, an external charger port, a wired / wireless data port, a memory card port, a port for connecting a device having an identification module, an audio I / O port, A video input / output (I / O) port, an earphone port, and the like may be included in the interface unit 170.

The identification module is a chip for storing various information for authenticating the usage right of the mobile terminal 100 and includes a user identification module (UIM), a subscriber identity module (SIM), a general user authentication module A Universal Subscriber Identity Module (USIM), and the like. Devices with identification modules (hereinafter referred to as "identification devices") can be manufactured in a smart card format. Accordingly, the identification device can be connected to the terminal 100 through the port.

When the portable terminal 100 is connected to an external cradle, the interface unit may be a path through which power from the cradle is supplied to the portable terminal 100, or various command signals input from the cradle by the user It can be a passage to be transmitted to the terminal. The various command signals input from the cradle or the power source may be operated as a signal for recognizing that the portable terminal is correctly mounted on the cradle.

The controller 180 typically controls the overall operation of the portable terminal. For example, voice communication, data communication, video communication, and the like. The control unit 180 may include a multimedia module 181 for multimedia playback. The multimedia module 181 may be implemented in the control unit 180 or may be implemented separately from the control unit 180. [

The controller 180 may perform a pattern recognition process for recognizing handwriting input or drawing input performed on the touch screen as characters and images, respectively.

When the display unit 151 is formed of an organic light-emitting diode (OLED) or a TOLED (Transparent OLED), the controller 180 controls the display unit 151, When the preview image is pulled up on the screen of the organic light-emitting diode (OLED) or the TOLED (Transparent OLED) and the size of the preview image is adjusted according to the user's operation, The power consumption of the power source supplied from the power supply unit 190 to the display unit 151 can be reduced by turning off the driving of the pixels in the second area other than the first area in which the preview image is adjusted.

The power supply unit 190 receives external power and internal power under the control of the controller 180 and supplies power necessary for operation of the respective components.

The various embodiments described herein may be embodied in a recording medium readable by a computer or similar device using, for example, software, hardware, or a combination thereof.

According to a hardware implementation, the embodiments described herein may be implemented as application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays May be implemented using at least one of a processor, controllers, micro-controllers, microprocessors, and other electronic units for performing other functions. In some cases, The embodiments described may be implemented by the control unit 180 itself.

According to a software implementation, embodiments such as the procedures and functions described herein may be implemented with separate software modules. Each of the software modules may perform one or more of the functions and operations described herein. Software code can be implemented in a software application written in a suitable programming language. The software code is stored in the memory 160 and can be executed by the control unit 180. [

2A is a perspective view of a portable terminal according to an embodiment of the present invention.

The disclosed mobile terminal 100 has a bar-shaped main body. However, the present invention is not limited thereto, and can be applied to various structures such as a slide type, a folder type, a swing type, and a swivel type in which two or more bodies are relatively movably coupled.

The body includes a case (a casing, a housing, a cover, and the like) which forms an appearance. In this embodiment, the case may be divided into a front case 101 and a rear case 102. [ A variety of electronic components are embedded in the space formed between the front case 101 and the rear case 102. At least one intermediate case may be additionally disposed between the front case 101 and the rear case 102. [

The cases may be formed by injection molding a synthetic resin, or may be formed to have a metal material such as stainless steel (STS) or titanium (Ti) or the like.

The front body 101 mainly includes a display unit 151, an audio output unit 152, a third camera 121c, user inputs 130/131 and 132, a microphone 122, an interface 170, .

The display unit 151 occupies most of the main surface of the front case 101. A sound output unit 151 and a camera 121 are disposed in an area adjacent to one end of both ends of the display unit 151 and a user input unit 131 and a microphone 122 are disposed in an area adjacent to the other end. The user input unit 132 and the interface 170 may be disposed on the side surfaces of the front case 101 and the rear case 102. [

The user input unit 130 is operated to receive a command for controlling the operation of the portable terminal 100 and may include a plurality of operation units 131 and 132. The operation units 131 and 132 may be collectively referred to as a manipulating portion.

The contents inputted by the first or second operation unit 131 or 132 may be variously set. For example, the first operation unit 131 receives commands such as start, end, scroll, and the like, and the second operation unit 132 controls the size of the sound output from the sound output unit 152 or the size of the sound output from the display unit 151 The touch recognition mode can be activated or deactivated.

FIG. 2B is a rear perspective view of the portable terminal shown in FIG. 2A.

Referring to FIG. 2B, a third camera 121c may be additionally mounted on the rear surface of the portable terminal body, that is, the rear case 102. The third camera 121c has a photographing direction substantially opposite to that of the first and second cameras 121a and 121b and may be a camera having the same or different pixels as the first and second cameras 121a and 121b have.

A flash 123 and a mirror 124 may be further disposed adjacent to the third camera 121c. The flash 123 illuminates the subject when the subject is photographed by the third camera 121c. The mirror 124 allows the user to illuminate the user's own face or the like when the user intends to take a picture of himself / herself (self-photographing) using the third camera 121c.

