Teaching quality evaluation system and method based on big data analysis

Abstract

The embodiment of the invention discloses a teaching quality evaluation system and method based on big data analysis, and belongs to the technical field of teaching analysis, and the method comprises the steps: obtaining historical scores of students, carrying out the analysis and evaluation, obtaining the rating of the students, carrying out the teaching testing of the students at preset intervals, and obtaining the current scores of the students. The current score of the student is compared with the historical score to obtain score change, the teaching content of the teacher in the current period is subjected to quality analysis and evaluation according to the historical rating and score change of the student to obtain a teaching quality evaluation result, the student subjectively scores and evaluates to obtain a subjective evaluation result, and the subjective evaluation result is subjected to evaluation. And adjusting the teaching quality evaluation result according to the subjective evaluation result to obtain a final evaluation result, according to the embodiment of the invention, an accurate teaching content evaluation result can be obtained through objective score change and subjective evaluation scoring, and meanwhile, a teacher can adjust the teaching content of different periods according to the evaluation results of different periods, so that the teaching quality is improved. The teaching quality is improved.

Description

Technical Field

[0001] The present application belongs to the field of teaching analysis technology, and specifically, relates to a teaching quality evaluation system and method based on big data analysis. Background Art

[0002] With the popularization of the Internet and the development of online education, more and more teaching is conducted online, including vocational skills training, certificate examination training, etc., which can facilitate students' learning process in terms of time and space through video. For education platforms, it is necessary to evaluate and manage the teaching status, teaching quality and teaching effect of teachers on the platform.

[0003] The existing education management method will evaluate the teaching quality according to the students' evaluation data, and then provide feedback to the corresponding teaching staff. However, different students have different evaluation standards, involving many factors, and there are subjective factors in the student evaluation process. Therefore, the reference value of the evaluation results is low, and only a rough judgment can be made from the overall situation. It is impossible to make a more accurate or detailed judgment on the deficiencies in the teaching of specific content in the teaching process. Moreover, after analysis, the teaching methods can only be modified in stages, and the teaching methods cannot be adjusted in time, which is not conducive to improving the teaching quality and efficiency. Summary of the invention

[0004] In order to solve the above problems and technical defects, the embodiment of the present application adopts the following technical solution, which is a teaching quality evaluation method based on big data analysis, including the following steps:

[0005] Step 1: Obtain the student's historical scores, analyze and evaluate the student's historical scores, and obtain the student's rating;

[0006] Step 2: Conduct teaching tests on students at preset intervals to obtain their current scores, compare their current scores with their historical scores, and obtain their score changes;

[0007] Step 3: Conduct quality analysis and evaluation of the teacher's teaching content in this period based on the students' historical ratings and grade changes to obtain the teaching quality evaluation results;

[0008] Step 4: Students conduct subjective scoring and evaluation of the teaching quality to obtain subjective evaluation results. The teaching quality evaluation results are adjusted according to the subjective evaluation results to obtain the final evaluation results.

[0009] Preferably, the ratings include: poor, average, good and top. The scores of students watching the target subject teaching are averaged and four score ranges are set up. The four score ranges are divided from large to small according to the score size: the first score range, the second score range, the third score range and the fourth score range. The first score range corresponds to the top, the second score range corresponds to the good, the third score range corresponds to the average, and the fourth score range corresponds to the poor. The corresponding score range and rating are obtained based on the average calculation; the score changes include: improvement, maintenance and regression.

