CN113989081A - Mixed intelligent-enhancement university student project intelligent evaluation system - Google Patents
Mixed intelligent-enhancement university student project intelligent evaluation system Download PDFInfo
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Abstract
The invention relates to the technical field of hybrid intelligence, in particular to a hybrid-enhanced intelligent university student project intelligent evaluation system which comprises a student mutual evaluation module, an intelligent review module and a teacher reevaluation module. According to the scheme, the student mutual evaluation and the teacher mutual evaluation are introduced into the artificial intelligence evaluation, a mixed enhanced intelligent evaluation system of a person in a loop is formed, a high-grade cognition mechanism of the student and the teacher for subjective item evaluation is closely coupled with an artificial intelligence model, and a feedback loop for improving the accurate and efficient intelligent evaluation level of the item is formed. Therefore, according to the scheme, through man-machine cooperation, when a teacher is helped to share the approval and the review of subjective exercises, the cognitive models of students and the teacher are introduced into the artificial intelligence model, so that man-machine cooperation evaluation is conducted on the subjective exercises, and the problems that in the current teaching process, project type subjective exercise operation evaluation quantity is large, efficiency is low, student knowledge and skill are not sufficient and a single evaluation mode with the teacher as the only main body cannot be fed back in time are effectively solved.
Description
Technical Field
The invention relates to the technical field of hybrid intelligence, in particular to a hybrid intelligent university student project intelligent evaluation system.
Background
With the continuous development of internet technology, the internet technology is spread to every corner of people's life, and schools, as a place for cultivating new social talents, are in the leading position of society for the contact and cognition of new technology. In modern colleges and universities, as the number of students in colleges and universities increases, teaching tasks of teachers are also increasing, and teachers often need to spend a large amount of time on correcting the homework of students. The existing online homework correcting system only meets the evaluation function of objective homework of students, and still has the problems of large evaluation amount, low correcting efficiency, incapability of accurately feeding back insufficient knowledge and skills of students in time, single evaluation mode taking teachers as the only main body and the like for subjective homework with more text information, so that an intelligent evaluation system capable of helping teachers correct subjective homework of students is urgently needed.
Disclosure of Invention
The invention aims to solve the technical problem that an intelligent evaluation system capable of helping teachers correct subjective task assignments of students is urgently needed.
The basic scheme provided by the invention is as follows: a mixed intelligent-enhancement university student project intelligent evaluation system comprises a student mutual evaluation module, an intelligent review module, a database and a teacher reevaluation module;
the database is used for storing subjective exercises, evaluation indexes and historical evaluation data;
the student mutual evaluation module is used for collecting mutual evaluation data generated by mutual evaluation of students on subjective exercises according to the evaluation indexes;
the intelligent evaluation module is used for establishing an artificial intelligence model according to historical evaluation data, and intelligently evaluating subjective exercises through the artificial intelligence model according to evaluation indexes and mutual evaluation data to generate corresponding confidence;
a confidence coefficient threshold value is set in the intelligent review module, when the confidence coefficient reaches the confidence coefficient threshold value, the confidence coefficient is high, when the confidence coefficient is lower than the confidence coefficient threshold value, the confidence coefficient is low, and the intelligent score of the subjective problem with high confidence coefficient is output as a project score; the subjective exercises with low confidence coefficient are transmitted to the teacher for reevaluation;
and the teacher reevaluation module is used for collecting reevaluation results of the teacher on the subjective exercises with low confidence coefficient and outputting the reevaluation results as item scores.