The sound output module 152 'may be further disposed on the rear surface of the portable terminal body. The sound output unit 152 'may implement the stereo function together with the sound output module 152 (see FIG. 2A), and may be used for the implementation of the speakerphone mode during a call.

In addition to the antenna for communication, a broadcast signal receiving antenna 116 may be additionally disposed on the side of the portable terminal body. The antenna 116, which forms part of the broadcast receiving unit 111 (see FIG. 1), may be installed to be able to be drawn out from the terminal body.

A power supply unit 190 for supplying power to the portable terminal 100 is mounted on the terminal body. The power supply unit 190 may be built in the terminal body or may be detachable from the outside of the terminal body.

The rear case 102 may further include a touch pad 135 for sensing a touch. The touch pad 135 may be of a light transmission type for the display unit 151. [ In this case, if the display unit 151 is configured to output the time information on both sides (i.e., in the directions of both the front and back sides of the mobile terminal), the time information can be recognized through the touch pad 135 do. The information output on both sides may be all controlled by the touch pad 135. [

Meanwhile, the display for exclusive use of the touch pad 135 may be separately installed, so that the touch screen may be disposed in the rear case 102 as well.

The touch pad 135 operates in correlation with the display portion 151 of the front case 101. The touch pad 135 may be disposed parallel to the rear of the display unit 151. The touch pad 135 may have a size equal to or smaller than that of the display unit 151.

On the other hand, as smartphones and social network services (SNS) become common, the types and amounts of data generated by billions of users around the world are increasing at an explosive rate, and the awake leaders of government, We are paying attention to data utilization.

The government is also in line with the global trend by introducing public data as a government 3.0 policy and fostering data-based new industries as a new government operating paradigm.

In particular, Big Data is more like a picture that expresses the needs and behaviors of individuals rather than data representing the group, so it is expected to be very useful in all fields that are oriented toward personalized personalized services.

However, the education sector is slow to prepare for data use rather than the public information openness or private business intelligence (Business Intelligence) field.

This does not motivate interested stakeholders and educational services agencies to share data, and the lack of a service model is also a major cause.

Generally, meaningful data is generated by various learning activities using ICT (Information and Communication Technology) in the classroom and online, but these data are discarded or only partially extracted and recorded when the activity or process ends.

Therefore, it is not easy to provide a personalized learning environment or to support level-level learning because it requires data and follow-up activities at the average level in situations where the learner does not understand the level of understanding and process correctly.

For example, in the existing offline education, only the final evaluation data such as the test results are manually recorded, and the meaningful activity record in the learning process is not accumulated, so that it faces the limit for level-specific learning guidance and individual learning .

Moreover, it is difficult to provide personalized feedback, such as learning habits and cognitive level, because it only measures the academic level of students through formal tests.

Therefore, there is a need for new data - based services to overcome these limitations and to provide support and synchronization for individual learners.

This specification proposes a use case that is expected to be provided as a learning analysis service.

In particular, the International Organization for Standardization has initiated efforts to establish the concept of learning analysis and to identify stakeholders in a concrete way, while the private organizations participating in the organizations are making practical efforts such as data collection system, Considering the characteristics of these two approaches, we propose a model to complete personalized learning services using learning analysis techniques.

Learning analysis is basically a concept that includes a whole series of processes that collect, process and analyze data generated by learning activities.

Based on this conceptual understanding, learning analysis can also be understood in the context of a big data workflow that collects and analyzes various types of data.

Analysis services based on most of the data are planned based on accurate understanding of data classification and characteristics in the field. Learning analysis is also very important to understand the data to be collected.

The IMS Global Learning Consortium (IMS Global), an international standardization organization, is actively promoting data identification for learning analysis by classifying the types of data that can be collected and analyzed in the education field for learning analysis into the following categories have

(1) data generated by digital contents (Learning Content Data)

(2) Learning activity data generated through the learning platform

(3) Operational data generated during training programs at educational institutions

(4) Data on career experiences and connections (Career Data)

(5) Data generated during profiling of a learner or a teacher (Profile Data)

Of the five types of data, learning analysis is data that is generated in relation to content utilization and learning activities, which are the focus of attention in learning analysis.

3 shows a specific example of a data model of the education field in connection with the present invention.

That is, FIG. 3 is a diagram illustrating relations between the five data types and representative examples of each data group.

Classification and understanding of the nature and form of these data should be preceded in order to collect data that is generated during learning activities and content utilization that focuses on learning analysis.

For example, data recorded in a database or data in the form of a spreadsheet is classified into structured data. The recording, management, analysis, and charting techniques for such formalized data have been used for a long time and are familiar.

However, the utility value of unstructured data such as system log files, messages, online bulletins, and submitted electronic documents, which have not been noticed in education using ICT including online contents, is newly being highlighted.

The distinction between formalized and non-standardized data is based on the technical difference between data and the method of collecting the data by type and the difference in procedure.

