WO2016114421A1

WO2016114421A1 - Method and service for designing portfolio using learning analysis data on basis of mobile terminal

Info

Publication number: WO2016114421A1
Application number: PCT/KR2015/000346
Authority: WO
Inventors: 조용상; 이재호
Original assignee: 한국교육학술정보원
Priority date: 2015-01-13
Filing date: 2015-01-13
Publication date: 2016-07-21

Abstract

The present invention relates to a method and service for designing a portfolio using learning analysis data on the basis of a mobile terminal. A system for providing a learning portfolio according to an example of the present invention may comprise: a memory for storing education course information and educational content information; a mobile terminal for providing learning to a user using the education course information and educational content information; a wireless communication unit for receiving the user's feedback information associated with the learning from the mobile terminal; and a control unit for generating analysis data using the education course information, the educational content information, and the feedback information, wherein the control unit determines learning guide information specialized for the user using the analysis data and controls the wireless communication unit to transmit the determined learning guide information to the mobile terminal.

Description

Method and service for designing portfolio using learning analysis data based on mobile terminal

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

Terminals such as personal computers, laptops, mobile phones, etc. may be configured to perform various functions. Examples of such various functions include data and voice communication functions, taking pictures or videos through a camera, storing voices, playing music files through a speaker system, and displaying images or videos. Some terminals include additional functionality to play games, while others are implemented as multimedia devices. Moreover, recent terminals can receive a broadcast or multicast signal to watch a video or television program.

In general, terminals may be divided into mobile / portable terminals and stationary terminals according to their mobility. The mobile terminal may be further classified into a handheld terminal and a vehicle mount terminal according to whether a user can directly carry it.

As the terminal functions are diversified, for example, such a terminal is a multimedia player having a complex function such as taking a picture or a video, playing a music or video file, playing a game, or receiving a broadcast. Is being implemented.

In order to support and increase the function of such a terminal, it may be considered to improve the structural part and / or the software part of the terminal.

Meanwhile, as smartphones and social network services (SNS) are becoming more common, the types and amounts of data generated by billions of users around the world are growing at an explosive rate. The focus is on data utilization.

The government is also in line with global trends by presenting a new government operating paradigm to open up public data and foster new industries based on data through government 3.0 policy.

In particular, big data is more like a picture that expresses individual needs and actions, rather than data representing a group, so it is expected to be very useful in all fields for personalized customized service.

However, the education sector is slower to prepare for data utilization than to open public information or private business intelligence.

This has not motivated stakeholders to share data with educational service providers, and the lack of a service model is also a major cause.

In general, meaningful data are generated by various learning activities utilizing Information and Communication Technology (ICT) in the classroom and online, but these data are discarded or partially extracted and recorded and managed when the activity or process is completed.

As a result, it is not easy to provide a personalized learning environment or support learning by level, because the average level of materials and follow-up activities are required in a situation where the learner's level of understanding and process are not accurately understood.

For example, in the existing offline education, only final evaluation data such as test results are recorded by hand, and since meaningful activity records are not accumulated in the learning process, students face limitations for guidance and individual learning by level. .

Moreover, students can only have a well-formed test to measure their academic level, which makes it difficult to provide personalized feedback such as learning habits and cognitive levels.

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

In this specification, we propose a use case that is expected to be provided as a learning analysis service.

In particular, while the International Organization for Standardization has begun efforts to establish the concept of learning analysis and to identify stakeholders in detail, the private organizations in which companies participate have made practical standardization efforts such as data collection systems. Considering the characteristics of these two approaches, we propose a model to complete a personalized learning service using learning analysis technology.

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

Specifically, an object of the present invention is to provide a new service based on data, that is, a use case, to overcome limitations and to support and motivate individual learners.

Technical problems to be achieved in the present invention are not limited to the technical problems mentioned above, and other technical problems not mentioned above will be clearly understood by those skilled in the art from the following description. Could be.

A system for providing a learning portfolio related to an embodiment of the present invention for realizing the above object, the system comprising: a memory for storing curriculum information and educational content information; A mobile terminal providing learning to a user using the curriculum information and educational content information; A wireless communication unit receiving feedback information of the user related to the learning from the mobile terminal; And a controller configured to generate analysis data using the curriculum information, educational content information, and the feedback information, wherein the controller determines the learning guide information specific to the user using the analysis data, and wherein the wireless communication unit The determined learning guide information may be controlled to be transmitted to the mobile terminal.

The curriculum information and educational content information may be changed, and the wireless communication unit may additionally receive the changed curriculum information and educational content information from the outside.

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

The educational content information may include academic database information, private database information, overseas educational content information, and individual educational content information provided by the school.

The feedback information may include data information generated through digital content, learning activity data information generated through a learning platform, data information generated while operating an educational program at an educational institution, data information about the user's career and networking, and It may include data information generated during profiling of the user.

In addition, the criteria for the control unit to generate the analysis data using the curriculum information, educational content information and the feedback information includes a learning activity measurement criteria, contextual criteria, participation criteria and achievement criteria, the learning activity Metrics can include reading, course, quiz, project, assignment, media, teaching, instruction, research, assessment, collaboration, annotation, gaming, social, messaging, scheduling, and discussion criteria.

In addition, the method for the controller to generate the analysis data using the curriculum information, educational content information and the feedback information, learning analysis dashboard method, predictive analysis method, adaptive learning analysis method, social network analysis method, discourse It may include analytical methods and evaluation methods using ICT.

In addition, the learning guide information may be learning guide information for supplementing the weakness of the user determined using the analysis data.

On the other hand, the method for providing a learning portfolio related to an embodiment of the present invention for realizing the above-mentioned problem, the method comprising the steps of: storing the curriculum information and educational content information; Providing, by the mobile terminal, learning to a user using the curriculum information and educational content information; Receiving feedback information of the user related to the learning from the mobile terminal; Generating analysis data using the curriculum information, educational content information, and the feedback information; Determining learning guide information specific to the user using the analysis data; And transmitting the determined learning guide information to the mobile terminal.

The curriculum information and educational content information may be changed, and the wireless communication unit may further include receiving the changed curriculum information and educational content information from the outside.

In addition, the criteria for generating analytical data using the curriculum information, educational content information, and the feedback information include learning activity measurement criteria, contextual criteria, participation criteria, and achievement criteria. Can include reading, courses, quizzes, projects, assignments, media, teaching, instruction, research, assessment, collaboration, annotation, gaming, social, messaging, scheduling, and discussion criteria.

