CN110349446A - Intelligent learning system and method - Google Patents
Intelligent learning system and method Download PDFInfo
- Publication number
- CN110349446A CN110349446A CN201810296616.6A CN201810296616A CN110349446A CN 110349446 A CN110349446 A CN 110349446A CN 201810296616 A CN201810296616 A CN 201810296616A CN 110349446 A CN110349446 A CN 110349446A
- Authority
- CN
- China
- Prior art keywords
- test
- knowledge point
- evaluation
- achievement
- learning
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 31
- 238000012360 testing method Methods 0.000 claims abstract description 251
- 238000011156 evaluation Methods 0.000 claims abstract description 149
- 238000000605 extraction Methods 0.000 claims abstract description 17
- 239000000284 extract Substances 0.000 claims abstract description 10
- 230000006870 function Effects 0.000 claims description 17
- 238000007596 consolidation process Methods 0.000 claims description 13
- 238000012552 review Methods 0.000 claims description 10
- 239000000203 mixture Substances 0.000 claims description 6
- 238000012546 transfer Methods 0.000 claims description 6
- 230000009191 jumping Effects 0.000 claims description 4
- 230000003993 interaction Effects 0.000 claims description 3
- 230000005055 memory storage Effects 0.000 claims description 3
- SBNFWQZLDJGRLK-UHFFFAOYSA-N phenothrin Chemical compound CC1(C)C(C=C(C)C)C1C(=O)OCC1=CC=CC(OC=2C=CC=CC=2)=C1 SBNFWQZLDJGRLK-UHFFFAOYSA-N 0.000 claims description 3
- 230000035945 sensitivity Effects 0.000 claims description 3
- 230000005540 biological transmission Effects 0.000 claims 1
- 239000003990 capacitor Substances 0.000 claims 1
- 235000013399 edible fruits Nutrition 0.000 claims 1
- 230000008569 process Effects 0.000 abstract description 7
- 230000000694 effects Effects 0.000 abstract description 5
- 230000008878 coupling Effects 0.000 abstract description 3
- 238000010168 coupling process Methods 0.000 abstract description 3
- 238000005859 coupling reaction Methods 0.000 abstract description 3
- 230000009286 beneficial effect Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000012797 qualification Methods 0.000 description 2
- 238000013461 design Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 238000003825 pressing Methods 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B5/00—Electrically-operated educational appliances
- G09B5/02—Electrically-operated educational appliances with visual presentation of the material to be studied, e.g. using film strip
-
- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B7/00—Electrically-operated teaching apparatus or devices working with questions and answers
- G09B7/02—Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by a student
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Business, Economics & Management (AREA)
- Physics & Mathematics (AREA)
- Educational Administration (AREA)
- Educational Technology (AREA)
- General Physics & Mathematics (AREA)
- Electrically Operated Instructional Devices (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a kind of intelligent learning system and methods, the system by it is wrong inscribe extraction module by learner evaluate and test in the mistake that occurs inscribe corresponding wrong knowledge point and extract, it is evaluated and tested again as the main test content for consolidating evaluation and test examination question again, the study of next knowledge point is just carried out after learner grasps the knowledge point, entire learning process makes learner obtain more preferably learning effect for the learning state targetedly coupling learning task of learner.Intelligence learning method of the invention provides different learning tasks for the learner in the different study stages, and when learner does not grasp the knowledge point completely, suitable learning tasks are matched again for learner, Key Learns are placed on the knowledge point that learner during last study does not grasp by this method during learning again, to consolidate the study of the knowledge point.
Description
Technical field
The present invention relates to smart electronics field and intelligence learning field, more particularly to a kind of intelligence learning
System and method.
Background technique
Currently, occurring a large amount of computer learning machines, computer learning machine in the market in Internet technology widely applied today
Appearance help the more efficient completion autonomous learning task of learner, it is complete to provide a support intelligence learning technology for learner
At the chance that knowledge point study is consolidated, but existing computer learning machine is guided by the learning test process of procedure mostly
Learner study, due to everyone learning ability, the degree of awareness and understandability be it is distinguishing, rely on a set of
Preset learning process is can not targetedly to solve to have the learner of different learning abilities to ask present in the learning process
Topic, thus most of learner after the learning tasks for completing a stage using computer learning machine its to the understanding of knowledge point with
And the promotion of learning ability is not significantly improved.
Therefore, how a kind of intelligent learning system of study understandability with strong points, can be improved learner is provided
The problem of being those skilled in the art's urgent need to resolve.
Summary of the invention
In view of this, the present invention provides a kind of intelligence of study understandability with strong points, can be improved learner
The learning method of learning system and the application system.
