Technical field
[0001]The present disclosure relates to an information processing apparatus and an information processing method.
BACKGROUND
[0002]In general, learning of the learning is evaluated on the basis of the curriculum prescribed by the public institutions pursuant to school or school. For example, the learner to take the test after receiving the lectures 10 hours, learning degree based on the scores of the test is evaluated.
[0003]However, in recent years, not a long learning as described above, short learning (hereinafter, also referred to as micro-learning) has attracted attention. For example, a person may want to learn from the conversation of about 10 minutes, learning by stacking of such short learning is important.
[0004]In Patent Document 1, a system for managing a micro-learning as described above is disclosed. In the system disclosed in Patent Document 1, the application purchase on Micro learning, sold by managing performance, to manage the micro learning.
CITATION
Patent Document
[0005]Patent Document 1: U.S. Patent Application Publication No. 2014/0343996 Pat
Summary of the Invention
Problems that the Invention is to Solve
[0006]However the technique disclosed in Patent Document 1, for managing a particular learning traded by the application, not be enough to manage the user's learning.
[0007]In this disclosure, which can be performed appropriately manage the user's learning, information processing apparatus and an information processing method are proposed.
Means for Solving the Problems
[0008]According to the present disclosure, the first learning unit certified based on the learning information, a predetermined condition, the second learning unit certified on the basis of the information about certified the second learning unit comprising a processing unit for registering the P2P database, the information processing apparatus is provided.
[0009]Further, according to the present disclosure, the computer, the first learning unit certified based on the learning information, the predetermined conditions, is certified second learning unit based on, certified the second and registers the information about the learning units P2P database, the information processing method is provided.
The invention's effect
[0010]According to this disclosure, the management of a wide range of micro-learning is performed.
[0011]Incidentally, the above effect is not necessarily limited, with the above effects, or in place of the above effects, other effects are achieved which can be grasped from either effect or herein, shown herein it may be.
BRIEF DESCRIPTION OF THE DRAWINGS
[0012]
[1] Figure 1 is a diagram schematically showing a block chain system according to an embodiment of the present disclosure.
FIG. 2 is a diagram schematically showing a block chain system according to an embodiment of the present disclosure.
FIG. 3 is a diagram schematically showing a block chain system according to an embodiment of the present disclosure.
[4] FIG. 4 is a diagram schematically showing the configuration of a learning management system according to an embodiment of the present disclosure.
FIG. 5 is a block diagram showing an example of a functional configuration of a learning apparatus according to an embodiment of the present disclosure.
FIG. 6 is a block diagram showing an example of the functional configuration of a server according to an embodiment of the present disclosure.
[7] FIG. 7 is a diagram showing an example of the information processing method according to an embodiment of the present disclosure.
[8] FIG. 8 is a diagram showing an example of the information processing method according to an embodiment of the present disclosure.
[9] FIG. 9 is a diagram showing a process of micro-learning units and comprehensive learning unit is certified in the embodiment of the present disclosure.
[10] FIG 10 is a diagram showing an example of information managed by the block chain system in the embodiment of the present disclosure.
[11] FIG 11 is a diagram showing an example of a hardware configuration of a learning apparatus according to an embodiment of the present disclosure.
[12] FIG 12 is a diagram showing an example of a hardware configuration of a server according to an embodiment of the present disclosure.
DESCRIPTION OF THE INVENTION
[0013]
　Reference will now be described in detail preferred embodiments of the present disclosure. In the specification and the drawings, components having substantially the same function and structure are a repeated explanation thereof by referring to the figures.
[0014]
　The description will be made in the following order.
　0. Overview of peer-to-peer database
　1. Overview of the learning management system
　2. Configuration of devices constituting a learning management system
　3. Information processing method in the learning management system
　4. Hardware configuration of each device
　5. Supplement
　6. Conclusion
[0015]
　<0. Overview> peer-to-peer database
　in the learning management system according to the present embodiment, distributed peer-to-peer database in circulation in the peer-to-peer network is utilized. Incidentally, peer-to-peer network may also be referred to as peer-to-peer distributed file system. In the following, "P2P network" peer-to-peer network, there is a case showing the peer-to-peer database as "P2P database". Examples of P2P database, there are cases where the block chain data are used in circulation in the P2P network. Thus it will be described first block chain system.
[0016]
　As shown in FIG. 1, a block chain data according to the present embodiment is data included continuous to as a plurality of blocks as if the chain. Each block, one or more target data can be stored as a transaction (transaction).
[0017]
　The block chain data according to the present embodiment, for example, block chain data used for exchanging data of the virtual currency such as Bitcoin. The block chain data used for exchanging data of the virtual currency, for example, a hash of the previous block include special value called a nonce. Hash of the previous block, correct continuous from the immediately preceding block is used to determine whether the "correct block". Nonce is used to prevent spoofing in authentication using the hash, tampering is prevented by the use of a nonce. The nonce, for example, a character string, numeric string or data indicating the combinations thereof.
[0018]
　Further, the block chain data, data for each transaction, the electronic signature using the encryption key is applied, or is encrypted using the encryption key. The data for each transaction is published, it is shared across the P2P network.
[0019]
　Figure 2 is the block chain system, which is a diagram showing how the target data is registered by the user A. User A, the target data to be registered in the block chain data, electronic signature using the private key of the user A. And the user A broadcasts transactions including digitally signed object data on the network. Thus, it is ensured holders of the target data is the user A.
[0020]
　Figure 3 is the block chain system, which is a diagram showing how the target data is migrated from the user A to the user B. User A performs a digital signature using the private key of the user A in the transaction, also include the public key of the user B to the transaction. Thus, target data is indicated that migrated from the user A to the user B. Further, user B, when trading target data, obtains the public key of the user A from the user A, which is an electronic signature or encrypted target data may be acquired.
