CN108665394A - Adaptive learning method and system - Google Patents

Adaptive learning method and system Download PDF

Info

Publication number
CN108665394A
CN108665394A CN201810424599.XA CN201810424599A CN108665394A CN 108665394 A CN108665394 A CN 108665394A CN 201810424599 A CN201810424599 A CN 201810424599A CN 108665394 A CN108665394 A CN 108665394A
Authority
CN
China
Prior art keywords
study
node
learning
topic
test
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.)
Granted
Application number
CN201810424599.XA
Other languages
Chinese (zh)
Other versions
CN108665394B (en
Inventor
唐伟
金善国
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beijing Mandarin Online Education Polytron Technologies Inc
Original Assignee
Beijing Mandarin Online Education Polytron Technologies Inc
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Beijing Mandarin Online Education Polytron Technologies Inc filed Critical Beijing Mandarin Online Education Polytron Technologies Inc
Priority to CN201810424599.XA priority Critical patent/CN108665394B/en
Publication of CN108665394A publication Critical patent/CN108665394A/en
Application granted granted Critical
Publication of CN108665394B publication Critical patent/CN108665394B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10Services
    • G06Q50/20Education
    • G06Q50/205Education administration or guidance
    • GPHYSICS
    • G09EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09BEDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B7/00Electrically-operated teaching apparatus or devices working with questions and answers
    • GPHYSICS
    • G09EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09BEDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B7/00Electrically-operated teaching apparatus or devices working with questions and answers
    • G09B7/06Electrically-operated teaching apparatus or devices working with questions and answers of the multiple-choice answer-type, i.e. where a given question is provided with a series of answers and a choice has to be made from the answers
    • GPHYSICS
    • G09EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09BEDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B7/00Electrically-operated teaching apparatus or devices working with questions and answers
    • G09B7/06Electrically-operated teaching apparatus or devices working with questions and answers of the multiple-choice answer-type, i.e. where a given question is provided with a series of answers and a choice has to be made from the answers
    • G09B7/08Electrically-operated teaching apparatus or devices working with questions and answers of the multiple-choice answer-type, i.e. where a given question is provided with a series of answers and a choice has to be made from the answers characterised by modifying the teaching programme in response to a wrong answer, e.g. repeating the question, supplying further information

Landscapes

  • Engineering & Computer Science (AREA)
  • Business, Economics & Management (AREA)
  • Theoretical Computer Science (AREA)
  • Educational Administration (AREA)
  • Educational Technology (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Strategic Management (AREA)
  • Tourism & Hospitality (AREA)
  • General Health & Medical Sciences (AREA)
  • Human Resources & Organizations (AREA)
  • Marketing (AREA)
  • Primary Health Care (AREA)
  • Economics (AREA)
  • General Business, Economics & Management (AREA)
  • Health & Medical Sciences (AREA)
  • Electrically Operated Instructional Devices (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The present invention relates to a kind of adaptive learning method and systems, are designed in order to facilitate user's adaptive learning.Method of the present invention includes:Obtain the characteristic information of learner's individual;The personal feature of acquisition is analyzed and assessed, the evaluation to learning effect is formed;According to the Assessment of Learning Effect, generating has in targetedly adaptive learning perhaps path.Learner center of the present invention, being provided for different people has targetedly learning Content or learning path.

