Auxiliary device matched with work quality evaluation system and reverse evaluation method

Abstract

The invention relates to the field of teaching quality evaluation methods, in particular to a reverse evaluation method for realizing quality evaluation after teaching homework collection and subsequent teaching. The problem that in the prior art, homework quality is not fed back in time in the higher education process is solved. The system comprises a keyword input module, a keyword extraction module, a keyword labeling module, a data analysis module for analyzing a keyword labeling result and a judgment module. The system has the advantages that the teaching quality is evaluated quickly by combining the working principle of image informatics and evaluating the completion degree in the homework collection process, and meanwhile, the subjective influence is reduced to the maximum extent.

Description

Technical Field

[0001] The invention relates to the field of teaching effect evaluation methods, in particular to a homework quality evaluation system, a matching auxiliary device and a reverse evaluation method. Background Art

[0002] Teaching evaluation is an important part of the educational process and a complex process that requires comprehensive consideration of multiple factors to ensure its fairness, effectiveness and practicality.

[0003] It has multiple functions: Improve teaching quality: Through evaluation, teachers can understand the effectiveness of teaching methods and content, so as to make adjustments and improvements; Promote student learning: Evaluation can help students understand their learning progress and mastery, and motivate them to study harder; Feedback information: Evaluation provides educational managers with important information about teaching effectiveness, which helps them make decisions; Diagnose problems: Evaluation can help identify students' learning difficulties and needs so as to provide personalized teaching support; Record achievements: Evaluation records students' learning outcomes within a specific period of time, providing a reference for future learning and development; Promote self-reflection: Evaluation prompts teachers and students to reflect on themselves and think about how to improve teaching and learning methods; Support educational research: Evaluation data can provide valuable information for educational research and help researchers understand the teaching and learning process.

[0004] The existing teaching evaluation process has the following problems: 1. In the publicly available technical literature, most of them adopt the mode of facial recognition plus the Internet of Things, which realizes the judgment of student teaching feedback through facial recognition of students. The applicant believes that this method cannot adapt to the complexity of higher education; 2. The current technical improvements are mostly aimed at classroom performance. However, for college education, there are many forms of education, such as group discussion, inter-group cooperation, and temporary practice. Therefore, classroom facial recognition is not suitable for this teaching task; 3. In higher education, the forms of testing classroom teaching results are often not limited to in-class exercises and homework, so traditional feedback has limited effect; 4. The completion effect of some subjective assignments often depends on the subjective experience of teachers, which is more like a governance activity. It has a good effect in itself, but is greatly affected by the status of teachers, and the evaluation standards themselves are inconsistent. It is more like an intellectual activity, and the overall effect is not stable.

[0005] In summary, the applicant believes that at the current stage of higher education, there is a lack of timely feedback channels on the quality of homework, and the after-class teaching evaluation is perfunctory and lacks effective data support, while the current technology is too dependent on subjectivity. Summary of the invention

[0006] The purpose of the present invention is to solve the problem of no timely feedback on homework quality in the process of higher education in the prior art.

[0007] The specific scheme of the present invention is: comprising a keyword input module, a keyword extraction module, a keyword marking module, a data analysis module for analyzing the keyword marking results, and a determination module; Among them, the keyword input module inputs keywords in the teaching process, homework to obtain the correct answer or logical necessary node keywords, and each keyword forms a predetermined array judgment set; The keyword extraction module includes a scanning module, which scans student assignments into JPG format, or receives electronic versions of assignments and converts them into JPG format for data storage; The keyword labeling module includes an image recognition module, which recognizes the images in the keyword extraction module one by one and puts them into each of the array judgment sets; The data analysis module includes extracting data information of each array determination set to form grayscale blocks to color the keywords in the picture layer by layer, that is, the initial coloring depth is 25 grayscales, the number of each single array determination set is increased by 1, and the grayscale level is increased by 5 to 25 until the grayscale level is capped at 200, and then the colored grayscale blocks are projected on each JPG picture in a positive film overlay form; The judgment module includes determining the degree of overlap between students' answers and the predetermined goals in the teaching syllabus based on the color coverage of each keyword, and inferring the shortcomings in the teaching work based on the grayscale level of the keyword.

[0008] In the specific implementation, it also includes an anti-plagiarism module, which imports homework questions from the homework question bank, and then randomly distributes the homework questions to each student according to their ID.