In addition, the method of generating the analysis data using the curriculum information, educational 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 It may include assessment methods using ICT.

On the other hand, in order to perform the learning portfolio providing method related to an example of the present invention for realizing the above-described problem, a program of instructions that can be executed by the digital processing apparatus is tangibly implemented and can be read by the digital processing apparatus. The method of claim 1, wherein the learning portfolio providing method comprises the steps of: storing curriculum information and educational content information; Providing, by the mobile terminal, learning to a user using the curriculum information and educational content information; Receiving feedback information of the user related to the learning from the mobile terminal; Generating analysis data using the curriculum information, educational content information, and the feedback information; Determining learning guide information specific to the user using the analysis data; And transmitting the determined learning guide information to the mobile terminal.

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

Specifically, the present invention may provide a user with a new service based on data, that is, a use case, to overcome limitations and to support and motivate individual learners.

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

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

2A is a front perspective view of an example of a mobile terminal according to the present invention;

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

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

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

5 illustrates a specific example of a conceptual diagram of convergence between learning analysis levels in relation to the present invention.

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

6B is a view for explaining an overseas case related to learning analysis in relation to the present invention.

FIG. 7 illustrates a specific example showing a subject unit connection of a mathematics subject in the ASN Framework.

8 illustrates a specific example of a learning path linking learning analysis and linked data technology related to the present invention.

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

10 illustrates a specific example of a cyclic model of a learning portfolio linked to a learning analysis proposed by the present invention.

Hereinafter, a portable terminal according to the present invention will be described in detail with reference to the drawings. The suffixes "module" and "unit" for components used in the following description are given or used in consideration of ease of specification, and do not have distinct meanings or roles from each other.

The portable terminal described in the present specification may include a mobile phone, a smart phone, a laptop computer, a digital broadcasting terminal, a personal digital assistant (PDA), a portable multimedia player (PMP), a navigation device, and the like. However, it will be readily apparent to those skilled in the art that the configuration according to the embodiments described herein may also be applied to fixed terminals such as digital TVs, desktop computers, and the like, except when applicable only to portable terminals.

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

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

The mobile 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, and an interface. The unit 170, the controller 180, and the battery 190 may be included. The components shown in FIG. 1 are not essential, so 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 mobile terminal 100 and the wireless communication system or between the mobile terminal 100 and a network in which the mobile 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, a location information module 115, and the like. .

The broadcast receiving module 111 receives a broadcast signal 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 mean a server that generates and transmits a broadcast signal and / or broadcast related information or a server that receives a previously generated broadcast signal and / or broadcast related information and transmits the same to a terminal. The broadcast signal may include not only a TV broadcast signal, a radio broadcast signal, and a data broadcast signal, but also a broadcast signal having a data broadcast signal combined with a TV broadcast signal or a radio broadcast signal.

The broadcast related information may mean information related to a broadcast channel, a broadcast program, or 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, it may exist in the form of Electronic Program Guide (EPG) of Digital Multimedia Broadcasting (DMB) or Electronic Service Guide (ESG) of Digital Video Broadcast-Handheld (DVB-H).

The broadcast receiving module 111 may include, for example, Digital Multimedia Broadcasting-Terrestrial (DMB-T), Digital Multimedia Broadcasting-Satellite (DMB-S), Media Forward Link Only (MediaFLO), and Digital Video Broadcast (DVB-H). Handheld), DVB-CBMS, OMA-BCAST, and ISDB-T (Integrated Services Digital Broadcast-Terrestrial) can be used to receive digital broadcast signals. Of course, the broadcast receiving module 111 may be configured to be suitable for not only the above-described digital broadcasting system but also other broadcasting systems.

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 a wireless signal with 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 according to transmission and reception of a voice call signal, a video call call signal, or a text / multimedia message. In addition, 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 provision of the 3D web page selected by the user. And a signal including a 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 embedded or external to the mobile terminal 100. In addition, the wireless internet module 113 connects communication with the 3D web providing server 700 under the control of the controller 180 and transmits a signal for requesting the provision of the 3D web page selected by the user. And a signal including a 3D web page according to the request from the 3D web providing server 700. As the technology of the wireless Internet, WLAN (Wireless LAN) (Wi-Fi), Wibro (Wireless broadband), Wimax (World Interoperability for Microwave Access), HSDPA (High Speed Downlink Packet Access), etc. may be used.

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

The location information module 115 is a module for acquiring the location of the mobile terminal 100, and a representative example thereof is a GPS (Global Position System) module. According to the current technology, the GPS module 115 calculates distance information and accurate time information away from three or more satellites, and then applies trigonometric methods to the calculated information, thereby providing three-dimensional chords according to latitude, longitude, and altitude. The location information can be calculated accurately. Currently, a method of calculating position and time information using three satellites and correcting the error of the calculated position and time information using another satellite is widely used. In addition, the GPS module 115 may calculate speed information by continuously calculating the current position in real time.

Referring to FIG. 1, the A / V 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 call mode or the photographing mode. The processed image frame may 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 according to the use environment.

For example, the camera 121 may be provided with 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. The third camera 121c for self-photographing of the user may be provided in a portion of the surface where the display unit 151 of the terminal 100 is provided.

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

The microphone 122 receives an external sound signal by a microphone in a call mode, a recording mode, a voice recognition mode, etc., and processes the external sound signal into electrical voice data. The processed voice data may be converted into a form transmittable to the mobile communication base station through the mobile communication module 112 and output in the call mode. The microphone 122 may implement various noise removing algorithms for removing noise generated in the process of receiving an external sound signal.

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

The user input unit 130 may receive a signal from a user, which designates two or more contents among contents displayed according to the present invention. The signal specifying two or more contents may be received through a touch input or may be received through a hard key and a soft key input.

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

As described above, the user input unit 130 may be composed of a direction key, a key pad, a dome switch, a touch pad (static pressure / capacitance), a jog wheel, a jog switch, and the like.

The sensing unit 140 detects a current state of the mobile terminal 100 such as an open / closed state of the mobile terminal 100, a position of the mobile terminal 100, presence or absence of a user contact, orientation of the mobile terminal, acceleration / deceleration of the mobile terminal, and the like. To generate 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, whether the slide phone is opened or closed may be sensed. In addition, whether the battery 190 is supplied with power or whether the interface unit 170 is coupled to an external device may be sensed. The sensing unit 140 may include a proximity sensor 141. The proximity sensor 141 will be described later with reference to a touch screen.