Description

Adaptive learning method and system
Technical field
Present invention relates particularly to a kind of adaptive learning method and systems.
Background technology
Under the premise of instructional objective is identical, there is the differences on learning foundation or learning ability each other by learner It is different, so if only providing identical learning Content or learning path, it can not reach and preferably be learned for school Practise effect.Therefore, it is necessary to a kind of learner centers, and being provided for different people has targetedly learning Content or Practise path.
Invention content
In order to solve the above technical problems, being that study individual formulation is efficient, with strong points the object of the present invention is to provide one kind Adaptive learning method and system.
Adaptive learning method of the present invention, including:
S1 user carries out node to the knowledge mapping of each study theme, obtains multiple study nodes, each to learn theme pair The study node answered includes the non-key node for having to the key node b of study and not being necessary study, wherein for all Key node indicates that each crucial study node includes learning Content and test topic, and non-key node is at least with set B Including learning Content, the non-key node in part further includes test topic, and there are front and back on learning sequence between node and node It relies on namely learning path is indicated for there is the node for the front and back dependence that cannot change with critical path BF;
S2 obtains the study theme of study individual choice, exports the corresponding preliminary test content of selected study theme, The preliminary test content is the corresponding roads the n test question destination aggregation (mda) of each key node in selected study theme;
S3 obtains the answer that study individual answers to test topic, and initial assessment score is obtained according to the answer, according to The initial assessment score generates corresponding initial learning path;
S4 obtains study individual complete after study individual completes the study of a study node in initial learning path At the node learning characteristic in the learning process of this study node, node evaluation is carried out to the node learning characteristic, according to Node evaluation result generates the corresponding new learning path of study individual again.
Further, the test topic types of preliminary test content are multiple-choice question;The selection option of study individual includes two Part, a part are test question purpose answer, and another part is certain situation of the user to test topic answer, the determining feelings The option of condition includes:Determine very much, be not sure, at will selecting three kinds;
It determines that study individual answers data to the test question purpose of each key node b, full marks key is deleted in set B Node generates initial learning path, wherein the full marks key node is:Study individual is corresponding to a key node all to be surveyed Examination question purpose data of answering are correct, determine very much that then the key node is full marks key node.
Further, S4 includes:
Acquisition study individual learn node total learning time, this learn node in topic answer knot Fruit;
It is specific to judge according to the answer of topic in study node as a result, whether judgement study individual is by the study node Method includes:
The case where study passes through:
If without test topic in the study node, then no less than teacher's preset minimum duration when study, as logical It crosses;
If having test topic in the study node, then test topic is completely correct, no matter whether study duration is more than most Low duration is all judged to pass through;
There is topic in several study nodes, then topic is not totally wrong, and learns duration and be no less than minimum duration, is judged to Pass through;
If the case where study does not pass through:
If being judged to not pass through then being less than teacher's preset minimum duration when study without test topic in node;
If study node has test topic, then the complete mistake of topic, is judged to not pass through;
If study node has test topic, the endless total correctness of topic, and learns duration and be less than minimum duration, it is judged to obstructed It crosses;
If study node has test topic, topic whole mistake all to sentence no matter whether study duration is no less than minimum duration Not pass through;
According to study individual whether by currently learning node, generates new study node without assessment mode again or have again Secondary assessment mode generates new study node, wherein
Generating new study node without assessment mode again includes:
Determine new learning path, including:The first new learning path determines method, including:If sentenced according to feature To pass through, then the study of next key node is entered directly into;If being judged to not pass through according to feature, commented according to the node Point result is inserted into the study node of non-key study node;
Have again assessment mode generate new study node and include:
The content of the key node b learnt according to upper one, output test topic, test topic types are multiple-choice question;With The selection result at family includes two parts, and a part is test question purpose answer, and another part is user to test topic answer The option of certain situation, the certain situation includes:Determine very much, be not sure, at will selecting three kinds;
It obtains study individual to answer data to test question purpose, wherein answer to user and analyze, obtain initial assessment Score, wherein initial assessment score include 6 kinds of situations:
One kind, the test question purpose selection result for learning individual is correct;Being selected as situation is grasped to determine very much;
Second, the test question purpose selection result for learning individual is correct;Being selected as situation is grasped to determine very much;
The third, the test question purpose selection result for learning individual is correct;Being selected as situation is grasped at will to select;
4th kind, the test question purpose selection result for learning individual is mistake;Being selected as situation is grasped to determine very much;
5th kind, the test question purpose selection result for learning individual is mistake;Being selected as situation is grasped to be not sure really It is fixed;
6th kind, the test question purpose selection result for learning individual is mistake;Being selected as situation is grasped at will to select;
The submission of only whole topics is combined as " correct:It is very determining " and it is " correct:Be not sure " when judge pass through, it is no Then all it is judged as not passing through.
If being judged to pass through according to assessment page, the study of next key node is entered directly into.
If being judged to not pass through according to assessment page, it is inserted into additional study node.
Adaptive and learning system of the present invention, including:
Learn node storage unit, for storing multiple study nodes, each corresponding study node of theme that learns is including must The key node b that need learn and be not necessary study non-key node, wherein for all key nodes, with set B come It indicates, each crucial study node includes learning Content and test topic, and non-key node includes at least learning Content, and part is non- Key node further include test topic, between node and node there are on learning sequence front and back dependence namely learning path, it is right In the node that there is the front and back dependence that cannot change, indicated with critical path BF;
Content push unit is tested, the study theme of study individual choice is obtained, selected study theme is exported and corresponds to Preliminary test content, the preliminary test content is each key node corresponding roads n test in selected study theme Inscribe destination aggregation (mda);