[0021]
　Further, the block chain system, for example, by utilizing the side chain technology, such as block chain data Bitcoin, the block chain data used for exchanging data existing virtual currency, different from the target data from the virtual currency it is possible to include. Here, other target data which is different from the virtual currency in the present embodiment is information related to learning unit.
[0022]
　By block chain data management information on such learning unit is utilized, the information about the learning unit in a state that is not tampered is held on the network. Further, by blocking the chain data are used, want to use the information contained in the block chain third party, by having the proper authority can access the information contained in the block chain. Note that the information about the learning units managed in the present embodiment is described below.
[0023]
　<1. Learning Management System Overview>
　above it has been described for the block chain system for use in learning management system according to an embodiment of the present disclosure. The following is an overview of a learning management system according to an embodiment of the present disclosure.
[0024]
　Figure 4 is a diagram showing the configuration of a learning management system of the present embodiment. Learning management system of the present embodiment, the learning device 100, a network 200, and a server 300. The learning apparatus 100 and the server 300 is an example of an information processing apparatus for executing information processing of the present embodiment.
[0025]
　Learning device 100 is a device used by a user for learning. For example, a user may read a book by using the learning device 100, with or receive a lecture, do the learning. The server 300, based on information from the learning apparatus 100 performs processing relating to later-described micro-learning unit (first learning unit) and / or comprehensive learning unit (second learning unit). Here, the micro-learning unit, a unit that is certified by a micro learning described above. Furthermore, a comprehensive learning unit is a unit that is certified based on a predetermined condition related to micro-learning unit. For example, a comprehensive learning unit is based on the fact that the micro-learning unit of predetermined number is authorized, it may be certified. Further, in the learning management system of the present embodiment, the server 300, the comprehensive learning unit is certified, and registers the information on the comprehensive learning units in the block chain data.
[0026]
　By information about this learning unit is managed, information related to a wide range of micro-learning is managed. Further, information on learning unit is held on the network in a state that is not tampered. Further, a third party who wants to use the information contained in the block chain, by having the proper authority can access the information contained in the block chain.
[0027]
　Next, it will be described in greater detail the components of the learning management system. Learning apparatus 100 is an information processing apparatus owned by the user. Learning apparatus 100 stores learning information. Further, the learning apparatus 100 may acquire the learning information through the network. Here learning information, for example, text data, voice data, image data (still image and includes a moving image), and the like behavior data.
[0028]
　In addition, text data, including text data with respect to the present, such as textbooks. In addition, the audio data, including voice data about the lecture. In addition, the image data includes the image data about the lecture.
[0029]
　Behavioral data, sensor (e.g. an acceleration sensor, a gyro sensor) provided in the learning apparatus 100 is acquired by, provide information about user behavior. For example, behavioral data, that the user is walking, the user is running, it is performing an action on a specific exercise or competition, which is information indicating, for example. Specifically, the action on a particular exercise or competition, that are swimming by the user, that the user has swung the bat, that the user is shaking the racket, that the user is throwing a ball, etc. It is included in the action. Incidentally, behavioral data, the user may be obtained by the waveform of the acceleration or the like that is statistically calculated when performing each action, and waveform detected by the sensor are compared.
[0030]
　Further, the learning information includes the formal learning information managed by the predetermined engine such as schools, informal learning information that is not managed by the predetermined engine.
[0031]
　Formal learning information, for example, is designated by a given authority, or information about the materials to be distributed. Furthermore, formal training information includes information about the lecture performed by a predetermined engine.
[0032]
　Informal learning information is, for example, contains information about the book that the user has purchased its own. In addition, the informal learning information, includes information about the user is subscribed to its own seminars. In addition, the informal learning information includes information about the conversation that the user has made with a third party.
[0033]
　Further, in the learning management system of the present embodiment, the learning information described above are managed in units of micro-learning is a short or a small amount of units. For example micro-learning unit about this may be managed for each page, each chapter may be managed for each predetermined number of characters. Moreover, conversation, micro learning unit relating Lecture or action, every predetermined time (for example, every 1 minute, every 10 minutes) may be managed in.
[0034]
　The user learns with learning apparatus 100, the learning apparatus 100 transmits the information about the learning made by the user to the server 300. For example, information on learning contents of the learning information used for learning may include such learning time. The learning device 100 may be configured by one apparatus, or may be constituted by a plurality of devices. For example, the learning device 100 may be a smart phone or laptop PC. Further, the learning apparatus 100, smartphones and may be constituted by a wearable device connected to the smartphone.
[0035]
　Server 300 evaluates the information about the learning transmitted from the learning device 100. For example, the server 300 evaluates the topic on the learning process, such as curriculum or syllabus schools, etc. to provide, whether there is a relationship between the learning information obtained from the learning apparatus 100. The server 300 transmits to the topics on the curriculum or syllabus provides such schools, learning information obtained from the learning apparatus 100 evaluates whether having novelty.
[0036]
　The server 300 may evaluate the topic the user has previously registered, whether there is a relationship between the learning information obtained from the learning apparatus 100. The server 300, the user has previously registered topic, learning information obtained from the learning apparatus 100 may assess whether a novelty.
[0037]
　Here, the topic of the present embodiment include various title. For example, the topic includes information about the subject specified by the predetermined engine such as schools. For example, the subject, foreign language, mathematics, chemistry, physics, geology, history and the like are included. In addition, topics, may be pre-registered by the user. For example, a user, programming, cooking, engine control, mechanical engineering, meteorology, astronomy, such as animation, the user can register a topic to learn in private. Incidentally, if the user registers a topic, information about a topic to be registered, for the assessment of relevance and novelty of the learning information, it may be registered by the user. Here, relevance and information on topics registered used for the assessment of novelty of the learning information can be a term used in the topic, are generally known in the topical information it may be.