To achieve the goals above, the present invention adopts the following technical scheme:
Intelligent learning system includes:
Touching type function key, the touching type function key need the knowledge point of selection for user's input；
Knowledge point video library, the knowledge point video library are stored with the video resource for knowledge point explanation；
Knowledge point video calling module, the knowledge point video calling module, which calls, selected in the knowledge point video library to be known
Know the corresponding video resource of point；
Display screen, the display screen show human-computer interaction interface；
Exam pool is practiced in knowledge point, and the knowledge point practice exam pool is using knowledge point and its multiple sub- knowledge points of subordinate as foundation
Classification storage has multiple tracks for consolidating the exercise of knowledge point；
Practice test volume generation module, the practice test volume generation module are called respectively in the knowledge point practice exam pool
The corresponding multiple tracks exercise in each sub- knowledge point of selected knowledge point forms more set practice test volumes；
Exam pool is evaluated and tested in knowledge point, and the knowledge point evaluation and test exam pool is using knowledge point and its multiple sub- knowledge points of subordinate as foundation
Classification storage has multiple tracks for evaluating and testing the test question of test；
Test paper generation module is evaluated and tested, the evaluation and test test paper generation module calls selected knowledge in the knowledge point evaluation and test exam pool
The corresponding multiple tracks test question in each sub- knowledge point and multiple tracks integrative test topic of point, and extract the corresponding test in every sub- knowledge point
Topic and integrative test topic are randomly ordered, the evaluation and test paper of composition evaluation and test test for the first time；
Institute's score of per pass test question in paper is evaluated and tested in evaluation result determination module, the evaluation result determination module analysis
Number, this evaluation and test test resultant assembly achievement of counting user, and be that user selects corresponding mode of learning according to evaluation and test achievement；
Mistake topic extraction module, the wrong topic extraction module transfer each test that the evaluation result determination module is analyzed
Obatained score is inscribed, the test question that score is lower than full marks is extracted, obtains the wrong topic of this test, and obtain according to the keyword in wrong topic
Corresponding sub- knowledge point is inscribed to mistake, the corresponding sub- knowledge point of the wrong topic of institute, obtains wrong knowledge point information in statistics evaluation and test paper,
The wrong knowledge point information is sent to evaluation and test test paper generation module；
The evaluation and test test paper generation module according to wrong knowledge point information press the corresponding examination question in wrong knowledge point with it is comprehensive
The ratio of test question is the evaluation and test paper that 4:1 extracts that test question is randomly ordered, and composition n-th evaluation and test is tested；
Memory, the memory storage user evaluate and test the achievement and wrong knowledge point information of test every time；
Microprocessor, the microprocessor by I/O port thereon respectively with touching type function key, knowledge point video
Calling module, wrong topic extraction module, evaluation result determination module, practice test volume generation module, is deposited at evaluation and test test paper generation module
Reservoir, display screen electrical connection；With
Power supply, the power supply are whole system power supply.
The beneficial effects of the present invention are: practicing exam pool by setting knowledge point video library, knowledge point, exam pool is evaluated and tested in knowledge point
For learner's learning tasks different in different study stage match, make again to evaluation and test rehearsal from video study to basic exercise
Learner deepens the understanding to knowledge point, if the learning effect of learner is unsatisfactory after evaluation and test, this system passes through
Mistake topic extraction module by learner evaluate and test in the corresponding wrong knowledge point of mistake topic that occurs extract, as consolidating evaluation and test examination again
The main test content of topic, and the another set of video transferred in the video library of knowledge point in the knowledge point for learner learns,
And evaluate and test again, the study of next knowledge point is just carried out after learner grasps the knowledge point, entire learning process is for
The learning state of habit person targetedly coupling learning task, makes learner obtain more preferably learning effect.
Further, the evaluation result determination module includes evaluation and test examination question marking unit, evaluation and test examination result unit, achievement
Grade judging unit and mode of learning selecting unit；
The evaluation and test examination question marking unit is compared according to preset model answer with the answer that learner provides, root
The score of current examination question is provided according to comparison result；
The evaluation and test examination result unit is electrically connected with evaluation and test examination question marking unit, the evaluation and test examination result unit
The score of each examination question is added up to obtain evaluation and test achievement score；
The achievement judging unit is electrically connected with the evaluation and test examination result unit, and the achievement judging unit will be preset
Score threshold is compared with the practical achievement score of evaluating and testing of learner, obtains evaluation and test achievement and determines result；
The mode of learning selecting unit is electrically connected with the achievement judging unit, the mode of learning selecting unit according to
Evaluation and test achievement determines that result is that learner selects corresponding mode of learning automatically；
The evaluation and test examination question marking unit is also electrically connected with the wrong topic extraction module, and the mode of learning selecting unit is also
It is electrically connected respectively with the microprocessor and knowledge point video calling module.
