阅读说明：本技术 一种教学辅导管理系统 (Teaching guidance management system ) 是由 许宇翔 于 2021-07-27 设计创作，主要内容包括：本发明公开了一种应用数学教学管理系统,包括教师教学模块,选择学习行为分析模块给出的点名名单的学生进行教学互动,学生学习模块用于完成与教师教学模块的教学互动,学生通过专属账号登录,接收教师教学模块课件,完成并提交课堂作业；课堂作业分配模块向学生学生学习模块发送随机生成的课堂作业,所述课堂作业由两种方式生成,收取学生学习模块提交课堂作业,批改并得出学生的课堂作业成绩；学习行为分析模块利用内置点名方法对学生课堂成绩成绩分析,生成课堂互动名单发送教师教学模块。本发明作业分析过程引入数绩点因子量化学生对知识的吸收程度,根据学生的学习特点配置不同的优质教学资源,实施个性化教学。(The invention discloses an applied mathematics teaching management system, which comprises a teacher teaching module, wherein students in a roll-call list given by a learning behavior analysis module are selected to perform teaching interaction, the student learning module is used for completing the teaching interaction with the teacher teaching module, and the students log in through a special account number, receive courseware of the teacher teaching module, complete and submit classroom homework; the classroom work distribution module sends classroom work generated randomly to the student learning module, the classroom work is generated by two modes, the student learning module is collected to submit classroom work, and the classroom work score of the student is obtained through correction; the learning behavior analysis module analyzes the class achievements of the students by using a built-in roll call method, generates a class interaction list and sends the list to the teacher teaching module. The invention introduces a performance factor in the homework analysis process to quantify the absorption degree of the students to the knowledge, configures different high-quality teaching resources according to the learning characteristics of the students and implements personalized teaching.)

1. An applied mathematics teaching management system, characterized by comprising:

the teacher teaching module is used for the teacher to carry out classroom interaction, checking the results of the students in classroom operation, receiving a report of the absorption degree of the students on classroom teaching contents analyzed by the learning behavior analysis module, and selecting the students in the roll name list given by the learning behavior analysis module to carry out teaching interaction;

the student learning module is used for completing teaching interaction with the teacher teaching module, and students log in through a special account, receive courseware of the teacher teaching module, complete and submit classroom homework;

the classroom work distribution module sends randomly generated classroom work to the student learning module, the classroom work is generated in two ways, and the teacher teaching module prepares in advance; the classroom work distribution module is generated by searching from the Internet according to the teaching content in the teacher teaching module, collects the classroom work submitted by the student learning module, corrects the classroom work and obtains the classroom work score of the student;

and the learning behavior analysis module acquires the class scores of the students from the classroom assignment module, analyzes the class scores of the students by using a built-in roll call method, generates a class interaction list and sends the list to the teacher teaching module.

2. The applied mathematics teaching management system of claim 1, wherein said learning behavior analysis module built-in roll calling method comprises the following steps:

step 1, obtaining system login records from a person logging in a system, and generating an original data set N by using the system login records, wherein the original data set N comprises N elements, and the information contained in each element comprises student names, job scores and performance point factors w;

N＝{m₁,m₂,m₃……m_n} (1)

step 2, carrying out first random roll calling, and if not, carrying out step 3;

step 3, after the first roll call, extracting the characteristics of the original data set N obtained in the step 1, wherein the extracted characteristics are the names of students and performance point factors W, and obtaining a performance point data set W;

step 4, screening the performance point data set W obtained in the step 3 to obtain a questioning list;

and 5, eliminating students of the questioning list by students of the performance point data set W, and screening the rest students of the performance point data set W to obtain an instructive list.

3. The applied mathematics teaching management system of claim 2, wherein said step 2 includes the following steps:

step 2.1, extracting characteristics of the original data set N obtained in the step 1, wherein the extracted characteristics are homework scores and student names, and obtaining a homework score data set Q;

2.2, screening the work result data set Q obtained in the step 2.1, and forming screened elements to obtain a first roll call data set P;

and 2.3, extracting the characteristics of the roll call data set P in the step 2.2, wherein the extracted characteristics are the names of students, obtaining a first roll call list, and roll calling according to the first roll call list.