Initial learning path generation unit obtains the answer that study individual answers to test topic, is obtained according to the answer Corresponding initial learning path is generated according to the initial assessment score to initial assessment score;
New learning path generation unit, when study individual completes the study of a study node in initial learning path Afterwards, node learning characteristic of the study individual in the learning process for completing this study node is obtained, the node is learnt special Sign carries out node evaluation, and the corresponding new learning path of study individual is generated again according to node evaluation result.
Further, new learning path generation unit includes:
The individual learning characteristic evaluation module of study, acquisition study individual learn node total learning time, this The answer result of topic in a study node;
Learn node whether by determination module, according to the answer of topic in study node as a result, judgement study individual is It is no by the study node, specific determination method includes:
The case where study passes through:
If without test topic in the study node, then no less than teacher's preset minimum duration when study, as logical It crosses;
If having test topic in the study node, then test topic is completely correct, no matter whether study duration is more than most Low duration is all judged to pass through;
There is topic in several study nodes, then topic is not totally wrong, and learns duration and be no less than minimum duration, is judged to Pass through;
If the case where study does not pass through:
If being judged to not pass through then being less than teacher's preset minimum duration when study without test topic in node;
If study node has test topic, then the complete mistake of topic, is judged to not pass through;
If study node has test topic, the endless total correctness of topic, and learns duration and be less than minimum duration, it is judged to obstructed It crosses;
If study node has test topic, topic whole mistake all to sentence no matter whether study duration is no less than minimum duration Not pass through;
New study node generation module, according to study individual whether by currently learning node, without assessment mode again Generate new study node or have again assessment mode generate new study node, wherein
Generating new study node without assessment mode again includes:
Determine new learning path, including:The first new learning path determines method, including:If sentenced according to feature To pass through, then the study of next key node is entered directly into;If being judged to not pass through according to feature, commented according to the node Point result is inserted into the study node of non-key study node;
Have again assessment mode generate new study node and include:
The content of the key node b learnt according to upper one, output test topic, test topic types are multiple-choice question;With The selection result at family includes two parts, and a part is test question purpose answer, and another part is user to test topic answer The option of certain situation, the certain situation includes:Determine very much, be not sure, at will selecting three kinds;
It obtains study individual to answer data to test question purpose, wherein answer to user and analyze, obtain initial assessment Score, wherein initial assessment score include 6 kinds of situations:
One kind, the test question purpose selection result for learning individual is correct;Being selected as situation is grasped to determine very much;
Second, the test question purpose selection result for learning individual is correct;Being selected as situation is grasped to determine very much;
The third, the test question purpose selection result for learning individual is correct;Being selected as situation is grasped at will to select;
4th kind, the test question purpose selection result for learning individual is mistake;Being selected as situation is grasped to determine very much;
5th kind, the test question purpose selection result for learning individual is mistake;Being selected as situation is grasped to be not sure really It is fixed;
6th kind, the test question purpose selection result for learning individual is mistake;Being selected as situation is grasped at will to select;
The submission of only whole topics is combined as " correct:It is very determining " and it is " correct:Be not sure " when judge pass through, it is no Then all it is judged as not passing through.
If being judged to pass through according to assessment page, the study of next key node is entered directly into.
If being judged to not pass through according to assessment page, it is inserted into additional study node.
According to the above aspect of the present invention, adaptive learning method of the present invention and system have at least the following advantages:
User of the present invention can directly be multiplexed the existing content of courses, provide the branch in adaptive learning Contents Construction resource Support.Each node in adaptive content can also be independently operated, completion teaching, fully promoted adaptive content application value and The task performance of faculty.
Above description is only the general introduction of technical solution of the present invention, in order to better understand the technical means of the present invention, And can be implemented in accordance with the contents of the specification, below with presently preferred embodiments of the present invention and after coordinating attached drawing to be described in detail such as.
Description of the drawings
Fig. 1 adaptive learning method flow charts of the present invention.
The test estimation flow figure of Fig. 2 adaptive learning methods of the present invention.
Specific implementation mode
With reference to the accompanying drawings and examples, the specific implementation mode of the present invention is described in further detail.Implement below Example is not limited to the scope of the present invention for illustrating the present invention.
Embodiment 1
The present embodiment adaptive learning method, including:
S1 user carries out node to the knowledge mapping of each study theme, obtains multiple study nodes, each to learn theme pair The study node answered includes the non-key node for having to the key node b of study and not being necessary study, wherein for all Key node indicates that each crucial study node includes learning Content and test topic, and non-key node is at least with set B Including learning Content, the non-key node in part further includes test topic, and there are front and back on learning sequence between node and node It relies on namely learning path is indicated for there is the node for the front and back dependence that cannot change with critical path BF;
S2 obtains the study theme of study individual choice, exports the corresponding preliminary test content of selected study theme, The preliminary test content is the corresponding roads the n test question destination aggregation (mda) of each key node in selected study theme;
S3 obtains the answer that study individual answers to test topic, and initial assessment score is obtained according to the answer, according to The initial assessment score generates corresponding initial learning path;
S4 obtains study individual complete after study individual completes the study of a study node in initial learning path At the node learning characteristic in the learning process of this study node, node evaluation is carried out to the node learning characteristic, according to Node evaluation result generates the corresponding new learning path of study individual again.
(1) based on test topic, if the associated topics of one of b, student all answers correct, and result is all It is " correct:It is very determining ", illustrate that student grasps this key node completely, then will remove in the B in adaptive content This b is " correct if there is removing:It is very determining " outer other result types, then b still retain in B, to ensure to allow as possible Raw abundant mastery learning content.