Beneficial effect using above-mentioned further scheme is: being given a mark by the evaluation and test examination question in evaluation result determination module single
Member, evaluation and test examination result unit, rating achievement rating judging unit and mode of learning selecting unit are learner's evaluation and test examination question marking, and
Judge that learner understands situation to the study of current knowledge point to by rating achievement rating judging unit, is selected by mode of learning single
Member according to the study situation of learner is that learner matches suitable mode of learning, thus for different learners to currently knowing
The understandability coupling learning task for knowing point, has achieved the effect that specific aim regularized learning algorithm scheme.
Further, the mode of learning includes continuing mode of learning and review and consolidation mode, is preset when evaluation and test achievement is greater than
Score threshold when, the achievement judging unit determines that current evaluation and test achievement is qualified, and the mode of learning selecting unit is study
Person, which matches, continues mode of learning, continues the study of next knowledge point；When evaluating and testing achievement less than preset score threshold, the achievement
Judging unit determines that current achievement evaluation and test is unqualified, and the mode of learning selecting unit is that learner matches review and consolidation mould
Formula sends N set video and transfers signal to the knowledge point video calling module.
Using the beneficial effect of above-mentioned further scheme is: different views is matched for learner according to the different study stages
Frequency learnt again, can make learner deeper into understanding current knowledge point.
Further, the preset score threshold is 80-95 points.The setting of specific score threshold can be according to learner
The understanding demand of current knowledge point is rationally arranged.
Further, the touching type function key is capacitance type touch key or resistance-type pressure sensitivity key.The design of key
It can rationally be arranged for specific installation equipment, the touching type function key in this system also could alternatively be common pressing
Key.
Further, the video resource in the knowledge point video library carries out classification storage, Mei Gezhi according to knowledge point classification
Knowing point includes multiple knowledge points, and each knowledge point corresponds to N number of video, and wherein N is the positive integer greater than 1.The specific value of N can be with
It is needed according to study and the memory capacity of storage equipment is rationally arranged, simultaneously qualification needs again in learner's first time evaluation result
When study, knowledge point video calling module can transfer the another set of video under the knowledge point for learner from the video library of knowledge point
Study.
The invention also discloses a kind of intelligence learning methods completed using above-mentioned intelligent learning system, this method comprises:
Step 1: selection needs the knowledge point learnt；
Step 2: recalling the corresponding first set study video in selected knowledge point and learnt；
Step 3: video observing selects a corresponding sub- knowledge point under the knowledge point selected to carry out practice consolidation after finishing watching；
Step 4: carrying out evaluation and test test for the first time after all sub- knowledge point practices；
Step 5: test complete after carry out evaluation and test achievement calculate, obtain evaluation and test achievement score value, and will evaluation and test achievement score value into
Row storage；
Step 6: judge whether the evaluation and test achievement of learner is qualified according to preset score threshold,
Step 7: if currently evaluation and test achievement is qualified, automatic jumping to continuation mode of learning, learner selects next knowledge point
Learnt；
Step 8: if evaluation and test is unqualified, automatic jumping to review and consolidation mode, recall N set study video for study
Person learns and practices consolidating；
Step 9: video observing evaluates and tests the mistake occurred in test according to the last time after finishing watching and practicing and inscribes corresponding mistake
Knowledge point simultaneously combines whole knowledge point to generate evaluation and test paper progress n-th evaluation and test test, step 5 is then branched to, until executing
To step 7, the study of this knowledge point terminates, and starts next knowledge point study.
Further, the preset score threshold is 80-95 points.
Further, the study video is stored in the form of video resource, and carries out classification storage according to knowledge point classification,
Each knowledge point includes multiple knowledge points, and each knowledge point corresponds to N number of video, and wherein N is the positive integer greater than 1.
Further, the corresponding examination question in mistake knowledge point is 80 points in the evaluation and test paper of n-th evaluation and test test, whole knowledge point
Corresponding examination question is 20 points.
It can be seen via above technical scheme that compared with prior art, intelligence learning method disclosed by the invention can be
Learner in the different study stages provides different learning tasks, and when learner does not grasp the knowledge point completely, then
Secondary to match suitable learning tasks for learner, Key Learns are placed on last study by this method during learning again
On the knowledge point that learner does not grasp in the process, such learner is by repeating and targetedly learning in more deep understanding
Once understand knowledge point not in place, to consolidate the study of the knowledge point, obtains more preferably learning effect.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
The embodiment of invention for those of ordinary skill in the art without creative efforts, can also basis
The attached drawing of offer obtains other attached drawings.