[0038]
　Server 300, based on the evaluation of the relevance and novelty described above, performs the recognition of micro-learning unit. The server 300 includes a micro-learning unit certified, based on a predetermined condition, to certify comprehensive learning unit. Then, the server 300 registers the information about the certified comprehensive learning units to block the chain data. Incidentally, certification method of the learning unit will be explained later using FIG. Further, information on a comprehensive learning units registered in the block chain data will be explained later using FIG. 10.
[0039]
　<2. Learning management configuration of an apparatus constituting the system>
　above was an overview of the learning management system according to an embodiment of the present disclosure. In the following is described the configuration of the apparatus constituting the learning management system according to an embodiment of the present disclosure.
[0040]
　(2-1. Configuration of the learning device 100)
　FIG. 5 is a diagram showing an example of the configuration of a learning apparatus 100 of the present embodiment. Comprising learning apparatus 100 is, for example, a processing unit 102, a first communication unit 104, a second communication unit 106, an operation unit 108, a display unit 110, a storage unit 112, a sensor 114, a microphone 116 .
[0041]
　Processing unit 102 processes the signals from the respective configuration of the learning apparatus 100. For example, the processing unit 102 performs decoding processing of the signal sent from the first communication unit 104 or the second communication unit 106, extracts the data. The processing unit 102 processes the signal from the operation unit 108 may perform an instruction to the application executed in the processing unit 102. The processing unit 102 reads data from the storage unit 112 may perform the processing for the read data. The processing unit 102 may process data obtained from the sensor 114 or the microphone 116.
[0042]
　The first communication unit 104 is a communication unit for connecting the learning apparatus 100 and the external network, for example, 3GPP (Third Generation Partnership Project) or may communicate using a communication scheme defined by 3GPP2. The first communication unit 104, W-CDMA, LTE (Long Term Evolution), may communicate with a communication system such as CDMA2000. The first communication unit 104 may download the learning information through the network. The communication system described above is an example, the communication method of the first communication unit 104 is not limited thereto.
[0043]
　The second communication unit 106 is a communication unit that communicates with an external device and the short-range wireless, for example, a communication scheme defined by IEEE802 Committee (e.g. Bluetooth (registered trademark)) may communicate with. The second communication unit 106 may communicate using a communication system such as Wi-Fi. The communication system described above is an example, the communication system of the second communication unit 106 is not limited thereto.
[0044]
　Operation unit 108 accepts an operation for the user of the learning device 100. The user can operate the operation unit 108 performs an operation for applications running for example by the learning device 100. The user can operate the operation unit 108, sets various functions of the learning apparatus 100.
[0045]
　Display unit 110 is used to display an image. For example, the display unit 110 displays the image relating to the application to be executed by the learning apparatus 100. The display unit 110 may display the learning information stored in the storage unit 112. For example, the display unit 110 may display the electronic book stored in the storage unit 112. Storage unit 112, an application executed by the learning apparatus 100, and stores programs such as an operating system. The storage unit 112 may store the learned information. For example, the storage unit 112 may store image data relating to text data or lectures on textbooks.
[0046]
　Sensor 114 senses the movement of a learning apparatus 100. For example, the sensor 114, an acceleration sensor, a gyro sensor, pressure sensor, and a geomagnetic sensor. The acceleration sensor detects an acceleration with respect to the learning apparatus 100. The gyro sensor detects the angular acceleration and angular velocity relative to the learning apparatus 100. Pressure sensor senses the pressure altitude learning apparatus 100 is calculated based on the sensed pressure. The geomagnetic sensor detects the geomagnetism, the orientation of the learning apparatus 100 is calculated based on the detected geomagnetic. The microphone 116 obtains audio data from the sound surrounding the learning apparatus 100.
[0047]
　(2-2. Configuration of Server 300)
　The above described the configuration of a learning apparatus 100 according to an embodiment of the present disclosure. Hereinafter will be described according to embodiments of the present disclosure the configuration of the server 300.
[0048]
　6, which can perform processing according to the processing method of the present embodiment, a diagram showing an example of a configuration of the server 300. Server 300 includes, for example, a processing unit 302, a communication unit 304, a storage unit 306. The processing unit 302 comprises an analysis unit 308, a discriminating section 310, a registration section 312, a.
[0049]
　Processing unit 302 processes the signals from the components of the server 300. For example, the processing unit 302 performs decoding processing sent from the communication unit 304 signals to extract the data. The processing unit 302 reads data from the storage unit 306, performs processing on the read data.
[0050]
　Analyzer 308, analyzes the learning information. For example, analysis unit 308 analyzes the text data by using a vector space model. Vector space model, to represent text data as vector data by using, for example, the number of occurrences or the appearance rate of the words contained in the text data. Further, the analysis unit 308 converts the audio data into text data. The analysis unit 308 converts the text data based on the audio data into vector data.
[0051]
　Discriminating section 310 evaluates the relevance and novelty of learning information obtained from the learning apparatus 100. Discriminating section 310, for example, by comparing the plurality of text data represented as vector data by the vector space model, to evaluate the similarity between a plurality of text data. Further, certification unit 310, using the existing image processing technique, by comparing the plurality of image data or image data, we evaluate the similarity between the plurality of image data or image data. Discriminating section 310, on the basis of the process for such an evaluation, to evaluate the relevance and novelty of learning information obtained from the learning apparatus 100. The discriminating section 310, based on the evaluation of the relevance and novelty, performs certification of micro learning unit.
[0052]
　Further, certification unit 310, a micro-learning unit certified, on the basis of the predetermined condition, to certify comprehensive learning unit. For example, certification unit 310, if the micro-learning unit of predetermined number is authorized to certify the comprehensive learning unit.