In addition to the differences in the technical form of the data, the classification of the content characteristics of the data to be collected should be defined.

The main reason for classifying the data to be collected according to the characteristics of the contents without collecting the data itself is measures for efficiently constructing the data collection system and improving the quality and accuracy of the data.

For example, considering that learning activities can be performed through a variety of learning platforms or services rather than only in one place, and that the contents and software utilized by the learners are utilized in various platforms and terminals And the need for a systematic data collection system.

4 shows a concrete example of a data matrix for learning analysis in connection with the present invention.

The aforementioned IMS Global, along with various stakeholders, presented the data matrix prototype for learning analysis as shown in Fig.

The left side of FIG. 4 is a group of data generated during a learning activity (or a learning process), and the data on the right side are used to measure an online service provision or a learning outcome, ) Data groups.

In order to analyze the learning, data for the left area and learning activity measurement of FIG. 4 are attracting attention.

Among the content characteristics of these data are expected to include a wide variety of activities such as reading records, lecture notes, quizzes and tests, assignments, project participation, social media usage, and online discussion participation.

In addition, the learning analysis service concept proposed by the present invention will be described.

In the early 2000s, various data were generated by utilizing contents and information through the Internet. However, as mobile devices such as smartphones and tablets become commonplace, data generated from more diverse learning environments is more explosive than ever before .

However, thanks to the development of technology for processing and analyzing large amounts of data, the education system has been able to provide a new opportunity to systematically support learners' learning activities .

UNESCO's report has introduced three levels of collecting and analyzing learning data.

5 shows a concrete example of the concept of fusion between learning analysis levels in connection with the present invention.

That is, FIG. 5 illustrates the concept of convergence between the analysis level and the analysis level.

(1) Micro-level analytics

It is used to track and interpret the learning activity data of individual learners or groups. These data are categorized as the finest and most detailed data in the learning analysis, collecting all collectable data that exists on-and-off-line to diagnose the learner's level of understanding.

(2) Meso-level analytics

It is an institutional level analysis that collects and analyzes data from databases and unstructured data that can be collected to redesign the workflow of educational institutions, diagnose departures of educational service customers, or prepare for future services.

(3) Macro-level analytics

It is possible to accumulate personal and institutional level data to perform macro-level analyzes such as regional, national, and world-level, for example, by using collected data to determine whether local or national curriculum goals are being achieved Expect.

The definition of concept and level of analysis presented above is very abstract.

In order to realize this concept more specifically, it is necessary to identify stakeholders and identify services that each stakeholder can expect.

ISO / IEC JTC1 SC36, an ISO International Organization for Standardization (ISO / IEC JTC1 SC36), outlined the following stakeholder and stakeholder expectations by establishing a working group dedicated to learning analysis technology.

<Learner Perspective>

(1) Support learning by measuring learning activity and progress

(2) Support learning by measuring emotion, motivation, and readiness

(3) (disability, etc.) Individual needs and (medium)

(4) Provide improved feedback through learning activities and assessments

(5) Provide early warning through advance prediction of whether normal learning process can be completed

(6) Personalized learning path generation and learning resource provision

<Teacher Perspective>

(1) Measuring learner and group activity and progress and understanding accurately

(2) Providing customized responses and advice on individual learners' needs and behaviors

(3) Early detection of poor student and group participation

(4) Expanding opportunities and opportunities to measure academic performance

(5) Utilizing visualized information that intuitively expresses learning results for individuals and groups

(6) Ability to design improved learning experiences and resources based on facts

<Educational institution perspective>

(1) Measuring the effectiveness of class and group activities and outcomes

(2) provide monitoring and measurement data on the effectiveness and validity of the learning environment provided by the institution

(3) Provide basic data for establishing strategies for enhancing re-enrollment rates (for higher education and lifelong educational institutions)

(4) Providing basic data for establishing strategies for improving the satisfaction of curriculum

(5) Provide data to support curriculum design

As can be easily deduced from the expectations presented above, there is a precondition that all stakeholders' expectations should first be gathered about the individual's data.

This is a very sensitive issue, as it involves collecting and analyzing data that contains personal information in any form, so anonymity must be guaranteed when thorough privacy policies and techniques are applied, and patterns that use collected data are analyzed. It is a point.

There will be no cases where collecting personal information from any country and analyzing it without the consent of the individual is unacceptable.

Therefore, institutional measures and technology development should be concurrently carried out to resolve the anxiety and concern of stakeholders.

Usually, information systems play a role of filtering or sorting the data scattered around the world into valuable information form.

If this role works well, we can understand complex phenomena simply and clearly.

On the other hand, if the system improperly processes information, important details may be missed.

In the field of learning analysis, there is a similar problem. As the learning analysis system can not express or express some information, there may be a difference in the interpretation power, so that effectiveness and fairness controversy may arise.

The list below lists some of the issues that have recently become a hot topic.