The principle and the advantages of the invention are as follows: according to the scheme, students perform mutual evaluation according to evaluation indexes to share teaching pressure for teachers, the subjective exercise is intelligently scored through an intelligent review module to generate confidence degrees corresponding to mutual evaluation results of the students, the accuracy of the intelligent scoring and whether objections exist are reflected according to the confidence degrees, if the confidence degrees are high, the intelligent scoring is output as project scoring, if the confidence degrees are low, the subjective exercise is submitted to the teachers for re-evaluation, and the re-evaluation results of the teachers are output as project scoring. Therefore, according to the scheme, the student mutual evaluation and the teacher mutual evaluation are introduced into the artificial intelligence evaluation, a mixed enhanced intelligent evaluation system of a person in a loop is formed, so that a high-level cognitive mechanism of the student and the teacher evaluating subjective items is closely coupled with an artificial intelligence model, and a feedback loop for improving the accurate and efficient intelligent evaluation level of the items is formed. Therefore, the scheme has the advantages that through man-machine cooperation, the respective specialties are exerted, the students and the teacher are introduced into the artificial intelligence model by the cognitive models of the students and the teacher while the teacher is helped to share the approval and evaluation of the subjective exercise, the man-machine cooperation evaluation is conducted on the subjective exercise, and the evaluation result is more accurate.
The system further comprises a course generation module and a project generation module, wherein the database also stores teaching contents and teaching exercises;
the course generation module is used for dividing teaching knowledge points according to the teaching content and generating course content;
the exercise generation module is used for extracting corresponding teaching exercises according to the course contents and the teaching knowledge points thereof and generating subjective exercises.
Has the advantages that: the corresponding teaching exercises are extracted according to the knowledge points in the course content and the subjective exercises are generated, so that the exercise training of students is better provided with the pertinence of the courses.
Further, the student mutual evaluation module comprises a student layering module and a mutual evaluation distribution module;
the student layering module is used for layering according to historical evaluation results of students;
and the mutual scoring matching module is used for distributing the subjective type exercises to students in the same level according to the student hierarchy for initial evaluation.
Has the advantages that: mutual evaluation is carried out among students in the same level, under the condition that respective bases are similar, the understanding ability of the students is also similar, and the students can more easily acquire experience in mutual evaluation among the levels.
Further, when the distribution rule of the mutual evaluation distribution module is used for mutual evaluation among students at the same level, complementary mutual evaluation is carried out according to the strong items and the weak items of the students in the historical evaluation data.
Has the advantages that: the students can mutually evaluate each other complementarily according to the strength items, and the review students can check errors in the exercises more easily.
And the teaching exercise generation module is used for designing subjective exercises including simple answers, calculation and analysis according to the course knowledge points.
Has the advantages that: and various types of subjective exercises are generated, so that the generated exercises have more comprehensive promotion effect on students.
Furthermore, the database also comprises an evaluation index library, and the evaluation index library is a multi-dimensional scoring index designed by facing subjective items.
Has the advantages that: and a multi-dimensional scoring index of the subjective item is designed, so that scoring is more standard and accurate.
Further, the system also comprises an individual promoting module, wherein the individual promoting module comprises a special promoting module and an individual mutual aid module;
the special item promoting module is used for generating a targeted exercise according to weak items in student evaluation;
the individual mutual-aid module is used for establishing mutual-aid relationship between the students which are weak items in a certain aspect and the students which are strong items in the aspect according to the strong items and the weak items in the student evaluation.
Has the advantages that: the students can establish complementary mutual-help relationship according to self strength and weakness items, so that the students can make progress together, and the study enthusiasm of the students can be improved.
The learning situation analysis module comprises a score ranking module, a learning trend module, a score distribution module, a learning detection module, a personalized recommendation module and a learning prediction module.
Has the advantages that: through the studying situation analysis module, the teacher is helped to know the studying situation of the students, and the individual studying recommendation can be intelligently provided according to the student scores, so that the student scores can be improved.
Drawings
Fig. 1 is a logic block diagram of a mixed intelligence-enhanced university student project intelligent evaluation system according to a first embodiment of the present invention.
Detailed Description
The following is further detailed by way of specific embodiments:
the specific implementation process is as follows:
example one
In one embodiment, as shown in fig. 1, an intelligent university student project evaluation system with hybrid enhanced intelligence includes a database, a course generation module, a problem generation module, a learning emotion analysis module, a student mutual evaluation module, an intelligent review module, an individual promotion module, and a teacher review module.