Fig. 1 is the structural block diagram of intelligent learning system provided by the invention；
Fig. 2 is the structural block diagram of evaluation result determination module in intelligent learning system provided by the invention；
Fig. 3 is the method flow diagram of intelligence learning method provided by the invention；
Fig. 4 is the flow chart of the concrete application process of intelligence learning method provided by the invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
Referring to attached drawing 1, intelligent learning system disclosed in the present embodiment includes:
Microprocessor 1, touching type function key 2, knowledge point video calling module 3, knowledge point video library 4, evaluation and test paper
Generation module 7, knowledge point evaluation and test exam pool 8, wrong topic extraction module 6, evaluation result determination module 5, practice test volume generation module
9, knowledge point practice exam pool 10, memory 11, display screen 12 and power supply 13,
Microprocessor 1 by I/O port thereon respectively with touching type function key 2, knowledge point video calling module 3, comment
Test volume generation module 7, wrong topic extraction module 6, evaluation result determination module 5, practice test volume generation module 7, memory 11,
Display screen 12 and power supply 13 are electrically connected, and knowledge point video library 4 is electrically connected with knowledge point video calling module 3, knowledge point
Evaluation and test exam pool 8 is electrically connected with evaluation and test test paper generation module 7, and knowledge point practices exam pool 10 and is electrically connected with practice test volume generation module 9
It connects, mistake topic extraction module 6 is also electrically connected with evaluation and test test paper generation module 7 and evaluation result determination module 5 respectively, and evaluation result is sentenced
Cover half block 5 is also electrically connected with knowledge point video calling module 3.
Lower mask body introduces the function of each module of the intelligent learning system in the present embodiment:
Touching type function key 2, touching type function key 2 need the knowledge point of selection for user's input；
Knowledge point video library 4, knowledge point video library 4 are stored with the video resource for knowledge point explanation；
Knowledge point video calling module 3, knowledge point video calling module 3, which calls in the knowledge point video library 4, selected to be known
Know the corresponding video resource of point；
Display screen 12, display screen 12 show human-computer interaction interface；
Exam pool 10 is practiced in knowledge point, and exam pool 10 is practiced using knowledge point and its multiple sub- knowledge points of subordinate as foundation in knowledge point
Classification storage has multiple tracks for consolidating the exercise of knowledge point；
Practice test volume generation module 9, practice test volume generation module 9 call selected in knowledge point practice exam pool 10 respectively
The corresponding multiple tracks exercise in each sub- knowledge point of knowledge point forms more set practice test volumes；
Exam pool 8 is evaluated and tested in knowledge point, and it is foundation point that exam pool 8 is evaluated and tested with knowledge point and its multiple sub- knowledge points of subordinate in knowledge point
Class is stored with multiple tracks for evaluating and testing the test question of test；
Test paper generation module 7 is evaluated and tested, evaluation and test test paper generation module 7 calls selected knowledge point in knowledge point evaluation and test exam pool 8
The corresponding multiple tracks test question in each sub- knowledge point and multiple tracks integrative test topic, and extract the corresponding test question in every sub- knowledge point and
Integrative test topic is randomly ordered, the evaluation and test paper of composition evaluation and test test for the first time；
Institute's score of per pass test question in paper is evaluated and tested in evaluation result determination module 5, the analysis of evaluation result determination module 5
Number, this evaluation and test test resultant assembly achievement of counting user, and be that user selects corresponding mode of learning according to evaluation and test achievement；
Mistake topic extraction module 6, mistake topic extraction module 6 transfer evaluation result determination module 5 and analyze obtained each test question institute
Goals for extracts the test question that score is lower than full marks, obtains the wrong topic of this test, and obtain mistake according to the keyword in wrong topic
Corresponding sub- knowledge point is inscribed, the corresponding sub- knowledge point of the wrong topic of institute, obtains wrong knowledge point information, by institute in statistics evaluation and test paper
It states wrong knowledge point information and is sent to evaluation and test test paper generation module 7；
It evaluates and tests test paper generation module 7 and the corresponding examination question in wrong knowledge point and integrative test is pressed according to wrong knowledge point information
The ratio of topic is the evaluation and test paper that 4:1 extracts that test question is randomly ordered, and composition n-th evaluation and test is tested；
Memory 11, the memory storage user evaluate and test the achievement and wrong knowledge point information of test every time；
Microprocessor 1, microprocessor 1 by I/O port thereon respectively with touching type function key 2, knowledge point video tune
With module 3, evaluation and test test paper generation module 7, wrong topic extraction module 6, evaluation result determination module 5, practice test volume generation module
9, memory 11, display screen 12 are electrically connected；With
Power supply 13, power supply 13 are whole system power supply.
Referring to attached drawing 2, the evaluation result determination module 5 in the present embodiment include evaluation and test examination question marking unit 51, evaluation and test at
Achievement statistic unit 52, rating achievement rating judging unit 53 and mode of learning selecting unit 54；
Evaluation and test examination question marking unit 51 is compared according to preset model answer with the answer that learner provides, according to
Comparison result provides the score of current examination question；
Evaluation and test examination result unit 52 is electrically connected with evaluation and test examination question marking unit 51, evaluates and tests examination result unit 52 for each examination
The score of topic is added up to obtain evaluation and test achievement score；
Achievement judging unit 53 is electrically connected with evaluation and test examination result unit 52, and achievement judging unit 53 is by preset score threshold
Value is compared with the practical achievement score of evaluating and testing of learner, obtains evaluation and test achievement and determines result；
Mode of learning selecting unit 54 is electrically connected with achievement judging unit 53, mode of learning selecting unit 54 according to evaluation and test at
Achievement determines that result is that learner selects corresponding mode of learning automatically；
Evaluation and test examination question marking unit 51 also with mistake topic extraction module 6 be electrically connected, mode of learning selecting unit 54 also respectively with
Microprocessor 1 and knowledge point video calling module 3 are electrically connected.
