CN110750634B - Method for effectively matching practicer with training test questions based on data statistics - Google Patents
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Abstract
The invention discloses a method for effectively matching a practicer with a training test question based on data statistics, which comprises the following steps: calculating the total score or total score rate or ranking percentage of the actual scores of the test questions trained by the students participating in the training; calculating the score or difficulty of the single item of the test question trained by the student; establishing a statistical graph of all single-channel questions in the trained test questions; calculating the ratio of the slope of the curve between the front and the back adjacent sections in the statistical chart and the average slope of the curve, or the difference of the score or the difference of the difficulty; judging whether the ratio of the slope of the curve between the front and the rear adjacent sections to the average slope of the curve is smaller than a first threshold or whether the difference of the score rate is smaller than a second threshold or whether the difference of the difficulty is smaller than a third threshold; if not, pushing the question to the corresponding practicer of the previous segment. The invention establishes a database about student-test questions by counting the answer data of each student to each test question, thereby effectively matching practicers with the test questions and improving the pertinence of training.
Description
Technical Field
The invention relates to the field of data analysis, in particular to a method for effectively matching a practicer with a training test question based on data statistics.
Background
At present, when training questions are provided for students, the same type of questions are generally sent to all students for doing, or related questions are simply pushed according to the score of the knowledge points related to the students (score of the question/score of the question x 100%), and the specific way is that the lower the score of the related knowledge is, the questions related to the knowledge points are pushed to the students for doing. The above method has several problems: 1. the number of samples is small, and the statistics of the score is inaccurate; 2. when the questions are recommended, pushing is carried out according to the score of the knowledge points, and the same knowledge point may contain different types of questions and is poor in pertinence; 3. it is impossible to predict whether the provided test question has an enhancing effect on the students who receive the test question, or which level (score or rank) the test question has an accelerating effect on the students.
Accordingly, the prior art is deficient and needs improvement.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, provides a method for effectively matching practicers and training test questions based on data statistics, and solves the problems of few samples of the statistical analysis score and inaccurate statistics in the prior art; the problem of carry out the propelling movement of topic with the knowledge point, the effect of pertinence training is relatively poor is solved, solve simultaneously that whether the test question that can't predict provides has the improvement effect to the student who accepts this test question, or this test question has the promotion effect to the student of which level (score section or rank).
The technical scheme of the invention is as follows: a method for effectively matching a practicer with a training test question based on data statistics comprises the following steps:
s1: and (4) statistically calculating the total score or total score rate or ranking percentage of the actual scores of the test questions trained by the students participating in the training.
The total yield is the actual total score/rolled total score multiplied by 100 percent, and the ranking percentage is the ranking/total number multiplied by 100 percent.
S2: and statistically calculating the scoring rate or difficulty of each single-channel subject of the test questions trained by the students with the same actual scoring total score or total scoring rate or ranking percentage in the S1.
The score rate is the average score/score of the subject of the students with the same actual score total score or ranking percentage multiplied by 100 percent, and the difficulty is the average score/score of the subject of the students with the same actual score total score or ranking percentage.
S3: and establishing a statistical chart of all the single-channel questions in the trained test questions, wherein the actual total score or the ranking percentage calculated statistically in S1 is used as an X axis, and the score or the difficulty calculated statistically in S2 is used as a Y axis.
S4: and calculating the ratio of the curve slope and the average curve slope between the front and the back adjacent sections in the statistical chart, or the difference of the score ratio or the difference of the difficulty.
S5: and judging whether the ratio of the slope of the curve between the front and the rear adjacent sections to the average slope of the curve is smaller than a first threshold or whether the difference of the score ratio is smaller than a second threshold or whether the difference of the difficulty is smaller than a third threshold.
S6: if not, the ratio of the curve slope between the front and rear adjacent sections to the average curve slope is not smaller than the first threshold, or the difference of the score rate is not smaller than the second threshold, or the difference of the difficulty is not smaller than the third threshold, pushing the similar subjects to students corresponding to the front section in the front and rear adjacent sections to practice.
S7: the data in S1-S6 are logged into the database.