4. A applied mathematics teaching management system according to claim 3, characterized in that the condition of step 2.2 screening is that the value of the job performance of a single element of the performance data set Q is less than the average value of the job performance of all elements.

5. The applied mathematics teaching management system of claim 4 wherein said performance factor w is calculated as follows:

in the formula (2), M is the total number of questions, M is the correct number of questions, and T is the predetermined job completion time. And t is the actual completion time of the student.

6. The applied mathematics teaching management system of claim 5, wherein said step 4 includes the following steps:

step 4.1, calculate the total performance factor W of the elements in the performance data set W_iThe calculation formula is as follows:

step 4.2, elements of the performance data set W are according to the total performance factor W_iAnd (4) carrying out feature extraction after the values are arranged in a descending order, wherein the extracted features are the names of students, and the generated list takes the front n bits to form a question list.

7. The applied mathematics teaching management system of claim 6, wherein said step 5 includes the following steps:

step 5.1, removing students from the questioning list, and setting the counseling weight Z of the students, wherein the initial value of Z is alpha;

step 5.2, if the performance factor w of the students in the previous class does not reach the average value of the whole classThen Z ═ α + 0.5;

step 5.3, the performance factor w of the student in the same chapter reaches the full class average value for the third timeThen Z is alpha- (beta-2) multiplied by 0.3, beta is more than or equal to 3, and beta is the number of times of class;

step 5.4, aiming at the student Z, when the accuracy of the single classroom test reaches 75% and exceeds the specified time, is alpha- (beta-2) multiplied by 0.1+0.4 gamma, beta is more than or equal to 3, and gamma is the overtime frequency of the submitted work of the student in the same chapter;

and 5.5, arranging the numbers corresponding to the rest students according to the guidance weight Z in a descending order, extracting features, wherein the extracted features are the names of the students, and the top m bits of the generated list form a guidance list.

Technical Field

The invention belongs to the technical field of courseware tutoring and relates to a teaching tutoring management system.

Background

The teaching system is a movable system for teachers and students to participate together and aims at achieving teaching targets. The teaching system is composed of teaching personnel (teachers and students), teaching information (software compiled in various forms), teaching materials and equipment (teaching hardware in various forms). The system comprises three subsystems of control, execution and feedback. The control system determines the motion direction and the work content of the whole system and adjusts the work of other subsystems. The teacher plays a main role in control and implementation.

The teaching system used in colleges and universities has the function of replacing a blackboard and utilizing computer programs for teaching, but the teaching system does not play a role in improving the teaching quality, so that colleges need to be concerned with and educate students who cannot master learning knowledge by analyzing the classroom knowledge and judging the absorption degree according to the results of classroom work.

Disclosure of Invention

The invention aims to provide a teaching guidance management system which has the characteristics of quantifying the classroom learning condition of students and being capable of guiding the students to learn in a targeted manner.

The technical scheme adopted by the invention is that a teaching guidance management system comprises:

the teacher teaching module is used for the teacher to carry out classroom interaction, checking the results of the students in classroom operation, receiving a report of the absorption degree of the students on classroom teaching contents analyzed by the learning behavior analysis module, and selecting the students in the roll name list given by the learning behavior analysis module to carry out teaching interaction;

the student learning module is used for completing teaching interaction with the teacher teaching module, and students log in through a special account, receive courseware of the teacher teaching module, complete and submit classroom homework;

the classroom work distribution module sends randomly generated classroom work to the student learning module, the classroom work is generated in two ways, and the teacher teaching module prepares in advance; the classroom work distribution module is generated by searching from the Internet according to the teaching content in the teacher teaching module, collects the classroom work submitted by the student learning module, corrects the classroom work and obtains the classroom work score of the student;

and the learning behavior analysis module acquires the class scores of the students from the classroom assignment module, analyzes the class scores of the students by using a built-in roll call method, generates a class interaction list and sends the list to the teacher teaching module.

