CN111708968A - Message reminding autonomous sending method and system in teaching management platform - Google Patents
Message reminding autonomous sending method and system in teaching management platform Download PDFInfo
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Abstract
The invention provides an autonomous message reminding sending method and system in a teaching management platform, wherein the method comprises the following steps: acquiring a task scene type, a task creating time and corresponding task parameters created by a teacher; under an examination scene, determining examination notification time according to task creation time, determining a message reminding object and time according to a task submission state and corresponding task parameters, and sending an examination notification, an examination advance notice and an examination submission reminding to the message reminding object; in the operation scene, determining operation notification time according to task creation time, determining a message reminding object according to a task submitting state, extracting operation attribute characteristics, determining operation difficulty degree by using a random forest algorithm, determining operation submission reminding time according to the operation difficulty degree, and sending an operation notification and an operation submission reminder to the message reminding object. The invention simultaneously considers two application scenes of online examination and homework, and avoids 'one-time cutting' of message reminding.
Description
Technical Field
The invention relates to the field of online teaching management, in particular to an autonomous message sending method and system in a teaching management platform.
Background
The more fields that come into widespread use of the internet, the educational field is no exception. In the field of education, teaching management is very important, the learning effect of students is the main basis for judging whether the teaching management is successful, and the monitoring of the learning process is the premise for ensuring the learning effect. In the learning process, homework and examination are the basis which can reflect the learning effect of students most, and the data of the two parts can be mastered to help teaching management to check defects and repair leakage. At the present stage, more and more teaching tasks are performed on the internet, so that the homework and the examination are performed, artificial field monitoring is lacked, and how to realize online monitoring becomes a difficult problem in an online teaching management platform.
The online management in the existing teaching management platform basically uses the traditional teaching mode continuously, a teacher or a executive is supervised to make a call, and a QQ or WeChat man-made management student completes an operation or an examination in time, and a very reasonable online monitoring method is not provided, so that the heavy workload of the teacher or the executive is caused, and the workload is mainly used for contacting and reminding the student to take an examination or complete the operation in time, so that if a method for autonomously sending an operation or examination message reminding in the platform can be designed, the working efficiency of the teaching management can be greatly improved.
The existing message reminding method in teaching management has the following problems: the considered automatic sending scenes of the message reminding are few, the flexibility is poor, for example, the scenes are examinations or homework in courses, the message reminding time of different scenes is different, and two extremes of untimely message reminding or excessive message can occur if all the scenes are switched; secondly, a message reminding function is not arranged in a plurality of online education platforms, so that the online education platforms are not beneficial to teaching management, because of the profound influence of a traditional teaching mode, a plurality of students still rely on-site supervision and study by teachers, which is not beneficial to training the autonomous learning ability of the students, and in the Internet education mode, the on-site supervision and study function of the teachers is weakened, the students can be supervised and promoted online, and the awareness of autonomous study of the students is trained.
Disclosure of Invention
In view of the above, the invention provides an autonomous message reminding sending method and device for online work or examination in a teaching management platform, which are used for solving the extreme situations that message reminding is not timely or too much in the existing teaching management platform.
In a first aspect of the present invention, an autonomous sending method for message alerts in a teaching management platform is provided, where the method includes:
s1, acquiring a task scene type, task creation time and corresponding task parameters created by a teacher, and monitoring the task submission state of students in real time, wherein the task scene type comprises an examination scene and an operation scene;
s2, under an examination scene, determining examination notification time according to task creation time, determining a message reminding object according to a task submission state, determining examination advance notice and examination submission reminding time according to corresponding task parameters, determining the specific content of message reminding according to the type of the task scene and the message reminding time, and sending the examination notification, the examination advance notice and the examination submission reminding to the message reminding object;
s3, under the operation scene, determining operation notification time according to the task creating time, determining a message reminding object according to the task submitting state, extracting operation attribute characteristics, determining operation difficulty degree by using a random forest algorithm, determining operation submitting reminding time according to the operation difficulty degree, and sending operation notification and operation submitting reminding to the message reminding object.
Preferably, in an examination scene, the corresponding task parameters include examination questions, examination start time, examination end time and examination duration; in a job scenario, the corresponding task parameters include a job title, job content, and submission time.
Preferably, the step S2 specifically includes:
taking the time for creating the examination as examination notification time, issuing examination notification information to each student needing to take the examination, wherein the specific content of the message prompt is the question, the starting time, the ending time and the examination duration of the examination;
acquiring the starting time of the examination and setting the duration t0If starttime-t0The examination forecast information is released to each student needing to take the examination later than the examination creating time;
and acquiring the task submission state of each student before the examination ending time, wherein the object for reminding the examination submission is the student who does not submit the examination, and the reminding time of the examination submission is duration 15 minutes before the examination ending time.
Preferably, the step S3 specifically includes:
when the homework is created, a homework notice is issued to each student, and the notice content is a homework title, homework content and submission time;
acquiring the task submission state of each student before the job submission time, wherein the object of job submission reminding is the student who does not submit the job; determining the difficulty level value of the operation, wherein the time for reminding the operation submission is 30 minutes before the time for submitting the operation;
the method for determining the difficulty level value of the operation comprises the following steps: dividing the difficulty level of the operation into three difficulty levels of difficulty, medium difficulty and easy difficulty level, taking the corresponding level values as 3, 2 and 1, and extracting operation attribute characteristics, wherein the attribute characteristics comprise the number X of knowledge points contained in the operation1The duration X of the video resource of the chapter corresponding to the operation2Average result of previous work X3Class X of students4Chapter importance X5(ii) a And sequentially using the five attribute characteristics as root nodes of the decision tree to construct a decision tree, carrying out decision tree judgment on the five attribute characteristics by each student, obtaining 5 decision results through five rounds of decision tree judgment, and obtaining a result with the highest ticket number, namely the value of the difficulty level.
