CN114971962A - Student homework evaluation method and device, electronic device and storage medium - Google Patents
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Abstract
The application provides a student homework evaluation method and device, electronic equipment and a storage medium. The evaluation and diagnosis method for the student stage homework comprises the following steps: collecting the homework information of students; analyzing the preset dimensionality of the student homework based on a pre-constructed homework information analysis model and the homework information; generating a student homework evaluation report according to the result of student homework analysis; wherein the preset dimensions comprise at least two of the following dimensions: the student work efficiency, the student work stability, the different problem types of student work score condition, the different degree of difficulty score condition of student work, student knowledge point master condition. The application provides and has carried out the analysis of multidimension degree to the periodic homework of student, can help the accurate advantage and the not enough of realizing self of student, improves the score fast, avoids because evaluation angle is single to cause the student to learn the condition and master not comprehensive, untimely problem.
Description
Technical Field
The application relates to the technical field of intelligent teaching management, in particular to a student homework evaluation method and device, electronic equipment and a storage medium.
Background
With the gradual electronization and informatization of teaching management and operation flows, the operation of students can be corrected and evaluated in a line mode.
The evaluation method of each education platform for student homework at the present stage is mainly from the perspective of knowledge points to analyze student homework.
However, the student homework is influenced by various factors, and the evaluation method is limited from the perspective of knowledge points, and the homework condition of the student and the mastering condition of the knowledge points cannot be analyzed completely, so that a personalized learning scheme cannot be provided for the student, and the student is helped to improve the learning score quickly.
Disclosure of Invention
The application provides a student homework evaluation method and device, electronic equipment and a storage medium. The student homework evaluation method is suitable for teaching management scenes, and provides an individual scheme for students so as to achieve the purpose of accurately improving the quality.
In a first aspect, the present application provides a student homework evaluation method for evaluating students from multiple angles in teaching management, the method comprising:
collecting the homework information of students;
analyzing the preset dimensionality of the student homework based on a pre-constructed homework information analysis model and the homework information; generating a student homework evaluation report according to the result of student homework analysis;
wherein the preset dimensions comprise at least two of the following dimensions:
the student homework efficiency, the student homework stability, the different question types of student homework score condition, the different degree of difficulty score condition of student homework, student knowledge point master condition.
The application provides an evaluation method of student's homework, analyzes homework information through the model, and the analytic process can be followed and is predetermine the dimension and set out, and wherein, predetermine the dimension and include two dimensions at least, can follow the multi-angle like this and carry out the analysis to student's homework, has avoided the analytic process angle single to reached and carried out more comprehensive analysis's purpose to student's homework condition.
Optionally, the analysis of the preset dimensionality for the student homework based on the pre-established homework information analysis model and the homework information includes:
extracting a plurality of corresponding operation characteristics based on a pre-constructed operation information analysis model and the operation information;
selecting at least one operation feature corresponding to each preset dimension from the operation features; and combining the selected at least one operation characteristic to obtain the evaluation corresponding to the preset dimension.
The homework characteristics of the students are obtained through model extraction, the characteristics reflect the completion conditions of the homework of the students, and the characteristics are combined respectively to form multiple dimensions, so that the proper characteristics and dimensions are selected, the analysis of the homework of the students is more comprehensive, and the purposeful analysis of the homework of the students is more convenient.
Optionally, the collecting the homework information of the student comprises:
based on a character recognition technology, information acquisition is carried out on homework of the online version to obtain homework information of students; the homework information comprises student homework score information, exercise information, difficulty information, question type information, knowledge point information and homework duration information; the method for extracting a plurality of corresponding operation characteristics based on the operation information analysis model constructed in advance and the operation information comprises the following steps: based on a pre-constructed homework information analysis model, student homework score information, exercise information, difficulty information, question type information, knowledge point information and homework duration information are input into the homework information analysis model, and a plurality of corresponding homework characteristics are extracted.
Because the homework information of gathering is many-sided, the student's homework characteristic of extracting has more convincing, and the angle is also more diversified, carries out the combination analysis with the student's homework characteristic of multi-angle, can be when the student's homework analysis, and is more comprehensive.
Optionally, the job information analysis model includes:
the student homework time effect submodel, the homework fluctuation level characterization submodel, the accuracy comprehensive evaluation submodel and the knowledge point grasping analysis submodel are combined;
based on the homework information analysis model which is constructed in advance, student homework score information, exercise information, difficulty information, question type information, knowledge point information and homework duration information are input into the model, and a plurality of corresponding homework characteristics are extracted, wherein the method comprises the following steps:
based on the student work timeliness sub-model, obtaining work timeliness characteristics according to the work duration information;
based on the homework fluctuation level characterization submodel, according to the student homework score information, obtaining a homework score transverse comparison characteristic and a homework score stability characteristic;
on the basis of the accuracy comprehensive evaluation submodel, obtaining score condition characteristics aiming at different question type topics and score condition characteristics aiming at different difficulty topics according to the question type information, the difficulty information and the student homework score information;
and obtaining the operation knowledge point mastery degree characteristics according to the exercise information, the knowledge point information and the score information based on the knowledge point mastery analysis submodel.
Based on different models, the homework characteristics in different aspects can be obtained, the characteristics are combined, the analysis directions of the student homework in different dimensions can be obtained, the question types and the questions of the difficulty which need to be focused are accurately analyzed, and key knowledge points are obtained, so that the students are helped to quickly improve the scores.
Optionally, the method further includes:
determining a wrong question according to the collected operation information, and extracting wrong question information corresponding to the wrong question;
retrieving to obtain a variant question corresponding to the wrong question according to the wrong question information;
and combining the error question and the variant question corresponding to the error question as a feedback question with the student homework evaluation report to generate a student homework feedback evaluation report.