After each training test, the total score or ranking percentage of the actual scores of the training test questions of the students participating in the training is calculated statistically, meanwhile, the score difficulty of the single topic of the training test questions of each student with the same total score or ranking percentage in S1 is calculated statistically, after the corresponding data statistics calculation is finished, the data obtained in S1 is used as the X axis and the data obtained in S2 is used as the Y axis for each topic, a statistical graph is established, after the statistical graph is established, the ratio of the curve slope and the average curve slope between the front and back adjacent sections in the statistical graph is calculated, the statistical graph is compared with a set first threshold value, whether the statistical graph is smaller than the first threshold value or not, or the difference of the score between the front and back adjacent sections is calculated and compared with a set second threshold value, whether the statistical graph is smaller than the second threshold value or the difference of the difficulty between the front and back adjacent sections is calculated, comparing the first threshold value with a set third threshold value, and judging whether the first threshold value is smaller than the third threshold value; if the ratio of the curve slope between the front and rear adjacent sections and the average curve slope is not less than a first threshold, or the difference of the score rates between the front and rear adjacent sections is not less than a second threshold, or the difference of the difficulty between the front and rear adjacent sections is not less than a third threshold, it is indicated that the mastered effect of the question is not good for students corresponding to the front section in the front and rear adjacent sections which is not less than the first threshold, the second threshold or the third threshold, so that the question is pushed to the students corresponding to the front section in the front and rear adjacent sections for practice, thereby carrying out targeted training, helping the students master the corresponding question, reducing inefficient non-targeted practice, and improving the training effectiveness; meanwhile, the grasping condition of the corresponding questions of the students corresponding to different actual score total scores or total score scores or ranking percentages can be judged through a statistical chart, and the different promotion effects of the same test question on the students corresponding to different actual score total scores or total score scores or ranking percentages are also shown; and recording related data in the whole process into a database so as to continuously count and calculate the data after each training test question, and establishing a database with huge data about the score or difficulty corresponding to different students on different test questions and corresponding to different actual score total scores or total score scores or ranking percentages, so that the effect of targeted training is further improved and the questions required by training are enriched.
Furthermore, the scale value of the X axis is determined according to a range value corresponding to the actual score total score or the total score ratio or the ranking percentage set on the X axis, the scale value of the Y axis is determined according to a range value corresponding to the score difficulty set on the Y axis, and the statistical graph is a broken line statistical graph or a curve statistical graph.
Further, the first threshold value is 0.4, the second threshold value is 5%, and the third threshold value is 0.05.
Further, the training questions include: examination paper examination questions and operation exercises. Meanwhile, the related data appearing in the test paper test questions and the homework exercises of all students participating in training are counted and calculated, the number of data statistics is effectively increased, the training questions are recommended according to the results of multiple times of counting and calculation, and the accuracy of the recommended questions is higher.
Further, the step S5 further includes the following steps:
s51: and judging whether the ratio of the slope of the curve between the front and the rear adjacent sections to the average slope of the curve is less than 0.4 or whether the difference of the score is less than 5% of difficulty and whether the difference is less than 0.05.
S52: if not, the ratio of the curve slope between the front and rear adjacent sections to the average curve slope is not less than 0.4, or the difference of the score is not less than 5% and the difference of the difficulty is not less than 0.05, and pushing the question to students corresponding to the front section in the front and rear adjacent sections to practice.
S53: if yes, the ratio of the slope of the curve between the front and rear adjacent sections to the average slope is not less than 0.4, or the difference of the score is not less than 5%, and the difference of the difficulty is not less than 0.05, and the question is not pushed to students corresponding to the front section in the front and rear adjacent sections to practice.
Judging whether the ratio of the curve slope between the front and rear adjacent sections to the average curve slope is less than 0.4, if not, indicating that the curve slope between the front and rear sections is greater than or equal to 0.4, and the curve slope between the front and rear adjacent sections is larger, indicating that the difference between the student corresponding to the front section and the student corresponding to the rear section in the front and rear adjacent sections is large, indicating that the mastering condition of the front section to the corresponding student to the question is poor, so in the rear training, the question can be recommended to the student corresponding to the front section in the front and rear adjacent sections; judging whether the difference of the score of the adjacent sections is less than 5%, if not less than 5%, indicating that the difference is greater than 5% or equal to 5%, the difference of the score rate between the front and rear sections is considered to be large, which indicates that the difference between the students corresponding to the front section and the rear section in the front and rear adjacent sections is large, which indicates that the mastering condition of the corresponding student to the subject is poor, the subjects can be recommended to students corresponding to the previous section in the front and back adjacent sections with emphasis, when the ratio of the curve slope between the front and back adjacent sections and the average curve slope is less than 0.4 or the difference of score is less than 5% and the difficulty difference is less than 0.05, the difference between the student corresponding to the previous section and the student corresponding to the next section in the adjacent sections is small, and the question is mastered by the corresponding student of the previous section, so that the question is not pushed to the corresponding student of the previous section; after the method is adopted for analysis, the training questions recommended to the students have pertinence to learning omission of the students, the training effectiveness is high, and the academic burden can be reduced while the learning quality is ensured.
Further, the step S1 is: and respectively and statistically calculating the total score or total score rate or ranking percentage of the individuals trained by each student who participates in the training.
Further, the step S3 is: establishing a statistical chart of all the single-channel questions in the trained test questions, wherein the total score or the ranking percentage of all the students participating in the training, which are statistically calculated in S1, is used as an X axis, and the score or the difficulty of all the single-channel questions, which are statistically calculated in S2, is used as a Y axis.