(1) Automated research and research are changing the definition of knowledge

(2) Assertions about objectivity and accuracy are misleading

(3) Data is not always better

(4) Not all data are equivalent

(5) Not everyone behaves ethically when anyone has access to data

(6) Restricted access to big data causes another information gap

In addition to the issues listed above, there is also debate about data neutrality, which is particularly pointed out.

This issue is that the life cycle stages of the learning analysis that follow up to data collection, processing, analysis, and coordination functions are not neutral because they involve judgments based on human expertise or experience.

In other words, it is pointed out that it is a very naive idea to believe that words are expressed in simple sentences that can identify all situations (contexts), and that data speaks for itself.

There is also concern about ethical issues. As mentioned above, learning analysis technology and services basically share personal information and interpret it, which is directly related to information ethics issue.

Unlike in the United States, indiscriminate collection is institutionally impossible because the process of collecting, storing and using personal information is strictly regulated in Korea.

However, because there are differences between what is institutionally impossible and what is technically impossible, ethical issues are taken seriously. The monitoring process should be supported to monitor whether the data is collected through legitimate procedures and whether the collected data is used only within the scope of obtaining prior consent, and the monitoring results should be transparent to each individual. In addition, the ethical issue is pointing out that unethical behaviors such as manipulating data for other purposes in the processing of collected data should also be observed.

The list below summarizes the ethical issues that are most often raised in connection with learning analysis.

(1) Who will judge the value of the log data?

(2) Is personal information cleanly organized as it is combined and accumulated with other data sets?

(3) Is the combined and accumulated data sets objectively comparable? (Issues about whether there are missing omissions or manipulated data)

(4) Who will decide to visualize the data? And does the represented data seem sufficiently interpretable?

(5) Can learners look up their own and peer group analysis results?

(6) Will teachers be able to intervene properly in learning activities based on the analysis results?

(7) Is the collected data sufficiently anonymous? And will data be allowed to be accessed at a reasonable level?

As we have seen so far, expectations and concerns about learning analysis have been raised to similar levels. Although the concept of learning analysis and technology development are relatively early, there seems to be a situation in which the issue of collecting and using personal information continues to emerge. Therefore, expectations and concerns about learning analysis are expected to grow for the time being.

Next, with reference to the present invention, the learning analysis use case will be described in detail.

Over the past 20 years, a wealth of digital materials and learning software have been introduced, attempting various educational methods using ICT at home and abroad.

Including online content, problem banks, games, and social networks.

However, content and services with new technologies are also limited in their support of personalized learning environments and in terms of motivating learners.

Based on these past experiences, notable use cases for learning analysis services based on learning data are presented, and some representative examples are introduced.

(1) Analytics Analysis Dashboard

The log data generated in the learning platform or the learning software is a type of data that is not provided to the general users as data in a highly technical format. Usually, log data was used for limited analysis of data using software for data mining, but it was not provided to end users such as professors or learners because it was processed into visualized formats such as tables and graphs. The learning analysis dashboard function is a function that visualizes and provides the log data to an individual user or a group easily.

In addition to the log data, the analysis dashboard can collect data from a variety of sources, including logs requested in a help desk operated for online learning support, reports submitted in electronic form, correlations between various predefined variables Etc. can be analyzed and visualized in a comprehensive manner. Through the information provided through the analytic dashboard, learners can identify their peers (relative to test scores, forum contributions, on-line seminar attendance / participation level) among peers.

(2) Predictive Analytics

Refers to a method of analyzing users using patterns of learner statistical data such as static data such as demographics or past attainment, dynamic data such as login patterns, and degree of participation in online discussions. Predictive analysis has the advantage of drawing the trajectories of learners at risk or superior levels and suggesting prescription actions at individual time points. For example, a predictive analysis can send a warning message to learners approaching the trajectory of the risk step and guide the activity trajectory to enter the average or superior stage. The most reliable way to judge whether or not you can pass an overall evaluation so far is to judge by taking the test at the beginning of the learning. However, since this method is static and has limitations that do not reflect the learning situation, the predictive analysis method is more effective to judge based on the current status and level of real-time learning.

(3) Adaptive Analytics

An adaptive learning platform is a model that measures learners' understanding of a particular subject (algebra, photosynthesis, dental procedures, etc.), provides detailed feedback, and provides learners with relevant digital resources as a follow up. One way to measure is to diagnose through a curriculum-based test, which is preferred because it is the most reliable method available today. The feature of this model is to diagnose the level of understanding that the learner has reached at the level of the current topic, and to make the adaptive presentation of content. In some cases, it may be necessary to model dynamic learner awareness or adaptive content delivery environments, since content of difficulty levels that the learner can not understand may be omitted. Above all, the model is operational based on a wealth of resources, contrasting with a blob like a traditional learning platform that provides only software functionality. In other words, the platform's emphasis is on functionality, but the platform must start with a rich set of resources.