[0009] In the specific implementation, it also includes a rejection module, which is nested in the keyword labeling module in a branch manner, and its opening status is controlled by a door switch set by the system. In the rejection module, each sample is sorted in the order of the time of submission of the assignment. The first sample is set as the initial sample. After data analysis and keyword calibration, the difference between the first sample and the answer sample is extracted by image screening, which is called the first wrong question sample. In the first wrong question sample, different sample groups are formed with the assignment number as the name. The image information of the wrong question in the sample group is used as sample data. Each sample data is For a single data, establish a wrong question sample series and put it into the single data; then select the second sample based on this, extract the second wrong question sample in the same process, extract the sample group with the same question number and compare it with the first wrong question sample for each single data, the data with high similarity are judged as identical, and the completely different data are taken as subsequent sample data and merged into the sample data under the question number until all the homework information is analyzed to form a wrong question form sample group for each wrong question; then compare the homework data and the wrong question form sample group for each student ID again, if there are more than 3 similarities, it is judged as plagiarism and the homework sample is eliminated.

[0010] It also includes a group work evaluation system that is suitable for group collaborative work evaluation, and the group work evaluation system includes multiple quality evaluation systems. The grayscale coloring in the quality evaluation system is replaced by a single-color coloring, namely red, yellow or blue. Finally, the corresponding color block data in each quality evaluation system are superimposed, and columnar data columns are first formed according to color, and then the data columns are merged, and the consistency in the collaborative cooperation is determined by the proportion of the length of the black data column.

[0011] A teaching evaluation auxiliary device, which assists in realizing data collection of quality evaluation after teaching assignments are collected, characterized in that: it includes a plurality of information cards, the input end of the information card is provided with an interface connected to campus card information, the output end is provided with an interface connected to a host, and a physical key for connecting to the network is provided inside the information card. After the line of the information card is activated, cloud information upload is enabled, and each of the information cards is provided with at least one physical interface The information card is provided with a tutoring call button, the key information is connected to the general information card held by the teacher, and the question information is sent regularly with the help of cloud information.

[0012] A correct answer subset is provided in the cloud information. The correct answer subset and the answer set are evaluated on key data to form teaching effect evaluation information, which is transmitted to the backend server via the network.

[0013] The information card is provided with a storage module, and the storage module stores the question information for summarizing.

[0014] The information card is provided with an IP address collection component and an inter-module distance sensing component.

[0015] A reverse evaluation method, using a quality evaluation system for an operation, comprises the following steps: (1) Teachers or teaching staff extract the key steps required to form answers in teaching exercises, input keywords into the system to form basic information, and simultaneously input options for independent work or group collaborative work to adapt to different homework task requirements; (2) Collect student assignments, use image processing to obtain the degree of overlap between assignment samples and correct results based on the basic information in the system, and use grayscale or color pixel images to provide overall teaching feedback on the assignments and evaluate the overall quality of collaborative assignments; Step (1) also includes analysis of wrong questions in student homework samples and analysis of repeated wrong questions in a single paper. When repeated wrong questions in a single paper appear, the homework sample is eliminated.

[0016] The beneficial effects of the present invention are: In this system, the key contradiction to be solved is that there is too much redundant data in homework feedback, which makes it difficult to analyze students' overall acceptance of knowledge points. Data analysis is carried out with the help of homework evaluation, so when there are many samples, redundant samples can be appropriately introduced for deletion. At the same time, the focus of data analysis is not on independent homework, but on the overall situation of the sample, which is closer to the overall average situation, avoiding errors in teaching evaluation caused by the uniqueness of independent samples.

[0017] Taking advantage of the fact that it is difficult to tell how the correct ideas are formed in most plagiarized assignments, we can effectively screen out assignments with a high probability of plagiarism and remove them from the evaluation system, thereby improving the accuracy of the evaluation system; Effective analysis of correct and incorrect questions also helps teachers find typical ideas for incorrect questions and effectively check for omissions and fill gaps; In order to facilitate group discussion, an information card the size of a USB flash drive is further designed, which can be connected to the campus network or the Internet in the form of a secret key to carry out group homework processing and answer homework questions. The distance sensing component in the information card can also be used to indirectly help teachers understand the real-time distance between groups, prevent students from plagiarizing, and affect the evaluation of homework feedback.

[0018] The applicant believes that through the above technical solution, each function can be relatively independent, thereby realizing the quality evaluation of the collected teaching assignments and the reverse evaluation of subsequent teaching. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0020] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention. Example 1