[0053]
　Registration unit 312 registers the information about the certified comprehensive learning units to block the chain data. Included comprehensive learning unit information about, for example, information about a topic, information on learning time, information about the number of units micro learning unit, information about the level of understanding of the learner, any one of the certification information how micro learning unit It is. Here, the information on the topic, for example, may include information about the subjects to be included in the curriculum of the school. Further, information on level of understanding of the learner may be determined based on the number of tests carried question by the server 300 for recognition of a comprehensive learning unit. In addition, certification method of micro-learning units, reading, attend lectures, viewing of video, may be included, such as conversation.
[0054]
　The communication unit 304 is a communication unit that communicates with an external device via wired or wireless communication, for example Ethernet may communicate using a communication scheme conforming to (R). Storage unit 306 stores various data used by the processing unit 302.
[0055]
　<3. An information processing method> in the learning management system
　above has been described for the configuration of each apparatus constituting the learning management system according to an embodiment of the present disclosure. In the following, it is described information processing method for learning management system according to an embodiment of the present disclosure.
[0056]
　(3-1. Micro processing method for certification of the learning unit)
　7 is a diagram showing an example of an information processing method executed in a learning management system of the present embodiment. In particular, in FIG. 7, it is described an information processing method for recognition of micro-learning unit.
[0057]
　In S102, the analysis unit 308 acquires the learning information from the learning apparatus 100. Learning information indicates information that the user has learned as described above. Thus, for example, if the user has read the book one page, the learning apparatus 100 transmits to the server 300 the text data read by the user as learning information. Further, the learning apparatus 100, when acquiring the voice data by the microphone 116 and transmits the voice data to the server 300. Learning information may from the learning apparatus 100 is transmitted from time to time, it may be transmitted together at regular intervals.
[0058]
　In S104, the analysis unit 308 analyzes the learning information obtained. For example, analyzer 308, using a vector space model, and converts the acquired text data into vector data. Further, the analysis unit 308 converts the acquired speech data to text data, and converts the converted text data into vector data.
[0059]
　In S106, certification unit 310, learning information obtained it is, determines whether there is relevant to a given topic. For example, if the topic is passive in English, discriminating section 310 uses the vector data described above, the learning information acquired determines whether associated with passive English.
[0060]
　Incidentally, certification unit 310, the data stored in the storage unit 306, and the acquired learned information may be determined whether have relevance. Specifically, discriminating section 310 compares the data that the user is already stored in the storage unit 306 as learning information learned, and the newly acquired learned information. For example, if a user is reading a book A previously, the contents of the A is stored in the storage unit 306 as learning data the user has already learned. On the other hand, the learning information newly acquired may be learned information based on the B. Is this case, certification unit 310, a learning information newly obtained (the content of the B), are relevant to the learning information that the user has already learned stored in the storage unit 306 (the contents of the A) it may determine whether.
[0061]
　Discriminating section 310 in S106, if the learning information obtained is determined to be relevant to a predetermined topic, the process proceeds to S108. In S108, certification unit 310, learning information obtained determines whether a novelty for a given topic. For example, discriminating section 310, on the basis of the data stored in the storage unit 306, a learning information acquired determines whether a novelty for a given topic. In other words, the user, whether to learn the new content is determined for a given topic.
[0062]
　Specifically, discriminating section 310 compares the data that the user is already stored in the storage unit 306 as learning information learned, and the newly acquired learned information. For example, if a user is reading already up to 30 pages of the book 100 pages, content from one page to 30 pages is stored in the storage unit 306 as learning data the user has already learned. The discriminating section 310 compares the learning information newly obtained (the content of page 31), and a learning information that the user has already learned stored in the storage unit 306 (content from one page to 30 pages) by learning information newly acquired, it determines whether it has a novelty for a given topic.
[0063]
　In S108, discriminating section 310, if the learning information obtained is determined to be novel for a given topic, the process proceeds to S110. In S110, certification unit 310, learning information obtained it is, determines whether a predetermined condition is satisfied. Wherein the predetermined condition may simply be to have a relevance and novelty for a given topic. The predetermined condition is, if the relevance and novelty is represented by a numerical value calculated by a predetermined algorithm, the total value of the relevance and novelty may be not less than a predetermined threshold value. The predetermined condition may be that the learning by the user is performed for a predetermined time. As a result, even when the user is simply such as skipping a book flipping through the pages, that the unit is certified it can be prevented. The predetermined condition is the number of scores of the test for measuring the intelligibility of users may be that a predetermined number or more. Thus, even if the user does not understand, is prevented units are certified.
[0064]
　In S110, discriminating section 310, if the learning information obtained is determined that the predetermined condition is satisfied, the process proceeds to S112. In S112, certification unit 310 certifies micro learning unit to the user. The discriminating section 310 stores information about the approved micro-learning unit in the storage unit 306. Here, the information on the micro-learning unit, information about the learning time for acquiring the micro learning units may include information about the number of units authorized micro-learning unit.
[0065]
　As described above, in the present embodiment, the learning information includes the formal learning information, and informal learning information may include. Here, authorized and micro learning unit for formal learning information, certification of micro learning unit for informal learning information may likewise be performed by the information processing method described with reference to FIG. It this case, the information on the micro-learning unit described above, a micro-learning unit obtained on the basis of the information or informal training information indicating that the micro-learning unit obtained on the basis of formal learning information it may include information indicating the.
[0066]
　Further, in the above example, certified micro learning unit is performed based on the same type of learning information. However, recognition of the micro-learning unit may be performed based on different kinds of learning information. That certified unit 310 may evaluate the relevance and novelty based on different types of learning information. Specifically, discriminating section 310 compares the learned information acquired based on the learning information and the text data acquired based on the audio data, it may be assessed relevance and novelty. Further, discriminating section 310 compares the acquired learned information based on the learning information and the text data acquired based on the action information, it may be assessed relevance and novelty.
[0067]
　(3-2. Comprehensive adjustment information processing method for certification units)
　above has been described for processing a method for recognition of micro-learning unit in learning management system. In the following, it is described information processing method for certification of a comprehensive learning unit in learning management system.