(2) initial learning characteristic is exactly the answer result of each b associations topic.
(3) these learning characteristics are used for judging which b can remove before adaptive learning in B, to save student The time is practised, learning efficiency is promoted.
(1) which data (learning characteristic) of acquisition study individual:Two data, one is total of this study node The time is practised, the other is this learns the answer result of topic in node.
(2) analysis method (algorithm):According to learning characteristic, there are two as a result, study passes through and learn not lead to for meeting after analysis It crosses.
The case where study passes through:If without topic in node, no less than teacher's preset minimum duration when study, As pass through;If there is topic in node, topic is completely correct, no matter whether study duration is more than minimum duration, all sentences To pass through;If there is topic in node, topic is not totally wrong, and learns duration and be no less than minimum duration, is judged to pass through.
The case where study does not pass through:If being less than teacher's preset minimum duration when learning without topic in node, It is judged to not pass through;If node has topic, the complete mistake of topic to be judged to not pass through;If node has topic, topic endless Total correctness, and learn duration and be less than minimum duration, it is judged to not pass through;If there is topic, topic whole mistake, no matter learn duration Whether it is no less than minimum duration, is all judged to not pass through.
(3) new learning path is obtained according to feature:
Divide two ways:A. being inserted into after b. key nodes have learnt without assessment page after key node has learnt has assessment page to insert Enter
a:It is inserted into without assessment page, the learning characteristic for being completely dependent on key node b carries out adaptive path planning
If being judged to pass through according to feature, the study of next key node is entered directly into.
If being judged to not pass through according to feature, it is inserted into additional study node.
b:There is assessment page to be inserted into, then the assessment result for being completely dependent on assessment page carries out adaptive path planning
Preceding test question of the content with push of page is assessed, difference lies in topic only has around the key node b just learnt Content, be not related to the relevant topic of other key nodes.
Appraisal procedure is different from preceding test, regular relative loose:The submission of only whole topics is combined as " correct:Very Determine " and it is " correct:Be not sure " when judge pass through, be otherwise all judged as not passing through.
If being judged to pass through according to assessment page, the study of next key node is entered directly into.
If being judged to not pass through according to assessment page, it is inserted into additional study node.
The operation principle of Adaptable System includes:
It is pre-created or splices micro- class;
The crucial micro- class of selection, creates adaptive micro- class;
The crucial micro- class of importing or addition content pages, selecting suitable position to be inserted into assessment page or select has adaptation function Single choice;
Assessment page is inserted into test topic or selectes with the option adaptively guided;
Score section delimited to be associated with micro- class or be associated with micro- class after particular options.
Further, learning path is the screening displaying to learning node and permutation and combination, it is therefore desirable to learning Content Carry out node.A kind of common form of node is exactly the knowledge mapping of the course.But the granularity of knowledge mapping is relatively adaptive It is still higher for should learning, therefore more fine-grained node can also be done.Most suitable granularity is that a study node exists Be not suitable for being further continued for dividing on learning path:Content order i.e. in node does not have the meaning of permutatation, all the elements It is impossible to delete or do again the additional supplement being not necessarily to.Certainly, under requirement adaptive in various degree, the rule of node Mould can also rise, for example can also meet certain adaptive requirement using the granularity of knowledge mapping as study node.
Node is related to the specific content of courses, thus node judgement and structure can in person have been participated in by faculty At.If knowledge mapping can refine to certain granularity, at the same all teaching materials can be referred to it is every on knowledge mapping A node simultaneously stamps type label, then the work of node can also be automatically performed by system.The node of the content of courses is Content basis based on path adaptive learning.
Further, instructional objective can also be split according to the thought of learning Content node, generate several compared with For specific Small object.Under explicitly teaching Small object, the adaptive learning path being built by study node must be one The path that item is limited in scope will not completely disengage instructional objective, while can cover some key nodes again.Here cannot jump It crosses the node for having to learn and is referred to as key node b.It for all key nodes, is indicated with set B, B can also be, There is no any key node under the learning objective.
There may be the front and back dependences on learning sequence between node and node, for there is clear front and back dependence in B Node can be indicated with critical path BF.For the difference set of B and BF --- it must be learned by but without the section relied on exact sequence Point can be inserted by certain rule on the path of BF, can also be by adaptive mode according to the learning characteristic of learner Selectively it is inserted into more particularly suitable position.In view of all extremely key can not be rejected the learning Content in B, and B interior joints Put in order and be also easy to generate a subjective Rational Path, therefore the present invention path final to B is simplified --- It is the identical set of element that all nodes, which have ordinal relation to each other, i.e. B and BF, in acquiescence B, while in the base of B BF also includes a fixed path relation of sequence on plinth.
Further, it can be considered additional nodes except the learning Content other than BF, be denoted as A, additional nodes structure on BF The path built out is considered as extra path, is denoted as AF.Therefore the present invention is discussed adaptive, and emphasis is based on additional on BF The adaptive problem of path AF.When BF is skyOr BF is very short and Instructional Design of faculty focus primarily on AF when It waits, comparatively the adaptive degree for the adaptive learning that the present invention is discussed can greatly improve.No matter but any journey be increased to Degree, the adaptive learning that the present invention discusses is all based on do not depart from clear instructional objective under the premise of be unfolded it is adaptive.
A is the supplement of B, for example consolidates, enhancing, extends.For instructional objective, A can help learning ability weaker Learner preferably reach target, or allow be easy to reach learning objective learner obtain surmount it is more outside set objective Learning Content and better learning effect.It is exactly the form of AF and BF specific to learning path.There are one usual instructional objectives Judge the baseline passed, but more than after baseline, is an effect section in fact.Outstanding faculty usually will not only meet Pass as a result, but obtaining better teaching efficiency in controlled conditions as far as possible.So A have for B it is more important Meaning, and AF also has very important significance for the adaptive of BF.Perhaps, supplement and promotion are only adaptively most Big value.