Specifically, the mode of learning in above-described embodiment includes continuing mode of learning and review and consolidation mode, when evaluation and test at
When achievement is greater than preset score threshold, achievement judging unit 53 determines currently to evaluate and test achievement qualification, mode of learning selecting unit 54
It is matched for learner and continues mode of learning, continue the study of next knowledge point；When evaluating and testing achievement less than preset score threshold, at
Achievement judging unit 53 determines that current achievement evaluation and test is unqualified, and mode of learning selecting unit 54 is that learner matches review and consolidation
Mode sends N set video and transfers signal to knowledge point video calling module 3.
Specifically, preset score threshold is 80-95 point in some embodiments, preset score threshold in the present embodiment
It is 90 points.
Specifically, the touching type function key in above-described embodiment be capacitance type touch key or resistance-type pressure sensitivity key,
Touching type function key in the present embodiment also could alternatively be common push type key.
Specifically, the video resource in knowledge point video library 4 carries out classification storage, each knowledge point according to knowledge point classification
Corresponding N number of video, wherein N is the positive integer greater than 1.
Referring to attached drawing 3, present embodiment discloses a kind of intelligence learning method using above-mentioned intelligent learning system, this method
Include:
S1: selection needs the knowledge point learnt；
S2: it recalls the corresponding first set study video in selected knowledge point and is learnt；
S3: video observing selects a corresponding sub- knowledge point under the knowledge point selected to carry out practice consolidation after finishing watching；
S4: evaluation and test test for the first time is carried out after all sub- knowledge point practices；
S5: test carries out evaluation and test achievement and calculates after completing, and obtains evaluation and test achievement score value, and evaluation and test achievement score value is deposited
Storage；
S6: judging whether the evaluation and test achievement of learner is qualified according to preset score threshold,
S7: if currently evaluation and test achievement is qualified, continuation mode of learning is automatic jumped to, learner selects next knowledge point to carry out
Study；
S8: if evaluation and test is unqualified, automatic jumping to review and consolidation mode, recalls N set study video for learner
Learnt and practices consolidating；
S9: video observing evaluates and tests the corresponding wrong knowledge of the mistake topic occurred in test according to the last time after finishing watching and practicing
It puts and whole knowledge point is combined to generate evaluation and test paper and carry out n-th evaluation and test test, then branch to S5, until S7 is gone to, this
Knowledge point study terminates, and starts next knowledge point study.
In some embodiments, preset score threshold is 80-95 points, and preset score threshold is 90 in the present embodiment
Point.
Learn video in the present embodiment to store in the form of video resource, and carry out classification storage according to knowledge point classification,
Each knowledge point corresponds to N number of video, and wherein N is the positive integer greater than 1.
Specifically, the corresponding examination question in mistake knowledge point is 80 points in the evaluation and test paper of n-th evaluation and test test in the present embodiment,
The corresponding examination question in whole knowledge point is 20 points.
4 pairs of methods provided by the invention do specific description with reference to the accompanying drawing:
S1: selection needs the knowledge point one learnt；
S2: it recalls the selected corresponding first set in knowledge point one study video and is learnt；
S3: video observing selects corresponding sub- knowledge point 1, sub- knowledge point 2, sub- knowledge point under the knowledge point selected after finishing watching
3 successively carry out practice consolidation；
S4: evaluation and test test for the first time is carried out after all sub- knowledge point practices；
S5: test carries out evaluation and test achievement and calculates after completing, and obtains evaluation and test achievement score value, and evaluation and test achievement score value is deposited
Storage；
S6: divide the evaluation and test achievement for judging learner whether qualified according to preset score threshold 90, list four herein
Example, 100 points, 95 points, 60 points and 0 point；
S7: if learner is scored at 100 points or 95 points, score value at this time is greater than 90 points, can carry out knowledge point two
Study, it is not difficult to find out that, as long as evaluation and test score value be not less than 90 points, can enter knowledge point two study；
S8: but if the score of learner is 60 points or 0 point, evaluates and tests score value at this time and be lower than 90 points, it needs to enter and review
Consolidate mode, recalls second set of study video at this time and learn for learner and practice consolidating；
S9: video observing evaluates and tests the corresponding wrong knowledge of the mistake topic occurred in test according to first time after finishing watching and practicing
It puts and whole knowledge point is combined to generate evaluation and test paper and carry out second of evaluation and test test, then branch to S5, until S7 is gone to, this
Knowledge point study terminates, and starts knowledge point two and learns.