(4) Social Network Analytics

Social network analysis is a well - known network model. This analytical model is used to help people understand how to form and maintain networks, and the frequency and trends of them can be analyzed in conjunction with the network. People can use social networks to create different types of relationships, ranging from direct affecting relationships to indirect relationships. In the field of education, there is an interest in analyzing whether learner's personal relationship setting or group structure has an effect on effective learning.

(5) Discourse Analytics

Quantitative information such as the number of logins, the number of posts, and the number of message registrations provided by the learning platform is very simple, and it is a natural function from the point of view of learning analysis. Learning analysis requires more than quantitative data, and the instructor needs to be provided with data that can be used to determine the quality contribution of learning activities. Discourse analysis is a model for judging the effectiveness of activities. It is a subject that has been studied for a long time in the field of pattern recognition and parsing technology. Now, there is a situation that can be applied to education field in earnest. Related studies are in the process of analyzing how teachers add essays and discussions, how writing and speaking affect learning, and how computers recognize good arguments.

(6) Assessment using ICT (ICT)

The UNESCO policy contribution distinguishes the evaluation subject from the assessing learning experience and the assessing individual. Among them, the assessment of the learning experience is not an assessment of the learner's performance, It is a process evaluation of whether it is well done. Although this report does not mention the details of the technology, evaluation of the learning experience is an assessment of whether the curriculum or goal is being achieved well, so it can be inferred when the evaluation results of the individual learners' cognitive level are accumulated . This is a topic that needs analysis that corresponds to the meso-level that is presented when explaining the level of learning analysis.

The evaluation using ICT should be able to be applied to the evaluation method of merely selected items or authentic type items or more. To do this, you need to be able to collect and analyze process data so you can make a judgment about how much you have learned and how much you have improved your problem-solving skills. Currently, the only way to consider this is to collect and analyze log data and clickstream data as previously discussed. However, since this method is not sufficient to measure the level, we can consider techniques applied to computer games to overcome the limitations. Stealth assessments can be considered, which is a way to dissolve the evaluation process into an educational program, similar to how performance data is collected, which is an important part of the game. This method is a method of blurring and integrating the evaluation process in the course of learning to eliminate the evaluation burden to learners. Reinterpreted in technical terms, learning analysis that collects and analyzes activity data is an alternative to evaluations that are performed in the traditional test format.

On the other hand, we will explain the learning activity data collection and analysis system on the basis of the above-mentioned contents.

The diversity of the technical or content of the data means that the process or method of collecting the data can be tricky, and a new infrastructure and method are required for data processing for analysis.

First of all, learning data collection and analysis is different from data mining, which is provided only to some decision makers as in the past, and it is necessary to be able to easily monitor data collection process and access to analysis results from learners and teachers who generate data. Data collection systems should be considered.

To embody this new type of data-based analysis service, a workflow design suitable for a new environment should be preceded.

6A shows a specific example of a main workflow for a learning analysis service related to the present invention.

The flow from the data collection system described in FIG. 6A to the processing, analysis, and visualization steps and characteristics of each step are described.

With the development of data collection technology, collection behavior can be implemented in any way, but there is a need to pay particular attention to the next step - data storage and processing.

Any form of data collection and analysis involves the inclusion of personal information so that anonymity must be ensured when analyzing patterns that utilize the environment and collected data that have been thoroughly protected by privacy policies and technologies.

There will be no cases where collecting personal information from any country and analyzing it without the consent of the individual is unacceptable. Therefore, it should be accompanied by the development of q technology that can relieve anxiety and concern of stakeholders.

If institutional devices and stable technologies for learning analysis services are provided, the expected effects are very diverse.

For example, you can expect to benefit from the ability to diagnose individual student learning habits and provide accurate and customized levels of progress checks and referral services.

In an intuitive way, called dashboards, I am motivated and curious about the level of understanding of the individual learners, the relative position within the group, the trajectory of the learners who have successfully completed the learning process in the past, You will be able to give us some information to raise.

6B is a diagram for explaining a foreign case related to learning analysis in connection with the present invention.

Some universities and companies have begun offering and demonstrating similar services, as shown in Figure 6b below.

Learning analysis services are expected to contribute not only to learner but also to teachers' understanding of all students in the class and to enhance understanding of individual learners.

Furthermore, the analysis of data accumulated under the guarantee of anonymity has an expected effect in that it can be extended to a level that can be used to diagnose the school-level education goals and to be used for the education offices and the government to diagnose policies.

In addition, the learning analysis system is expected to be able to infer individual learner's level of understanding without the test in conjunction with the curriculum, and it can control itself by presenting learning materials and contents You will be able to provide a learning path.

In particular, if mobile services are becoming commonplace and considering the learning environment where diverse applications such as digital textbooks, online content question banks, learning software, and social networks are used, the data collection step needs to be designed more specifically.

The feature of the reference model that describes the learning data collection system is that the place where the data is generated first must be structured systematically.

