CN112907086A - University classroom teaching quality evaluation method - Google Patents
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Abstract
The invention belongs to the technical field of teaching management, and particularly relates to a university classroom teaching quality evaluation method, which mainly comprises the following steps: 1. filling the blank information of student achievement; 2. extracting the information of the opened course related to the evaluated course, and calculating the association degree between the opened course and the evaluated course; 3. counting evaluation index information for measuring the evaluated course, and calculating the weight of each index in the evaluated course; 4. calculating the weight of the student in the evaluation of the evaluated course; 5. calculating the correlation coefficient between the evaluation problem in the evaluation questionnaire and each evaluation index in the student performance of the course, and establishing a classroom quality evaluation model for a university teacher; 6. for ease of comparison, the scores of the evaluated courses were normalized. The invention overcomes the problem that the evaluation of the existing method is not objective and credible, and provides a beneficial method for classroom teaching quality evaluation.
Description
The technical field is as follows:
the invention belongs to the technical field of teaching management, and particularly relates to a university classroom teaching quality evaluation method.
Background art:
classroom teaching is the core of college education, and is the main channel for college to realize knowledge teaching and skill culture. Colleges and universities realize that the improvement of the classroom teaching quality is of great significance to the improvement of the overall teaching quality of colleges and universities, and various behaviors and data of teachers and students in three stages of class front, class middle and class back are important parts for classroom teaching quality evaluation. By analyzing the classroom teaching conditions of teachers and students, an effective information feedback mechanism is formed, classroom teaching quality evaluation and management modes are optimized, the development of students and teachers is promoted, and the classroom teaching quality is improved.
The electronic questionnaire is the most common classroom teaching quality evaluation method at present, and can help colleges and universities to know classroom quality to a certain extent, but has the following problems: (1) the evaluation result can not objectively reflect the teaching quality, for example, many students who are not going to go to class can evaluate the teaching posture problem of a teacher, so that the evaluation result is not credible; (2) the degree of intelligence is not high, for example, the evaluation cannot be completed due to the lack of some evaluation data; (3) differences of students and courses cannot be fully considered, so that the evaluation is inaccurate.
The invention content is as follows:
the invention aims to solve the problems that the classroom evaluation of the existing university teachers is not objective and the evaluation result is unreasonable, and provides a university classroom teaching quality evaluation method. The evaluation data is perfected by utilizing grey prediction, the relation between the evaluated course and other courses is investigated by adopting grey correlation, the grey correlation value of each part score of the evaluated course and the grade of the evaluated course is calculated, and a university classroom teaching quality evaluation model is established.
The technical scheme adopted by the invention is as follows:
a university classroom teaching quality evaluation method comprises the following steps:
filling blank information of student scores;
the method for filling the blank information of the student achievement comprises the following steps:
due to the reasons of lack of examination and the like, partial information is always vacant in the student score information, and the vacancy of the information can cause the inaccuracy of the calculation weight in the evaluation of the evaluated course, so that the partial information needs to be filled. The invention fills the blank information by adopting the following method.