Each embodiment in this specification is described in a progressive manner, the highlights of each of the examples are with other
The difference of embodiment, the same or similar parts in each embodiment may refer to each other.For device disclosed in embodiment
For, since it is corresponded to the methods disclosed in the examples, so being described relatively simple, related place is said referring to method part
It is bright.
The foregoing description of the disclosed embodiments enables those skilled in the art to implement or use the present invention.
Various modifications to these embodiments will be readily apparent to those skilled in the art, as defined herein
General Principle can be realized in other embodiments without departing from the spirit or scope of the present invention.Therefore, of the invention
It is not intended to be limited to the embodiments shown herein, and is to fit to and the principles and novel features disclosed herein phase one
The widest scope of cause.
Claims (9)
1. a kind of intelligent learning system characterized by comprising
Touching type function key, the touching type function key need the knowledge point of selection for user's input；
Knowledge point video library, the knowledge point video library are stored with the video resource for knowledge point explanation；
Knowledge point video calling module, the knowledge point video calling module call selected knowledge point in the knowledge point video library
Corresponding video resource；
Display screen, the display screen show human-computer interaction interface；
Exam pool is practiced in knowledge point, and the knowledge point practice exam pool is according to classification with knowledge point and its multiple sub- knowledge points of subordinate
Multiple tracks is stored with for consolidating the exercise of knowledge point；
Practice test volume generation module, the practice test volume generation module call selected in the knowledge point practice exam pool respectively
The corresponding multiple tracks exercise in each sub- knowledge point of knowledge point forms more set practice test volumes；
Exam pool is evaluated and tested in knowledge point, and the knowledge point evaluation and test exam pool is according to classification with knowledge point and its multiple sub- knowledge points of subordinate
Multiple tracks is stored with for evaluating and testing the test question of test；
Test paper generation module is evaluated and tested, the evaluation and test test paper generation module calls selected knowledge point in the knowledge point evaluation and test exam pool
The corresponding multiple tracks test question in each sub- knowledge point and multiple tracks integrative test topic, and extract the corresponding test question in every sub- knowledge point and
Integrative test topic is randomly ordered, the evaluation and test paper of composition evaluation and test test for the first time；
The obatained score of per pass test question in paper is evaluated and tested in evaluation result determination module, the evaluation result determination module analysis,
The evaluation and test achievement of this evaluation and test test of counting user obtains evaluation and test achievement and determines as a result, and determining to tie according to the evaluation and test achievement
Fruit is that user selects corresponding mode of learning；
Mistake topic extraction module, the wrong topic extraction module transfer each test question institute that the evaluation result determination module is analyzed
Goals for extracts the test question that score is lower than full marks, obtains the multiple tracks mistake topic of this test, and obtain according to the keyword in wrong topic
Corresponding sub- knowledge point is inscribed to mistake, the corresponding sub- knowledge point of the wrong topic of institute, obtains wrong knowledge point information in statistics evaluation and test paper,
The wrong knowledge point information is sent to evaluation and test test paper generation module；
The evaluation and test test paper generation module presses the corresponding examination question in wrong knowledge point and integrative test according to wrong knowledge point information
The ratio of topic is the evaluation and test paper that 4:1 extracts that test question is randomly ordered, and composition n-th evaluation and test is tested；
Memory, the memory storage user evaluate and test the achievement and wrong knowledge point information of test every time；
Microprocessor, the microprocessor are called with touching type function key, knowledge point video respectively by I/O port thereon
Module, evaluation and test test paper generation module, wrong topic extraction module, evaluation result determination module, practice test volume generation module, storage
Device, display screen electrical connection；With
Power supply, the power supply are whole system power supply.
2. a kind of intelligent learning system according to claim 1, which is characterized in that the evaluation result determination module includes
Evaluate and test examination question marking unit, evaluation and test examination result unit, rating achievement rating judging unit and mode of learning selecting unit；
Evaluation and test examination question marking unit is compared according to preset model answer with the answer that learner provides, according to than
The score of current examination question is provided to result；
The evaluation and test examination result unit is electrically connected with evaluation and test examination question marking unit, and the evaluation and test examination result unit will be each
The score of examination question is added up to obtain evaluation and test achievement score；
The achievement judging unit is electrically connected with the evaluation and test examination result unit, and the achievement judging unit is by preset score
Threshold value is compared with the practical achievement score of evaluating and testing of learner, obtains evaluation and test achievement and determines result；
The mode of learning selecting unit is electrically connected with the achievement judging unit, and the mode of learning selecting unit is according to evaluation and test
Achievement determines that result is that learner selects corresponding mode of learning automatically；
The evaluation and test examination question marking unit is also electrically connected with the wrong topic extraction module, and the mode of learning selecting unit is also distinguished
It is electrically connected with the microprocessor and knowledge point video calling module.