The output unit 150 is used to generate an output related to visual, auditory or tactile senses, which includes a display unit 151, an audio output module 152, an alarm unit 153, a haptic module 154, and a projector module ( 155) may be included.

The display unit 151 displays (outputs) information processed by the mobile terminal 100. For example, when the mobile terminal is in a call mode, a user interface (UI) or a graphic user interface (GUI) related to a call is displayed. When the mobile terminal 100 is in a video call mode or a photographing mode, the mobile terminal 100 displays a photographed and / or received image, a UI, and a GUI.

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 the general display device 151a as shown in FIG. 5. The optical parallax barrier 50 may be operated using the switch liquid crystal 151b to control the traveling direction of the light as shown in FIG. 5A to separate the light to reach the left and right eyes. Therefore, when a combination image of the right eye image and the left eye image is displayed on the display device 151a, the user's point of view of the image corresponding to each eye is felt as if displayed in three dimensions.

That is, 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 under the control of the controller 180. Perform a normal 2D display operation.

In addition, the display unit 151 drives the switch liquid crystal 151b, the optical parallax barrier 50, and the display device 151a in the 3D display mode under the control of the controller 180. 3D display operation is performed by driving only 151a.

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

Meanwhile, the display unit 151 may be a liquid crystal display (LCD), a thin film transistor-liquid crystal display (TFT LCD), or an organic light-emitting diode (OLED). The display device may include at least one of a flexible display and a 3D display.

Some of these displays can be configured to be transparent or light transmissive so that they can be seen from the outside. This may be referred to as a transparent display. A representative example of the transparent display is TOLED (Transparant OLED). The rear structure of the display unit 151 may also be configured as a light transmissive structure. With this structure, the user can see the 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 implementation form of the mobile terminal 100. For example, the plurality of display units may be spaced apart or integrally disposed on one surface of the portable terminal 100, or may be disposed on different surfaces.

When the display unit 151 and a sensor for detecting a touch operation (hereinafter, referred to as a touch sensor) form a mutual layer structure (hereinafter referred to as a touch screen), the display unit 151 may be configured in addition to an output device. Can also be used as an input device. The touch sensor may have, for example, a form of a touch film, a touch sheet, a touch pad, or the like.

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

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

The proximity sensor 141 may be disposed in an inner region of the mobile terminal surrounded by the touch screen or near 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 an object present in the vicinity without using a mechanical contact by using an electromagnetic force or infrared rays. Proximity sensors have a longer life and higher utilization than touch sensors.

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

Hereinafter, for convenience of explanation, the act of allowing the pointer to be recognized without being in contact with the touch screen so that the pointer is located on the touch screen is referred to as a "proximity touch", and the touch The act of actually touching the pointer on the screen is called "contact touch." The position where the proximity touch is performed by the pointer on the touch screen refers to a position where the pointer is perpendicular to the touch screen when the pointer is in proximity proximity.

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

The sound 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, a call mode or a recording mode, a voice recognition mode, a broadcast reception mode, and the like. The sound output module 152 may also output a sound signal related to a function (eg, a call signal reception sound, a message reception sound, etc.) performed by the portable terminal 100. The sound output module 152 may include a receiver, a speaker, a buzzer, and the like.

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

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

In addition to vibration, the haptic module 154 may be configured to provide a pin array that vertically moves with respect to the contact skin surface, a jetting force or suction force of air through the jetting or suction port, grazing to the skin surface, contact of the electrode, electrostatic force, and the like. Various tactile effects can be generated, such as effects by the endothermic and the reproduction of a sense of cold using the elements capable of endotherm or heat generation.

The haptic module 154 may not only deliver the haptic effect through direct contact, but also may implement the user to feel the haptic effect through a muscle sense such as a finger or an arm. Two or more haptic modules 154 may be provided according to a configuration aspect of the mobile terminal 100.

The projector module 155 is a component for performing an image project function using the portable terminal 100 and is the same as an image displayed on the display unit 151 according to a control signal of the controller 180. Or at least partially different images may be displayed on an external screen or wall.

In detail, the projector module 155 may include a light source (not shown) for generating light (for example, laser light) for outputting the image to the outside, and an image for output to the outside using the light generated by the light source. And an image generating means (not shown), and a lens (not shown) for expanding and outputting the image to the outside at a predetermined focal length. In addition, the projector module 155 may include an apparatus (not shown) which may mechanically move the lens or the entire module to adjust the image projection direction.

The projector module 155 may be divided into a cathode ray tube (CRT) module, a liquid crystal display (LCD) module, a digital light processing (DLP) module, and the like, according to the device type of the display means. In particular, the DLP module may be advantageous in miniaturization of the projector module 151 by expanding and projecting an image generated by reflecting light generated from a light source to a digital micromirror device (DMD) chip.

Preferably, the projector module 155 may be provided in the longitudinal direction on the side, front, or back of the portable terminal 100. Of course, the projector module 155 may be provided at any position of the mobile terminal 100 as necessary.

The memory 160 may store a program for processing and controlling the controller 180, and input / output data (for example, a phone book, a message, an audio, a still image, an e-book, a video, a transmission / reception message). Function for temporary storage of history, etc.). The memory 160 may also store a frequency of use of each of the data (eg, a phone number, a message, and a frequency of use of each multimedia). In addition, the memory unit 160 may store data regarding vibration and sound of various patterns output when a touch input on the touch screen is performed.

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

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). ), Random Access Memory (RAM), Static Random Access Memory (SRAM), Read-Only Memory (ROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Programmable Read-Only Memory (PROM), Magnetic At least one type of storage medium may include a memory, a magnetic disk, and an optical disk. The mobile 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 with all external devices connected to the mobile terminal 100. The interface unit 170 receives data from an external device, receives power, transfers the power to each component inside the mobile terminal 100, or transmits data inside the mobile terminal 100 to an external device. For example, wired / wireless headset ports, external charger ports, wired / wireless data ports, memory card ports, ports for connecting devices with identification modules, audio input / output (I / O) ports, The video input / output (I / O) port, the earphone port, and the like may be included in the interface unit 170.

The identification module is a chip that stores various types of information for authenticating the use authority of the mobile terminal 100, and includes a user identification module (UIM), a subscriber identification module (SIM), and a universal user authentication module ( Universal Subscriber Identity Module (USIM), and the like. A device equipped with an identification module (hereinafter referred to as an 'identification device') may be manufactured in the form of a smart card. Therefore, the identification device may be connected to the terminal 100 through a port.