[0021] A method to evaluate the quality of teaching assignments collected and to conduct reverse evaluation of subsequent teaching, see Figure 1 ,design It includes a keyword input module, a keyword extraction module, a keyword annotation module, a data analysis module for analyzing keyword annotation results, and a judgment module; Among them, the keyword input module inputs keywords in the teaching process, homework to obtain the correct answer or logical necessary node keywords, and each keyword forms a predetermined array judgment set; The keyword extraction module includes a scanning module, which scans student assignments into JPG format, or receives electronic versions of assignments and converts them into JPG format for data storage; The keyword labeling module includes an image recognition module, which recognizes the images in the keyword extraction module one by one and puts them into each of the array judgment sets; The data analysis module includes extracting data information of each array determination set to form grayscale blocks to color the keywords in the picture layer by layer, that is, the initial coloring depth is 25 grayscales, the number of each single array determination set is increased by 1, and the grayscale level is increased by 5 to 25 until the grayscale level is capped at 200, and then the colored grayscale blocks are projected on each JPG picture in a positive film overlay form; The judgment module includes judging the degree of overlap between the student's answer and the predetermined goal in the syllabus according to the color overlap of each keyword, and inferring the shortcomings in the teaching work based on the gray level of the keyword. If after the evaluation, the corresponding keywords in the student sample group overlap more deeply, it means that the coherence and consistency of the ideas and logic in the group activity is higher.

[0022] It also includes an anti-plagiarism module, which imports homework questions from the homework question bank and then randomly distributes the homework questions to each student according to their IDs.

[0023] It also includes a removal module, which is nested in the keyword marking module in a branch manner, and its opening status is controlled by a door switch set by the system. In the removal module, each sample is sorted in the order of the time of submission of the homework. The first sample is set as the initial sample. After data analysis and calibration of keywords, image screening is used to extract the gap between the first sample and the answer sample, which is called the first wrong question sample. In the first wrong question sample, different sample groups are formed with the homework question number as the name, and the image information of the wrong question in the sample group is used as sample data. Each sample data is a single data, and a wrong question sample series is established to put the single data; then the second sample is selected in this way, and the second wrong question sample is extracted by the same process. The sample group with the same question number is extracted and compared with each single data of the first wrong question sample. The data with high similarity is determined to be identical, and the completely different data is used as subsequent sample data and merged into the back of the sample data under the question number until all homework information analysis is completed to form a wrong question form sample group of each wrong question; then the homework data of each student ID and the wrong question form sample group are compared again. If there are more than 3 identical places, plagiarism is determined and the homework sample is eliminated.

[0024] During the work, the determination of keywords can be based on the teaching syllabus. The applicant believes that the core of this application is to infer the degree of compliance of each answer with the teaching requirements through the number of repeated appearances.

[0025] The present invention also relates to a teaching evaluation auxiliary device, which assists in realizing data collection of quality evaluation after teaching assignments are collected, including several information cards, the input end of the information card is provided with an interface connected to the campus card information, the output end is provided with an interface connected to the host, and a physical key connected to the network is provided inside. After the line of the information card is activated, the cloud information upload is started, and each of the information cards is provided with at least one physical interface. In specific work, one information card is held by a group, and group assignments are uploaded regularly. The role of the key is to form an encrypted door switch to prevent inter-group communication.

[0026] The information card is provided with a tutoring call button, the key information is connected to the general information card held by the teacher, and the question information is sent regularly with the help of cloud information.

[0027] A correct answer subset is provided in the cloud information. The correct answer subset and the answer set are evaluated on key data to form teaching effect evaluation information, which is transmitted to the backend server via the network.

[0028] The information card is provided with a storage module, and the storage module stores the question information for summarizing.

[0029] The information card is provided with an IP address collection component and an inter-module distance sensing component.

[0030] The present invention also relates to a reverse evaluation method, using a quality evaluation system for an operation, comprising the following steps: (1) Teachers or teaching staff extract the key steps required to form answers in teaching exercises, input keywords into the system to form basic information, and simultaneously input options for independent work or group collaborative work to adapt to different homework task requirements; (2) Collect student assignments, use image processing to obtain the degree of overlap between assignment samples and correct results based on the basic information in the system, and use grayscale or color pixel images to provide overall teaching feedback on the assignments and evaluate the overall quality of collaborative assignments; Step (1) also includes analysis of wrong questions in student homework samples and analysis of repeated wrong questions in a single paper. When repeated wrong questions in a single paper appear, the homework sample is eliminated. Example 2

[0031] In this embodiment, the working principle is the same as that of embodiment 1, except that: It also includes a group work evaluation system that is suitable for group collaborative work evaluation, and the group work evaluation system includes multiple quality evaluation systems. The grayscale coloring in the quality evaluation system is replaced by a single-color coloring, namely red, yellow or blue. Finally, the corresponding color block data in each quality evaluation system are superimposed, and columnar data columns are first formed according to color, and then the data columns are merged, and the consistency in the collaborative cooperation is determined by the proportion of the length of the black data column.

[0032] That is, there are three groups, and the colors of a keyword that leads to a conclusion idea are respectively red, yellow, and blue. After each group is evaluated independently, the colors are superimposed. Finally, the chromaticity of the mixed colors is used to determine the number of times the keyword appears in the three groups, and then the logical consistency of the grouping work is indirectly judged.