Evaluation point of the present invention is the assessment to assessing section, and assessment section can be that (micro- class is by page for one or more pages Face is constituted), consider from form consistency, evaluation point can also be shown with an independent page.If assessment is specific Operate it is fairly simple clear, such as only assessment user which option is had submitted in the page, then evaluation point can not need yet It is individually shown with a page.
From the dimension of assessment object, assessment is comprising objective and two kinds subjective.Objective i.e. completeness, accuracy, completion Time, submission the information such as option.Subjectivity can directly allow user to do topic and investigate or test, and the study to obtain user is commented Valence.
From the purpose dimension of assessment, for example purpose is to find the point of interest of student, then can directly be carried from user The number duration of the option of friendship or each page browsing determines.
Assessment needs to integrate various data, has certain complexity, therefore still to focus and really use field Scape and operational effect are adjusted.
To the behavioral data of study:Completeness, duration, submission option, accuracy etc. count, and can be used as objective item The assessment that mesh is automated.In addition to this it is possible to provide important supplement of the test as assessment.From evaluation learning effect For purpose, it is the most effective means for comparing other modes to pass a test and carry out assessment.
For learning effect:It is assessed in evaluation point addition test, different AF is guided according to test result.
For user behavior:Corresponding AF is directly linked to after the option of multiple-choice question.
Embodiment 2
The present embodiment adaptive and learning system, in order to realize the method described in above-described embodiment 1, including:
Learn node storage unit, for storing multiple study nodes, each corresponding study node of theme that learns is including must The key node b that need learn and be not necessary study non-key node, wherein for all key nodes, with set B come It indicates, each crucial study node includes learning Content and test topic, and non-key node includes at least learning Content, and part is non- Key node further include test topic, between node and node there are on learning sequence front and back dependence namely learning path, it is right In the node that there is the front and back dependence that cannot change, indicated with critical path BF;
Content push unit is tested, the study theme of study individual choice is obtained, selected study theme is exported and corresponds to Preliminary test content, the preliminary test content is each key node corresponding roads n test in selected study theme Inscribe destination aggregation (mda);
Initial learning path generation unit obtains the answer that study individual answers to test topic, is obtained according to the answer Corresponding initial learning path is generated according to the initial assessment score to initial assessment score;
New learning path generation unit, when study individual completes the study of a study node in initial learning path Afterwards, node learning characteristic of the study individual in the learning process for completing this study node is obtained, the node is learnt special Sign carries out node evaluation, and the corresponding new learning path of study individual is generated again according to node evaluation result.
New learning path generation unit includes:
The individual learning characteristic evaluation module of study, acquisition study individual learn node total learning time, this The answer result of topic in a study node;
Learn node whether by determination module, according to the answer of topic in study node as a result, judgement study individual is It is no by the study node, specific determination method includes:
The case where study passes through:
If without test topic in the study node, then no less than teacher's preset minimum duration when study, as logical It crosses;
If having test topic in the study node, then test topic is completely correct, no matter whether study duration is more than most Low duration is all judged to pass through;
There is topic in several study nodes, then topic is not totally wrong, and learns duration and be no less than minimum duration, is judged to Pass through;
If the case where study does not pass through:
If being judged to not pass through then being less than teacher's preset minimum duration when study without test topic in node;
If study node has test topic, then the complete mistake of topic, is judged to not pass through;
If study node has test topic, the endless total correctness of topic, and learns duration and be less than minimum duration, it is judged to obstructed It crosses;
If study node has test topic, topic whole mistake all to sentence no matter whether study duration is no less than minimum duration Not pass through;
New study node generation module, according to study individual whether by currently learning node, without assessment mode again Generate new study node or have again assessment mode generate new study node, wherein
Generating new study node without assessment mode again includes:
Determine new learning path, including:The first new learning path determines method, including:If sentenced according to feature To pass through, then the study of next key node is entered directly into;If being judged to not pass through according to feature, commented according to the node Point result is inserted into the study node of non-key study node;
Have again assessment mode generate new study node and include:
The content of the key node b learnt according to upper one, output test topic, test topic types are multiple-choice question;With The selection result at family includes two parts, and a part is test question purpose answer, and another part is user to test topic answer The option of certain situation, the certain situation includes:Determine very much, be not sure, at will selecting three kinds;
It obtains study individual to answer data to test question purpose, wherein answer to user and analyze, obtain initial assessment Score, wherein initial assessment score include 6 kinds of situations:
One kind, the test question purpose selection result for learning individual is correct;Being selected as situation is grasped to determine very much;
Second, the test question purpose selection result for learning individual is correct;Being selected as situation is grasped to determine very much;
The third, the test question purpose selection result for learning individual is correct;Being selected as situation is grasped at will to select;
4th kind, the test question purpose selection result for learning individual is mistake;Being selected as situation is grasped to determine very much;
5th kind, the test question purpose selection result for learning individual is mistake;Being selected as situation is grasped to be not sure really It is fixed;
6th kind, the test question purpose selection result for learning individual is mistake;Being selected as situation is grasped at will to select;
The submission of only whole topics is combined as " correct:It is very determining " and it is " correct:Be not sure " when judge pass through, it is no Then all it is judged as not passing through.
If being judged to pass through according to assessment page, the study of next key node is entered directly into.
If being judged to not pass through according to assessment page, it is inserted into additional study node.
The above is only a preferred embodiment of the present invention, it is not intended to restrict the invention, it is noted that for this skill For the those of ordinary skill in art field, without departing from the technical principles of the invention, can also make it is several improvement and Modification, these improvements and modifications also should be regarded as protection scope of the present invention.