The interface unit may be a passage through which power from the cradle is supplied to the portable terminal 100 when the portable terminal 100 is connected to an external cradle, or various command signals inputted from the cradle by a user may be carried. It may be a passage that is delivered to the terminal. Various command signals or power input from the cradle may be operated as signals for recognizing that the portable terminal is correctly mounted in the cradle.

The controller 180 typically controls the overall operation of the mobile terminal. For example, perform related control and processing for voice calls, data communications, video calls, and the like. The controller 180 may include a multimedia module 181 for playing multimedia. The multimedia module 181 may be implemented in the controller 180 or may be implemented separately from the controller 180.

The controller 180 may perform a pattern recognition process for recognizing a writing input or a drawing input performed on the touch screen as text and an image, respectively.

Meanwhile, when the display unit 151 is provided with an organic light-emitting diode (OLED) or a TOLED (Transparant OLED), the controller 180 is input through the camera 121 according to the present invention. When the preview image is pulled up and displayed on the screen of the organic light-emitting diode (OLED) or TOLED (Transparant OLED), when the size of the preview image is adjusted according to a user's operation, the size is displayed on the screen. The power consumption of the power supplied from the power supply unit 190 to the display unit 151 may be reduced by turning off the driving of the pixels in the second area except the first area in which the adjusted preview image is displayed.

The power supply unit 190 receives an external power source and an internal power source under the control of the controller 180 to supply power for operation of each component.

Various embodiments described herein may be implemented 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 include application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), and the like. It may be implemented using at least one of processors, controllers, micro-controllers, microprocessors, and electrical units for performing other functions. The described embodiments may be implemented by the controller 180 itself.

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

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

The body includes a casing (casing, housing, cover, etc.) that forms an exterior. In this embodiment, the case may be divided into a front case 101 and a rear case 102. Various electronic components are built in the space formed between the front case 101 and the rear case 102. At least one intermediate case may be further disposed between the front case 101 and the rear case 102.

The cases may be formed by injecting synthetic resin or may be formed of a metal material, for example, a metal material such as stainless steel (STS) or titanium (Ti).

The mobile terminal body, mainly the front case 101, includes a display unit 151, an audio output unit 152, a third camera 121c, a user input unit 130/131, 132, a microphone 122, an interface 170, and the like. Can be arranged.

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

The user input unit 130 is manipulated 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

manipulation units

131 and 132 may also be collectively referred to as a manipulating portion.

The content input by the first or

second manipulation units

131 and 132 may be variously set. For example, the first manipulation unit 131 receives a command such as start, end, scroll, and the like, and the second manipulation unit 132 adjusts the volume of the sound output from the sound output unit 152 or displays 151. Command, such as activating / deactivating the touch recognition mode.

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 of the portable terminal body, that is, the rear case 102. The third camera 121c may be a camera having a photographing direction substantially opposite to the first and

second cameras

121a and 121b and having the same or different pixels as the first and

second cameras

121a and 121b. have.

The flash 123 and the mirror 124 may be further disposed adjacent to the third camera 121c. The flash 123 shines light toward the subject when the subject is photographed by the third camera 121c. The mirror 124 allows the user to see his / her own face or the like when the user wishes to photograph (self-photograph) the user using the third camera 121c.

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

In addition to the antenna for a call or the like, an antenna 116 for receiving a broadcast signal may be additionally disposed on the side of the portable terminal body. The antenna 116 constituting a part of the broadcast receiving unit 111 (refer to FIG. 1) may be installed to be pulled out from the terminal body.

The terminal body is equipped with a power supply unit 190 for supplying power to the portable terminal 100. The power supply unit 190 may be built in the terminal body or may be directly detachable from the outside of the terminal body.

The rear case 102 may be further equipped with a touch pad 135 for sensing a touch. The touch pad 135 may be configured to be light transmissive for the display unit 151. In this case, if the display unit 151 is configured to output visual information on both sides (i.e., in the direction of both the front and rear surfaces of the mobile terminal), the visual information may be recognized through the touch pad 135. do. The information output on both surfaces may be controlled by the touch pad 135.

Meanwhile, since a display dedicated to the touch pad 135 is separately installed, the touch screen may be disposed on the rear case 102.

The touch pad 135 operates in association with the display unit 151 of the front case 101. The touch pad 135 may be disposed in parallel to the rear of the display unit 151. The touch pad 135 may have the same or smaller size as the display unit 151.

Learning analysis is basically a concept that includes a whole series of processes for collecting, processing, and analyzing data generated by learning activities.

Based on this conceptual understanding, learning analysis can also be understood in the same context as big data workflows that collect and analyze various types of data.

Most data-based analysis services are designed based on an accurate understanding of the data classification and characteristics of the field. Learning analysis is also very important for understanding the data to be collected.

The IMS Global Learning Consortium (IMS Global), an international standardization organization, is actively pursuing data analysis for learning analysis by dividing the types of data that can be collected and analyzed in the education field for learning analysis into five types as listed below. have

(1) Learning Content Data

(2) Learning Activity Data generated through the Learning Platform

(3) Operational data generated during the operation of educational programs at educational institutions

(4) Career Data on Learner's Career and Network

(5) Profile data generated during profiling of learner or instructor

Of the five types of data, learning analytics is the data that is generated in the context of learning analysis.

That is, FIG. 3 illustrates the relationship between the five data types and representative examples of each data group.

In order to collect content generated during learning activities and content utilization focused on learning analysis, classification and understanding of characteristics and forms of these data must be preceded.

For example, data recorded in a database or data in a spreadsheet form are classified as structured data. The recording, management, analysis and tabulation techniques for these formal data have been used for a long time and are familiar.

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

The distinction between structured data and unstructured data is classified into technical forms, which can be attributed to differences in methods and procedures for collecting data by type.

In addition to the differences in the technical form of the data, a 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 rather than collecting them by itself is to effectively organize the data collection system and to improve the quality and accuracy of analysis.

For example, given that learning activities can be performed through multiple learning platforms or services instead of only one place, and the content or software used by the learner is not used in one place but in multiple platforms or terminals, Empathizes with the need for a systematic data collection system.

IMS Global, mentioned above, presented a prototype of the data matrix for learning analysis as shown in FIG. 4 with various stakeholders.