In the case of big data, unstructured data is collected without special rules, and analysis algorithm is applied. In learning analysis, the quality of data and accuracy of analysis result can be improved by targeting qualified data from the collection stage Can be found in.

For example, data generated from a learning platform that manages online content and learning activities, and data generated by an e-book viewer such as a digital textbook are data that is generated elsewhere, but an agent (or API) It should be collected and used in one place.

The information contained in the log file must be integrated into the data collection system while maintaining a consistent user identification system, so it needs to be represented as a data measurement profile.

Data Collection API As can be seen in the endpoint, when data is exposed and collected in compliance with various data measurement profiles in an established data collection environment, all data is collected into the repository of the data analysis system.

Therefore, a standardized data exposure and collection system needs to be highlighted as a key success factor for creating a data ecosystem for learning analysis.

The priority of the international standardization organization and the private organizations that have recognized the importance of the learning data collection system is very high, and the current standard development is under way.

In addition, analyzing learning data and intuitively presenting the current level to individual learners is a much different service than in the past.

However, in order to maximize the effects of collecting and analyzing learning data, it is necessary to provide methods and materials that can complement the individual learners in addition to suggesting areas for improvement.

To do this, you need to take into account available methods other than learning analysis techniques. An alternative is to use linked data.

The National Science Foundation has provided semantic analysis of the curriculum of 50 states in the United States for five years from 2009 to 2014 and has supported research on publishing detailed topics in Linked Data.

The result is called the Achievement Standards Network (ASN) Framework and is currently being expanded to attempt to semantically link the subjects of primary and secondary education curriculums in English-speaking countries such as Australia and UK.

Fig. 7 is a concrete example showing a topic unit connection of a mathematics subject in the ASN Framework.

That is, FIG. 7 is an example showing how the subject units of the mathematics subject are composed among the subject information of the various subjects constituting the ASN Framework.

Each topic is linked by a conceptual subordinate relationship, and since it is published as linked data, a unique identification system is assigned to each topic, so extensibility is considered to be able to link themes between subjects.

In addition, by publishing the topic unit information of the curriculum as Linked data, it is possible to retrieve the required criteria based on the detailed topic as in the case where the curriculum is referred to as the achievement criterion document.

This type of data disclosure can be understood as part of the public information disclosure policy of the government 3.0 in a large framework and it is understood that the understanding of the curriculum limited to only some experts has been provided to a wider range of stakeholders such as parents and students The effect can be expected.

In order for semantically linked Linked Data to be reflected in the learning path of the actual learners, each detailed topic needs to be linked to digital data or content.

Digital data and contents have been used to organize the sharing system so that the metadata can be searched on the Internet so far, and it is expected that the utilization will be improved by linking them to the topic unit of the curriculum.

As with the curriculum, each resource is given a unique identification scheme so that if any topic is relevant, it can be linked repeatedly, which can increase the utilization rate more than any other method.

The US ASN Framework also tries to link digital content to testability, and it is likely to link more content and resources in the future.

Now, if curriculum and digital resources are linked with linked data, it becomes possible to reflect on the results of the learning analysis. If the weakness of the learners' weak points, for example, the figure part of the mathematics subject, is found as a weak point through the learning analysis, it will be possible to construct the learning path as to which of the detailed topics need further understanding.

Learning nodes consist of thematic units. In addition, each learning node has digital resources (image, video, animation) and contents (cyber learning, EBS etc) that can be used for learning. have.

FIG. 8 illustrates a concrete example of a learning path linking learning analysis and linked data technology related to the present invention, and is a drawing illustrating the concept described above.

On the other hand, the results of collecting and analyzing data on learning activities will include meaningful data that can be organized into individual learning portfolios such as reading notes, task submissions, and clipping materials for themes.

For example, if the student records recorded in the NEIS (National Education Information System) are interpreted as the results of the learning activities, the learning data and analysis results used for the learning analysis may be given meaning as intermediate values.

Therefore, if we understand the process and the result, it is expected that the major stakeholders such as learners, teachers, and parents will be able to understand more concrete and insightful, and will also have the effect of giving advice and help.

Learning portfolio management environment linked with learning analysis should also be approached differently from before.

One of the important functions of the cloud service is to support learning activities by classifying the main records and analysis results generated by the students during the learning process and transferring them to the personal storage space and managing them in the form of a portfolio.

This portfolio environment can be expected to enable learners to preserve their learning records as they manage blogs, and to develop them into creative personal works through peer groups and exchange with talented donors.

Among the targeted data, learning data such as learning records such as tasks and collaborative artifacts, personal records such as reading notes, and online activity data such as online discussions and messages can be included. The portfolio environment can easily support systematic management by classifying such data by type . If the learning portfolio is managed systematically, the learner 's records will be able to be published as an e - book - type individual work, and services can be considered to be shared through open distribution systems such as social networks.

9 shows an example of a conceptual configuration of a learning portfolio related to the present invention.

Specifically, FIG. 9 is a drawing of four steps constituting the learning portfolio listed up to now.