The database is used for storing student project design, evaluation indexes, teaching contents, teaching exercises, an evaluation index database and historical evaluation data, and the historical evaluation data comprises historical evaluation results of students. Specifically, the evaluation index library comprises three evaluation indexes of content scoring, result scoring and summary scoring; the content scoring comprises scoring of three items of content which are fully functional, normatively readable and annotated; the result scores comprise scores of correctness and format; the summary score is the score for the highlights, the test spots and the question.
In this embodiment, the course generation module is configured to divide teaching knowledge points according to teaching contents and generate course contents, the problem generation module is configured to extract corresponding teaching problems according to the course contents and the teaching knowledge points thereof to generate subjective problems including simple answers, calculations, and analyses, and the subjective problems include three parts, namely contents, results, and summaries, and correspond to the three evaluation indexes one to one.
The student mutual evaluation module comprises a student layering module and a mutual evaluation distribution module, wherein the student layering module is used for extracting evaluation results in historical evaluation data and layering students, and the students are divided into different learning levels according to the total scores of all the evaluation results of the students, and the three levels of common, advanced and difficult are included in the embodiment.
The mutual evaluation matching module is used for distributing the subjective type exercises to students in the same level for initial evaluation according to the student hierarchy, the mutual evaluation matching module is provided with a distribution rule, and during distribution, the mutual evaluation distribution module distributes the subjective type exercises of the students with low historical scores to the students with high historical scores for initial evaluation according to the scores of the students in the historical evaluation data, so that complementary mutual evaluation is formed.
The intelligent evaluation module is used for establishing an artificial intelligence model according to historical evaluation data, and intelligently scoring the subjective exercises through the artificial intelligence model according to the evaluation indexes and the mutual evaluation data and generating corresponding confidence degrees.
The intelligent review module comprises a confidence coefficient analysis module, the confidence coefficient analysis module is provided with a confidence coefficient threshold value, when the standard deviation of five mutual-evaluation scores is greater than the confidence coefficient threshold value, the mutual-evaluation result is low confidence coefficient, at the moment, the subjective exercise is transmitted to the teacher re-evaluation module for re-evaluation, and the re-evaluation result after the teacher re-evaluation is output as the project score; and when the standard deviation of the five mutual evaluation scores is smaller than the confidence coefficient threshold value, the mutual evaluation result is high confidence coefficient, and the intelligent score at the moment is output as the project score.
The intelligent review module also comprises a machine evaluation module and a machine updating module; the machine evaluation module is used for evaluating the subjective exercises through the artificial intelligence model and generating an intelligent score; and the machine updating module is used for training an artificial intelligence model according to historical evaluation data.
Specifically, the machine updating module extracts features, such as annotations, variable naming norms and integrality, of content parts in the historical evaluation result according to the historical evaluation data, then trains by adopting various learning algorithms (logistic regression, decision tree, random forest, naive Bayes, KNN and SVM), and selects a model with the highest accuracy to maintain model parameters; for the result part, extracting features of the data picture by a deep convolutional neural network, and then training by machine learning; for the summary part, feature extraction is carried out in a natural language processing mode, and then training is carried out; therefore, accurate intelligent evaluation can be obtained through the artificial intelligence model obtained after the training of the historical evaluation result is completed.
The individual promoting module comprises a special promoting module and an individual mutual aid module, and the special promoting module is used for generating a targeted exercise according to weak items in student evaluation; the individual mutual-aid module is used for establishing a mutual-aid relationship between the students which are weak items in a certain aspect and the students which are strong items in the aspect according to the strong items and the weak items in the evaluation of the students; the strong item and the weak item are judged according to the grade of the student evaluation.