3. a kind of intelligent learning system according to claim 2, which is characterized in that the mode of learning includes continuing to learn
Mode and review and consolidation mode, when evaluating and testing achievement greater than preset score threshold, the achievement judging unit judgement is currently commented
It is qualified to survey achievement, the mode of learning selecting unit is that learner matches continuation mode of learning, continues the study of next knowledge point；
When evaluating and testing achievement less than preset score threshold, the achievement judging unit determines that current achievement evaluation and test is unqualified, described
Mode of learning selecting unit is that learner matches review and consolidation mode, and transmission N set video is transferred signal and regarded to the knowledge point
Frequency calling module.
4. a kind of intelligent learning system according to claim 3, which is characterized in that the preset score threshold is 80-
95 points.
5. a kind of intelligent learning system according to claim 1, which is characterized in that the touching type function key is capacitor
Formula touch key-press or resistance-type pressure sensitivity key.
6. a kind of intelligent learning system according to claim 1, which is characterized in that the video in the knowledge point video library
Resource carries out classification storage according to knowledge point classification, and each knowledge point corresponds to N number of video, and wherein N is the positive integer greater than 1.
7. a kind of intelligence learning method using intelligent learning system described in any one of claims 1-6, which is characterized in that packet
It includes:
Step 1: selection needs the knowledge point learnt；
Step 2: recalling the corresponding first set study video in selected knowledge point and learnt；
Step 3: video observing selects a corresponding sub- knowledge point under the knowledge point selected to carry out practice consolidation after finishing watching；
Step 4: carrying out evaluation and test test for the first time after all sub- knowledge point practices；
Step 5: test carries out evaluation and test achievement and calculates after completing, and obtains evaluation and test achievement score value, and evaluation and test achievement score value is deposited
Storage；
Step 6: judging whether the evaluation and test achievement of learner is qualified according to preset score threshold；
Step 7: if currently evaluation and test achievement is qualified, automatic jumping to continuation mode of learning, learner selects next knowledge point to carry out
Study；
Step 8: if evaluation and test is unqualified, automatic jump to review and consolidation mode, recall N set study video for learner into
Row learns and practices consolidating；
Step 9: video observing evaluates and tests the corresponding wrong knowledge of the mistake topic occurred in test according to the last time after finishing watching and practicing
It puts and whole knowledge point is combined to generate evaluation and test paper and carry out n-th evaluation and test test, step 5 is then branched to, until going to step
Rapid 7, the study of this knowledge point terminates, and starts next knowledge point study.
8. intelligence learning method according to claim 7, which is characterized in that the preset score threshold is 80-95 points.
9. intelligence learning method according to claim 7, which is characterized in that the study video is in the form of video resource
Storage, and classification storage is carried out according to knowledge point classification, each knowledge point corresponds to N number of video, and wherein N is the positive integer greater than 1.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810296616.6A CN110349446A (en) | 2018-04-02 | 2018-04-02 | Intelligent learning system and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810296616.6A CN110349446A (en) | 2018-04-02 | 2018-04-02 | Intelligent learning system and method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110349446A true CN110349446A (en) | 2019-10-18 |
Family
ID=68172543
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810296616.6A Pending CN110349446A (en) | 2018-04-02 | 2018-04-02 | Intelligent learning system and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110349446A (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110942683A (en) * | 2019-12-02 | 2020-03-31 | 西安冉科信息技术有限公司 | Online learning system with assisting and practicing functions |
| CN111191910A (en) * | 2019-12-26 | 2020-05-22 | 上海乂学教育科技有限公司 | Learning system based on learning path planning |
| CN111444391A (en) * | 2020-04-09 | 2020-07-24 | 圆梦共享教育科技(深圳)有限公司 | Video learning effect evaluation method based on artificial intelligence |
| CN111583743A (en) * | 2020-06-29 | 2020-08-25 | 甘肃省定西理工中等专业学校 | Thinking and administration consolidation review platform system based on Internet |
| CN113256252A (en) * | 2021-05-25 | 2021-08-13 | 上海金程教育培训有限公司 | B/S architecture-based test system |
| CN114241835A (en) * | 2021-11-17 | 2022-03-25 | 北京执象科技发展有限公司 | Student spoken language quality evaluation method and device |