[0010] Furthermore, the detailed steps of conducting quality analysis and evaluation of the teacher's teaching content in this cycle based on the student's historical ratings and grade changes are as follows:

[0011] If the student's rating is poor and the change in performance is improved, it is judged that the teacher's teaching content in this cycle is suitable for poor students;

[0012] If the student's rating is poor and the grade change is maintained, it is judged that the teacher's teaching content in this cycle is not suitable for poor students;

[0013] If the student is rated as average and the change in performance is improved, then the teacher’s teaching content during this cycle is judged to be suitable for average students;

[0014] If the student is rated as average and the change in performance is maintained or deteriorated, it is judged that the teacher's teaching content in this cycle is not suitable for average students;

[0015] If the student's rating is good and the grade change is improvement or maintenance, then it is judged that the teacher's teaching content in this cycle is suitable for excellent students;

[0016] If the student's rating is good and the change in performance is deteriorating, it is judged that the teacher's teaching content in this cycle is not suitable for excellent students;

[0017] If the student's rating is top and the grade change is maintained, it is judged that the teacher's teaching content in this cycle is suitable for top students;

[0018] If a student's rating is top-notch and the change in grades is declining, it is judged that the teacher's teaching content during this cycle is not suitable for top students.

[0019] Furthermore, when the teaching content of the teacher in this cycle is not suitable for poor students, ordinary students, excellent students and top students at the same time, the quality evaluation of the teaching content of the teacher in this cycle is not suitable for students to learn and watch;

[0020] When the teaching content of the teacher in this cycle is suitable for one or more of poor students, average students, excellent students and top students, the quality evaluation of the teaching content of the teacher in this cycle is suitable for some students to learn and watch;

[0021] When the teacher's teaching content during this cycle is suitable for poor students, ordinary students, excellent students and top students at the same time, the quality evaluation of the teacher's teaching content during this cycle is suitable for all students to learn and watch.

[0022] Furthermore, the adjustment of the teaching quality evaluation results according to the subjective evaluation results is that students subjectively score teachers and teaching contents, and convert the subjective scores into subjective evaluation levels, and the subjective evaluation levels include: liked by students, average and not liked by students;

[0023] If the subjective evaluation is that the film is not liked by students and the quality evaluation is that it is suitable for all students to learn and watch, then the final evaluation result is that it is suitable for some students to learn and watch;

[0024] If the subjective evaluation is that the film is liked by students and the quality evaluation is that it is not suitable for students to watch, then the final evaluation result is that it is suitable for some students to watch;

[0025] Otherwise, the quality evaluation result will not be modified and will be used as the final evaluation result.

[0026] The teaching quality evaluation system based on big data analysis includes:

[0027] The student evaluation module is used to obtain the student's historical scores, analyze and evaluate the student's historical scores, and obtain the student's rating;

[0028] The grade change module is used to conduct teaching tests on students at preset intervals to obtain the students' current grades, compare the students' current grades with their historical grades, and obtain the students' grade changes;

[0029] The quality evaluation module is used to analyze and evaluate the quality of the teacher's teaching content in this cycle based on the students' historical ratings and grade changes, and obtain the teaching quality evaluation results;

[0030] The final evaluation module is used for students to conduct subjective scoring and evaluation of teaching quality, obtain subjective evaluation results, adjust the teaching quality evaluation results according to the subjective evaluation results, and obtain the final evaluation results.

[0031] Preferably, the ratings in the student evaluation module include: poor, average, good and top. The scores of students watching the target subject teaching are averaged, and then four score ranges are set up. The four score ranges are divided from large to small according to the score size: the first score range, the second score range, the third score range and the fourth score range. The first score range corresponds to the top, the second score range corresponds to the good, the third score range corresponds to the average, and the fourth score range corresponds to the poor. The corresponding score range and rating are obtained based on the average calculation; the score changes include: improvement, maintenance and regression.