The left side of FIG. 4 is a data group generated during a learning activity (or a learning process), and the data on the right side is used for measuring online service provision or learning outcome (mostly recorded in a database). ) A list of data groups.

For the analysis of learning, the left area of FIG. 4, data for measuring learning activity are attracting attention.

The nature of these data is expected to include a wide variety of types of activities, including reading records, lecture records, quizzes and tests, assignments, project participation, social media use, and online discussions.

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

In the early 2000s, various data were being generated while using contents and information through the Internet, but data generated from a more diverse learning environment has become more explosive than ever before as mobile devices such as smartphones and tablets have become commonplace. .

Until now, this rapidly growing data has been recognized as heterogeneous data and managed or discarded separately.However, thanks to the development of technology that processes and analyzes large amounts of data, the educational community has a new opportunity to systematically support learning analysis. Began to accept.

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

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

(1) Micro-level analytics

It is used to track and interpret activity data of individual learners or groups. These data are classified as the finest and most detailed data in the learning analysis, which collects all collectable data that exists online and offline to diagnose the learner's level of understanding.

(2) Meso-level analytics

Institutional analysis, which collects and analyzes data from databases and collectable atypical data to redesign educational workflows, proactively diagnose deviations from educational services customers, or prepare for future services.

(3) Macro-level analytics

It is to accumulate individual and institutional data and conduct macroscopic analysis of regional, national and global levels. For example, it is possible to diagnose whether regional or national curriculum goals are being achieved using collected data. Expect.

The concept of learning analysis and the definition of the level of analysis introduced above are very abstract.

To realize this concept more concretely, it is necessary to identify stakeholders and identify services that can be expected for each stakeholder.

The ISO / IEC JTC1 SC36 (ISO / IEC JTC1 SC36), an international standardization organization, established a working group dedicated to learning and analysis technology, and summarized the following stakeholders and their expectations.

<Learner's Perspective>

(1) Support learning by measuring learning activity and progress

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

(3) Organize the learning environment by identifying in advance the needs of the individual (disability, etc.) and (media) preferences

(4) Provide improved feedback through learning activities and assessments

(5) Provide early warning by predicting whether the normal learning process can be completed

(6) Create personalized learning paths and provide learning resources

Teacher Perspective

(1) Measure learner and group activities and progress for accurate understanding

(2) provide tailored responses and advice on the needs and behaviors of individual learners;

(3) Early detection of underperforming students and groups

(4) To expand methods and opportunities for measuring academic performance

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

(6) Ability to design fact-based improved learning experiences and resources

Educational Perspective

(1) measuring 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) Providing basic data for establishing strategies for improving re-enrollment rate (for higher and lifelong educational institutions)

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

(5) Providing data to support curriculum design

As can be easily deduced from the expectations presented above, there is a precondition that all stakeholder expectations must first be able to collect data on individuals.

This is a very sensitive matter, because it collects and analyzes data that contains personal information in any form, so that anonymity must be guaranteed when analyzing the environment in which strict privacy policies and technologies are applied and patterns that utilize the collected data. Is the point.

Regardless of the country, the collection of personal information and the analysis without personal consent will not be tolerated.

Therefore, institutional measures and technology development that can resolve the anxiety and concern of stakeholders should be combined.

Information systems usually filter or classify data scattered around the world and process it into valuable information.

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

On the other hand, if the system misprocesses the information, it may miss important details.

In the field of learning analysis, a similar problem is faced, and the effectiveness of analysis and fairness may arise because of differences in interpretation power depending on what information the learning analysis system does or does not represent.

The list below lists some of the issues that are currently under issue.

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

(2) Claims of objectivity and accuracy are misleading

(3) A lot of data is not always better

(4) Not all data is equivalent

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

(6) Limited access to big data leads to another information gap

In addition to the issues listed above, there is also controversy over data neutrality, which is particularly serious.

This issue is not neutral because each stage of the life cycle of learning analytics, from data collection, processing, analysis, and coordination, involves judgment based on human expertise and experience.

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

In addition, there are concerns about ethical issues. As mentioned above, learning analysis technologies and services are basically related to information ethics because they share and interpret personal information.

Unlike in the United States, domestic conditions are strictly regulated in the process of collecting, storing, and using personal information.

However, ethical issues are taken seriously because there is a difference between institutionally impossible and technically impossible. Monitoring procedures should be supported to ensure that data is collected primarily through legitimate procedures and that the collected data are only used within the scope of prior consent, and the results of the monitoring should be transparent to each individual. In addition, ethical issues point out that in the process of processing the collected data, unethical behaviors such as manipulating the data for other purposes must also be observed.

The following list summarizes the ethical issues that arise mainly in learning analytics.

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

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

(3) Are the combined and accumulated data sets objectively comparable? (Issue with no intentional missing or manipulated data)

(4) Who will decide to present the data visually? And does the data presented seem sufficiently interpretable?

(5) Can learners access the results of their own and peer group analyzes?

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

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

As introduced so far, expectations and concerns for learning analytics are being raised at similar levels. Although the concept of learning analysis and the development of skills are relatively early, the background of the voice of concern seems to be due to the recent emergence of issues related to the collection and use of personal information. Therefore, expectation and concern about learning analysis will grow together for the time being.

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

Over the past two decades, various digital methods and learning software have been introduced while attempting various educational methods using ICT at home and abroad.

Among them are examples of the latest technologies, including online content, question banks, games and social networks.

However, experiences that have been somewhat limited in terms of supporting personalized learning environments and motivating learning are also disappointing.

Based on these past experiences, notable use cases for learning analytics services based on learning data are suggested. Here are some representative examples.

(1) Analytics Analytics Dashboard

Log data that occurs on a learning platform or learning software is a very technical format of data that is not available to end users. Although log data is usually used to analyze data using software for data mining, it is not information provided to end users such as instructors or learners because it is processed into visualized formats such as tables and graphs. The learning analytics dashboard feature visualizes log data to individual users or groups for easy understanding.

In addition to log data, analytics dashboards can collect and present data from a variety of sources, including logs requested to helpdesks operated for online learning support, reports submitted in electronic form, and correlations between various preset variables. Etc. can be comprehensively analyzed and visualized. Through the information provided through the analytics dashboard, learners can also identify their relative position among peer groups (relative to test scores, forum contributions, and on / offline participation in online and offline seminars).