The method collects the wrong question information of the students, retrieves the related variable questions, and puts the variable questions into the student homework evaluation report, thereby providing a way for the students to correct the wrong questions and consolidate the knowledge points.
Optionally, the exercise information includes:
the homework questions in the evaluation period and the feedback questions in the student homework feedback evaluation report corresponding to the previous evaluation period.
The method has the advantages that wrong questions of the students are collected and corrected again and analyzed, a way for consolidating knowledge is provided for the students, and teachers are helped to know error prone points and difficulty points in student homework.
In a second aspect, the present application provides a student homework evaluation method for evaluating students from five angles in teaching management, the method including:
collecting the homework information of students;
analyzing the preset dimensionality of the student homework based on a pre-constructed homework information analysis model and the homework information; generating a student homework evaluation report according to the result of student homework analysis;
the preset dimensionality comprises student work efficiency, student work stability, the scoring conditions of different question types of student work, the scoring conditions of different difficulty of student work and the mastering conditions of student knowledge points.
In a third aspect, the present application provides an evaluation device for student's homework, comprising:
the information acquisition module is used for acquiring the homework information of students;
the model analysis module is used for analyzing the preset dimensionality of the student homework based on a pre-constructed homework information analysis model and the homework information;
the report generation module is used for generating a student work evaluation report according to the result of the student work analysis;
wherein the preset dimensions comprise at least two of the following dimensions:
the student work efficiency, the student work stability, the different problem types of student work score condition, the different degree of difficulty score condition of student work, student knowledge point master condition.
Optionally, the information acquisition module is specifically configured to:
extracting a plurality of corresponding operation characteristics based on a pre-constructed operation information analysis model and the operation information;
selecting at least one operation feature corresponding to each preset dimension from the plurality of operation features for each preset dimension; and combining the selected at least one operation characteristic to obtain the evaluation corresponding to the preset dimension.
Optionally, the information acquisition module is specifically configured to:
based on a character recognition technology, information acquisition is carried out on homework of the online version to obtain homework information of students; the homework information comprises student homework score information, exercise information, difficulty information, question type information, knowledge point information and homework duration information; the model analysis module is specifically configured to, when extracting a plurality of corresponding job features based on a pre-constructed job information analysis model and the job information:
based on a pre-constructed homework information analysis model, student homework score information, exercise information, difficulty information, question type information, knowledge point information and homework duration information are input into the homework information analysis model, and a plurality of corresponding homework characteristics are extracted.
Optionally, the job information analysis model includes:
the student homework time effect submodel, the homework fluctuation level characterization submodel, the accuracy comprehensive evaluation submodel and the knowledge point grasping analysis submodel are combined;
the model analysis module is based on the homework information analysis model that founds in advance, in with student's homework score information, exercise information, degree of difficulty information, question type information, knowledge point information, the time length information input model during of the homework, when extracting corresponding a plurality of homework characteristics, specifically is used for:
based on the student work timeliness sub-model, obtaining work timeliness characteristics according to the work duration information;
based on the homework fluctuation level characterization submodel, according to the student homework score information, obtaining a homework score transverse comparison characteristic and a homework score stability characteristic;
on the basis of the accuracy comprehensive evaluation submodel, obtaining score condition characteristics aiming at different question type topics and score condition characteristics aiming at different difficulty topics according to the question type information, the difficulty information and the student homework score information;
and obtaining the operation knowledge point mastery degree characteristics according to the exercise information, the knowledge point information and the score information based on the knowledge point mastery analysis submodel.
Optionally, the apparatus further includes a feedback question retrieving module, specifically configured to:
determining a wrong question according to the collected operation information, and extracting wrong question information corresponding to the wrong question;
retrieving to obtain a variable question corresponding to the wrong question according to the wrong question information;
and combining the error question and the variable question corresponding to the error question as a feedback question with the student homework evaluation report to generate a student homework feedback evaluation report.
Optionally, the exercise information includes:
the homework questions in the evaluation period and the feedback questions in the student homework feedback evaluation report corresponding to the previous evaluation period.
The application provides another student's homework's evaluation device includes:
the information acquisition module is used for acquiring the homework information of students;
the model analysis module is used for analyzing the preset dimensionality of the student homework based on a pre-constructed homework information analysis model and the homework information;
the report generation module is used for generating a student homework evaluation report according to the result of student homework analysis;
the preset dimensionality comprises student work efficiency, student work stability, the scoring conditions of different question types of student work, the scoring conditions of different difficulty of student work and the mastering conditions of student knowledge points.
In a fourth aspect, the present application provides an electronic device comprising: a memory having stored thereon a computer program which is loadable by the processor and adapted to perform any of the methods of the first aspect or the second aspect.
In a fifth aspect, the present application provides a computer readable storage medium storing a computer program that can be loaded by a processor and executed to perform any one of the methods of the first aspect or the second aspect.
The application provides evaluation method, device, electronic equipment and storage medium of student's homework, carries out the analysis to the homework information through the model, and the analytic process can be followed and predetermine the dimension and set out, and wherein, predetermine the dimension and include two dimensions at least, can follow the multi-angle like this and carry out the analysis to the student's homework, has avoided the analytic process angle single to reach the purpose of carrying out more comprehensive analysis to the student's homework condition.