[0032] Furthermore, the detailed steps of the quality evaluation module for analyzing and evaluating the quality of the teacher's teaching content in this cycle based on the student's historical ratings and grade changes are as follows:

[0033] If the student's rating is poor and the change in performance is improved, it is judged that the teacher's teaching content in this cycle is suitable for poor students;

[0034] If the student's rating is poor and the grade change is maintained, it is judged that the teacher's teaching content in this cycle is not suitable for poor students;

[0035] If the student is rated as average and the change in performance is improved, then the teacher’s teaching content during this cycle is judged to be suitable for average students;

[0036] If the student is rated as average and the change in performance is maintained or deteriorated, it is judged that the teacher's teaching content in this cycle is not suitable for average students;

[0037] If the student's rating is good and the grade change is improvement or maintenance, then it is judged that the teacher's teaching content in this cycle is suitable for excellent students;

[0038] If the student's rating is good and the change in performance is deteriorating, it is judged that the teacher's teaching content in this cycle is not suitable for excellent students;

[0039] If the student's rating is top and the grade change is maintained, it is judged that the teacher's teaching content in this cycle is suitable for top students;

[0040] If a student's rating is top-notch and the change in grades is declining, it is judged that the teacher's teaching content during this cycle is not suitable for top students.

[0041] Furthermore, when the teaching content of the teacher in this cycle is not suitable for poor students, ordinary students, excellent students and top students at the same time, the quality evaluation of the teaching content of the teacher in this cycle is not suitable for students to learn and watch;

[0042] When the teaching content of the teacher in this cycle is suitable for one or more of poor students, average students, excellent students and top students, the quality evaluation of the teaching content of the teacher in this cycle is suitable for some students to learn and watch;

[0043] When the teacher's teaching content during this cycle is suitable for poor students, ordinary students, excellent students and top students at the same time, the quality evaluation of the teacher's teaching content during this cycle is suitable for all students to learn and watch.

[0044] Furthermore, the final evaluation module adjusts the teaching quality evaluation results according to the subjective evaluation results by having students subjectively score teachers and teaching contents, and converting the subjective scores into subjective evaluation levels, wherein the subjective evaluation levels include: liked by students, average, and not liked by students;

[0045] If the subjective evaluation is that the film is not liked by students and the quality evaluation is that it is suitable for all students to learn and watch, then the final evaluation result is that it is suitable for some students to learn and watch;

[0046] If the subjective evaluation is that the film is liked by students and the quality evaluation is that it is not suitable for students to watch, then the final evaluation result is that it is suitable for some students to watch;

[0047] Otherwise, the quality evaluation result will not be modified and will be used as the final evaluation result.

[0048] Compared with the prior art, the beneficial effects of the embodiments of the present application are:

[0049] This application obtains four score ranges through students' historical grades, and then students' ratings. After students complete their studies, the teaching content is analyzed and evaluated for quality based on changes in students' grades. Based on different student ratings and grade changes, it is judged whether the teacher's teaching content in this cycle is suitable for poor students, ordinary students, excellent students and top students, thereby obtaining different teaching quality evaluation results. Finally, students conduct subjective scoring and evaluation, and the teaching quality evaluation results are adjusted based on the subjective evaluation results to obtain the final evaluation results. Through objective grade changes and subjective evaluation and scoring, accurate teaching content evaluation results are obtained to judge whether the teaching content is suitable for some students or all students. At the same time, teachers can adjust the teaching content of different cycles based on the evaluation results of different cycles to improve teaching quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In the attached picture:

[0051] Figure 1 A schematic diagram of the method steps of an embodiment of the present application;

[0052] Figure 2 Schematic diagram of the system structure of an embodiment of the present application. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Generally, the components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations.

[0054] Example 1

[0055] like Figure 1 As shown, the historical scores of students are obtained, the historical scores of students are analyzed and evaluated, and the ratings of students are obtained;

[0056] The ratings include: poor, average, good and top. The scores of students watching the target subject teaching are averaged and four score ranges are set up. The four score ranges are divided from large to small: the first score range, the second score range, the third score range and the fourth score range. The first score range corresponds to the top, the second score range corresponds to good, the third score range corresponds to average, and the fourth score range corresponds to poor. The corresponding score range and rating are obtained based on the average calculation.

[0057] Conduct teaching tests on students at preset intervals to obtain their current scores, compare their current scores with their historical scores, and obtain their score changes;

[0058] Performance changes include: improvement, maintenance, and regression.