(2) Predictive Analytics

A method of analyzing a user using patterns of learner statistical data such as static data such as demographics or past achievements, and dynamic data such as login patterns and participation in online discussions. Predictive analysis has the advantage of drawing the trajectories of learners at risk or storm level and suggesting precautionary measures when needed individually. For example, predictive analytics can deliver warning messages to learners approaching the trajectory of a risk phase and guide the activity trajectory to enter an average or stormwater level. Until now, the most reliable way to determine whether you can pass a global assessment has been to take a test at the beginning of learning. However, since this method is static and does not reflect the learning status, the predictive analysis method is more effective to judge based on the real-time learning status and level.

(3) Adaptive Analytics

An adaptive learning platform is a model that provides detailed feedback by measuring learners' understanding of a particular subject (algebra, photosynthesis, dental procedures, etc.) and providing relevant digital resources to learners as follow-up. One method of measurement is to make a diagnosis based on a curriculum-based test, which is the preferred method because it is the most reliable method of current technology. The feature of this model is to diagnose what level of understanding the learner currently has on the chosen topic and to present the appropriate presentation of content. In some cases, content of difficulty that the learner cannot understand may be omitted, so modeling of dynamic learner recognition or adaptive content delivery environment is necessary. Best of all, this model is run from a rich resource, and contrasts with an empty bottle that provides only software features like a traditional learning platform. In other words, the functionality of the platform is emphasized, but the platform must start with abundant resources.

(4) Social Network Analytics

Social network analysis is a well-known form of network analysis model. This analytical model is used to help people understand how to build and maintain a network, and can also analyze the frequency or trend of a topic in conjunction with the network. People can form different types of relationships using social networks, and the degree and scope of relationship establishment are diversifying, from direct-influenced ones to indirect ones. In the field of education, the main concern is the establishment of learners' personal relationships and the analysis of the effect of group structure on effective learning.

(5) Discourse Analytics

Quantitative information such as the number of logins, article views, and message registrations provided by the learning platform is very simple, and it is a natural function from a learning analysis point of view. Learning analysis needs more than quantitative data, and instructors need to be provided with data to determine the quality contribution of learning activities. Discourse analysis is a model for judging the substance of activities. It is a topic that has been studied for a long time in the field of pattern recognition and parsing technology, and it is now creating conditions for full-scale application to education. 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 debate.

(6) Assessment using ICT

UNESCO's policy contributions categorize the subjects of assessment into an assessment of learning experience and an assessment of an individual, among which assessment of learning experience is not an assessment of the learner's performance. It's a process assessment of how well it's done. Although this report does not mention specific technical details, the assessment of learning experience is to assess whether the curriculum or objectives are well being achieved, which can be inferred when accumulating the results of individual learners' cognitive levels. Can be. This is a topic that needs to be analyzed at the Meso-level presented when explaining the level of learning analysis.

Evaluation using ICT should be able to be applied to the evaluation method more than just selective questions or authentic questions. To do this, process data must be collected and analyzed so that the learner can judge how much they have learned and how much they have improved their problem-solving skills. The current consideration is to collect and analyze log data and clickstream data as previously considered. However, because this method is not sufficient to measure levels, we can consider techniques applied to computer games to overcome the limitations. Stealth assessments can be considered, incorporating an assessment process into an educational program, similar to performance data collection, which is an important part of the game. This is a method that integrates the process of evaluation by blurring and integrating the process of evaluation to remove the burden of evaluation on the learner. In technical terms, learning analysis, which collects and analyzes activity data, replaces traditional assessments.

Meanwhile, the learning activity data collection and analysis system will be described in detail based on the above description.

The variety of technical or content forms of the data means that the process or method of collecting the data can be tricky, and data processing for analysis requires new infrastructure and methods.

Above all, unlike the data mining that is provided only to some decision makers as in the past, the learning data collection and analysis takes into account the characteristics that learners and teachers who generate data should easily monitor the data collection process and access the analysis results. Consideration should be given to the data collection system.

In order to materialize this new type of data-based analysis service, a workflow design suitable for a new environment must be preceded.

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

Advances in data collection technology may enable the collection to be implemented in any way, but the next step, storage and processing, requires special attention.

Any form of collection and analysis of data containing personal information is required to ensure anonymity when analyzing the environment in which strict privacy policies and technologies are applied and the patterns using collected data.

Regardless of the country, the collection of personal information and the analysis without personal consent will not be tolerated. Therefore, q technology development should be parallel to resolve stakeholder anxiety and concerns.

If institutional arrangements and stable technologies for learning analytics services are in place, the expected effects vary.

For example, one can expect the benefits of diagnosing individual student learning habits and providing accurate, level-specific and customized services.

Inspire your learners with motivation and curiosity, including the level of understanding of individual learners, their relative position within the group, the trajectories of learners who have successfully completed their learning process in the past, and a comparison of my current situation. It can give you information to raise.

Some universities and companies have begun to offer similar services as pilots. Figure 6b below summarizes a representative example.

Learning analytics services are expected to make a significant contribution not only to learners, but also to teachers' understanding of individual students, as well as for the whole class.

Furthermore, the data analysis accumulated under the anonymity guarantee has the expectation that it can be extended to the diagnosis of school-level educational goals and to the level that can be used by the DOE and the government to diagnose policies.

In addition, the learning analysis system is expected to be able to infer the level of understanding of individual learners without a test in connection with the curriculum, and can be adjusted by presenting learning materials and contents that can identify and improve the weak points of learners. Provide a learning path.

In particular, considering the learning environment in which mobile services are universal and various applications such as digital textbooks, online content problem banks, learning software, and social networks are used, the data collection step needs to be designed more specifically.

The characteristic of reference model that describes learning data collection system is that the place where data is generated should be organized systematically.

In the case of big data, unstructured data is collected without special rules and analysis algorithms are applied, whereas in learning analysis, data quality and accuracy of analysis results can be improved by targeting qualified data from the collection stage. You can find the difference at

For example, data generated by a learning platform that manages online content and learning activities and data generated by e-book viewers, such as digital textbooks, are generated from different sources, but may be agents that collect data. To be gathered in one place.

The information contained in the log files also needs to be represented in the data measurement profile because the information contained in the log files must be integrated into the data collection system while maintaining a consistent user identification system.

As can be seen from the data collection API endpoint, when data exposure and collection process complying with various data measurement profiles is performed in the data collection environment where the authentication scheme is established, all data is collected into the storage of the data analysis system.