Drawings
FIG. 1 is a schematic diagram of an application scenario provided in the present application;
fig. 2 is a flowchart of an evaluation method for student assignments according to an embodiment of the present application;
3 a-3 g are schematic illustrations of some student assignment evaluations provided by an embodiment of the present application;
fig. 4 is a schematic structural diagram of an evaluation apparatus for student assignments according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the objects, 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 with reference to the drawings in the embodiments of the present application. It is to be understood that the embodiments described are only a few embodiments of the present application and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In addition, the term "and/or" herein is only one kind of association relationship describing an associated object, and means that there may be three kinds of relationships, for example, a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship, unless otherwise specified.
The embodiments of the present application will be described in further detail with reference to the drawings attached hereto.
Fig. 1 is a schematic view of an application scenario provided in the present application, in which a student of a classmate needs to be evaluated in a certain work or a certain period of student work. Due to the fact that factors influencing the student homework are numerous, in order to comprehensively evaluate the student homework, the method is applied to evaluate the student homework. Specifically, the student homework evaluation method can be deployed in a server. After the student homework is uploaded to the server, the server executes the method, evaluates the student homework and further obtains comprehensive evaluation of the student homework in multiple dimensions. The following embodiments may be referred to for implementation of specific processing at the server.
Fig. 2 is a flowchart of an evaluation method for student assignments according to an embodiment of the present application. The method of the embodiment is used for evaluating the student homework from multiple dimensions when evaluating the student homework, and can be applied to the server in the scene and other electronic equipment with computing capacity.
As shown in fig. 2, the method of the present embodiment includes:
s201, collecting the homework information of students.
The collection source of the homework information can be an online version of the homework of the student which is read and finished.
In particular, the student assignment may be an online assignment. At this time, the online operation can be directly uploaded, and information acquisition can be performed on the uploaded online operation.
The student assignments may also be paper versioning. At the moment, the operation of the paper version can be converted into the operation of the online version through the electronic equipment, and then the converted operation of the online version is uploaded and information is acquired. For example, the exercise homework on the student exercise book can be scanned by using the scanner to obtain the exercise homework of the online version, so that the exercise homework of the online version is uploaded, and the exercise information of the student is collected from the exercise homework of the online version.
In some scenes, in order to improve the reading and amending efficiency of the student homework and realize the timely reading and feedback of the student homework, the student homework can be submitted to a scoring system for reading and amending. At this time, when the homework information of the student is collected, the homework information of the student homework completed by the rating system is collected.
Compared with the traditional manual review mode, the review speed of the scoring system is higher, but some problems exist, such as the accuracy rate of the scoring system review task is lower than that of the manual review for the open test question. Thus, in some embodiments, the student assignment may be reviewed by the teacher for open questions before being submitted to the scoring system for review. At this time, when job information is collected, job information composed of open test question contents read by a teacher and other contents read by a scoring system is collected. For example, a student homework is divided into a subjective question and an objective question, and the accuracy of manually reviewing the subjective question is better than that of reviewing by a scoring system, so that a teacher can review the subjective question in the homework first, then submit the student homework to the scoring system, and review the objective question in the student homework by the scoring system, so that when homework information is collected, the collected homework information is formed by the contents of the manually reviewed subjective question and the contents of the objective question reviewed by the scoring system.
In some embodiments, a trigger condition may be set for the student assignment evaluation method. The trigger condition may be a period condition, for example, a week is set as a period, and all jobs uploaded in the period are evaluated once at that time. The trigger condition may also be a number condition, for example, ten times are set as one node, and when the number of uploaded student assignments reaches ten times, the ten student assignments are evaluated once; or, the node is set once, namely, each time the student homework is uploaded, the student homework is immediately evaluated. Here, the period with other lengths and other times conditions may be set, which is not limited.
S202, analyzing the preset dimensionality of the student homework based on the pre-constructed homework information analysis model and the homework information.
The preset dimension refers to an angle selected for evaluating the student assignment before evaluating the student assignment. In some embodiments, the preset dimensions include at least two of the following dimensions: the student work efficiency, the student work stability, the different problem types of student work score condition, the different degree of difficulty score condition of student work, student knowledge point master condition.
The student homework efficiency dimension can reflect the overall quality condition of the student completing homework; the student homework stability dimension can reflect the score fluctuation condition of students among multiple homework in the evaluation and the score fluctuation condition among multiple evaluations; the dimensionality of the scoring conditions of different question types of the student homework can reflect the scoring conditions of students under each question type; the dimension of different difficulty scoring conditions of the student homework refers to the scoring condition of the student under each difficulty exercise; the dimension of the mastering situation of the knowledge points of the students can reflect the mastering situation of the students on different knowledge point questions.
Inputting the homework information collected in the step S201 into a homework information analysis model, analyzing the homework of the student according to the selected preset dimensionality by the model aiming at each preset dimensionality to obtain corresponding evaluation, and outputting the evaluation corresponding to the preset dimensionality.
And S203, generating a student work evaluation report according to the result of the student work analysis.
And combining the evaluations of the selected preset dimensions to generate a student homework evaluation report. Besides using comment display, the student homework evaluation report can also have a plurality of display modes. For example, the stability of the student homework can be displayed through a homework curve graph, so that the larger fluctuation of a certain homework of the student can be more visually displayed, and the student is reminded to consolidate the practice; the different difficulty scoring conditions of the student homework can be displayed through the histogram, the student homework difficulty is divided into simple, common, difficult and very difficult, the scoring condition of a certain difficulty of the student can be observed visually, and the condition that the item scoring rate of the simple difficulty and the common difficulty is lower is reminded. Here, only by way of example, there are also various display modes of student's homework evaluation reports, which are not described in detail.