[0059] Conduct quality analysis and evaluation of the teacher's teaching content during this period based on students' historical ratings and grade changes, and obtain teaching quality evaluation results;

[0060] Students rated as poor are poor students, students rated as average are average students, students rated as good are excellent students, and students rated as top are top students. Among them, the number of poor students and top students is small, and they account for a small proportion of the total students. The number of average students and excellent students is large, and they account for a large proportion of the total students.

[0061] The detailed steps for conducting quality analysis and evaluation of the teacher's teaching content in this cycle based on the student's historical ratings and grade changes are as follows:

[0062] If the student's rating is poor and the change in performance is improved, it is judged that the teacher's teaching content in this cycle is suitable for poor students;

[0063] If the student's rating is poor and the grade change is maintained, it is judged that the teacher's teaching content in this cycle is not suitable for poor students;

[0064] If the student is rated as average and the change in performance is improved, then the teacher’s teaching content during this cycle is judged to be suitable for average students;

[0065] If the student is rated as average and the change in performance is maintained or deteriorated, it is judged that the teacher's teaching content in this cycle is not suitable for average students;

[0066] If the student's rating is good and the grade change is improvement or maintenance, then it is judged that the teacher's teaching content in this cycle is suitable for excellent students;

[0067] If the student's rating is good and the change in performance is deteriorating, it is judged that the teacher's teaching content in this cycle is not suitable for excellent students;

[0068] If the student's rating is top and the grade change is maintained, it is judged that the teacher's teaching content in this cycle is suitable for top students;

[0069] If the student's rating is top-notch and the change in grades is declining, it is judged that the teacher's teaching content in this cycle is not suitable for top students;

[0070] When the teaching content of the teacher in this cycle is not suitable for poor students, ordinary students, excellent students and top students at the same time, the quality evaluation of the teaching content of the teacher in this cycle is not suitable for students to learn and watch;

[0071] When the teaching content of the teacher in this cycle is suitable for one or more of poor students, average students, excellent students and top students, the quality evaluation of the teaching content of the teacher in this cycle is suitable for some students to learn and watch;

[0072] When the teacher's teaching content during this cycle is suitable for poor students, ordinary students, excellent students and top students at the same time, the quality evaluation of the teacher's teaching content during this cycle is suitable for all students to learn and watch.

[0073] Students give subjective scoring evaluations on the teaching quality to obtain subjective evaluation results, and the teaching quality evaluation results are adjusted based on the subjective evaluation results to obtain the final evaluation results.

[0074] The adjustment of the teaching quality evaluation results according to the subjective evaluation results is that students give subjective scores to teachers and teaching contents, and convert the subjective scores into subjective evaluation grades, and the subjective evaluation grades include: liked by students, average and not liked by students; for example, the subjective scores are in percentage, and the average score of 0 to 60 is not liked by students, the average score of 60 to 80 is average, and the average score of 80 to 100 is liked by students;

[0075] If the subjective evaluation is that the video is not liked by students and the quality evaluation is that it is suitable for all students to learn and watch, then the final evaluation result is that it is suitable for some students to learn and watch; although the teaching quality is high, the teaching style is not liked by students, and students who study and watch for a long time are likely to develop a dislike for learning;

[0076] If the subjective evaluation is that it is liked by students and the quality evaluation is that it is not suitable for students to learn and watch, the final evaluation result is that it is suitable for some students to learn and watch; although the teaching quality is low, the teaching style is liked by students, and students can easily develop a love for learning by watching for a long time. First, cultivate students' interest and habit in learning, and then watch other high-quality teaching content to improve students' grades;

[0077] Otherwise, the quality evaluation result will not be modified and will be used as the final evaluation result.