Further, in the step S3, the following six polyline statistical graphs or curve statistical graphs may be established: (the actual score is divided into X axis, the score is Y axis), (the actual score is divided into X axis and difficulty is Y axis), (the total score is X axis and the score is Y axis), (the total score is X axis and the difficulty is Y axis), (the ranking percentage is X axis and the score is Y axis), (the ranking percentage is X axis and the difficulty is Y axis). One or more types can be selected from the six types of broken line statistical graphs or curve statistical graphs according to the data condition of actual statistical analysis to establish the broken line statistical graph or the curve statistical graph.
By adopting the scheme, the invention provides a method for effectively matching practicers and training test questions based on data statistics, which is characterized in that after each training test question, the total score or ranking percentage of the actual scores of the training test questions of students participating in training is statistically calculated, meanwhile, the score or difficulty of each single question of the training test questions of the students with the same total score or ranking percentage in S1 is statistically calculated, after the statistical calculation of corresponding data is completed, the data obtained in S1 is taken as an X axis for each question, the data obtained in S2 is taken as a Y axis, a statistical chart is established, after the statistical chart is established, the ratio of the curve slope between the front and back adjacent sections in the statistical chart and the average curve slope is calculated, and compared with a set first threshold value, whether the ratio is smaller than the first threshold value or not, or the difference value between the front and back adjacent sections is calculated, comparing the difference value with a set second threshold value, judging whether the difference value is smaller than the second threshold value or not, or calculating the difference value of the difficulty between the front section and the rear section, comparing the difference value with a set third threshold value, and judging whether the difference value is smaller than the third threshold value or not; if the ratio of the curve slope between the front and rear adjacent sections and the average curve slope is not less than a first threshold, or the difference of the score rates between the front and rear adjacent sections is not less than a second threshold, or the difference of the difficulty between the front and rear adjacent sections is not less than a third threshold, it is indicated that the mastered effect of the question is not good for students corresponding to the front section in the front and rear adjacent sections which is not less than the first threshold, the second threshold or the third threshold, so that the question is pushed to the students corresponding to the front section in the front and rear adjacent sections for practice, thereby performing targeted training, being beneficial to the students to master the corresponding question, thereby reducing low-efficiency non-targeted practice and improving the effectiveness of training; meanwhile, the grasping condition of the corresponding subjects of the students corresponding to different actual score total scores or total score scores or ranking percentages can be judged through a statistical chart; the related data involved in the whole process is recorded into a database, data after test questions are trained each time are continuously counted and calculated, a database which is huge in data and relates to the score or difficulty corresponding to different students on different test questions and corresponding to different actual score total scores or total score scores or ranking percentages is established, the effect of targeted training is further improved, and the questions required by training are enriched.
Drawings
FIG. 1 is a block flow diagram of the present invention;
FIG. 2 is a block flow diagram of step S5 further including steps;
FIG. 3 is a graph of a statistical broken line with total score as X-axis and difficulty as Y-axis.
Detailed Description
The invention is described in detail below with reference to the figures and the specific embodiments.
Referring to fig. 1-3, the present invention provides a method for effectively matching a practicer with a training test question based on data statistics, comprising the following steps:
s1: and (5) counting and calculating the total score of the test questions trained by the students participating in the training.
The total score rate is the actual score/rolled total score multiplied by 100%
S2: and (5) statistically calculating the difficulty of the single subject of the test questions made by the students with the same total score in the step S1.
The difficulty is the average score/score of the subject of the students with the same actual score total score or ranking percentage.
S3: and (4) establishing a polyline statistical graph by taking the total score fraction calculated in the S1 as an X axis and the difficulty calculated in the S2 as a Y axis.
S4: the ratio of the curve slope between the front and back adjacent segments in fig. 3 to the average curve slope is calculated as follows:
a, B, C points with coordinate values of (0.05, 0), (0.15, 0.14) and (0.95, 0.92) are taken;
A. the slope of the line segment between the two points B is: kAB＝(0.15-0.05)/(0.14-0)＝0.71；
The average slope is: kAC＝(0.95-0.05)/(0.92-0)＝0.98；
KABAnd KACThe ratio of (A) to (B) is: kAB/KAC＝0.71/0.98＝0.72；
S5: and judging whether the ratio of the slope of the curve between the front and the back adjacent sections to the average slope of the curve is smaller than a first threshold value.
S6: 0.72 is not less than 0.4, the subjects are pushed to students with score of < 10% for practice.
S7: the data in S1-S6 are logged into the database.