The learning portfolio has been studied and structured for most of the time using ICT in the education field, so there are many cases where the learning portfolio consists of six or more steps depending on the viewpoint.

In order to express the abstract concept briefly, this study summarizes the main points in the following four steps, reflecting the social network and the cloud service.

In order for the learning portfolio to have a substantial effect, it is important to be reflected in the learner's learning experience.

If the record and experience are not tied together, it is no different than to forget it after storing it on a removable storage device such as USB.

As records and experience continue to accumulate in the learning portfolio, learners will also be able to recognize their strengths and weaknesses and weaknesses in learning themes, and will also have insights into what will be developed in the future. Previously, the learning process and activities were tailored to the average group, but the learning portfolio can be used to optimize planning and design for individuals and groups.

It is possible to increase the accuracy of the data search and to expect the linked data enough to support such search.

When new learning and activities are carried out, the portfolio can be made public and shared through interfaces such as blogs or social media, which are familiar media formats. An objective evaluation can be expected from feedback from teachers, colleagues, and experts.

After the improvement plan reflecting the feedback collected at the end and the problem diagnosis stage, the cycle that is reflected in the learning experience continues to develop again. As the circulation cycle repeats, the accumulating individual's portfolio can be a small history and can give a great meaning as a record to reflect on oneself.

In particular, as blogs and social media use become more common, creative ideas recorded in a learning portfolio are selectively disclosed by the will of the learner or the teacher, and communities of interest (such as social networks) There are also cases of adopting and realizing.

This experience will help learners to better understand the community and develop creative and practical problem solving skills.

The local governments have asked the students of the local schools to present the solution to the waste disposal of local governments. In fact, the ideas that have been adopted include the cost of consulting and the adoption of local policies.

Private companies have also collaborated with elementary school groups to develop new products. Motorola's R & D department in the United States has developed a StarTAC design, a flip-type mobile phone model, in collaboration with elementary school students.

Similarly, the task of understanding our village is frequently carried out as a collaborative project of students. We need to think about ways to propose a local development strategy or extend the cases adopted by the local government, with the help of talented donors.

First of all, the biggest advantage that can be expected through learning portfolio linked with learning analysis is systematic and accurate aptitude and career counseling.

FIG. 10 shows a specific example of a circulation model of a learning portfolio linked with the learning analysis proposed by the present invention.

Referring to FIG. 10, the diagnosis of the curriculum learning through learning analysis is first introduced to find out the strengths and weaknesses of the subject of the learner, and to motivate and prescribe the learning.

It is expected that the learning portfolio will be an important data for aptitude and career counseling because it can understand the process of changing or developing the interest and interest of learners in addition to subject learning.

To this end, the aptitude and career information needs to be published as linked data so that learners themselves can judge their interests and future hopes based on their learning portfolios. Most parents are very interested in their aptitude and careers, but they do not have enough objective data to identify and use paid counseling.

This phenomenon may lead to differences in opportunity depending on the income gap and may lead to indiscriminate competition due to vague anxiety.

Therefore, providing unconditional tutoring and parents' systematic management of a specific learning attitude, current status, and other learning records in order to resolve vague anxiety will also help strengthen the in-depth communication channel with parents.

For more effective portfolio understanding and communication, a dashboard method that uses an intuitive graphical information presentation method as well as a learning portfolio dashboard service would be appropriate.

A comprehensive analysis of learning activities and learning portfolios is expected to be of great help in searching for aptitude and career information for individuals rather than for groups.

Data-based realistic analysis and intuitive information delivery will help parents eliminate vague anxieties and reduce their dependence on unnecessary private tutoring.

The present invention can also be embodied as computer-readable codes on a computer-readable recording medium. A computer-readable recording medium includes all kinds of recording apparatuses in which data that can be read by a computer system is stored. Examples of the computer-readable recording medium include a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like, and may be implemented in the form of a carrier wave (for example, transmission over the Internet) . In addition, the computer-readable recording medium may be distributed over network-connected computer systems so that computer readable codes can be stored and executed in a distributed manner. And functional programs, codes, and code segments for implementing the present invention can be easily inferred by programmers skilled in the art to which the present invention pertains.

It should be noted that the above-described apparatus and method are not limited to the configurations and methods of the embodiments described above, but the embodiments may be modified so that all or some of the embodiments are selectively combined .