[0078] Example 2

[0079] like Figure 2 As shown in the figure, the teaching quality evaluation system based on big data analysis includes:

[0080] The student evaluation module is used to obtain the student's historical scores, analyze and evaluate the student's historical scores, and obtain the student's rating;

[0081] The ratings in the student evaluation module include: poor, average, good and top. The scores of students watching the target subject teaching are averaged, and then four score ranges are set up. The four score ranges are divided from large to small: the first score range, the second score range, the third score range and the fourth score range. The first score range corresponds to the top, the second score range corresponds to good, the third score range corresponds to average, and the fourth score range corresponds to poor. The corresponding score range and rating are obtained based on the average calculation.

[0082] The grade change module is used to conduct teaching tests on students at preset intervals to obtain the students' current grades, compare the students' current grades with their historical grades, and obtain the students' grade changes, which include: improvement, maintenance, and regression.

[0083] The quality evaluation module is used to analyze and evaluate the quality of the teacher's teaching content in this cycle based on the students' historical ratings and grade changes, and obtain the teaching quality evaluation results;

[0084] The detailed steps of the quality evaluation module for quality analysis and evaluation of the teacher's teaching content in this cycle based on the student's historical ratings and grade changes are as follows:

[0085] If the student's rating is poor and the change in performance is improved, it is judged that the teacher's teaching content in this cycle is suitable for poor students;

[0086] If the student's rating is poor and the grade change is maintained, it is judged that the teacher's teaching content in this cycle is not suitable for poor students;

[0087] If the student is rated as average and the change in performance is improved, then the teacher’s teaching content during this cycle is judged to be suitable for average students;

[0088] If the student is rated as average and the change in performance is maintained or deteriorated, it is judged that the teacher's teaching content in this cycle is not suitable for average students;

[0089] If the student's rating is good and the grade change is improvement or maintenance, then it is judged that the teacher's teaching content in this cycle is suitable for excellent students;

[0090] If the student's rating is good and the change in performance is deteriorating, it is judged that the teacher's teaching content in this cycle is not suitable for excellent students;

[0091] If the student's rating is top and the grade change is maintained, it is judged that the teacher's teaching content in this cycle is suitable for top students;

[0092] If a student's rating is top-notch and the change in grades is declining, it is judged that the teacher's teaching content during this cycle is not suitable for top students.

[0093] When the teaching content of the teacher in this cycle is not suitable for poor students, ordinary students, excellent students and top students at the same time, the quality evaluation of the teaching content of the teacher in this cycle is not suitable for students to learn and watch;

[0094] When the teaching content of the teacher in this cycle is suitable for one or more of poor students, average students, excellent students and top students, the quality evaluation of the teaching content of the teacher in this cycle is suitable for some students to learn and watch;

[0095] When the teacher's teaching content during this cycle is suitable for poor students, ordinary students, excellent students and top students at the same time, the quality evaluation of the teacher's teaching content during this cycle is suitable for all students to learn and watch.

[0096] The final evaluation module is used for students to conduct subjective scoring and evaluation of teaching quality, obtain subjective evaluation results, adjust the teaching quality evaluation results according to the subjective evaluation results, and obtain the final evaluation results.

[0097] In the final evaluation module, the teaching quality evaluation results are adjusted according to the subjective evaluation results. Students give subjective scores to teachers and teaching content, and convert the subjective scores into subjective evaluation levels. The subjective evaluation levels include: liked by students, average, and not liked by students;

[0098] If the subjective evaluation is that the film is not liked by students and the quality evaluation is that it is suitable for all students to learn and watch, then the final evaluation result is that it is suitable for some students to learn and watch;

[0099] If the subjective evaluation is that the film is liked by students and the quality evaluation is that it is not suitable for students to watch, then the final evaluation result is that it is suitable for some students to watch;

[0100] Otherwise, the quality evaluation result will not be modified and will be used as the final evaluation result.

[0101] The above-mentioned embodiments only express the preferred implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for ordinary technicians in this field, several modifications, improvements and substitutions can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application.