The application provides evaluation method of student's homework, analyzes the homework information through the model, and the analytic process can be followed and is predetermine the dimension and set out, and wherein, predetermine the dimension and include two dimensions at least, can follow the multi-angle like this and carry out the analysis to student's homework, avoided the analytic process angle single to reached and carried out more comprehensive analysis's purpose to student's homework condition.
The specific process of the S202, based on the pre-constructed job information analysis model and the job information, performing analysis of the student job with the preset dimension may include: extracting a plurality of corresponding operation characteristics based on a pre-constructed operation information analysis model and the operation information; selecting at least one operation feature corresponding to each preset dimension from the plurality of operation features for each preset dimension; and combining the selected at least one operation characteristic to obtain the evaluation corresponding to the preset dimension.
In some embodiments, based on a pre-constructed job information analysis model and the job information, job characteristics that can be extracted may include job timeliness characteristics, job score lateral contrast characteristics, job score stability characteristics, score situation characteristics for different topic types, score situation characteristics for different difficulty topics, job knowledge point mastery characteristics, and the like.
Wherein, the homework timeliness characteristic is a characteristic used for indicating the relationship between the time and the score of the student homework; the assignment score lateral contrast feature is a feature used to refer to the relationship between the student assignment score and the class score; the job score stability feature is a feature used to indicate whether the score is stable or not; the score condition characteristics aiming at different question types and topics are characteristics used for referring to the relationship between different question types and scores and fractions; the scoring condition characteristics aiming at different difficulty topics are characteristics used for indicating the relationship between different difficulty topics and scoring rates; the operation knowledge point mastery degree feature is a feature used to refer to a relationship between different knowledge point topics and score ratios.
The homework information analysis model can calculate the numerical values corresponding to the different homework characteristics according to the homework information, and can quantify the completion condition of the student homework aiming at the numerical values, so that the evaluation of the student homework can be obtained according to the quantified result.
Taking a one-cycle homework as an example, suppose that a student submits N times of homework H ═ { H) in the cycle 1 ,H 2 ,...,H N N times, including M exercises E ═ E in total 1 ,E 2 ,...,E m }。
And inputting the operation information into the operation information analysis model, and obtaining operation timeliness characteristics through the characteristic extraction process. Specifically, first, the duration T of each operation in the completion cost cycle of the student can be counted student Calculating the average value of the time spent on the homework in the student period based on the time spent on the homework in the student period, and subtracting the average value of the time spent on the homework in the student period from the average value of the time spent on the homework in the student period to obtain the aged longitudinal fluctuation characteristic of the student homework
Subtracting the average value of the student in the period of the homework from the average value of the student in the period of the class to obtain the aged transverse fluctuation characteristic of the student in the homework
Based on
And
and further calculating to obtain the operation aging characteristic F (T).
Similarly, the job information is input into the job information analysis model, and the job score transverse comparison feature and the job score stability feature can be obtained through the feature extraction process. Specifically, the score S of each homework in the student' S period is counted student Calculating the average value of the homework scores in the period of the student based on the average value, and subtracting the average value of the homework scores in the period of the student from the average value of the homework scores in the period of the student to obtain the longitudinal fluctuation characteristics of the homework scores of the student
Subtracting the average value of the homework scores in the student period from the average value of the class homework scores in the student period to obtain the transverse fluctuation characteristic of the student homework scores
Can be based on
Calculating the stability sigmas of student' S homework score using the following formula student ：
Further, based on
σS student Calculating to obtain the job score stability characteristic F (S).
Similarly, the job information is input into the job information analysis model, and the score condition characteristics for different question types can be obtained through the characteristic extraction process. Specifically, the scoring conditions S of different types of subjects in the student book period can be counted type Calculating the score of each type of subject in the student period based on the above information, subtracting the score of each type of subject in the student period from the score of the corresponding type of subject in the student period to obtain the level of the same type of subjectContrast feature
Subtracting the score of each type of subject in the student's book period from the score of the corresponding type of subject in the student's previous period to obtain the longitudinal contrast characteristic of the same type of subject
Such as: the students have reading comprehension type subjects in homework, the scoring rate of the reading comprehension type subjects in the period of the same school is obtained by counting the scoring rates of all the reading comprehension type subjects in the period, and then the scoring rate of the reading comprehension type subjects in the period of the same school is subtracted from the scoring rate of all the reading comprehension type subjects in the class to obtain the horizontal contrast characteristic of the reading comprehension type subjects in the same school
Subtracting the score of the reading understanding type in the current period from the score of the reading understanding type in the previous period to obtain the longitudinal contrast characteristic of the same type of subjects
The operation information is input into the operation information analysis model, and score condition characteristics aiming at different difficulty topics can be obtained through the characteristic extraction process. Specifically, the scoring conditions S of the subjects with different degrees of difficulty in the student' S period are counted difficulty Calculating the score of each difficulty question in the student period based on the above, subtracting the score of the corresponding difficulty question in the period of the class of the student from the score of each difficulty question in the student period to obtain the horizontal contrast characteristic of the questions with the same difficulty
Subtracting the score of the difficulty question corresponding to the previous period of the student from the score of each difficulty question in the current period of the student to obtain the longitudinal contrast characteristic of the questions with the same difficulty
The statistical period of homework contains M exercises E, the homework relates to knowledge points KP, and the mastery degree of students on the knowledge points can be calculated according to the following formula:
obtaining mastery degree characteristics F (KP) of knowledge points mn )。
In some embodiments, the work of the schoolmate of the class-one hill is evaluated in one week period. The general evaluation of the corresponding population in the student assignment evaluation report output in one period is shown in fig. 3 a.
