CN107832453A - Virtual test paper recommendation method oriented to personalized learning scheme - Google Patents
Virtual test paper recommendation method oriented to personalized learning scheme Download PDFInfo
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Abstract
The invention provides a virtual test paper recommendation method facing an individualized learning scheme, which is characterized in that a series of virtual test papers with the quantity percentages distributed around the left side and the right side of a main difficulty coefficient in a uniform gradient descending manner are generated according to a wheel disc selection method, the understanding degree coefficient of knowledge points of test questions in the test papers is matched in DNA information of students, the theoretical scores of the students are calculated by combining the full scores of the questions, the theoretical scores of each test question in the test papers are summed, the theoretical scores of the test questions of the student book set can be obtained, the theoretical scores are taken as a reference target, and test papers with the sequential difficulty are recommended according to the difficulty and the weakness of the students, so that the aim of gradually improving the learning score of the students is fulfilled.
Description
Technical field
The present invention relates to artificial intelligence and big data technical field, more specifically, is related to a kind of towards individualized learning
The virtual paper of scheme recommends method.
Background technology
With the popularization of Internet technology, the arriving in big data epoch, Web education has obtained rapid development, in face of mesh
The TB of preceding accumulation even the mass digital educational resource of PB levels, the similar big data information processing technology demand of data mining is increasingly
Urgently.Educational resource push is the production of educational pattern and method reform in teaching that Modern Education Technology is guided using network by carrier
A kind of thing, it is intended to explore Student oriented and teacher, there is provided the service mode of high-quality information resources.And personalized recommendation is this
Popular domain in research, personalized recommendation is combined with educational resource, learner is extracted with related big data digging technology
Learning behavior feature, be each user it is customized rationally effective Learning Scheme.
In modern education, because of technology and the missing of resource integrated method, student can not often find rapidly from a large number of homework exercises for primary and middle school students
The method for lifting oneself achievement；Teachers still remain the method that Traditional Man makes the test when end of term group is rolled up.In fact, pass through
Count substantial amounts of student and do the common problem inscribed and recorded with regard to students can be excavated, the achievement with regard to student can be greatly improved.
The content of the invention
In view of the above problems, it is an object of the invention to provide a kind of virtual paper recommendation side towards individualized learning scheme
Method, it is difficult to study condition for single student to solve traditional paper, the problem of recommending optimal personalized paper.
Virtual paper provided by the invention towards individualized learning scheme recommends method, including：
Step S1：Preset main degree-of-difficulty factor；Wherein, main degree-of-difficulty factor is higher than the learning adjustment difficulty of student at this stage；
Step S2：A set of volume percentage is generated according to wheel disc back-and-forth method gradient decline distribution is presented around main degree-of-difficulty factor
Virtual paper；Wherein, step S2 includes：
Step S21：The volume for 10 degree-of-difficulty factors for including main degree-of-difficulty factor area percentage shared in wheel disc is set
Than；Wherein, the selected probability P (i) of the volume of each degree-of-difficulty factor surrounds left and right two of the main degree-of-difficulty factor to main degree-of-difficulty factor
Side declines distribution in uniform gradient；
Step S22：The volume that the examination question of 10 degree-of-difficulty factors in virtual paper is produced by wheel disc back-and-forth method is distributed；
Step S23：Volume according to the examination question of 10 degree-of-difficulty factors caused by step S22, which is distributed from test item bank, extracts examination
Topic forms virtual paper；
Step S3：Virtual paper is combined with the DNA information of student to obtain theoretical score；
Wherein, DNA information is the three-dimensional tensor being made up of knowledge point, degree of understanding coefficient and time, and knowledge point is to institute
The high level overview of category section purpose core content；Degree of understanding coefficient refers to after student completes the exercise of certain knowledge point, and this is known
Know the description of the overall grasp situation of point；Time refer to student to the degree of understanding coefficient of knowledge point from a upper grade rise to
The time span of next grade；And
Degree of understanding coefficient of the student to the knowledge point is obtained by the knowledge point of per pass examination question in virtual paper, under utilization
State formula and obtain theoretical score of the student to virtual paper：
In above formula, Score is theoretical score of the student to the virtual paper；STgFor the full marks of g problems, wherein g
=1 ..., n；UDiKnowledge point i degree of understanding coefficient is inscribed to g for the student；
Step S4：Virtual paper of all theoretical scores in 60 to 80 points is saved as virtual Pipers database；
Step S5：Virtual paper is extracted from virtual Pipers database and recommends student.