Claims

1. A teaching quality evaluation method based on big data analysis, characterized in that: The following steps are involved: Step 1: Obtain the student's historical scores, analyze and evaluate the student's historical scores, and obtain the student's rating; Step 2: Conduct teaching tests on students at preset intervals to obtain their current scores, compare their current scores with their historical scores, and obtain their score changes; Step 3: Conduct quality analysis and evaluation of the teacher's teaching content in this period based on the students' historical ratings and grade changes to obtain the teaching quality evaluation results; Step 4: Students conduct subjective scoring and evaluation of the teaching quality to obtain subjective evaluation results. The teaching quality evaluation results are adjusted according to the subjective evaluation results to obtain the final evaluation results.

2. The teaching quality evaluation method based on big data analysis according to claim 1 is characterized in that: The ratings include: poor, average, good and top. The scores of students watching the target subject teaching are averaged and four score ranges are set up. The four score ranges are divided from large to small according to the score size: the first score range, the second score range, the third score range and the fourth score range. The first score range corresponds to the top, the second score range corresponds to the good, the third score range corresponds to the average, and the fourth score range corresponds to the poor. The corresponding score range and rating are obtained based on the average calculation; the score changes include: improvement, maintenance and regression.

3. The teaching quality evaluation method based on big data analysis according to claim 2 is characterized in that: The detailed steps for conducting quality analysis and evaluation of the teacher's teaching content in this cycle based on the student's historical ratings and grade changes are as follows: If the student's rating is poor and the change in performance is improved, it is judged that the teacher's teaching content in this cycle is suitable for poor students; If the student's rating is poor and the grade change is maintained, it is judged that the teacher's teaching content in this cycle is not suitable for poor students; If the student is rated as average and the change in performance is improved, then the teacher’s teaching content during this cycle is judged to be suitable for average students; If the student is rated as average and the change in performance is maintained or deteriorated, it is judged that the teacher's teaching content in this cycle is not suitable for average students; If the student's rating is good and the grade change is improvement or maintenance, then it is judged that the teacher's teaching content in this cycle is suitable for excellent students; If the student's rating is good and the change in performance is deteriorating, it is judged that the teacher's teaching content in this cycle is not suitable for excellent students; If the student's rating is top and the grade change is maintained, it is judged that the teacher's teaching content in this cycle is suitable for top students; If a student's rating is top-notch and the change in grades is declining, it is judged that the teacher's teaching content during this cycle is not suitable for top students.

4. The teaching quality evaluation method based on big data analysis according to claim 3 is characterized in that: When the teaching content of the teacher in this cycle is not suitable for poor students, ordinary students, excellent students and top students at the same time, the quality evaluation of the teaching content of the teacher in this cycle is not suitable for students to learn and watch; When the teaching content of the teacher in this cycle is suitable for one or more of poor students, average students, excellent students and top students, the quality evaluation of the teaching content of the teacher in this cycle is suitable for some students to learn and watch; When the teacher's teaching content during this cycle is suitable for poor students, ordinary students, excellent students and top students at the same time, the quality evaluation of the teacher's teaching content during this cycle is suitable for all students to learn and watch.

5. The teaching quality evaluation method based on big data analysis according to claim 4 is characterized in that: The adjustment of the teaching quality evaluation results according to the subjective evaluation results is that students subjectively score teachers and teaching contents, and convert the subjective scores into subjective evaluation levels, and the subjective evaluation levels include: liked by students, average and not liked by students; If the subjective evaluation is that the film is not liked by students and the quality evaluation is that it is suitable for all students to learn and watch, then the final evaluation result is that it is suitable for some students to learn and watch; If the subjective evaluation is that the film is liked by students and the quality evaluation is that it is not suitable for students to watch, then the final evaluation result is that it is suitable for some students to watch; Otherwise, the quality evaluation result will not be modified and will be used as the final evaluation result.