The studying situation analysis module comprises a score ranking module, a learning trend module, a score distribution module, a learning detection module, a personalized recommendation module and a learning prediction module. The score ranking module, the learning trend module and the score distribution module are used for displaying the score level distribution of the whole students; the learning detection module is used for providing the shortages of homework for students according to historical evaluation data and generating corresponding training suggestions; the personalized recommendation module is used for recommending the teaching content of the current level for the students only and helping the students progress gradually; the learning detection module is used for displaying the variation and fluctuation of the student scores and helping teachers to know the learning conditions of students.
The foregoing are merely exemplary embodiments of the present invention, and no attempt is made to show structural details of the invention in more detail than is necessary for the fundamental understanding of the art, the description taken with the drawings making apparent to those skilled in the art how the several forms of the invention may be embodied in practice with the teachings of the invention. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several changes and modifications can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.
Claims (8)
1. The utility model provides a mixed intelligent college student project intelligent evaluation system that strengthens intelligence which characterized in that: the system comprises a student mutual evaluation module, an intelligent evaluation module, a database and a teacher reevaluation module;
the database is used for storing subjective exercises, evaluation indexes and historical evaluation data;
the student mutual evaluation module is used for collecting mutual evaluation data generated by mutual evaluation of students on student project design according to evaluation indexes;
the intelligent evaluation module is used for establishing an artificial intelligence model according to historical evaluation data, intelligently evaluating the project design through the artificial intelligence model according to the evaluation index and the mutual evaluation data and generating a corresponding confidence coefficient;
a confidence coefficient threshold value is set in the intelligent review module, when the confidence coefficient reaches the confidence coefficient threshold value, the confidence coefficient is high, when the confidence coefficient is lower than the confidence coefficient threshold value, the confidence coefficient is low, and the intelligent score of the project design with high confidence coefficient is output as the project score; the project design with low confidence coefficient is transmitted to a teacher for reevaluation;
and the teacher reevaluation module is used for collecting reevaluation results of the teacher on the project design with low confidence coefficient and outputting the reevaluation results as the project scores.
2. The intelligent mixed enhanced intelligence university student project evaluation system of claim 1 wherein: the teaching system also comprises a course generation module and an exercise generation module, wherein the database also stores teaching contents and teaching exercises;
the course generation module is used for dividing teaching knowledge points according to the teaching content and generating course content;
the exercise generation module is used for extracting corresponding teaching exercises according to the course contents and the teaching knowledge points thereof and generating subjective exercises.
3. The intelligent mixed enhanced intelligence university student project evaluation system of claim 1 wherein: the student mutual evaluation module comprises a student layering module and a mutual evaluation distribution module;
the student layering module is used for layering according to historical evaluation results of students;
and the mutual scoring matching module is used for distributing the subjective type exercises to students in the same level according to the student hierarchy for initial evaluation.
4. The intelligent mixed enhanced intelligence university student project evaluation system of claim 3 wherein: when the distribution rules of the mutual evaluation distribution module are used for mutual evaluation among students at the same level, complementary mutual evaluation is carried out according to the strong items and the weak items of the students in the historical evaluation data.
5. The intelligent mixed enhanced intelligence university student project evaluation system of claim 4 wherein: the teaching exercise generation module is used for designing subjective exercises including simple answers, calculation and analysis according to the course knowledge points.
6. The intelligent mixed enhanced intelligence university student project evaluation system of claim 5 wherein: the database also comprises an evaluation index library, wherein the evaluation index library is a multi-dimensional scoring index designed by facing subjective items.
7. The intelligent mixed enhanced intelligence university student project evaluation system of claim 6 wherein: the system also comprises an individual promoting module, wherein the individual promoting module comprises a special promoting module and an individual mutual aid module;
the special item promoting module is used for generating a targeted exercise according to weak items in student evaluation;
the individual household main module is used for establishing a mutual aid relationship between the students which are weak items in a certain aspect and the students which are strong items in the aspect according to the strong items and the weak items in the student evaluation.
8. The intelligent mixed enhanced intelligence university student project evaluation system of claim 7 wherein: the learning situation analysis module comprises a score ranking module, a learning trend module, a score distribution module, a learning detection module, a personalized recommendation module and a learning prediction module.
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