Corresponding to the dimension of the work efficiency of the students in 202, the work aging characteristics and the work score transverse comparison characteristics can be selected from the characteristics and analyzed, and the work aging characteristics and the work score transverse comparison characteristics are combined to obtain the evaluation corresponding to the dimension of the work efficiency.
In particular, when
When the student works, the student works for a long time, but works for a good quality, and for the condition, the evaluation corresponding to the dimension can be output to prompt the student to pay attention to the working time; when in use
When the student works, the student works for a long time, but the work quality is poor, and for the condition, the evaluation corresponding to the dimension can be output to prompt the student to complete the work seriously and pay attention to the induction and summarization of the work knowledge points; when in use
The evaluation corresponding to the dimension can be output aiming at the condition that the student works in a shorter time and works in a better quality, the completion of the student works is praised and the student is prompted to keep attention; when in use
In the time, the student works for a short time, but the work quality is poor, and for the condition, the evaluation corresponding to the dimension can be output to prompt the student to pay attention to missing and filling up the lack, and carefully complete the work.
In accordance with the dimension of job stability of the student in the above 202, the job stability feature f(s) can be selected from the above features and analyzed to obtain an evaluation corresponding to the dimension of job stability.
Specifically, when F (S) is more than or equal to 0, the homework of the student in the period is stable, the student is prompted to play a stable homework, the comprehensive performance of the score is good, and the student is encouraged to continue to maintain; when F (S) is less than 0, the fluctuation of the students in the period is large, the students are prompted to have large fluctuation of the current homework, the comprehensive level needs to be improved, and basic exercises are recommended to be strengthened.
In some embodiments, a specific evaluation of the dimension of student assignment stability may be presented in the manner shown in fig. 3b and 3 c.
Corresponding to the dimension of the scoring condition of different question types of the student assignment in the step 202, the scoring condition characteristics of different question types of the student assignment can be selected from the characteristics and analyzed, and the corresponding evaluation of the dimension of the scoring condition of different question types of the student assignment can be obtained.
Specifically, when the score rates of the multiple types of questions are higher than the average score rate of the corresponding class, the completion condition of the multiple types of questions in the period is better, and the student is prompted to keep the completion condition of the current homework better; when the score of the multiple types of questions is lower than the corresponding class average score, the completion conditions of the multiple types of questions in the period are poor, and the students are prompted to have high error rate of the multiple question types in the current homework and pay attention to answering the questions carefully.
Corresponding to the dimension of the above 202 student homework with different difficulty scores, the score features for different difficulty topics can be selected from the above features for analysis, and the corresponding evaluation of the dimension of the student homework with different difficulty scores can be obtained.
Specifically, when the score of the question with a certain difficulty is lower than the score of the corresponding class, the student is prompted to pay attention to the exercise of the question type with the certain difficulty.
In some specific embodiments, specific evaluations of the score case feature dimension for different question types and the score case feature dimension for different difficulty questions can be shown by the presentation of fig. 3 d.
Corresponding to the dimension of the knowledge point mastering situation of the student in 202, the operation knowledge point mastering degree characteristics can be selected for analysis, so that the evaluation of the knowledge point mastering situation is obtained, and the knowledge point with better mastering degree and the knowledge point with poorer mastering degree are prompted.
In some specific embodiments, the overall grasping condition of the knowledge points, better knowledge points (advantages) grasped by the students and worse knowledge points (disadvantages) grasped by the students can be respectively displayed through the display modes of fig. 3e, 3f and 3g, and specific evaluation for the dimension of the grasping condition of the knowledge points of the students can be obtained.
The homework characteristics of the students are obtained through model extraction, the characteristics reflect the completion conditions of the homework of the students, and the characteristics are combined respectively to form multiple dimensions, so that the proper characteristics and dimensions are selected, the student homework analysis is more comprehensive, and the purposeful analysis of the student homework is more convenient.
In some embodiments, for the collection of the student homework information, the on-line version homework can be collected based on character recognition technology to obtain the student homework information, wherein the homework information includes student homework score information, exercise information, difficulty information, question type information, knowledge point information and homework duration information.
The homework score information refers to the score of each topic in the student homework; the exercise information refers to the total number of the questions in the student homework and the score of each question; the difficulty information refers to the difficulty of each subject in the student homework; the question type information refers to the type of each question in the student homework; the knowledge point information refers to knowledge points covered by each exercise in the operation exercises; the work duration information refers to the length of time that the student completes each work.
The collected operation information can be input into the operation information analysis model, namely, score information, exercise information, difficulty information, question type information, knowledge point information and operation duration information are input into the operation information analysis model, so that a plurality of corresponding operation characteristics are extracted. Specifically, according to the homework duration information, the homework timeliness characteristics are obtained through a student homework analysis model; according to the student homework score information, obtaining homework score transverse comparison characteristics and homework score stability characteristics through a student homework analysis model; according to the homework item type information, the difficulty information and the student homework score information, obtaining score condition characteristics aiming at different item type items and score condition characteristics aiming at different difficulty items through a student homework analysis model; and obtaining the mastery characteristics of the exercise knowledge points through a student exercise analysis model according to the exercise information, the knowledge point information and the score information.
Because the homework information of gathering is many-sided, the student's homework characteristic of extracting has more convincing, and the angle is also more diversified, carries out the combination analysis with the student's homework characteristic of multi-angle, can be when the student's homework analysis, and is more comprehensive.
In some embodiments, in order to analyze the job information in more detail, the student job analysis model may be divided into four sub-models, which are a student job aging sub-model, a job fluctuation level characterization sub-model, a correct rate comprehensive evaluation sub-model, and a knowledge point grasping analysis sub-model, and through the four sub-models, score information, problem information, difficulty information, problem model information, knowledge point information, and job duration information may be input to extract a plurality of corresponding job characteristics.