The invention is also characterized in that:

the roll call method with the built-in learning behavior analysis module comprises the following steps:

step 1, obtaining system login records from a person logging in a system, and generating an original data set N by using the system login records, wherein the original data set N comprises N elements, and the information contained in each element comprises student names, job scores and performance point factors w;

N＝{m₁,m₂,m₃……m_n} (1)

step 2, carrying out first random roll calling, and if not, carrying out step 3;

step 3, after the first roll call, extracting the characteristics of the original data set N obtained in the step 1, wherein the extracted characteristics are the names of students and performance point factors W, and obtaining a performance point data set W;

and 4, screening the performance point data set W obtained in the step 3 to obtain a questioning list.

The step 2 comprises the following steps:

step 2.1, extracting characteristics of the original data set N obtained in the step 1, wherein the extracted characteristics are homework scores and student names, and obtaining a homework score data set Q;

2.2, screening the work result data set Q obtained in the step 2.1, and forming screened elements to obtain a first roll call data set P;

step 2.3, extracting the features of the roll call data set P in the step 2.2, wherein the extracted features are student names to obtain a first roll call list, and roll calls according to the first roll call list;

the condition of the step 2.2 screening is that the value of the job achievement of a single element in the achievement data set Q is smaller than the average value of the job achievements of all elements.

5. The applied mathematics teaching management system of claim 1 wherein said performance factor w is calculated as follows:

in the formula (2), M is the total number of questions, M is the correct number of questions, and T is the predetermined job completion time. t is the actual completion time of the student,

step 4 comprises the following steps:

step 4.1, calculate the total performance factor W of the elements in the performance data set W_iThe calculation formula is as follows:

step 4.2, elements of the performance data set W are according to the total performance factor W_iAnd (4) carrying out feature extraction after the values are arranged in a descending order, wherein the extracted features are the names of students, and the generated list takes the front n bits to form a question list.

Step 5 comprises the following steps:

step 5.1, removing students from the questioning list, and setting the counseling weight Z of the students, wherein the initial value of Z is alpha;

step 5.2, if the performance factor w of the students in the previous class does not reach the average value of the whole classThen Z ═ α + 0.5;

step 5.3, the performance factor w of the student in the same chapter reaches the full class average value for the third timeThen Z is alpha- (beta-2) multiplied by 0.3, beta is more than or equal to 3, and beta is the number of times of class;

step 5.4, aiming at the student Z, when the accuracy of the single classroom test reaches 75% and exceeds the specified time, is alpha- (beta-2) multiplied by 0.1+0.4 gamma, beta is more than or equal to 3, and gamma is the overtime frequency of the submitted work of the student in the same chapter;

and 5.5, arranging the numbers corresponding to the rest students according to the guidance weight Z in a descending order, extracting features, wherein the extracted features are the names of the students, and the top m bits of the generated list form a guidance list.

The invention has the beneficial effects that:

1. the learning behavior analysis module is combined with the classroom work distribution module, and each class tracks the learning condition of students in the class, so that a teacher can focus on the students with poor learning effect in subsequent classes.

2. And (4) introducing a digital performance point factor to quantify the absorption degree of the students to the knowledge, configuring different high-quality teaching resources according to the learning characteristics of the students, and implementing personalized teaching.

Drawings

FIG. 1 is a schematic diagram of a tutorial management system of the present invention;

fig. 2 is a schematic flow chart of a tutoring management system according to the present invention.