Claims (5)

1. a kind of adaptive learning method, which is characterized in that including:
S1 user carries out node to the knowledge mapping of each study theme, obtains multiple study nodes, and each study theme is corresponding Study node includes the non-key node for having to the key node b of study and not being necessary study, wherein for all keys Node indicates that each crucial study node includes learning Content and test topic, and non-key node is included at least with set B Learning Content, the non-key node in part further include test topic, and there are the front and back dependences on learning sequence between node and node Namely learning path is indicated for there is the node for the front and back dependence that cannot change with critical path BF;
S2 obtains the study theme of study individual choice, exports the corresponding preliminary test content of selected study theme, described Preliminary test content is the corresponding roads the n test question destination aggregation (mda) of each key node in selected study theme;
S3 obtains the answer that study individual answers to test topic, initial assessment score is obtained according to the answer, according to described Initial assessment score generates corresponding initial learning path;
S4 obtains study individual and completes this after study individual completes the study of a study node in initial learning path Node learning characteristic in the learning process of a study node, carries out node evaluation, according to node to the node learning characteristic Assessment result generates the corresponding new learning path of study individual again.
2. adaptive learning method according to claim 1, which is characterized in that the test topic types of preliminary test content For multiple-choice question;The selection option of study individual includes two parts, and a part is test question purpose answer, and another part is user couple The certain situation of topic answer is tested, the option of the certain situation includes:Determine very much, be not sure, at will selecting three kinds;
Determine that study individual answers data to the test question purpose of each key node b, the deletion full marks key section in set B Point generates initial learning path, wherein the full marks key node is:The all tests corresponding to a key node of study individual The data of answering of topic are correct, determine very much that then the key node is full marks key node.
3. adaptive learning method according to claim 1, which is characterized in that S4 includes:
Acquisition study individual learn node total learning time, this learn node in topic answer result;
According to the answer of topic in study node as a result, whether judgement study individual passes through the study node, specific determination method Including:
The case where study passes through:
If without test topic in the study node, then no less than teacher's preset minimum duration when study, as passes through;
If having test topic in the study node, then test topic is completely correct, no matter whether study duration is more than minimum It is long, it is all judged to pass through;
There is topic in several study nodes, then topic is not totally wrong, and learns duration and be no less than minimum duration, is judged to lead to It crosses;
If the case where study does not pass through:
If being judged to not pass through then being less than teacher's preset minimum duration when study without test topic in node;
If study node has test topic, then the complete mistake of topic, is judged to not pass through;
If study node has test topic, the endless total correctness of topic, and learns duration and be less than minimum duration, it is judged to not pass through;
If study node has test topic, topic whole mistake to be all judged to not no matter whether study duration is no less than minimum duration Pass through;
According to study individual whether by currently learning node, generates new study node without assessment mode again or have and comment again Estimate mode and generate new study node, wherein
Generating new study node without assessment mode again includes:
Determine new learning path, including:The first new learning path determines method, including:If being judged to lead to according to feature It crosses, then enters directly into the study of next key node;If being judged to not pass through according to feature, is scored and tied according to the node Fruit is inserted into the study node of non-key study node;
Have again assessment mode generate new study node and include:
The content of the key node b learnt according to upper one, output test topic, test topic types are multiple-choice question;User's Selection result includes two parts, and a part is test question purpose answer, and another part is determination of the user to test topic answer The option of situation, the certain situation includes:Determine very much, be not sure, at will selecting three kinds;
It obtains study individual to answer data to test question purpose, wherein answer to user and analyze, obtain initial assessment and obtain Point, wherein initial assessment score includes 6 kinds of situations:
One kind, the test question purpose selection result for learning individual is correct;Being selected as situation is grasped to determine very much;
Second, the test question purpose selection result for learning individual is correct;Being selected as situation is grasped to determine very much;
The third, the test question purpose selection result for learning individual is correct;Being selected as situation is grasped at will to select;
4th kind, the test question purpose selection result for learning individual is mistake;Being selected as situation is grasped to determine very much;
5th kind, the test question purpose selection result for learning individual is mistake;It grasps being selected as situation and is not sure determination;
6th kind, the test question purpose selection result for learning individual is mistake;Being selected as situation is grasped at will to select;
The submission of only whole topics is combined as " correct:It is very determining " and it is " correct:Be not sure " when judge pass through, otherwise all It is judged as not passing through.
If being judged to pass through according to assessment page, the study of next key node is entered directly into.