The score of the ith student is expressed as S ═ Si×1,si×2,si×3,…,φi×o,…,si×k,…,si×n]In the formula si×kIndicates the kth student's score, phii×oIndicating the blank of the course score information and adopting a gray prediction model to predict phii×oValue of (phi)i×oThe solving process for the values can be expressed as:
in the formula, i is the serial number of the student,
is s isi×oThe predicted value of (a) is determined,
is composed of
Primary accumulated value of s1 i×oIs s isi×oThe avgs is the average score of all courses of the ith student, the avg is the average score of all the courses of all the students, a is the student score prediction development coefficient, mu is the student score prediction gray contribution amount, and n is the total number of courses;
extracting the information of the opened course related to the evaluated course, and calculating the association degree between the opened course and the evaluated course;
the calculation method for extracting the opened course information related to the evaluated course and calculating the relevance between the opened course and the evaluated course is as follows:
extracting the opened course and the evaluated course score related to the course according to the teaching outline
Is represented by the formula (I) in which C0×iIndicating the score of the ith student of the evaluated course, for the kth course score
Is represented by the formula (I) in which Ck×iRepresents the score of the ith student of the kth class, then C0And CkRelation expression gammak(Ck,C0) Comprises the following steps:
wherein q is the course correlation degree calculation intermediate variable, ζ is the course correlation resolution coefficient, and nstuThe total number of students;
thirdly, counting evaluation index information of the evaluated courses, and calculating the weight of each index in the evaluated courses;
the evaluation index information for measuring the evaluated course is counted, and the weight of each index in the evaluated course is calculated as follows:
and (5) counting the evaluation indexes of the evaluated courses, such as the ordinary score, the rolling score, the homework score, the attendance score and the like. The relation between the mth evaluation index formed by the scores of the evaluated lessons and the evaluated lessons can adopt an intra-lesson grey correlation coefficient alpha (X)m,C0) Expressed by the following expression:
in the formula (I), the compound is shown in the specification,
indicating the m-th performance, x, of the course evaluatedm×iThe score of the ith student of the mth evaluation index of the evaluated course, tau is the distinguishing coefficient of each evaluation index of the evaluated course and the score of the evaluated course, nitemF is a temporary calculation variable of the student serial number, and f is the total number of parts into which the scores of the evaluated course can be divided;
step four, calculating the weight of the student in the evaluation of the evaluated course;
the weight calculation method of the student in the evaluation model of the evaluated course is as follows:
calculation weight beta of ith student in evaluation of evaluated courseiWith each part of score x acquired by the studentm×numAnd alpha (X) established by the partial achievement and the total achievementm,C0) And gamma of the course and the started coursek(Ck,C0) Are all related, soiCan be expressed as:
calculating the correlation coefficient between the evaluation problem in the evaluation questionnaire and each evaluation index in the student performance of the course, and establishing a classroom quality evaluation model of a university teacher;
the points for evaluating the teaching quality of the examination classroom for different questions in the questionnaire are different, for example, one of the evaluation points is as follows: whether the sound of teaching is flood or not and whether the posture is natural or not by a teacher can not be known by students who have not yet listened to the teaching, so that the correlation coefficient between the problem in the evaluation questionnaire and each part in the student performance of the course needs to be calculated.
The method for calculating the correlation coefficient between the problems in the evaluation questionnaire and each evaluation index in the student performance of the course and establishing the classroom quality evaluation model of the university teacher is as follows:
achievement review of evaluated course questionnaire of ith studentiCan be expressed as:
wherein z is the serial number of the test questions in the evaluation questionnaire,numrevtotal number of questions for evaluating questionnaires, fenzScore to evaluate the score of the z-th question in the questionnairei×zScore, associated with z-topic in the evaluation questionnaire, for the ith studentiScoring the ith student's home course;
the classroom quality evaluation model for university teachers is as follows:
in the formula, Eva is the score of the evaluated course;
sixthly, in order to facilitate comparison, the scores of the evaluated courses are subjected to standardized processing;
the method for standardizing the scores of the evaluated courses is as follows:
the score calculated according to the invention may exceed 100 points, while the highest score in habitual evaluation is 100 points, for which a normalization process is required, and the score Eva of the course evaluated after the normalization process100The expression is as follows:
in the formula, max is the highest score in the lessons evaluated according to the method.
The invention has the beneficial effects that: the method solves the problems that the classroom evaluation of the existing university teachers is not objective and the evaluation result is unreasonable, and provides a university classroom teaching quality evaluation method. The evaluation data is perfected by utilizing grey prediction, the relation between the evaluated course and other courses is investigated by adopting grey correlation, the grey correlation value of each part score of the evaluated course and the grade of the evaluated course is calculated, and a university classroom teaching quality evaluation model is established. Its main advantage is as follows:
(1) the grey prediction method is adopted to fill the blank information of the student performance, so that a data completeness basis is provided for accurate classroom teaching quality evaluation of the present university;
(2) the university classroom teaching quality evaluation model is established, the influence of individual differences of each course and each student on evaluation is fully considered, and an objective and accurate classroom quality evaluation method is provided.