Specifically, based on the student work timeliness sub-model, obtaining work timeliness characteristics according to the work duration information; based on the homework fluctuation level characterization submodel, according to the student homework score information, obtaining a homework score transverse comparison characteristic and a homework score stability characteristic; on the basis of the accuracy comprehensive evaluation submodel, obtaining score condition characteristics aiming at different question type topics and score condition characteristics aiming at different difficulty topics according to the question type information, the difficulty information and the student homework score information; and obtaining the operation knowledge point mastery degree characteristics according to the exercise information, the knowledge point information and the score information based on the knowledge point mastery analysis submodel.
The student work timeliness sub-model is established according to the following formula so as to realize the calculation process of the work timeliness characteristics in the embodiment:
wherein F (T) is the aging characteristic of the student's assignment, β, obtained in the above embodiment 0 、β 1 、β 2 The parameters obtained in the above embodiment are preset parameters
And
the time efficiency characteristic F (T) of the student homework is obtained by inputting the numerical value into the model formula. And the parameters may be modified when the evaluation criteria change.
The operation fluctuation level characterization submodel is established according to the following formula so as to realize the calculation process of the operation score stability characteristics in the embodiment:
wherein F(s) is the job score stability characteristic, β, obtained in the above embodiment 0 、β 1 、β 2 The parameters obtained in the above embodiment are preset parameters
And σ S student The stability characteristics f(s) of the student's homework are obtained in the numerical input model formula (a). And the parameters may be modified when the evaluation criteria change.
The accuracy comprehensive evaluation sub-model is established according to the following formula:
wherein F (si) is the overall accuracy of the operation score, beta 0 、β 1 、β 2 、β 3 、β 4 The parameters obtained in the above embodiment are preset parameters
And
and
the accuracy characteristics F (si), F(s) of the student homework are obtained in the numerical value input model formula. And the parameters may be modified when the evaluation criteria change.
The knowledge point mastering analysis submodel is established according to the following formula so as to realize the calculation process of the operation knowledge point mastering degree characteristics in the embodiment:
wherein, F(KP) is the characteristic of the degree of grasp of the operation knowledge points, β, obtained in the above-described embodiment 0 、β 1 、β 2 The parameters obtained in the above embodiment are preset parameters
And
the value of (2) is input into the model formula to obtain the mastery degree characteristics F (KP) of the student homework knowledge points. And the parameters may be modified when the evaluation criteria change.
Based on different models, the homework characteristics in different aspects can be obtained, the characteristics are combined, the analysis directions of the student homework in different dimensions can be obtained, topics needing important attention and the topics of difficulty can be accurately analyzed, and key knowledge points can be obtained, so that the students can be helped to quickly improve the scores.
In some embodiments, in order to improve the mastery condition of students on homework and better consolidate the knowledge points in homework, the wrong questions can be determined according to the collected homework information, and the wrong question information corresponding to the wrong questions is extracted; retrieving to obtain a variant question corresponding to the wrong question according to the wrong question information; and combining the error question and the variable question corresponding to the error question as a feedback question with the student homework evaluation report to generate a student homework feedback evaluation report.
Firstly, determining wrong questions in the operation according to the operation information, extracting wrong question information in the wrong questions, searching variable questions in an existing question bank according to the wrong question information, and performing fitting calculation according to the difficulty and knowledge points of the wrong question information, wherein the higher the coincidence degree of the difficulty and the knowledge points of the variable questions and the wrong questions is, the higher the fitting degree is, and thus a variable question list ordered according to the fitting degree is obtained; and finally, combining the error questions and the corresponding variable questions into a group of feedback questions, combining the plurality of groups of feedback questions and the student homework evaluation report together, and generating a homework feedback evaluation report for feedback.
In some embodiments, in order to make the difficulty and knowledge point of the error problem more accurate, and thus make the retrieved variation problem more accurate, and thus provide a more accurate feedback problem for students, the text information and picture information in the error problem can be identified by using a character identification technology and a picture identification technology, the problem with the highest similarity to the error problem in the designated database is obtained by using natural semantic analysis and a neural network, and the label attributes of the current problem are corrected according to the label attributes of the problem with the highest similarity, where the label attributes include attributes such as knowledge point, difficulty, subject, section, and the like. Then, the variable questions are searched in the existing question bank according to the wrong question information and the corrected label attribute.
In some scenes, wrong questions and variant questions in the operation feedback evaluation report are classified according to the knowledge points, and the wrong questions and variant questions of the same knowledge point are placed under the same question class, so that the strengthening exercise can be conveniently carried out aiming at the specific knowledge points.
In one implementation, the system may select a plurality of exercises with the highest fitting degree with the wrong exercise from the variable exercise list, and feed the exercises as variable exercises back to the students. In another implementation, the teacher may select a variation question suitable for the current student from the variation question list as a feedback question to feed back to the student. Therefore, the variable form question is provided for students accurately, and the students are helped to master knowledge points in wrong questions.
In other embodiments, the student works with high completion degree and high completion quality without wrong questions, and the system or the teacher selects the questions to be promoted as the student's exercise for consolidating the knowledge points. Similarly, the quality improvement questions are combined with the student homework evaluation report to generate a homework feedback evaluation report which is fed back to the students, so that the purpose of helping the students improve the quality is achieved.
The method collects the wrong question information of the students, retrieves the related variable questions, and puts the variable questions into the student homework evaluation report, thereby providing a way for the students to correct the wrong questions and consolidate the knowledge points.