If being judged to not pass through according to assessment page, it is inserted into additional study node.
4. a kind of adaptive and learning system, which is characterized in that including:
Learn node storage unit, for storing multiple study nodes, each corresponding study node of theme that learns includes having to The key node b of study and be not necessary study non-key node, wherein for all key nodes, with set B come table Show, each crucial study node includes learning Content and test topic, and non-key node includes at least learning Content, the non-pass in part Key node further include test topic, between node and node there are on learning sequence front and back dependence namely learning path, for In the presence of the node for the front and back dependence that cannot change, indicated with critical path BF;
Content push unit is tested, the study theme of study individual choice is obtained, it is corresponding just to export selected study theme Pacing tries content, and the preliminary test content is that topic is tested in the corresponding roads n of each key node in selected study theme Set;
Initial learning path generation unit obtains the answer that study individual answers to test topic, is obtained just according to the answer Begin assessment score, according to the initial assessment score, generates corresponding initial learning path;
New learning path generation unit, after study individual completes the study of a study node in initial learning path, Obtain study individual complete this study node learning process in node learning characteristic, to the node learning characteristic into Row node evaluation generates the corresponding new learning path of study individual again according to node evaluation result.
5. adaptive and learning system according to claim 4, which is characterized in that new learning path generation unit includes:
The individual learning characteristic evaluation module of study, acquisition study individual are learning node total learning time, this Practise the answer result of topic in node;
Learn node whether by determination module, according to the answer of topic in study node as a result, whether judgement study individual leads to The study node is crossed, specific determination method includes:
The case where study passes through:
If without test topic in the study node, then no less than teacher's preset minimum duration when study, as passes through;
If having test topic in the study node, then test topic is completely correct, no matter whether study duration is more than minimum It is long, it is all judged to pass through;
There is topic in several study nodes, then topic is not totally wrong, and learns duration and be no less than minimum duration, is judged to lead to It crosses;
If the case where study does not pass through:
If being judged to not pass through then being less than teacher's preset minimum duration when study without test topic in node;
If study node has test topic, then the complete mistake of topic, is judged to not pass through;
If study node has test topic, the endless total correctness of topic, and learns duration and be less than minimum duration, it is judged to not pass through;
If study node has test topic, topic whole mistake to be all judged to not no matter whether study duration is no less than minimum duration Pass through;
Whether new study node generation module generates according to study individual by currently learning node without assessment mode again New study node or have again assessment mode generate new study node, wherein
Generating new study node without assessment mode again includes:
Determine new learning path, including:The first new learning path determines method, including:If being judged to lead to according to feature It crosses, then enters directly into the study of next key node;If being judged to not pass through according to feature, is scored and tied according to the node Fruit is inserted into the study node of non-key study node;
Have again assessment mode generate new study node and include:
The content of the key node b learnt according to upper one, output test topic, test topic types are multiple-choice question;User's Selection result includes two parts, and a part is test question purpose answer, and another part is determination of the user to test topic answer The option of situation, the certain situation includes:Determine very much, be not sure, at will selecting three kinds;
It obtains study individual to answer data to test question purpose, wherein answer to user and analyze, obtain initial assessment and obtain Point, wherein initial assessment score includes 6 kinds of situations:
One kind, the test question purpose selection result for learning individual is correct;Being selected as situation is grasped to determine very much;
Second, the test question purpose selection result for learning individual is correct;Being selected as situation is grasped to determine very much;
The third, the test question purpose selection result for learning individual is correct;Being selected as situation is grasped at will to select;
4th kind, the test question purpose selection result for learning individual is mistake;Being selected as situation is grasped to determine very much;
5th kind, the test question purpose selection result for learning individual is mistake;It grasps being selected as situation and is not sure determination;
6th kind, the test question purpose selection result for learning individual is mistake;Being selected as situation is grasped at will to select;
The submission of only whole topics is combined as " correct:It is very determining " and it is " correct:Be not sure " when judge pass through, otherwise all It is judged as not passing through.
If being judged to pass through according to assessment page, the study of next key node is entered directly into.
If being judged to not pass through according to assessment page, it is inserted into additional study node.
CN201810424599.XA 2018-05-07 2018-05-07 Self-adaptive learning method and system Active CN108665394B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201810424599.XA CN108665394B (en) 2018-05-07 2018-05-07 Self-adaptive learning method and system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201810424599.XA CN108665394B (en) 2018-05-07 2018-05-07 Self-adaptive learning method and system