6. The teaching quality evaluation system based on big data analysis is characterized by: include: The student evaluation module is used to obtain the student's historical scores, analyze and evaluate the student's historical scores, and obtain the student's rating; The grade change module is used to conduct teaching tests on students at preset intervals to obtain the students' current grades, compare the students' current grades with their historical grades, and obtain the students' grade changes; The quality evaluation module is used to analyze and evaluate the quality of the teacher's teaching content in this cycle based on the students' historical ratings and grade changes, and obtain the teaching quality evaluation results; The final evaluation module is used for students to conduct subjective scoring and evaluation of teaching quality, obtain subjective evaluation results, adjust the teaching quality evaluation results according to the subjective evaluation results, and obtain the final evaluation results.

7. The teaching quality evaluation system based on big data analysis according to claim 6 is characterized in that: The ratings in the student evaluation module include: poor, average, good and top. The scores of students watching the target subject teaching are averaged and four score ranges are set up. The four score ranges are divided from large to small according to the score size: the first score range, the second score range, the third score range and the fourth score range. The first score range corresponds to the top, the second score range corresponds to the good, the third score range corresponds to the average, and the fourth score range corresponds to the poor. The corresponding score range and rating are obtained based on the average calculation; the score changes include: improvement, maintenance and regression.

8. The teaching quality evaluation system based on big data analysis according to claim 7 is characterized in that: The detailed steps of the quality evaluation module for analyzing and evaluating the quality of the teacher's teaching content in this cycle based on the student's historical ratings and grade changes are as follows: If the student's rating is poor and the change in performance is improved, it is judged that the teacher's teaching content in this cycle is suitable for poor students; If the student's rating is poor and the grade change is maintained, it is judged that the teacher's teaching content in this cycle is not suitable for poor students; If the student is rated as average and the change in performance is improved, then the teacher’s teaching content during this cycle is judged to be suitable for average students; If the student is rated as average and the change in performance is maintained or deteriorated, it is judged that the teacher's teaching content in this cycle is not suitable for average students; If the student's rating is good and the grade change is improvement or maintenance, then it is judged that the teacher's teaching content in this cycle is suitable for excellent students; If the student's rating is good and the change in performance is deteriorating, it is judged that the teacher's teaching content in this cycle is not suitable for excellent students; If the student's rating is top and the grade change is maintained, it is judged that the teacher's teaching content in this cycle is suitable for top students; If a student's rating is top-notch and the change in grades is declining, it is judged that the teacher's teaching content during this cycle is not suitable for top students.

9. The teaching quality evaluation system based on big data analysis according to claim 8 is characterized in that: When the teaching content of the teacher in this cycle is not suitable for poor students, ordinary students, excellent students and top students at the same time, the quality evaluation of the teaching content of the teacher in this cycle is not suitable for students to learn and watch; When the teaching content of the teacher in this cycle is suitable for one or more of poor students, average students, excellent students and top students, the quality evaluation of the teaching content of the teacher in this cycle is suitable for some students to learn and watch; When the teacher's teaching content during this cycle is suitable for poor students, ordinary students, excellent students and top students at the same time, the quality evaluation of the teacher's teaching content during this cycle is suitable for all students to learn and watch.

10. The teaching quality evaluation system based on big data analysis according to claim 9 is characterized in that: The final evaluation module adjusts the teaching quality evaluation results according to the subjective evaluation results by students subjectively scoring the teachers and teaching contents, and converting the subjective scores into subjective evaluation levels, where the subjective evaluation levels include: liked by students, average, and not liked by students; If the subjective evaluation is that the film is not liked by students and the quality evaluation is that it is suitable for all students to learn and watch, then the final evaluation result is that it is suitable for some students to learn and watch; If the subjective evaluation is that the film is liked by students and the quality evaluation is that it is not suitable for students to watch, then the final evaluation result is that it is suitable for some students to watch; Otherwise, the quality evaluation result will not be modified and will be used as the final evaluation result.

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