Claims (19)

A system for providing a learning portfolio,
A memory for storing curriculum information and education content information;
A mobile terminal for providing learning to a user using the training course information and the training content information;
A wireless communication unit for receiving feedback information of the user related to the learning from the mobile terminal; And
And a controller for generating analysis data using the training course information, the training content information, and the feedback information,
Wherein the control unit determines the learning guidance information specific to the user using the analysis data and controls the wireless communication unit to transmit the determined learning guidance information to the mobile terminal. The method according to claim 1,
The training course information and the training content information can be changed,
Wherein the wireless communication unit further receives the changed curriculum information and education content information from the outside. The method according to claim 1,
Wherein the training course information comprises:
A learning portfolio system, comprising elementary, middle and high school curriculum, vocational training curriculum, higher education curriculum and foreign curriculum. The method according to claim 1,
The training content information includes:
Academic database information, private database information, overseas education content information, and individual education content information provided by the institute. The method according to claim 1,
The feedback information
Data generated through digital contents, learning activity data information generated through the learning platform, data information generated during the operation of the education program in the educational institution, data information about the user's career and connections, and information during the profiling of the user Wherein the learning information includes at least one of the following: The method according to claim 1,
The criterion for the analysis unit to generate the analysis data using the training course information, the training content information,
Learning activity metrics, contextual criteria, participation criteria, and achievement criteria,
The learning activity measurement standard includes:
Wherein the learning portfolio includes a reading, a lecture, a quiz, a project, a task, a media, a tutorial, a map, an investigation, an evaluation, a collaboration, an annotation, a gaming, a social messaging, a scheduling and a discussion criterion. The method according to claim 1,
Wherein the controller generates analysis data using the training course information, the training content information, and the feedback information,
A learning analysis dashboard method, a predictive analysis method, an adaptive learning analysis method, a social network analysis method, a discourse analysis method, and an evaluation method using ICT. The method according to claim 1,
Wherein the learning guidance information includes:
And the learning information is information for supplementing the weakness of the user determined using the analysis data. The method according to claim 1,
At least one of a short-distance communication and a long-distance communication is used between the mobile terminal and the wireless communication unit,
The local area communication includes ANT, Bluetooth, Radio Frequency Identification (RFID), infrared data association (IrDA), Ultra Wideband (UWB), ZigBee technology,
The long-range communication includes code division multiple access (CDMA), frequency division multiple access (FDMA), time division multiple access (TDMA), orthogonal frequency division multiple access (OFDMA), and single carrier frequency division multiple access The learning portfolio providing system comprising: In a method for providing a learning portfolio,
Storing training course information and training content information;
Providing the user with learning using the training course information and the training content information;
Receiving feedback information of the user associated with the learning from the mobile terminal;
Generating analysis data using the training course information, the training content information, and the feedback information;
Determining learning guidance information specific to the user using the analysis data; And
And transmitting the determined learning guidance information to the mobile terminal. 11. The method of claim 10,
The training course information and the training content information can be changed,
Wherein the wireless communication unit further receives the changed curriculum information and education content information from an external source. 11. The method of claim 10,
Wherein the training course information comprises:
A method for providing a learning portfolio, the method comprising the steps of: (a) providing a learning portfolio comprising an elementary school, a middle school and a high school curriculum, a vocational training curriculum, a higher education curriculum, and an overseas curriculum. 11. The method of claim 10,
The training content information includes:
Academic database information, private database information, overseas education content information, and individual education content information provided by the institute. 11. The method of claim 10,
The feedback information
Data generated through digital contents, learning activity data information generated through the learning platform, data information generated during the operation of the education program in the educational institution, data information about the user's career and connections, and information during the profiling of the user Wherein the learning information includes at least one of the following: 11. The method of claim 10,
The criterion for generating the analysis data using the training course information, the training content information,
Learning activity metrics, contextual criteria, participation criteria, and achievement criteria,
The learning activity measurement standard includes:
Reading, teaching, lecture, quiz, project, assignment, media, teaching, guidance, research, evaluation, collaboration, annotation, gaming, social, messaging, scheduling and discussion criteria. 11. The method of claim 10,
The method of generating analysis data using the training course information, the training content information, and the feedback information,
Learning analysis dashboard method, predictive analysis method, adaptive learning analysis method, social network analysis method, discourse analysis method, and evaluation method using ICT. 11. The method of claim 10,
Wherein the learning guidance information includes:
And the learning information is supplementary to weaknesses of the user determined using the analysis data. 11. The method of claim 10,
Wherein at least one of the local communication and the remote communication is used for the transmission to the mobile terminal or the reception from the mobile terminal,
The local area communication includes ANT, Bluetooth, Radio Frequency Identification (RFID), infrared data association (IrDA), Ultra Wideband (UWB), ZigBee technology,
The long-range communication includes code division multiple access (CDMA), frequency division multiple access (FDMA), time division multiple access (TDMA), orthogonal frequency division multiple access (OFDMA), and single carrier frequency division multiple access Wherein the learning portfolio comprises a plurality of learning portfolios. A recording medium on which a program of instructions executable by a digital processing apparatus to implement a learning portfolio providing method is tangibly embodied and which can be read by the digital processing apparatus,
Wherein the learning portfolio providing method comprises:
Storing training course information and training content information;
Providing the user with learning using the training course information and the training content information;
Receiving feedback information of the user associated with the learning from the mobile terminal;
Generating analysis data using the training course information, the training content information, and the feedback information;
Determining learning guidance information specific to the user using the analysis data; And
And transmitting the determined learning guidance information to the mobile terminal.

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