Compared with prior art, the virtual paper provided by the invention towards individualized learning scheme recommends method, passes through
Wheel disc back-and-forth method produces virtual paper, and look-ahead goes out the theoretical score of student's paper under certain difficulty, when with this theoretical score
For reference target, when difficult point and weakness for student recommend the paper of difficulty successively, just can rationally be adjusted by its performance
Whole study plan, reach the purpose for stepping up Students ' Learning achievement.
Brief description of the drawings
By reference to the explanation below in conjunction with accompanying drawing, and with the present invention is more fully understood, of the invention is other
Purpose and result will be more apparent and should be readily appreciated that.In the accompanying drawings：
Fig. 1 is to set figure according to the area percentage of the virtual paper of the embodiment of the present invention.
Embodiment
Virtual paper provided by the invention towards individualized learning scheme recommends method, comprises the following steps：
Step S1：Preset main degree-of-difficulty factor.
Default main degree-of-difficulty factor should be higher than that the learning adjustment difficulty of student at this stage.
Step S2：A set of volume percentage is generated according to wheel disc back-and-forth method gradient decline distribution is presented around main degree-of-difficulty factor
Virtual paper.
Detailed process is as follows：
Step S21：The volume for 10 degree-of-difficulty factors for including main degree-of-difficulty factor area percentage shared in wheel disc is set
Than；Wherein, the selected probability P (i) of the volume of each degree-of-difficulty factor surrounds left and right two of the main degree-of-difficulty factor to main degree-of-difficulty factor
Side declines distribution in uniform gradient.
The present invention sets altogether the volume of 10 degree-of-difficulty factors, and 1 in 10 degree-of-difficulty factors be main degree-of-difficulty factor, residue
9 be other degree-of-difficulty factors, the probability that the volumes of 9 other degree-of-difficulty factors is selected in virtual paper, be designated as P (i), its
In, i=1 ..., 10, here obvious Sum (P)=1, P (i) around the right and left from main degree-of-difficulty factor to main degree-of-difficulty factor in equal
Even gradient declines distribution.
One degree-of-difficulty factor represents the difficulty of a grade.
Such as area percentage can be set to as shown in figure 1, each difficulty system by the virtual paper that main degree-of-difficulty factor is 5
Several probability distribution are：
Step S22：The volume that the examination question of 10 degree-of-difficulty factors in virtual paper is produced by wheel disc back-and-forth method is distributed.
Total volume of virtual paper can be with self-defined.
Such as：Total volume of virtual paper is 25 problems, toward the wheel disc for divided sector in throw away dice, throw away 25 every time,
Wheel disc is motionless, and the region that dice is fallen is selection result.Experiment 1000 times is repeated, draws end product.Obviously, sector is bigger,
The probability chosen by dice is bigger.That is, the examination question amount of difficulty 5 is maximum in virtual paper under difficulty 5, next to that difficult
5 neighbouring difficulty 4 and 6 are spent, difficulty 10 volume farthest from difficulty 5 is minimum, i.e., the examination question of difficulty 10 farthest from difficulty 5 is to learning
The raw help learnt at present is minimum.
Step S23：Volume according to the examination question of 10 degree-of-difficulty factors caused by step S22, which is distributed from test item bank, extracts examination
Topic forms virtual paper.
When extracting examination question, the examination question under same difficulty is randomly selected, and can be attempted all with the method traversal of permutation and combination
The possibility of examination question combination.
Step S3：Virtual paper is combined with the DNA information of student to obtain theoretical score.
The DNA information of student is the three-dimensional tensor being made up of knowledge point, degree of understanding coefficient and time, and knowledge point is subordinated to
Subject, it is, and high level overview to section purpose core content subdivided to section's purpose；
Degree of understanding coefficient refers to after student completes the exercise of certain knowledge point, to the overall grasp situation of this knowledge point
Description, degree of understanding coefficient utilize big data analytical technology, pass through COMPREHENSIVE CALCULATING knowledge point exercise accuracy and deadline
The ratio for accounting for the stipulated time is drawn；Time refers to that student is risen to next to the degree of understanding coefficient of knowledge point from a upper grade
The time span of individual grade.