In order to make the effect of the feedback questions better, in some embodiments, the collected exercise information may include, in addition to the exercise questions in the evaluation period, the feedback questions in the student exercise feedback evaluation report corresponding to the previous evaluation period. The collection mode and evaluation mode of the feedback questions are consistent with the implementation mode of the signing embodiment, and the details are not repeated here.
The method has the advantages that wrong questions of the students are collected and corrected again and analyzed, a way for consolidating knowledge is provided for the students, and teachers are helped to know error prone points and difficulty points in student homework.
In some embodiments, in order to make evaluation of students more comprehensive, four preset dimensions may be selected to evaluate the student homework, specifically, based on an OCR character recognition technology, collecting homework information from on-line versions of student homework, inputting student homework score information, exercise information, difficulty information, question type information, knowledge point information, and homework duration information into the homework information analysis model, extracting a plurality of corresponding homework features, and for each preset dimension, selecting at least one homework feature corresponding to the preset dimension from the plurality of homework features; and combining the selected at least one homework characteristic to obtain an evaluation corresponding to the preset dimension, and generating a student homework evaluation report by using the evaluation.
Therefore, the evaluation of the student homework can be more comprehensive and convincing.
Fig. 4 is a schematic structural diagram of an evaluation apparatus for student's activities according to an embodiment of the present application, and as shown in fig. 4, the evaluation apparatus 400 for student's activities according to the present embodiment includes: an information acquisition module 401, a model analysis module 402, and a report generation module 403.
The information acquisition module 401 is used for acquiring the homework information of students;
the model analysis module 402 is used for analyzing the preset dimensionality of the student homework based on a pre-constructed homework information analysis model and the homework information;
a report generation module 403, configured to generate a student assignment evaluation report according to the result of student assignment analysis;
wherein the preset dimensions comprise at least two of the following dimensions:
the student work efficiency, the student work stability, the different problem types of student work score condition, the different degree of difficulty score condition of student work, student knowledge point master condition.
Optionally, the information acquisition module 401 is specifically configured to:
extracting a plurality of corresponding operation characteristics based on a pre-constructed operation information analysis model and the operation information;
selecting at least one operation feature corresponding to each preset dimension from the plurality of operation features for each preset dimension; and combining the selected at least one operation characteristic to obtain the evaluation corresponding to the preset dimension.
Optionally, the information collecting module 401 is specifically configured to:
based on a character recognition technology, information acquisition is carried out on homework of the online version to obtain homework information of students; the homework information comprises student homework score information, exercise information, difficulty information, question type information, knowledge point information and homework duration information; the model analysis module 402 is specifically configured to, when extracting a plurality of corresponding job features based on a pre-constructed job information analysis model and the job information:
based on a pre-constructed homework information analysis model, student homework score information, exercise information, difficulty information, question type information, knowledge point information and homework duration information are input into the homework information analysis model, and a plurality of corresponding homework characteristics are extracted.
Optionally, the job information analysis model includes:
the student homework time effect submodel, the homework fluctuation level characterization submodel, the accuracy comprehensive evaluation submodel and the knowledge point grasping analysis submodel are combined;
the model analysis module 402 is based on a pre-constructed homework information analysis model, and is specifically used for inputting student homework score information, exercise question information, difficulty information, question type information, knowledge point information and homework duration information into the model and extracting a plurality of corresponding homework characteristics:
based on the student work timeliness sub-model, obtaining work timeliness characteristics according to the work duration information;
based on the homework fluctuation level characterization submodel, obtaining a homework score transverse comparison characteristic and a homework score stability characteristic according to the student homework score information;
on the basis of the accuracy comprehensive evaluation submodel, obtaining score condition characteristics aiming at different question type topics and score condition characteristics aiming at different difficulty topics according to the question type information, the difficulty information and the student homework score information;
and acquiring the operation knowledge point mastery degree characteristics according to the exercise information, the knowledge point information and the score information based on the knowledge point mastery analysis submodel.
Optionally, the apparatus further includes a feedback question retrieving module 404, specifically configured to:
determining a wrong question according to the collected operation information, and extracting wrong question information corresponding to the wrong question;
retrieving to obtain a variant question corresponding to the wrong question according to the wrong question information;
and combining the error question and the variable question corresponding to the error question as a feedback question with the student homework evaluation report to generate a student homework feedback evaluation report.
Optionally, the exercise information includes:
the homework questions in the evaluation period and the feedback questions in the student homework feedback evaluation report corresponding to the previous evaluation period.
The apparatus of this embodiment may be configured to perform the method of any of the above embodiments, and the implementation principle and the technical effect are similar, which are not described herein again.
The application provides another student's homework's evaluation device includes:
the information acquisition module is used for acquiring the homework information of students;
the model analysis module is used for analyzing the preset dimensionality of the student homework based on a pre-constructed homework information analysis model and the homework information;
the report generation module is used for generating a student homework evaluation report according to the result of student homework analysis;
the preset dimensionality comprises student work efficiency, student work stability, the scoring conditions of different question types of student work, the scoring conditions of different difficulty of student work and the mastering conditions of student knowledge points.
The apparatus of this embodiment may be configured to perform the method of any of the above embodiments, and the implementation principle and the technical effect are similar, which are not described herein again.
Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application, and as shown in fig. 5, an electronic device 500 according to the embodiment may include: a memory 501 and a processor 502.
The memory 501 has stored thereon a computer program that can be loaded by the processor 502 and executed to perform the method in the above-described embodiments.
The processor 502 is coupled to the memory 501, such as via a bus.
Optionally, the electronic device 500 may also include a transceiver. It should be noted that the transceiver in practical application is not limited to one, and the structure of the electronic device 500 is not limited to the embodiment of the present application.