Description of the drawings:
FIG. 1 is a flow chart of a first embodiment;
FIG. 2 is a diagram of data after filling blank information according to an embodiment;
FIG. 3 is a graph illustrating the relationship between the lessons studied and the lessons tested according to an embodiment of the present invention;
FIG. 4 is a graph of weights of various indicators in the course being evaluated according to the first embodiment;
FIG. 5 is a graph of weights for evaluating students according to the first embodiment;
FIG. 6 is a graph of the correlation coefficient between the evaluation question and each part of the evaluation indexes in the student performance in the first embodiment of the course;
FIG. 7 is a diagram of the recognition degree of the conventional evaluation result and the evaluation result of the method according to the first embodiment.
The specific implementation mode is as follows:
example one
Referring to the figures, the quality evaluation method for the classroom teaching of university comprises the following steps:
filling blank information of student scores;
the method for filling the blank information of the student achievement comprises the following steps:
due to the reasons of lack of examination and the like, partial information is always vacant in the student score information, and the vacancy of the information can cause the inaccuracy of the calculation weight in the evaluation of the evaluated course, so that the partial information needs to be filled. The invention fills the blank information by adopting the following method.
The score of the ith student is expressed as S ═ Si×1,si×2,si×3,…,φi×o,…,si×k,…,si×n]In the formula si×kIndicates the kth student's score, phii×oIndicating that the course achievement information is blank,prediction of phi using a gray prediction modeli×oValue of (phi)i×oThe solving process for the values can be expressed as:
in the formula, i is the serial number of the student,
is s isi×oThe predicted value of (a) is determined,
is composed of
Primary accumulated value of s1 i×oIs s isi×oThe avgs is the average score of all courses of the ith student, the avg is the average score of all the courses of all the students, the alpha is the student score prediction development coefficient, the mu is the student score prediction gray acting amount, and the n is the total number of the courses;
extracting the information of the opened course related to the evaluated course, and calculating the association degree between the opened course and the evaluated course;
the calculation method for extracting the opened course information related to the evaluated course and calculating the relevance between the opened course and the evaluated course is as follows:
extracting the opened course and the evaluated course score related to the course according to the teaching outline
Is represented by the formula (I) in which C0×iIndicating the score of the ith student of the evaluated course, for the kth course score
Is represented by the formula (I) in which Ck×iRepresents the score of the ith student of the kth class, then C0And CkRelation expression gammak(Ck,C0) Comprises the following steps:
wherein q is the course correlation degree calculation intermediate variable, ζ is the course correlation resolution coefficient, and nstuThe total number of students;
thirdly, counting evaluation index information of the evaluated courses, and calculating the weight of each index in the evaluated courses;
the evaluation index information for measuring the evaluated course is counted, and the weight of each index in the evaluated course is calculated as follows:
and (5) counting the evaluation indexes of the evaluated courses, such as the ordinary score, the rolling score, the homework score, the attendance score and the like. The relation between the mth evaluation index formed by the scores of the evaluated lessons and the evaluated lessons can adopt an intra-lesson grey correlation coefficient alpha (X)m,C0) Expressed by the following expression:
in the formula (I), the compound is shown in the specification,
indicating the m-th performance, x, of the course evaluatedm×iThe score of the ith student of the mth evaluation index of the evaluated course, tau is the distinguishing coefficient of each evaluation index of the evaluated course and the score of the evaluated course, nitemF is a temporary calculation variable of the student serial number, and f is the total number of parts into which the scores of the evaluated course can be divided;
step four, calculating the weight of the student in the evaluation of the evaluated course;
the weight calculation method of the student in the evaluation model of the evaluated course is as follows:
calculation weight beta of ith student in evaluation of evaluated courseiWith each part of score x acquired by the studentm×numAnd alpha (X) established by the partial achievement and the total achievementm,C0) And the course and the past dateGamma of coursek(Ck,C0) Are all related, soiCan be expressed as:
calculating the correlation coefficient between the evaluation problem in the evaluation questionnaire and each evaluation index in the student performance of the course, and establishing a classroom quality evaluation model of a university teacher;
the points for evaluating the teaching quality of the examination classroom for different questions in the questionnaire are different, for example, one of the evaluation points is as follows: whether the sound of teaching is flood or not and whether the posture is natural or not by a teacher can not be known by students who have not yet listened to the teaching, so that the correlation coefficient between the problem in the evaluation questionnaire and each part in the student performance of the course needs to be calculated.