[0068]
　In S202, discriminating section 310 determines a plurality of micro-learning unit whether certified. Discriminating section 310 determines that the plurality of micro-learning unit certified, the process proceeds to S204. In S204, discriminating section 310 determines whether or not a predetermined condition is satisfied.
[0069]
　Here, the predetermined condition may be a condition regarding the number of units authorized micro-learning unit. For example, the predetermined condition may be that micro-learning unit is a predetermined number authorized.
[0070]
　The predetermined condition may be a condition based on a micro-learning units based on micro-learning unit and / or informal training information based on formal learning information. For example, the predetermined condition, the micro-learning unit may be that it has been predetermined number certification based on formal learning information. Further, the predetermined condition, the micro-learning unit may be that it has been predetermined number certification based on informal learning information. The predetermined condition is micro-learning unit predetermined number certification based on formal training information, may micro learning units based on informal learning information also even that has been predetermined number authorized. Thus, micro-learning units based on formal or informal training information, by used to determine the predetermined condition, it is possible to recognition of units based on a variety of learning information.
[0071]
　For example, when a predetermined condition is based on the number of units of micro learning units based on formal learning information, by the quality of the learning information is ensured, credibility of the certified is comprehensive learning unit is improved. Further, when a predetermined condition is based on the number of units of micro learning units based on informal learning information, it is possible to evaluate the autonomy of a user. Further, when a predetermined condition is based on the number of units of micro learning units based on micro learning units and informal learning information based on formal learning information, it is compensated by the learning performing learning that takes place at schools user private it can.
[0072]
　Further, in S204, the predetermined condition may be determined based on the understanding of the user. Understood by the user, for example, after the micro-learning unit of predetermined number is authorized, may be determined by the test scores for a given topic is question by the server 300. The user uses the learning apparatus 100 to answer to the test, the learning apparatus 100 transmits an answer of the user to the server 300. Then, the server 300, based on the result of the test to calculate the level of understanding of the user. By thus understood by the user is used for determining a predetermined condition, when the user understand the learning content, comprehensive learning unit is certified.
[0073]
　The predetermined condition may be determined based on the learning time of the learning performed by the user until the micro learning unit is certified. By thus learning time is used in the determination of a predetermined condition, it is possible to ensure that the user has performed the learning.
[0074]
　The predetermined condition includes a number of unit micro learning unit, and understood by the user, in combination with the learning time may be determined. The predetermined condition may be determined by combining two of the above-mentioned indicators, it may be determined by combining three of the above-mentioned index.
[0075]
　In S204, discriminating section 310 determines that the predetermined condition is satisfied, the process proceeds to S206. In S206, certification unit 310 certifies comprehensive learning unit. Then, the registration unit 312 in S208, the information on Comprehensive learning unit certified in S206, and registers the block chain data.
[0076]
　(3-3. An example of credits)
　above has been described for an information processing method for qualifying micro learning units and comprehensive learning units. In the following, an example of a credit transfer by the information processing method described above.
[0077]
　Figure 9 is a diagram showing an example of a unit certified by the described information processing method with reference to FIGS. In the following, the predetermined condition in S204 of FIG. 8 (conditions for comprehensive learning unit is certified) is described an example in which the number of units authorized by micro learning unit. Here, conditions for comprehensive learning unit is certified, is that 100 units micro learning units are certified.
[0078]
　Further, FIG. 9, the user A whose user ID is "abc1234" indicates an example of learning for passive English. Here the English passive is above topics, the topics may be a topic that is specified by the curriculum or syllabus given institutions such as schools, the user may be registered in advance topic .
[0079]
　First, because of the recognition of comprehensive learning unit, the user A may have to acquire the micro learning units 100 units, it is set. Then, user A, by performing learning, micro learning unit is certified. For example, if the micro-learning unit 50 units be certified, approved micro-learning unit is 50 units, that the remaining micro learning unit is 50 units are recorded.
[0080]
　Then, when the user A continues to learn, certified micro learning unit becomes 100 units, also when the rest of the micro-learning unit becomes 0 units, inclusive learning unit is certified.
[0081]
　Here, now certified micro learning units 100 units, also when the rest of the micro-learning unit becomes 0 units, to try understood by the user, the test for passive in English, server 300 it may be performed by. Then, the scores of the test, comprehensive learning unit may be certified.
[0082]
　In the example described above, it has been described for the case the topic is English. However, the topic may be other topics. For example, the topic is, may be a topic for exercise. In addition, topics related to exercise, for example, may be a marathon. In this case, for example, a unit micro learning units may be authorized each time the user runs 1km. Further, one unit micro learning units may be certified each time the user runs 10 minutes.
[0083]
　(3-4. An example of information registered in the block chain)
　in the above has been described an example of credits of micro learning units and comprehensive learning units. In the following, an example of information on Comprehensive learning units registered in the block chain.
[0084]
　Figure 10 is a diagram showing an example of information on Comprehensive learning units registered in the block chain. In the learning information management system of the present embodiment, information on Comprehensive learning unit shown in FIG. 10, in place of the transaction information existing block chain such as Bitcoin, or transactions existing block chain such as Bitcoin It is registered in association with the information.
[0085]
　As shown in FIG. 10, the learning information management system of this embodiment, for example, a user ID, topic (major classification and minor classification), understood by the user, the learning time, number of units of certified micro learning units, method of acquiring micro learning units, may be registered in the block chain data.
[0086]
　Large classification of topics as described above, foreign language, mathematics, chemistry, physics, geology, history, programming, cooking, engine control, mechanical engineering, meteorology, astronomy, may be included, such as animation. In addition, the topic of small classification, if the large classification of the topic of English, for example, passive voice, use of prepositions, present perfect, speaking, may be included, such as listening.