Per pass examination question in virtual paper forms examination question DNA, examination question DNA and student by numbering, knowledge point and degree-of-difficulty factor
DNA information be combined and obtain theoretical score.Specifically, student is obtained to this by the knowledge point of per pass examination question in virtual paper
The degree of understanding coefficient of knowledge point, theoretical score of the student to virtual paper is obtained using following formula：
In above formula, Score is theoretical score of the student to the virtual paper；STgFor the full marks of g problems, wherein g
=1 ..., n；UDiThe degree of understanding coefficient of knowledge point is inscribed to g for the student, i is the knowledge point of g topics.
The degree of understanding coefficient of corresponding knowledge point in the DNA information of student is looked for by the knowledge point of examination question, is inscribed with this
Full marks score be multiplied by theoretical score of the student to i.e. this subject of degree of understanding coefficient of the knowledge point, then the reason of n roads examination question
By the theoretical score of the cumulative i.e. virtual paper of this set of score.
Step S4：Virtual paper of all theoretical scores in 60 to 80 points is saved as virtual Pipers database.
Wherein, paper of the theoretical score below 60 points should be that difficulty is higher for the student, and theoretical score is relatively low；Together
Sample, paper of the theoretical score more than 80 points is easier to student's difficulty, comparatively the paper in the two sections does not possess
Improve the effect of student performance.Therefore, virtual paper of the theoretical score in 60 to 80 points can weigh student to knowledge point
Grasping level.
By virtual paper of the theoretical score in 60 to 80 points be integrated into just can be faster more accurate in a Pipers database realization
Personalized recommendation.
Such as：Zhang San is as follows for the degree of understanding of a set of virtual paper including five problems：
Then Zhang San is scored to the theory of the virtual paper of the set：
The full marks of the virtual paper of the set are 45 points, then it is 30.6/45=68% that Zhang San's score, which accounts for total score ratio,
Then this set examination question belongs to the medium paper of difficulty to Zhang San classmate, is included in the virtual Pipers database of Zhang San.
Step S5：Virtual paper is extracted from virtual Pipers database and recommends student.
When extracting virtual paper, it is contemplated that the factor such as the degree-of-difficulty factor of paper, theoretical score, Distribution of knowledge gists, also may be used
Rational personalized recommendation is carried out automatically according to the weak knowledge point of student.
Step S6：Student performs study according to the virtual paper of recommendation.
Step S7：Update the DNA information of student.
Student accounts for the stipulated time after paper is completed, according to the time that student completes the accuracy of certain topic and completes the topic
Ratio renewal knowledge point degree of understanding coefficient UDi, and record degree of understanding coefficient UD of the student to the topic knowledge pointiRise to
Preceding time and the time after rising to, so as to update the DNA information of student.
The foregoing is only a specific embodiment of the invention, but protection scope of the present invention is not limited thereto, any
Those familiar with the art the invention discloses technical scope in, change or replacement can be readily occurred in, should all be contained
Cover within protection scope of the present invention.Therefore, protection scope of the present invention described should be defined by scope of the claims.