The method for calculating the correlation coefficient between the problems in the evaluation questionnaire and each evaluation index in the student performance of the course and establishing the classroom quality evaluation model of the university teacher is as follows:
achievement review of evaluated course questionnaire of ith studentiCan be expressed as:
wherein z is the serial number of the test questions in the evaluation questionnaire,numrevtotal number of questions for evaluating questionnaires, fenzScore to evaluate the score of the z-th question in the questionnairei×zScore, associated with z-topic in the evaluation questionnaire, for the ith studentiScoring the ith student's home course;
the classroom quality evaluation model for university teachers is as follows:
in the formula, Eva is the score of the evaluated course;
sixthly, in order to facilitate comparison, the scores of the evaluated courses are subjected to standardized processing;
the method for standardizing the scores of the evaluated courses is as follows:
the score calculated according to the invention may exceed 100 points, while the highest score in habitual evaluation is 100 points, for which a normalization process is required, and the score Eva of the course evaluated after the normalization process100The expression is as follows:
in the formula, max is the highest score in the lessons evaluated according to the method.
The implementation flow of the method is shown in fig. 1, taking the course of evaluating the sensor and testing technology as an example, in order to verify the correctness of the blank information filling method provided by the method, the score of a certain subject is 78 points, the subject is replaced by the blank information, and the score obtained by the blank information filling method provided by the method is 80 parts, as shown in fig. 2, so that the correctness of the blank information filling method provided by the method can be known.
The association degree between the course and other learned courses in the sensor and testing technology is shown in fig. 3, the weight of each index in the evaluated course is shown in fig. 4, the weight occupied by the evaluation student is shown in fig. 5, and the association coefficient between each evaluation index in a certain evaluation problem and the student score of the course is shown in fig. 6. The acceptance of 10 courses with larger disputes is shown in FIG. 7. As can be seen from FIG. 7, the results of the method acceptance were all higher than 87%, and all higher than the prior evaluation method.
The foregoing is a more detailed description of the present invention that is presented in conjunction with specific embodiments, which are not to be construed as limiting the invention to the specific embodiments described above. Numerous other simplifications or substitutions may be made without departing from the spirit of the invention as defined in the claims and the general concept thereof, which shall be construed to be within the scope of the invention.