Publications (2)

Publication Number Publication Date
CN108665394A true CN108665394A (en) 2018-10-16
CN108665394B CN108665394B (en) 2021-11-30

Family

ID=63778046

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201810424599.XA Active CN108665394B (en) 2018-05-07 2018-05-07 Self-adaptive learning method and system

Country Status (1)

Country Link
CN (1) CN108665394B (en)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109255994A (en) * 2018-10-26 2019-01-22 北京智能优学科技有限公司 A kind of foreign language teaching adaptive learning method and computer readable storage medium
CN109255998A (en) * 2018-10-25 2019-01-22 杭州数理大数据技术有限公司 A kind of student performance diagnosis lifting system
CN109615278A (en) * 2019-01-24 2019-04-12 张震浩 Study growth management method based on normal distribution
CN110009957A (en) * 2019-04-10 2019-07-12 上海乂学教育科技有限公司 The big knowledge mapping test macro of mathematics and method in adaptive learning
CN113469346A (en) * 2021-08-31 2021-10-01 盛隆电气集团有限公司 Supervision method and device for predicting short-time regional power utilization condition

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106600065A (en) * 2016-12-16 2017-04-26 中山大学 Individualized learning path extraction and jointing method and system based on directed hypergraph
WO2017084362A1 (en) * 2015-11-18 2017-05-26 百度在线网络技术(北京)有限公司 Model generation method, recommendation method and corresponding apparatuses, device and storage medium
CN107665473A (en) * 2016-07-27 2018-02-06 科大讯飞股份有限公司 Learning path planning method and device

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2017084362A1 (en) * 2015-11-18 2017-05-26 百度在线网络技术(北京)有限公司 Model generation method, recommendation method and corresponding apparatuses, device and storage medium
CN107665473A (en) * 2016-07-27 2018-02-06 科大讯飞股份有限公司 Learning path planning method and device
CN106600065A (en) * 2016-12-16 2017-04-26 中山大学 Individualized learning path extraction and jointing method and system based on directed hypergraph

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109255998A (en) * 2018-10-25 2019-01-22 杭州数理大数据技术有限公司 A kind of student performance diagnosis lifting system
CN109255994A (en) * 2018-10-26 2019-01-22 北京智能优学科技有限公司 A kind of foreign language teaching adaptive learning method and computer readable storage medium
CN109615278A (en) * 2019-01-24 2019-04-12 张震浩 Study growth management method based on normal distribution
CN110009957A (en) * 2019-04-10 2019-07-12 上海乂学教育科技有限公司 The big knowledge mapping test macro of mathematics and method in adaptive learning
CN113469346A (en) * 2021-08-31 2021-10-01 盛隆电气集团有限公司 Supervision method and device for predicting short-time regional power utilization condition

Also Published As

Publication number Publication date
CN108665394B (en) 2021-11-30

Similar Documents

Publication Publication Date Title
CN108665394A (en) Adaptive learning method and system
Melhuish et al. Elementary school teachers’ noticing of essential mathematical reasoning forms: Justification and generalization
CN107544973B (en) Method and device for processing data
US20040202987A1 (en) System and method for creating, assessing, modifying, and using a learning map
CN109388746A (en) A kind of education resource intelligent recommendation method based on learner model
US20160019802A1 (en) Neural adaptive learning device and neural adaptive learning method using realtional concept map
US20120077180A1 (en) Method and system for knowledge representation and processing using a structured visual idea map
CN106228480A (en) A kind of net work teaching system and method
Jong et al. Diagnostic and remedial learning strategy based on conceptual graphs
Aboalela et al. Model of learning assessment to measure student learning: inferring of concept state of cognitive skill level in concept space
Coenen et al. Combinatorial reasoning to solve problems
KR102179957B1 (en) Method and system for analyzing the learning status of learner and selecting corresponding supplementary problem
Mislevy Test theory reconceived
Leddo et al. Cognitive Structure Analysis: A technique for assessing what students know, not just how they perform
Brusilovsky Domain modeling for personalized guidance
Mediani et al. Towards a recommendation system for the learner from a semantic model of knowledge in a collaborative environment
Wu Adaptive learning diagnosis mechanisms for e-learning
Ramesh et al. Annotating the domain ontology of a course with its syllabus and learning objectives
da Silva et al. Adaptation in educational hypermedia based on the classification of the user profile
Zatarain-Cabada et al. A learning social network with recognition of learning styles using neural networks
Maddalora Personalized learning model using item response theory,”
Green Do structured manipulatives aid understanding of additive reasoning, and addition and subtraction fluency in a sample of Year 7 and 8 students?
Ko et al. Applying Data Mining to Explore Students' Self-Regulation in Learning Contexts
Aboalela et al. Computation of assessing the knowledge in one domain by using cognitive skills levels
Hosseini et al. A comparative study of visual cues for annotation-based navigation support in adaptive educational hypermedia

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
GR01 Patent grant
GR01 Patent grant
CP02 Change in the address of a patent holder
CP02 Change in the address of a patent holder

Address after: 1001, Unit 2, 9th Floor, Building 2-1, No. 82 East Fourth Ring Middle Road, Chaoyang District, Beijing, 100000

Patentee after: BEIJING ULEARNING EDUCATION TECHNOLOGY CO.,LTD.

Address before: Room 606, building 1, courtyard 4, Guanghua Road, Chaoyang District, Beijing 100026

Patentee before: BEIJING ULEARNING EDUCATION TECHNOLOGY CO.,LTD.