[0033] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A quality evaluation system for an operation, characterized in that: It includes a keyword input module, a keyword extraction module, a keyword annotation module, a data analysis module for analyzing keyword annotation results, and a judgment module; Among them, the keyword input module inputs keywords in the teaching process, homework to obtain the correct answer or logical necessary node keywords, and each keyword forms a predetermined array judgment set; The keyword extraction module includes a scanning module, which scans student assignments into JPG format, or receives electronic versions of assignments and converts them into JPG format for data storage; The keyword labeling module includes an image recognition module, which recognizes the images in the keyword extraction module one by one and puts them into each of the array judgment sets; The data analysis module includes extracting data information of each array determination set to form grayscale blocks to color the keywords in the picture layer by layer, that is, the initial coloring depth is 25 grayscales, the number of each single array determination set is increased by 1, and the grayscale level is increased by 5 to 25 until the grayscale level is capped at 200, and then the colored grayscale blocks are projected on each JPG picture in a positive film overlay form; The judgment module includes determining the degree of overlap between students' answers and the predetermined goals in the teaching syllabus based on the color coverage of each keyword, and inferring the shortcomings in the teaching work based on the grayscale level of the keyword.

2. The operation quality evaluation system according to claim 1, characterized in that: It also includes an anti-plagiarism module, which imports homework questions from the homework question bank and then randomly distributes the homework questions to each student according to their IDs.

3. The operation quality evaluation system according to claim 1, characterized in that: It also includes a removal module, which is nested in the keyword marking module in a branch manner, and its opening status is controlled by a door switch set by the system. In the removal module, each sample is sorted in the order of the time of submission of the homework. The first sample is set as the initial sample. After data analysis and calibration of keywords, image screening is used to extract the gap between the first sample and the answer sample, which is called the first wrong question sample. In the first wrong question sample, different sample groups are formed with the homework question number as the name, and the image information of the wrong question in the sample group is used as sample data. Each sample data is a single data, and a wrong question sample series is established to put the single data; then the second sample is selected in this way, and the second wrong question sample is extracted by the same process. The sample group with the same question number is extracted and compared with each single data of the first wrong question sample. The data with high similarity is determined to be identical, and the completely different data is used as subsequent sample data and merged into the back of the sample data under the question number until all homework information analysis is completed to form a wrong question form sample group of each wrong question; then the homework data of each student ID and the wrong question form sample group are compared again. If there are more than 3 identical places, plagiarism is determined and the homework sample is eliminated.

4. The operation quality evaluation system according to claim 1, characterized in that: It also includes a group work evaluation system that is suitable for group collaborative work evaluation, and the group work evaluation system includes multiple quality evaluation systems. The grayscale coloring in the quality evaluation system is replaced by a single-color coloring, namely red, yellow or blue. Finally, the corresponding color block data in each quality evaluation system are superimposed, and columnar data columns are first formed according to color, and then the data columns are merged, and the consistency in the collaborative cooperation is determined by the proportion of the length of the black data column.

5. A teaching evaluation auxiliary device, which assists in realizing the data collection for the quality evaluation of the collected teaching assignments as claimed in claim 1, characterized in that: It includes several information cards, the input end of the information card is provided with an interface connected to the campus card information, the output end is provided with an interface connected to the host, and a physical key for connecting to the network is provided inside. After the line of the information card is activated, the cloud information upload is started, and each information card is provided with at least one physical interface.

6. The teaching evaluation auxiliary device according to claim 4, characterized in that: The information card is provided with a tutoring call button, the key information is connected to the general information card held by the teacher, and the question information is sent regularly with the help of cloud information.

7. The teaching evaluation auxiliary device according to claim 5, characterized in that: A correct answer subset is provided in the cloud information. The correct answer subset and the answer set are evaluated on key data to form teaching effect evaluation information, which is transmitted to the backend server via the network.

8. The teaching evaluation auxiliary device according to claim 6, characterized in that: The information card is provided with a storage module, and the storage module stores question information.

9. The teaching evaluation auxiliary device according to claim 7, characterized in that: The information card is provided with an IP address collection component and an inter-module distance sensing component.

10. A reverse evaluation method, using the job quality evaluation system according to claim 2, characterized in that: The steps include: (1) Teachers or teaching staff extract the key steps required to form answers in teaching exercises, input keywords into the system to form basic information, and simultaneously input options for independent work or group collaborative work to adapt to different homework task requirements; (2) Collect student assignments, use image processing to obtain the degree of overlap between assignment samples and correct results based on the basic information in the system, and use grayscale or color pixel images to provide overall teaching feedback on the assignments and evaluate the overall quality of collaborative assignments; Step (1) also includes analysis of wrong questions in student homework samples and analysis of repeated wrong questions in a single paper. When repeated wrong questions in a single paper appear, the homework sample is eliminated.

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