[0087]
　In addition, large classification of topics, may be a topic related to behavior or movement of the user. For example, the topic large classification of behavioral or exercise, baseball, soccer, running, may be included such as walking. In addition, the topic of small classification, if the large classification of the topic of baseball, for example, pitching, batting, fielding, may be included, such as base running. In this way, by the topic is classified in the large classification and small classification, in more detail learning is managed.
[0088]
　Comprehension may be determined based on the number of tests performed on the user. Further, the method of acquiring the micro-learning unit, or micro learning units are certified based on the official learning information, or micro learning units are certified based on the informal training information, also contains information indicating the good.
[0089]
　Furthermore, training time, in FIG. 10, as the time until all the micro-learning unit is acquired, 10 hours is shown. However, the learning time may be recorded in more detail. For example, the learning time is the time until the micro learning unit is acquired may be recorded.
[0090]
　Here, the method of acquiring the micro units based on formal learning information, for example, to read a textbook that has been distributed from the predetermined institutions such as schools, to attend the lectures of a given institution, also be included, such as good. In addition, the method of acquiring the micro units based on informal learning information, with a third party such as a friend conversation, to read a book purchased by the user on its own, to study sessions were carried out in a friend or colleague and private it may be included, such as attendance.
[0091]
　Thus, by information on Comprehensive learning unit is managed by the block chain data, in a state that is not the tampering of information, and control over micro learning a third party user performs in an easy state using information line divide.
[0092]
　<4. Hardware Configuration> of each apparatus
　above has been described for an information processing method executed in a learning management system and learning management system according to the present embodiment. In the following are described the hardware configuration of each device of the learning management system.
[0093]
　(4-1. Learning device hardware configuration)
　below, with reference to FIG. 11, the hardware configuration of the learning apparatus 100 according to an embodiment of the present disclosure will be described in detail. Figure 11 is a block diagram for explaining a hardware configuration of a learning apparatus 100 according to an embodiment of the present disclosure (e.g., smart phone).
[0094]
　Learning apparatus 100 mainly includes a CPU 801, a ROM 803, a RAM 805, a. Further, the learning apparatus 100 further includes a host bus 807, a bridge 809, an external bus 811, an interface 813, an input device 815, an output device 817, a storage device 819, a drive 821, a second communication device and 823, and a first communication device 825.
[0095]
　CPU801 functions as a central processing unit and a control unit, ROM 803, RAM 805, according to the storage device 819, or a removable recording medium 827 to various programs recorded, and controls the overall operation or a part of the learning device 100 . Incidentally, CPU 801 may have a function of processing unit 102. ROM803 stores programs and operation parameters used by the CPU 801. RAM805 stores programs used by the CPU 801, temporarily stores the parameters that appropriately change during execution of the program. These are mutually connected by the host bus 807 by an internal bus such as CPU bus.
[0096]
　The host bus 807 via a bridge 809, and is connected to the external bus 811 such as PCI (Peripheral Component Interconnect / Interface) bus.
[0097]
　Input device 815 is, for example, operation means electrostatic or pressure-sensitive touch panel, a button, a user such as switches and a jog dial is operated. Further, the input device 815, for example, based on information input by a user with the above operation means generates an input signal is an input control circuit for outputting the CPU 801. The user operates the input device 815, and can instruct the input processing operation of various data to the learning apparatus 100. The input device 815 may have a function of the operation unit 108.
[0098]
　The output device 817 is configured from a device capable of visually or audibly notifying the user of acquired information. As such device, a liquid crystal display device, there is an EL display device and a display device such as a lamp, or a speaker and an audio output device such as headphones. The output device 817 outputs, for example, results obtained by various processing by the learning apparatus 100 has performed. More specifically, the display device, a result obtained by various processing by the learning device 100 has performed, to display a text or an image. On the other hand, the audio output device converts audio signals composed of audio data, acoustic data or the like which is reproduced into an analog signal. The display device of the output device 817 may have a function of the display unit 110.
[0099]
　The storage device 819 is a device for storing the data used in the learning apparatus 100. The storage device 819 is, for example, a HDD (Hard Disk Drive), a magnetic storage device, semiconductor storage device, an optical storage device, or magneto-optical storage device. The storage device 819 stores programs and various data CPU801 executes, and various data obtained from the outside.
[0100]
　Drive 821 is a reader writer for recording medium, and is embedded in the learning apparatus 100, or externally. Drive 821, a mounted magnetic disk, optical disk, magneto-optical disc, or reads information recorded on the removable recording medium 827 such as a semiconductor memory, and outputs to the RAM 805. The drive 821 can write information into the removable recording medium 827 such as a magnetic disk, an optical disk, a magneto-optical disk or semiconductor memory mounted. The removable recording medium 827, for example, a DVD media, HD-DVD media, Blu-ray (registered trademark) media and the like. The removable recording medium 827 may be a CompactFlash (registered trademark) (CompactFlash: CF), a flash memory, or may be an SD memory card (Secure Digital memory card). The removable recording medium 827, for example, IC card may be (Integrated Circuit card) or electronic equipment equipped with a contactless IC chip.
[0101]
　The second communication device 823 by establishing a communication with the external connection device 829 is used to exchange data with an external connection device. As an example of the second communication device 823, IEEE 802.11 port, there is a IEEE802.15 port like. By being connected to the external connection device 829 by the second communication device, the learning apparatus 100 obtains various data directly from the external connection device 829, and transmits various data to the externally connected apparatus 829.
[0102]
　The first communication device 825 is a communication interface configured by a communication device for connecting to a communication network 831. The first communication device 825, for example, a modem circuit which operates in compliance with the standard specified by 3GPP. Communication scheme conforming to standards 3GPP defines, for example W-CDMA, LTE, and the like. The first communication device 825, for example, can transmit and receive a signal in accordance with a predetermined protocol such as TCP / IP or the like to and from the Internet or carrier networks. The communication network 831 connected to the first communication device 825 is configured from a network or the like connected by wireless, for example, the Internet, may be a network of a communication carrier.