Claims (1)
1. A university classroom teaching quality evaluation method is characterized in that: the university classroom teaching quality evaluation method comprises the following steps:
filling blank information of student scores;
the method for filling the blank information of the student achievement comprises the following steps:
the score of the ith student is expressed as S ═ Si×1,si×2,si×3,…,φi×o,…,si×k,…,si×n]In the formula si×kIndicates the kth student's score, phii×oIndicating the blank of the course score information and adopting a gray prediction model to predict phii×oValue of (phi)i×oThe solving process for the values can be expressed as:
in the formula, i is the serial number of the student,
is s isi×oThe predicted value of (a) is determined,
is composed of
Primary accumulated value of s1 i×oIs s isi×oThe avgs is the average score of all courses of the ith student, the avg is the average score of all the courses of all the students, a is the student score prediction development coefficient, mu is the student score prediction gray contribution amount, and n is the total number of courses;
extracting the information of the opened course related to the evaluated course, and calculating the association degree between the opened course and the evaluated course;
the calculation method for extracting the opened course information related to the evaluated course and calculating the relevance between the opened course and the evaluated course is as follows:
extracting the opened course and the evaluated course score related to the course according to the teaching outline
Is represented by the formula (I) in which C0×iIndicating the score of the ith student of the evaluated course, for the kth course score
Is represented by the formula (I) in which Ck×iRepresents the score of the ith student of the kth class, then C0And CkRelation expression gammak(Ck,C0) Comprises the following steps:
wherein q is the course correlation degree calculation intermediate variable, ζ is the course correlation resolution coefficient, and nstuThe total number of students;
thirdly, counting evaluation index information of the evaluated courses, and calculating the weight of each index in the evaluated courses;
the evaluation index information for measuring the evaluated course is counted, and the weight of each index in the evaluated course is calculated as follows:
the relation between the mth evaluation index formed by the scores of the evaluated lessons and the evaluated lessons can adopt an intra-lesson grey correlation coefficient a (X)m,C0) Expressed by the following expression:
in the formula (I), the compound is shown in the specification,
indicating the m-th performance, x, of the course evaluatedm×iThe mth evaluation index of the evaluated course is the ith studyThe score of the student, tau is the distinguishing coefficient between each evaluation index of the evaluated course and the score of the evaluated course, nitemF is a temporary calculation variable of the student serial number, and f is the total number of parts into which the scores of the evaluated course can be divided;
step four, calculating the weight of the student in the evaluation of the evaluated course;
the weight calculation method of the student in the evaluation model of the evaluated course is as follows:
calculation weight beta of ith student in evaluation of evaluated courseiWith each part of score x acquired by the studentm×numA (X) of the partial achievement and the total achievementm,C0) And gamma of the course and the started coursek(Ck,C0) Are all related, soiCan be expressed as:
calculating the correlation coefficient between the evaluation problem in the evaluation questionnaire and each evaluation index in the student performance of the course, and establishing a classroom quality evaluation model of a university teacher;
the method for calculating the correlation coefficient between the problems in the evaluation questionnaire and each evaluation index in the student performance of the course and establishing the classroom quality evaluation model of the university teacher is as follows:
achievement review of evaluated course questionnaire of ith studentiCan be expressed as:
wherein z is the number of test questions in the evaluation questionnaire, numrevTotal number of questions for evaluating questionnaires, fenzScore to evaluate the score of the z-th question in the questionnairei×zScore, associated with z-topic in the evaluation questionnaire, for the ith studentiScoring the ith student's home course;
the classroom quality evaluation model for university teachers is as follows:
in the formula, Eva is the score of the evaluated course;
sixthly, in order to facilitate comparison, the scores of the evaluated courses are subjected to standardized processing;
the method for standardizing the scores of the evaluated courses is as follows:
the score calculated according to the invention may exceed 100 points, while the highest score in habitual evaluation is 100 points, for which a normalization process is required, and the score Eva of the course evaluated after the normalization process100The expression is as follows:
in the formula, max is the highest score in the lessons evaluated according to the method.
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| CN113408957A (en) * | 2021-07-20 | 2021-09-17 | 北京师范大学 | Classroom teaching evaluation method based on combined empowerment method |
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| CN113408957A (en) * | 2021-07-20 | 2021-09-17 | 北京师范大学 | Classroom teaching evaluation method based on combined empowerment method |
| CN113408957B (en) * | 2021-07-20 | 2023-07-18 | 北京师范大学 | Classroom teaching evaluation method based on combined weighting method |
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Application publication date: 20210604 |