Claims (2)
1. a kind of virtual paper towards individualized learning scheme recommends method, including：
Step S1：Preset main degree-of-difficulty factor；Wherein, the main degree-of-difficulty factor is higher than the learning adjustment difficulty of student at this stage；
Step S2：A set of volume percentage is generated according to wheel disc back-and-forth method gradient decline distribution is presented around the main degree-of-difficulty factor
Virtual paper；Wherein, the step S2 includes：
Step S21：The volume for 10 degree-of-difficulty factors for including main degree-of-difficulty factor area percentage shared in wheel disc is set
Than；Wherein, the selected probability P (i) of the volume of each degree-of-difficulty factor surrounds the main degree-of-difficulty factor to the main degree-of-difficulty factor
The right and left in uniform gradient decline distribution；
Step S22：The volume that the examination question of 10 degree-of-difficulty factors in virtual paper is produced by the wheel disc back-and-forth method is distributed；
Step S23：Volume according to the examination question of 10 degree-of-difficulty factors caused by the step S22, which is distributed from test item bank, extracts examination
Topic forms the virtual paper；
Step S3：The virtual paper is combined with the DNA information of student to obtain theoretical score；
Wherein, the DNA information is the three-dimensional tensor being made up of knowledge point, degree of understanding coefficient and time, and the knowledge point is
To the high level overview of affiliated section's purpose core content；The degree of understanding coefficient refers to the exercise that certain knowledge point is completed in student
Afterwards, to the description of the overall grasp situation of this knowledge point；The time refers to student to the degree of understanding coefficient of knowledge point from upper
One grade rises to the time span of next grade；And
Degree of understanding coefficient of the student to the knowledge point is obtained by the knowledge point of per pass examination question in the virtual paper, under utilization
State formula and obtain theoretical score of the student to the virtual paper：
<mrow>
<mi>S</mi>
<mi>c</mi>
<mi>o</mi>
<mi>r</mi>
<mi>e</mi>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mn>1</mn>
<mi>n</mi>
</munderover>
<msub>
<mi>ST</mi>
<mi>g</mi>
</msub>
<mo>&times;</mo>
<msub>
<mi>UD</mi>
<mi>i</mi>
</msub>
</mrow>
In above formula, Score is theoretical score of the student to the virtual paper；STgFor the full marks of g problems, wherein g=
1,...,n；UDiKnowledge point i degree of understanding coefficient is inscribed to g for the student；
Step S4：Virtual paper of all theoretical scores in 60 to 80 points is saved as virtual Pipers database；
Step S5：Virtual paper, which is extracted, from the virtual Pipers database recommends student.
2. the virtual paper according to claim 1 towards individualized learning scheme recommends method, virtually tried from described
Extracted in item pool after virtual paper recommends student, in addition to：
The accuracy of i-th topic is completed according to student and the deadline accounts for the ratio renewal student of stipulated time to the i-th topic knowledge point
Degree of understanding coefficient UDi, and record degree of understanding coefficient UD of the student to the i-th topic knowledge pointiTime before rising to and rise to
Time afterwards, update the DNA information of student.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110334204A (en) * | 2019-05-27 | 2019-10-15 | 湖南大学 | A kind of exercise similarity calculation recommended method based on user record |
| CN112235333A (en) * | 2019-07-15 | 2021-01-15 | 北京字节跳动网络技术有限公司 | Function package management method, device, equipment and storage medium |
| CN115905576A (en) * | 2023-01-09 | 2023-04-04 | 北京布局未来教育科技有限公司 | Test paper generation method and device, electronic equipment and medium |
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| CN105469145A (en) * | 2016-01-15 | 2016-04-06 | 清华大学 | Intelligent test paper method based on genetic particle swarm optimization algorithm |
| CN106095812A (en) * | 2016-05-31 | 2016-11-09 | 广东能龙教育股份有限公司 | Intelligent test paper generation method based on similarity measurement |
| CN107203583A (en) * | 2017-03-27 | 2017-09-26 | 杭州博世数据网络有限公司 | It is a kind of that method is inscribed based on the smart group that big data is analyzed |
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| CN105469145A (en) * | 2016-01-15 | 2016-04-06 | 清华大学 | Intelligent test paper method based on genetic particle swarm optimization algorithm |
| CN106095812A (en) * | 2016-05-31 | 2016-11-09 | 广东能龙教育股份有限公司 | Intelligent test paper generation method based on similarity measurement |
| CN107203583A (en) * | 2017-03-27 | 2017-09-26 | 杭州博世数据网络有限公司 | It is a kind of that method is inscribed based on the smart group that big data is analyzed |
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| 朱天宇等: "基于认知诊断的个性化试题推荐方法", 《计算机学报》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110334204A (en) * | 2019-05-27 | 2019-10-15 | 湖南大学 | A kind of exercise similarity calculation recommended method based on user record |
| CN110334204B (en) * | 2019-05-27 | 2022-10-18 | 湖南大学 | Exercise similarity calculation recommendation method based on user records |
| CN112235333A (en) * | 2019-07-15 | 2021-01-15 | 北京字节跳动网络技术有限公司 | Function package management method, device, equipment and storage medium |
| CN115905576A (en) * | 2023-01-09 | 2023-04-04 | 北京布局未来教育科技有限公司 | Test paper generation method and device, electronic equipment and medium |
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