Thus, standardized data exposure and collection systems need to be identified as key success factors for creating a data ecosystem for learning analysis.

Recognizing the importance of the learning data collection system, international standards organizations and private organizations are focusing on this topic.

In addition, the analysis of the learning data to present the current level intuitively to individual learners can be said to be a very different service from the past.

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

To do this, it is necessary to consider other available methods in addition to the learning analysis technique. An alternative method is to use linked data.

For five years from 2009 to 2014, the National Science Foundation supported research that semantically analyzed curricula in 50 US states and published detailed topics as linked data.

The result, called the ASN (Achievement Standards Network) Framework, is now expanding to attempt to semantically link the subjects of elementary and secondary curriculum in English-speaking countries such as Australia and the United Kingdom.

That is, FIG. 7 illustrates an example of how each subject unit of a mathematics subject is configured among subject information of various subjects of the ASN Framework.

Each subject is connected in a conceptual dependency relationship, and published as linked data, each subject is given a unique identification system, and scalability is also considered to enable subject linkage between subjects.

In addition, when the subject unit information of the curriculum is published as linked data, it is possible to search the necessary requirement criteria in detail subject units as if the information was searched on the Internet in the way that the curriculum was accessed as the achievement standard document.

This approach to data disclosure can also be understood as part of the government's public policy openness policy in 3.0 and provides a broader stakeholder, including parents and students, with an understanding of the curriculum that has so far been limited to some experts. You can expect the effect to be.

In order for linked data semantically linking the curriculum to be reflected in the learner's learning path, each detailed subject needs to be linked to digital materials or content.

Until now, digital materials and contents have been used to form a shared system that can be searched on the Internet by granting metadata. In the future, it is expected to improve utilization by connecting to thematic units of the curriculum.

Like the curriculum, each resource is given a unique identification system, which can be linked repeatedly if it is relevant to any topic, increasing the opportunities for use over any previous method.

The ASN Framework in the US has also piloted the possibility of connecting digital content to the public, and is expected to link more content and resources in the future.

Now, if curricula and digital resources are linked with linked data, they can be reflected in learning analytics. If the learner's weaknesses are found as weaknesses in the mathematics department through learning analysis, it is possible to construct a learning path of which detailed topics of the figures are more necessary.

Learning nodes are organized by topic, and each learning node has digital resources (images, videos, animations) and contents (cyber learning, EBS, etc.) that can be used for learning. have.

FIG. 8 illustrates a specific example of a learning path linking learning analysis and linked data technology related to the present invention, and is a graphical representation of the aforementioned concept.

On the other hand, the data collected and analyzed for learning activities are expected to include meaningful materials that can be managed and organized into an individual's learning portfolio, such as reading notes, assignment submissions, and subject clipping materials.

For example, if the student record recorded in the National Education Information System (NEIS) is interpreted as the result of the learning activity, the learning data and the analysis result used for the learning analysis may have a mean value.

Therefore, if we understand the process and the result, it is expected that the major stakeholders such as learners, teachers, parents, etc. will not only have a more specific and insightful understanding but also double the effect of giving or receiving advice or help.

The learning portfolio management environment in conjunction with learning analytics should also be approached differently than before.

A cloud service that classifies students' major records and analysis results generated during the learning process by type and transfers them to a personal storage space and manages them in a portfolio form is also noted as an important function to support learning activities.

This portfolio environment can also be expected to enable learners to preserve their learning records as if they were managing blogs and to develop creative personal works through interaction with peer groups and talent donors.

Target data may include learning records such as assignments or collaborative deliverables, personal records such as reading notes, and activity data such as online discussions or messages. The portfolio environment can categorize these data by type to facilitate systematic management. Should be If the learning portfolio is systematically managed, learners' records can be published as personal works in the form of e-books in the future, and the service of sharing through open distribution systems such as social networks can be considered.

Specifically, FIG. 9 is a diagram summarizing four steps of configuring the learning portfolios listed so far.

Learning portfolios have been studied and formulated for most of the time ICT has been used in education, and, in many cases, they are organized into six or more levels.

In order to simplify the abstract concept, this study summarizes the main points in four steps as follows, reflecting social networks and cloud services.

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

If the experience is not linked to the record, it's as if you forget it after storing it on a removable storage device such as USB.

As records and experiences continue to accumulate in the learning portfolio, learners will be able to recognize their strengths and weaknesses, their weaknesses and strengths, and gain insight into what is going to happen. Previously, the courses and activities were tailored to the average group, but the learning portfolio can help you plan and design for individuals and groups.

You will be able to increase the accuracy of your data search, and expect to see enough linked data to support such a search.

As new learning and activities are carried out, portfolios can be made public and shared through interfaces such as blogs or social media, which are familiar media formats. You can expect an objective evaluation by giving feedback on the results from teachers, colleagues, and experts.

Finally, after the improvement plan and problem diagnosis phase reflects the converged feedback, the cycle continues to be reflected in the learning experience. An individual's portfolio that accumulates as the cycle repeats can give great significance as a small history and a record that reflects itself.

In particular, as the use of blogs and social media is becoming more common, creative ideas recorded in learning portfolios are selectively disclosed at the will of the learner or the recommendation of teachers. There are also cases of adoption and realization.

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

The municipal waste disposal problem was asked by the students of the local school to provide a solution, and the idea adopted was to pay consulting fees and adopt it as a local policy.

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

Similarly, the task of 'Understanding Our Villages' is often carried out as a collaborative project among students, and it is necessary to consider how to add talent donors to the outcomes to suggest regional development strategies or increase the cases adopted by local governments. .

Above all, the greatest advantage that can be expected from the learning portfolio linked with learning analysis is the systematic and accurate aptitude and career counseling.

Referring to FIG. 10, first, the diagnosis of subject learning through learning analysis may find out the strengths and weaknesses of the subjects of the learners, and may provide motivation and prescriptive measures for learning.

Learning portfolios are expected to be an important resource for aptitude and career counseling in addition to curriculum learning, as they can understand how learners' interests and interests change or develop.

To this end, aptitude and career information also needs to be published as linked data so that learners can now judge their interests and hopes based on their learning portfolio. Most parents are very interested in their child's aptitude and career path, but they don't have the available objective data to use paid counseling.

This can lead to differences in opportunities due to income gaps, and indiscriminate competition due to vague anxiety.

Therefore, it would be helpful to reinforce in-depth communication channels with parents by providing an environment that can systematically manage specific learning attitudes, current situation, and other learning records in a portfolio for unconditional private education and parents' vague anxiety.