[0103]
　(4-2. Server hardware configuration)
　below, with reference to FIG. 12, the hardware configuration of the server 300 according to an embodiment of the present disclosure will be described in detail. Figure 12 is a block diagram for explaining the hardware configuration of the server 300 according to an embodiment of the present disclosure.
[0104]
　Server 300 mainly includes a CPU 901, a ROM 903, a RAM 905, a. The server 300 further includes a host bus 907, a bridge 909, an external bus 911, an interface 913, an input device 915, an output device 917, a storage device 919, a drive 921, a connection port 923, and a communication device 925.
[0105]
　CPU901 functions as a central processing unit and a control unit, ROM 903, RAM 905, the storage device 919, or various programs recorded on the removable recording medium 927, and controls the overall operation or a part of the server 300. Incidentally, CPU 901 may have a function of processing unit 302. Further, CPU 901, the analysis unit 308, discriminating section 310, may constitute a registration unit 312, respectively. ROM903 stores programs, operation parameters CPU901 uses. RAM905 the programs used CPU901 is primarily stores the parameters that appropriately change during execution of the program. These are connected to each other by the host bus 907 configured from an internal bus such as CPU bus.
[0106]
　Input device 915 may, for example, a mouse, a keyboard, a touch panel, a button, a user such as a switch and a lever. The input device 915 is, for example, based on information input by a user with the above operation means generates an input signal is an input control circuit for outputting the CPU 901. The user operates the input device 915, and can instruct the input processing operation of various types of data to the server 300.
[0107]
　The output device 917 includes a device capable of visually or audibly notifying the user of acquired information. Such devices, CRT display device, a liquid crystal display device, a plasma display device, a display device and an EL display device and lamps, audio output devices such as speakers and a headphone, a printer, a mobile phone, a facsimile, and the like. For example, the output device 917 outputs results obtained by various processing by the server 300 is performed. More specifically, the display device, a result obtained by various processing server 300 has performed, to display a text or an image. On the other hand, the audio output device converts audio signals composed of audio data, acoustic data or the like which is reproduced into an analog signal.
[0108]
　The storage device 919 is a device for data storage configured as an example of the storage unit 306 of the server 300. The storage device 919 is, for example, a HDD (Hard Disk Drive), a magnetic storage device, semiconductor storage device, an optical storage device, or magneto-optical storage device. The storage device 919 stores programs and various data CPU901 executes, and the various data and the like acquired from outside. The storage device 919 may have a function of the storage unit 306.
[0109]
　The drive 921 is a reader writer for recording medium, and is embedded in the server 300 or externally attached. Drive 921, a mounted magnetic disk, optical disk, magneto-optical disc, or reads information recorded on the removable recording medium 927 such as a semiconductor memory, and outputs to the RAM 905. The drive 921 can write the recording on a magnetic disk, an optical disk, a magneto-optical disc removable recording medium 927 or a semiconductor memory mounted. The removable recording medium 927 is, for example, a DVD media, HD-DVD media, Blu-ray (registered trademark) media and the like. The removable recording medium 927 may be a CompactFlash (registered trademark) (CompactFlash: CF), a flash memory, or may be an SD memory card (Secure Digital memory card). The removable recording medium 927 is, for example, IC card may be (Integrated Circuit card) or electronic equipment equipped with a contactless IC chip.
[0110]
　The connection port 923 is a port for allowing devices to directly connect to the server 300. As an example of the connection port 923, USB (Universal Serial Bus) port, there is an IEEE1394 port, SCSI (Small Computer System Interface) port, and the like. Other examples of the connection port 923, there is a RS-232C port, an optical audio terminal, HDMI (TM) (High-Definition Multimedia Interface) port, and the like. By connecting the external connection device 929 to this connection port 923, the server 300 obtains various data directly from the externally connected apparatus 929 and provides various data to the externally connected apparatus 929.
[0111]
　Communication device 925 is a communication interface configured by a communication device for connecting to a communication network 931. The communication device 925 is, for example, a wired or wireless LAN (Local Area Network), or WUSB a communication card for (Wireless USB). The communication device 925 may be a router for optical communication, a router for ADSL (Asymmetric Digital Subscriber Line), or may be a modem for various communications. The communication device 925 can be transmitted and received, for example, signals in accordance with a predetermined protocol such as TCP / IP or the like on the Internet and with other communication devices. The communication network 931 connected to the communication device 925 is configured by a network or the like connected by wired or wireless, for example, the Internet, home LAN, infrared communication, radio wave communication or satellite communication .
[0112]
　　<5. Supplement>
　has been described in detail preferred embodiments of the present disclosure with reference to the accompanying drawings, the technical scope of the present disclosure is not limited to such an example. It would be appreciated by those skilled in the art of the present disclosure, within the scope of the technical idea described in the claims, it is clear that to cover various modifications, combinations, for these also, naturally belong to the technical scope of the present disclosure.
[0113]
　For example, in the above example, certification units, was done on the server 300. However certification units may be performed by the learning device 100. That learning apparatus 100 may have the functions of the server of the analyzer 308 and the discriminating section 310. Further, the learning apparatus 100, the information about the certified comprehensive learning units may be registered in the block chain. That learning apparatus 100 may have a function of registering unit 312 of the server 300.
[0114]
　Further, in the above example, information on learning units, is registered in the block chain data. However, information on learning unit may be registered in the system other than the block chain. For example, information on learning unit may be managed by the server group to build a cloud system. Further, information on learning unit may be managed by existing P2P networks.
[0115]
　Further, the information processing of the present embodiment, a tablet computer, desktop computer, PDA, may be performed by an information processing apparatus such as automotive devices. The server 300 may not be connected to other devices by wire or may be a portable computer.
[0116]
　Further, the processing unit 302 of the processing unit 102 and the server 300 of the learning device 100, a computer program for causing an operation as described above with reference to FIGS. 7 and 8 may be provided. A storage medium such program is stored may be provided.