In summary, the present invention provides a method for effectively matching trainees and training test questions based on data statistics, wherein after each training test question, the total score rate of the training test questions of students participating in training is statistically calculated, the difficulty of a single question of the training test questions of the students participating in training is also statistically calculated, after the statistical calculation of corresponding data is completed, a broken line statistical graph is established with the total score rate as an X axis and the difficulty as a Y axis for each question, after the statistical graph is established, the ratio of the curve slope between the front and rear adjacent segments and the average curve slope in the statistical graph is calculated, the curve slope between the front and rear adjacent segments is compared with a set first threshold, whether the curve slope between the front and rear segments is smaller than the first threshold is determined, if the ratio of the curve slope between the front and rear adjacent segments and the average curve slope is not smaller than the first threshold, the question is indicated to students corresponding to the segment before the first threshold, the effect of grasping is not good, so the class of questions is pushed to exercise for the students corresponding to the previous section in the front and back adjacent sections, the pertinence training is carried out, the students can grasp the corresponding questions, the low-efficiency non-pertinence exercise is reduced, the training effectiveness is improved, and the academic burden is reduced while the learning quality is ensured.
The present invention is not limited to the above preferred embodiments, and any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (7)
1. A method for effectively matching a practicer with a training test question based on data statistics is characterized by comprising the following steps:
s1: counting and calculating the total score or total score rate or ranking percentage of the actual scores of the test questions trained by the students participating in the training;
the total score rate = actual score/volume total score × 100%, and the ranking percentage = ranking/total number × 100%;
s2: statistically calculating the scoring rate or difficulty of each single subject of the test questions trained by the students with the same actual scoring total score or total scoring rate or ranking percentage in the S1;
the score of the single-channel subject = the average score/score of the subject of students with the same total score or the same ranking percentage, and the difficulty = the average score/score of the subject of students with the same total score or ranking percentage;
s3: establishing a statistical graph of all the single-channel questions in the trained test questions, taking the actual score total score or the total score rate or the ranking percentage statistically calculated in S1 as an X axis, and taking the score rate or the difficulty statistically calculated in S2 as a Y axis;
s4: calculating the ratio of the slope of the curve between the front and the back adjacent sections in the statistical chart and the average slope of the curve, or the difference of the score or the difference of the difficulty;
s5: judging whether the ratio of the slope of the curve between the front and the rear adjacent sections to the average slope of the curve is smaller than a first threshold or whether the difference of the score rate is smaller than a second threshold or whether the difference of the difficulty is smaller than a third threshold;
s6: if not, the ratio of the curve slope between the front and rear adjacent sections to the average curve slope is not smaller than the first threshold, or the difference of the score rate is not smaller than the second threshold, or the difference of the difficulty is not smaller than the third threshold, pushing the subject of the category corresponding to the single subject to the student corresponding to the front section in the front and rear adjacent sections for practice;
s7: the data in S1-S6 are logged into the database.
2. The method as claimed in claim 1, wherein the scale value of the X-axis is determined according to a range value corresponding to the total score or the ranking percentage of the actual scores set on the X-axis, the scale value of the Y-axis is determined according to a range value corresponding to the score or the difficulty set on the Y-axis, and the statistical graph is a polygonal statistical graph or a curved statistical graph.
3. The method of claim 1, wherein the first threshold is 0.4, the second threshold is 5%, and the third threshold is 0.05.
4. The method of claim 1, wherein the training test question comprises: examination paper examination questions and operation exercises.
5. The method of claim 3, wherein the step S5 further comprises the following steps:
s51: judging whether the ratio of the slope of the curve between the front and the rear adjacent sections to the average slope of the curve is less than 0.4 or whether the difference of the score is less than 5% or whether the difference of the difficulty is less than 0.05;
s52: if not, the ratio of the curve slope between the front and rear adjacent sections to the average curve slope is not less than 0.4, or the difference of the score is not less than 5%, or the difference of the difficulty is not less than 0.05, pushing the category subject to a student corresponding to the front section in the front and rear adjacent sections to practice;
s53: if yes, the ratio of the slope of the curve between the front and rear adjacent sections to the average slope is not less than 0.4, the difference of the score is not less than 5%, or the difference of the difficulty is not less than 0.05, and the question is not pushed to students corresponding to the front section in the front and rear adjacent sections to practice.
6. The method for effectively matching a practicer with a training test question based on data statistics as claimed in claim 1, wherein the step S1 is: and respectively and statistically calculating the total score or total score rate or ranking percentage of the individuals trained by each student who participates in the training.
7. The method of claim 2, wherein the step S3 is implemented by creating the following six kinds of statistical polygonal line or curve charts: (the actual score is divided into X axis, the score is Y axis), (the actual score is divided into X axis and difficulty is Y axis), (the total score is X axis and the score is Y axis), (the total score is X axis and the difficulty is Y axis), (the ranking percentage is X axis and the score is Y axis), (the ranking percentage is X axis and the difficulty is Y axis).
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