For more effective portfolio understanding and communication, as with the dashboard service of the learning analysis, the learning method of the portfolio with the intuitive graphical information presentation method would be appropriate.

Comprehensive analysis of learning activities and learning portfolios is expected to be very helpful in exploring aptitude and career information for individuals, not as a group.

Data-based realistic analytical results and an intuitive way of providing information will help parents resolve vague anxiety and reduce unnecessary reliance on private tutoring.

On the other hand, the present invention can also be embodied as computer readable codes on a computer readable recording medium. Computer-readable recording media include all kinds of recording devices that store data that can be read by a computer system. Examples of computer-readable recording media include ROM, RAM, CD-ROM, magnetic tape, floppy disks, optical data storage devices, and the like, which are also implemented in the form of carrier waves (for example, transmission over the Internet). Include. The computer readable recording medium can also be distributed over network coupled computer systems so that the computer readable code is stored and executed in a distributed fashion. In addition, functional programs, codes, and code segments for implementing the present invention can be easily inferred by programmers in the art to which the present invention belongs.

In addition, the above-described apparatus and method may not be limitedly applied to the configuration and method of the above-described embodiments, but the embodiments may be selectively combined in whole or in part in each of the embodiments so that various modifications may be made. It may be configured.

Claims

In a system that provides a learning portfolio,

A memory for storing curriculum information and educational content information;

A mobile terminal that provides learning to a user using the curriculum information and educational content information;

A wireless communication unit receiving feedback information of the user related to the learning from the mobile terminal; And

And a controller configured to generate analysis data using the curriculum information, educational content information, and the feedback information.

And the control unit determines the learning guide information specific to the user using the analysis data, and controls the wireless communication unit to transmit the determined learning guide information to the mobile terminal.
The method of claim 1,

The curriculum information and educational content information can be changed,

The wireless communication unit further receives the changed curriculum information and educational content information from the outside, learning portfolio providing system.
The method of claim 1,

The curriculum information,

A learning portfolio provision system, comprising elementary, middle and high school curriculum, vocational training curriculum, higher curriculum and overseas curriculum.
The method of claim 1,

The educational content information,

A learning portfolio providing system, comprising academic database information, private database information, overseas educational content information, and individual educational content information provided by academy.
The method of claim 1,

The feedback information is

Data information generated through digital content, learning activity data information generated through a learning platform, data information generated while operating an educational program at an educational institution, data information about the user's career and networking, and generated during the profiling of the user A learning portfolio providing system, characterized in that it comprises data information.
The method of claim 1,

The reference for the control unit to generate the analysis data using the curriculum information, educational content information and the feedback information,

Includes learning activity metrics, contextual criteria, engagement criteria, and achievement criteria,

The learning activity metric,

A learning portfolio delivery system, including reading, lectures, quizzes, projects, assignments, media, teaching, instruction, research, assessment, collaboration, annotation, gaming, social, messaging, scheduling, and discussion criteria.
The method of claim 1,

The control unit generates the analysis data using the curriculum information, educational content information and the feedback information,

A learning portfolio providing system, comprising 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 of claim 1,

The learning guide information,

And learning guide information for supplementing weaknesses of the user determined by using the analysis data.
The method of claim 1,

At least one of short range communication and long range communication is used between the mobile terminal and the wireless communication unit.

The short range communication includes ANT, Bluetooth, Radio Frequency Identification (RFID), Infrared Data Association (IrDA), Ultra Wideband (UWB), ZigBee technology,

The telecommunication 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 (SC-FDMA). A learning portfolio providing system, characterized in that.
In providing a learning portfolio,

Storing curriculum information and educational content information;

Providing, by the mobile terminal, learning to a user using the curriculum information and educational content information;

Receiving feedback information of the user related to the learning from the mobile terminal;

Generating analysis data using the curriculum information, educational content information, and the feedback information;

Determining learning guide information specific to the user using the analysis data; And

And transmitting the determined learning guide information to the mobile terminal.
The method of claim 10,

The curriculum information and educational content information can be changed,

The wireless communication unit further comprises the step of receiving the changed curriculum information and educational content information from the outside, further comprising a learning portfolio providing method.
The method of claim 10,

The curriculum information,

A method of providing a learning portfolio, comprising elementary, middle and high school curriculum, vocational training curriculum, higher education curriculum and foreign curriculum.
The method of claim 10,

The educational content information,

Method for providing a learning portfolio, characterized in that it comprises academic database information, private database information, overseas educational content information and individual educational content information provided by the school.
The method of claim 10,

The feedback information is

Data information generated through digital content, learning activity data information generated through a learning platform, data information generated while operating an educational program at an educational institution, data information about the user's career and networking, and generated during the profiling of the user Method for providing a learning portfolio, characterized in that it comprises data information.
The method of claim 10,

Criteria for generating analysis data using the curriculum information, educational content information and the feedback information,

Includes learning activity metrics, contextual criteria, engagement criteria, and achievement criteria,

The learning activity metric,

A method of providing a learning portfolio, including reading, lectures, quizzes, projects, assignments, media, teaching, instruction, research, evaluation, collaboration, annotation, gaming, social, messaging, scheduling, and discussion criteria.
The method of claim 10,

The method for generating analysis data using the curriculum information, educational content information, and the feedback information may include:

A learning portfolio providing method comprising 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 of claim 10,

The learning guide information,

And learning guide information for supplementing the weakness of the user determined using the analysis data.
The method of claim 10,

Transmission to or reception from the mobile terminal uses at least one of short range communication and long range communication,

The short range communication includes ANT, Bluetooth, Radio Frequency Identification (RFID), Infrared Data Association (IrDA), Ultra Wideband (UWB), ZigBee technology,

The telecommunication 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 (SC-FDMA). Method for providing a learning portfolio, characterized in that.
In the recording medium that can be read by the digital processing device is implemented programmatically, the program of instructions that can be executed by the digital processing device to perform the learning portfolio providing method,

The learning portfolio providing method,

Storing curriculum information and educational content information;

Providing, by the mobile terminal, learning to a user using the curriculum information and educational content information;

Receiving feedback information of the user related to the learning from the mobile terminal;

Generating analysis data using the curriculum information, educational content information, and the feedback information;

Determining learning guide information specific to the user using the analysis data; And

And transmitting the determined learning guide information to the mobile terminal.