[0117]
　<6. Conclusion>
　In the present disclosure learning information management system as described above, the block chain data is used to manage information about the learning unit. Thus, information on learning unit in a state that is not tampered is held on the network. Further, by blocking the chain data are used, want to use the information contained in the block chain third party, by having the proper authority can access the information contained in the block chain.
[0118]
　Further, the learning information management system of the present disclosure, the micro-learning units based on micro-learning is managed. Thus, in existing systems the management of extensive micro learning management is difficult is performed. Further, certification of the unit described above is performed on the basis of formal learning information and / or informal training information. Thereby, the existing system management units certified based on informal learning information management is difficult is performed.
[0119]
　Also within the scope of the present disclosure the following configurations.
(1)
　a first learning units certified based on the learned information, certifies a predetermined condition, the second learning unit based on the information about certified the second learning units P2P database comprising a processing unit for registering the information processing apparatus.
(2)
　wherein the processing unit certifies the learning information and determines novelty with respect to the given topic relevance and the learning information with a predetermined topic, the first learning unit based on a result of the determination to, the information processing apparatus according to (1).
(3)
　the processing unit, and the learning information, the relevance and novelty of the topic, determines by using the spatial vector model, the information processing apparatus according to (2).
(4)
　the learning information includes formal learning information managed in a predetermined engine, and informal learning information that is not managed in a predetermined engine, one or both of, the from the (1) ( 3) the information processing apparatus according to any one of.
(5)
　the topic of a given body on the learning process, the information processing apparatus according to any one of (2) from said (4).
(6)
　The topic is registered by the user, the information processing apparatus according to any one of (2) from said (4).
(7)
　The second learning unit the predetermined for qualifying conditions, the number of units authorized the first learning unit relating information processing according to any one of the above (1) (6) apparatus.
(8)
　wherein the predetermined condition for qualifying second learning unit relates understood by the user, the information processing apparatus according to any one of (1) the (6).
(9)
　wherein the predetermined condition for qualifying second learning unit learning includes a time information processing apparatus according to any one of (1) the (6).
(10)
　the processing unit determines the said predetermined conditions for qualifying second learning units, based on the first learning unit that are certified based on the informal learning information, the the information processing apparatus according to (4).
(11)
　the processing unit, the predetermined condition for qualifying the second learning unit, the first learning unit and the informal learning information has been certified on the basis of the formal learning information based judged based on the first learning unit certified, the information processing apparatus according to (4).
(12)
　said information on the second learning unit, information about a topic, information on learning time, information about the number of units of said first learning unit, information relating to understood by the user, certification method of the first learning unit relates including any one of the information processing apparatus according to any one of (11) from said (1).
(13)
　The learning information for qualifying first learning unit is text information, audio information, image information, including the action information, the information processing apparatus according to any one of the from the (1) (12).
(14)
　to a computer, the first learning unit certified based on the learning information, the predetermined conditions, is certified second learning unit based on the information about certified the second learning unit to be registered in the P2P database, information processing method.
DESCRIPTION OF SYMBOLS
[0120]
　100 learning apparatus
　102 processing unit
　104 first communication part
　106 second communication unit
　108 operation unit
　110 display unit
　112 storage unit
　114 sensor
　116 microphone
　200 network
　300 server
　302 processing unit
　304 communication unit
　306 storage unit
　308 analyzing unit
　310 certification unit
　312 registers part

The scope of the claims
[Requested item 1]
　A first learning units certified based on the learned information, certifies a predetermined condition, the second learning units based on registers information about certified the second learning units P2P database processing comprising a part, the information processing apparatus.
[Requested item 2]
　Wherein the processing unit is configured to determine the novelty with respect to the given topic relevance and the learning information and learning information and a predetermined topic, certifies the first learning unit based on the determination result, wherein the information processing apparatus according to claim 1.
[Requested item 3]
　Wherein the processing unit, the learning information and the relevance and novelty of the topic, determines by using the spatial vector model, the information processing apparatus according to claim 2.
[Requested item 4]
　The learning information includes formal learning information managed in a predetermined engine, and informal learning information that is not managed in a predetermined engine, one or both of the information processing apparatus according to claim 1.
[Requested item 5]
　The topic of the predetermined body on the learning process, the information processing apparatus according to claim 2.
[Requested item 6]
　The topic is registered by the user, the information processing apparatus according to claim 2.
[Requested item 7]
　Wherein the predetermined condition for qualifying second learning unit, the unit number of qualified first learning unit relating information processing apparatus according to claim 1.
[Requested item 8]
　Wherein the predetermined condition for qualifying the second learning unit relates understood by the user, the information processing apparatus according to claim 1.
[Requested item 9]
　Wherein the predetermined condition for qualifying the second learning unit containing a learning time, the information processing apparatus according to claim 1.
[Requested item 10]
　The processing unit, the predetermined condition for qualifying the second learning unit, said determining based on the first learning unit that are certified based on the informal learning information, in claim 4 the information processing apparatus according.
[Requested item 11]
　Wherein the processing unit, authorized the said predetermined conditions for qualifying second learning unit, on the basis of the said first learning unit and the informal learning information has been certified on the basis of formal learning information determining based on the first learning unit that is, the information processing apparatus according to claim 4.
[Requested item 12]
　Said information on the second learning unit, information about a topic, information on learning time, the first information on the number of units learning unit, information about the level of understanding of the user, information on certification method of the first learning unit comprising any one, the information processing apparatus according to claim 1.
[Requested item 13]
　The first learning information for qualifying learning units of text information, audio information, image information, including behavioral information processing apparatus according to claim 1.
[Requested item 14]
　A computer, a first learning units certified based on the learning information, the predetermined conditions, is certified second learning unit based on the information about certified the second learning units P2P database to register, information processing method.