The Processor 502 may be a CPU (Central Processing Unit), a general purpose Processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other Programmable logic device, transistor logic, hardware components, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. The processor 502 may also be a combination of computing functions, e.g., comprising one or more microprocessors, DSPs, and microprocessors, among others.
A bus may include a path that transfers information between the above components. The bus may be a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus.
The Memory 501 may be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical Disc storage, optical Disc storage (including Compact Disc, laser Disc, optical Disc, digital versatile Disc, blu-ray Disc, etc.), a magnetic Disc storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to these.
The memory 501 is used for storing application program codes for executing the scheme of the application, and the processor 502 is used for controlling the execution. The processor 502 is used to execute the memory 501
501 to implement what is shown in the foregoing method embodiments.
Among them, electronic devices include but are not limited to: mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like. But also a server, etc. The electronic device shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
The electronic device of this embodiment may be configured to perform the method of any of the above embodiments, and the implementation principle and the technical effect are similar, which are not described herein again.
The electronic device of this embodiment may specifically be the server described above, or other electronic devices with computing capabilities (e.g., a computer, a smart phone, a tablet computer, etc.).
The present application also provides a computer readable storage medium storing a computer program that can be loaded by a processor and executed to perform the method as in the above embodiments.
Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Claims (10)
1. A student work evaluation method is characterized by comprising the following steps:
collecting the homework information of students;
analyzing the preset dimensionality of the student homework based on a pre-constructed homework information analysis model and the homework information;
generating a student homework evaluation report according to the result of student homework analysis;
wherein the preset dimensions comprise at least two of the following dimensions:
the student homework efficiency, the student homework stability, the different question types of student homework score condition, the different degree of difficulty score condition of student homework, student knowledge point master condition.
2. The method of claim 1, wherein the analysis of the student's homework in a preset dimension based on the pre-constructed homework information analysis model and the homework information comprises:
extracting a plurality of corresponding operation characteristics based on a pre-constructed operation information analysis model and the operation information;
selecting at least one operation feature corresponding to each preset dimension from the plurality of operation features for each preset dimension;
and combining the at least one selected operation characteristic to obtain the evaluation corresponding to the preset dimension.
3. The method of claim 2, wherein collecting student work information comprises:
based on a character recognition technology, information acquisition is carried out on homework of the online version to obtain homework information of students; the homework information comprises student homework score information, exercise information, difficulty information, question type information, knowledge point information and homework duration information;
the method for extracting a plurality of corresponding operation characteristics based on the operation information analysis model constructed in advance and the operation information comprises the following steps:
based on a pre-constructed homework information analysis model, student homework score information, exercise information, difficulty information, question type information, knowledge point information and homework duration information are input into the homework information analysis model, and a plurality of corresponding homework characteristics are extracted.
4. The method of claim 3, wherein the job information analysis model comprises:
the student homework time effect submodel, the homework fluctuation level characterization submodel, the accuracy comprehensive evaluation submodel and the knowledge point grasping analysis submodel are combined;
based on the homework information analysis model which is constructed in advance, student homework score information, exercise information, difficulty information, question type information, knowledge point information and homework duration information are input into the model, and a plurality of corresponding homework characteristics are extracted, wherein the method comprises the following steps:
based on the student homework timeliness submodel, obtaining homework timeliness characteristics according to the homework duration information;
based on the homework fluctuation level characterization submodel, according to the student homework score information, obtaining a homework score transverse comparison characteristic and a homework score stability characteristic;
on the basis of the accuracy comprehensive evaluation submodel, obtaining score condition characteristics aiming at different question type topics and score condition characteristics aiming at different difficulty topics according to the question type information, the difficulty information and the student homework score information;
and obtaining the operation knowledge point mastery degree characteristics according to the exercise information, the knowledge point information and the score information based on the knowledge point mastery analysis submodel.
5. The method of claim 3, further comprising:
determining a wrong question according to the collected operation information, and extracting wrong question information corresponding to the wrong question;
retrieving to obtain a variant question corresponding to the wrong question according to the wrong question information;
and combining the error question and the variable question corresponding to the error question as a feedback question with the student homework evaluation report to generate a student homework feedback evaluation report.
6. The method of claim 5, wherein the problem information comprises:
the homework questions in the evaluation period and the feedback questions in the student homework feedback evaluation report corresponding to the previous evaluation period.
7. A student work evaluation method is characterized by comprising the following steps:
collecting the homework information of students;
analyzing the preset dimensionality of the student homework based on a pre-constructed homework information analysis model and the homework information;
generating a student homework evaluation report according to the result of student homework analysis;
the preset dimensionality comprises student work efficiency, student work stability, the scoring conditions of different question types of student work, the scoring conditions of different difficulty of student work and the mastering conditions of student knowledge points.
8. An evaluation device for student's work, comprising:
the information acquisition module is used for acquiring the homework information of students;
the model analysis module is used for analyzing the preset dimensionality of the student homework based on a pre-constructed homework information analysis model and the homework information;
the report generation module is used for generating a student homework evaluation report according to the result of student homework analysis;
wherein the preset dimensions comprise at least two of the following dimensions:
the student work efficiency, the student work stability, the different problem types of student work score condition, the different degree of difficulty score condition of student work, student knowledge point master condition.
9. An electronic device, comprising: memory and processor, the memory having stored thereon a computer program which can be loaded by the processor and which performs the method of any of claims 1 to 7.
10. A computer-readable storage medium, in which a computer program is stored which can be loaded by a processor and which executes the method of any one of claims 1 to 7.
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