| CN115147254A (en) * | 2022-09-05 | 2022-10-04 | 小白智能科技（长春）股份有限公司 | Robot for actively guiding and guiding children to learn and control method thereof |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2001343887A (en) * | 2000-05-31 | 2001-12-14 | Proaxis Co Ltd | Learning support system |
| CN101000643A (en) * | 2006-01-10 | 2007-07-18 | 英业达股份有限公司 | Study system and method with review function |
| CN102074135A (en) * | 2010-10-21 | 2011-05-25 | 无敌科技(西安)有限公司 | Method and device for building question bank |
| CN103870463A (en) * | 2012-12-10 | 2014-06-18 | 中国电信股份有限公司 | Method and system for selecting test subjects |
| CN105374244A (en) * | 2015-12-10 | 2016-03-02 | 广东小天才科技有限公司 | Learning method and system based on wrong question analysis |
| CN107844898A (en) * | 2017-10-26 | 2018-03-27 | 湖南考神信息科技有限责任公司 | The evaluation method and evaluation system of a kind of study |
-
2018
- 2018-04-02 CN CN201810296616.6A patent/CN110349446A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2001343887A (en) * | 2000-05-31 | 2001-12-14 | Proaxis Co Ltd | Learning support system |
| CN101000643A (en) * | 2006-01-10 | 2007-07-18 | 英业达股份有限公司 | Study system and method with review function |
| CN102074135A (en) * | 2010-10-21 | 2011-05-25 | 无敌科技(西安)有限公司 | Method and device for building question bank |
| CN103870463A (en) * | 2012-12-10 | 2014-06-18 | 中国电信股份有限公司 | Method and system for selecting test subjects |
| CN105374244A (en) * | 2015-12-10 | 2016-03-02 | 广东小天才科技有限公司 | Learning method and system based on wrong question analysis |
| CN107844898A (en) * | 2017-10-26 | 2018-03-27 | 湖南考神信息科技有限责任公司 | The evaluation method and evaluation system of a kind of study |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110942683A (en) * | 2019-12-02 | 2020-03-31 | 西安冉科信息技术有限公司 | Online learning system with assisting and practicing functions |
| CN111191910A (en) * | 2019-12-26 | 2020-05-22 | 上海乂学教育科技有限公司 | Learning system based on learning path planning |
| CN111444391A (en) * | 2020-04-09 | 2020-07-24 | 圆梦共享教育科技(深圳)有限公司 | Video learning effect evaluation method based on artificial intelligence |
| CN111444391B (en) * | 2020-04-09 | 2023-08-11 | 圆梦共享教育科技(深圳)有限公司 | Video learning achievement evaluation method based on artificial intelligence |
| CN111583743A (en) * | 2020-06-29 | 2020-08-25 | 甘肃省定西理工中等专业学校 | Thinking and administration consolidation review platform system based on Internet |
| CN113256252A (en) * | 2021-05-25 | 2021-08-13 | 上海金程教育培训有限公司 | B/S architecture-based test system |
| CN114241835A (en) * | 2021-11-17 | 2022-03-25 | 北京执象科技发展有限公司 | Student spoken language quality evaluation method and device |
| CN114241835B (en) * | 2021-11-17 | 2024-08-20 | 北京执象科技发展有限公司 | Student spoken language quality evaluation method and device |
| CN115147254A (en) * | 2022-09-05 | 2022-10-04 | 小白智能科技（长春）股份有限公司 | Robot for actively guiding and guiding children to learn and control method thereof |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110349446A (en) | Intelligent learning system and method | |
| CN106781785B (en) | Topic difficulty construction method and device based on big data and service equipment | |
| CN106409034B (en) | Intelligent arrangement method and equipment for home operation | |
| CN103577556B (en) | Device and method for obtaining association degree of question and answer pair | |
| CN102385807B (en) | Electronic detection system and method | |
| CN102074135A (en) | Method and device for building question bank | |
| CN106611522A (en) | Application of learning software system based on objective questions | |
| CN109887362A (en) | A kind of man-machine interactive automatic display system for teaching | |
| CN107844898A (en) | The evaluation method and evaluation system of a kind of study | |
| CN110222195A (en) | Topic is answered the method for digging and electronic device of result and knowledge point relationship | |
| CN109214962A (en) | Web education learning method, system, terminal and its storage medium | |
| CN110377689A (en) | Paper intelligent generation method, device, computer equipment and storage medium | |
| CN106201898A (en) | A kind of method and device of test software based on artificial intelligence | |
| CN107221212A (en) | A kind of on-line study person's cognitive style analysis method based on time series | |
| CN107977350A (en) | Intelligent examination system examination question generation method | |
| CN109240786A (en) | Theme changing method and electronic equipment | |
| CN109636218A (en) | Learning content recommendation method and electronic equipment | |
| CN110930275A (en) | Reading training learning system based on mobile terminal | |
| CN109615009A (en) | Learning content recommendation method and electronic equipment | |
| CN108831229A (en) | A kind of Chinese automatic grading method | |
| CN108091194A (en) | Intelligent clearance examination management method | |
| CN107424476A (en) | A kind of instrumental music training mate system | |
| CN110491222A (en) | Writing in classical Chinese learning system | |
| CN108804648A (en) | New word receiving and recording method based on voice search and electronic equipment | |
| CN112836994A (en) | Big data visualization method for online remote education and online education server |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20191018 |
|
| RJ01 | Rejection of invention patent application after publication |