Detailed Description

The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

A tutoring management system, as shown in fig. 1, comprising:

the teacher teaching module is used for the teacher to carry out classroom interaction, checking the results of the students in classroom operation, receiving a report of the absorption degree of the students on classroom teaching contents analyzed by the learning behavior analysis module, and selecting the students in the roll name list given by the learning behavior analysis module to carry out teaching interaction;

the student learning module is used for completing teaching interaction with the teacher teaching module, and students log in through a special account, receive courseware of the teacher teaching module, complete and submit classroom homework;

the classroom work distribution module sends randomly generated classroom work to the student learning module, the classroom work is generated in two ways, and the teacher teaching module prepares in advance; the classroom work distribution module is generated by searching from the Internet according to the teaching content in the teacher teaching module, collects the classroom work submitted by the student learning module, corrects the classroom work and obtains the classroom work score of the student;

and the learning behavior analysis module acquires the class scores of the students from the classroom assignment module, analyzes the class scores of the students by using a built-in roll call method, generates a class interaction list and sends the list to the teacher teaching module.

As shown in fig. 2, the roll call method built in the learning behavior analysis module includes the following steps:

step 1, obtaining system login records from a person logging in a system, and generating an original data set N by using the system login records, wherein the original data set N comprises N elements, and the information contained in each element comprises student names, job scores and performance point factors w;

N＝{m₁,m₂,m₃……m_n} (1)

step 2, carrying out first random roll calling, and if not, carrying out step 3;

step 3, after the first roll call, extracting the characteristics of the original data set N obtained in the step 1, wherein the extracted characteristics are the names of students and performance point factors W, and obtaining a performance point data set W;

and 4, screening the performance point data set W obtained in the step 3 to obtain a questioning list.

The step 2 comprises the following steps:

step 2.1, extracting characteristics of the original data set N obtained in the step 1, wherein the extracted characteristics are homework scores and student names, and obtaining a homework score data set Q;

2.2, screening the work result data set Q obtained in the step 2.1, and forming screened elements to obtain a first roll call data set P;

step 2.3, extracting the features of the roll call data set P in the step 2.2, wherein the extracted features are student names to obtain a first roll call list, and roll calls according to the first roll call list;

the condition of the step 2.2 screening is that the value of the job achievement of a single element in the achievement data set Q is smaller than the average value of the job achievements of all elements.

The performance factor w is calculated as follows:

in the formula (2), M is the total number of questions, M is the correct number of questions, and T is the predetermined job completion time. t is the actual completion time of the student,

step 4 comprises the following steps:

step 4.1, calculate the total performance factor W of the elements in the performance data set W_iThe calculation formula is as follows:

step 4.2, elements of the performance data set W are according to the total performance factor W_iAnd (4) carrying out feature extraction after the values are arranged in a descending order, wherein the extracted features are the names of students, and the generated list takes the front n bits to form a question list.

Step 5 comprises the following steps:

step 5.1, removing students from the questioning list, and setting the counseling weight Z of the students, wherein the initial value of Z is alpha;

step 5.2, if the performance factor w of the students in the previous class does not reach the average value of the whole classThen Z ═ α + 0.5;

step 5.3, the performance factor w of the student in the same chapter reaches the full class average value for the third timeThen Z is alpha- (beta-2) multiplied by 0.3, beta is more than or equal to 3, and beta is the number of times of class;

step 5.4, aiming at the student Z, when the accuracy of the single classroom test reaches 75% and exceeds the specified time, is alpha- (beta-2) multiplied by 0.1+0.4 gamma, beta is more than or equal to 3, and gamma is the overtime frequency of the submitted work of the student in the same chapter;

and 5.5, arranging the numbers corresponding to the rest students according to the guidance weight Z in a descending order, extracting features, wherein the extracted features are the names of the students, and the top m bits of the generated list form a guidance list.

The invention discloses an applied mathematics teaching management system, which has the advantages that: the learning behavior analysis module is combined with the classroom work distribution module, and each class tracks the learning condition of students in the class, so that a teacher can focus on the students with poor learning effect in subsequent classes. The homework analysis process introduces a performance factor to quantify the absorption degree of the students to the knowledge, and configures different high-quality teaching resources according to the learning characteristics of the students to implement personalized teaching. The maximum utilization of education resources is realized, and the problem that the teaching quality is neglected due to too many students in a university classroom is avoided.