Preferably, in step S4, the constructing a decision tree by sequentially using the five attribute features as root nodes of the decision tree specifically includes:
① first use knowledge point number X1As the root node of the decision tree, the judgment is based on the following:
when X is present1>When 5, continue to judge the chapter importanceDegree X5If the chapter is important, the difficulty level is difficult, the chapter is general or not important, and the difficulty level is middle;
when X is more than or equal to 31When the number of the students is less than or equal to 5, continuously judging the class X of the students4If the student category is the president, the difficulty level is middle, and if the student category is the special promotion or the president, the difficulty level is easy;
when X is present1<When the number of the jobs is 3, the average score X of the last job is continuously judged3If X is3More than or equal to 60 points, the difficulty is middle, if X is3<60 minutes, the difficulty is easy, ② the time length X of using the video resource corresponding to the chapter for the second time2As the root node of the decision tree, the judgment is based on the following:
when X is present2>At 20 minutes, the chapter importance level X is continuously judged5If the chapter is important, the difficulty level is difficult, the chapter is general or not important, and the difficulty level is middle;
when X is more than or equal to 102When the time is less than or equal to 20 minutes, continuously judging the class X of the student4If the student category is the president, the difficulty level is middle, and if the student category is the special promotion or the president, the difficulty level is easy;
when X is present2<When 10 minutes, the number X of the knowledge points contained in the homework or the examination is continuously judged1If X is1More than or equal to 3, the difficulty is medium, X1<3, the difficulty is easy;
③ average score X of the last operation used for the third time3As the root node of the decision tree, the judgment is based on the following:
when X is present3>At 80 minutes, continuously judging the class X of the student4If the student category is the president, the difficulty level is difficult, and if the student category is the special promotion or the president, the difficulty level is medium;
when X is more than or equal to 603When the degree of importance X of the chapters is less than or equal to 80, continuing to judge the degree of importance X of the chapters5If the chapter is important, the difficulty level is middle, the chapter is general or not important, and the difficulty level is easy;
when X is present3<At 60, the knowledge contained in the current homework or examination is continuously judgedNumber of dots X1If X is1More than or equal to 3, the difficulty is medium, X1<3, the difficulty is easy;
④ fourth use student class X4As the root node of the decision tree, the judgment is based on the following:
when the student category is the student, continuously judging the chapter importance degree X5If the chapter is important, the difficulty level is difficult, the chapter is general or not important, and the difficulty level is middle;
when the class of the student is the special notebook, continuously judging the duration X of the video resource2If X is2More than or equal to 10 minutes, the difficulty is medium, X2<The difficulty level is easy within 10 minutes;
when the class of the student is a specialist student, the number X of the knowledge points contained in the homework or the examination is continuously judged1If X is1More than or equal to 3, the difficulty is medium, X1<3, the difficulty is easy;
⑤ fifth use chapter importance X5As the root node of the decision tree, the judgment is based on the following:
when the chapter importance degree is important, the student category X is continuously judged4If the student category is the president, the difficulty level is difficult, and if the student category is the special promotion or the president, the difficulty level is medium;
when the chapter importance degree is general, continuously judging the number X of the knowledge points contained in the current homework or examination1If X is1More than or equal to 3, the difficulty is medium, X1<3, the difficulty is easy;
when the chapter importance degree is unimportant, continuously judging the duration X of the video resource2If X is2More than or equal to 10 minutes, the difficulty is medium, X2<The hardness is easy within 10 minutes.
In a second aspect of the present invention, an autonomous sending system for message alerts in a teaching management platform is provided, where the system includes:
a parameter acquisition module: the system comprises a task management system, a task management system and a task management system, wherein the task management system is used for acquiring a task scene type, task creation time and corresponding task parameters created by a teacher and monitoring the task submission state of students in real time, and the task scene type comprises an examination scene and an operation scene;
the examination reminding module comprises: the system comprises a task creating module, a processing module and a display module, wherein the task creating module is used for creating task time according to the task creating module; determining a message reminding object according to the task submission state, determining examination advance notice and examination submission reminding time according to corresponding task parameters, determining specific content of the message reminding according to the task scene type and the message reminding time, and sending the examination advance notice and the examination submission reminding to the message reminding object;
operation reminding module: the system comprises a task creating module, a task setting module and a task sending module, wherein the task creating module is used for creating task time according to the task creating time; determining a message reminding object according to the task submitting state, extracting the attribute characteristics of the operation, sequentially using the attribute characteristics as root nodes of the decision tree to construct the decision tree, determining the difficulty level of the operation by using a random forest algorithm, determining the time of the job submitting reminding according to the difficulty level of the operation, and sending the job submitting reminding to the message reminding object.
Compared with the prior art, the invention has the following beneficial effects:
(1) and automatically evaluating the difficulty degree of the homework by adopting a random forest algorithm, and further carrying out homework submission reminding at different times according to different difficulty degrees of the homework, so that the actual requirements of students are fully considered.
(2) The online examination and homework application scenes are considered at the same time, and the 'one-time' message reminding is avoided, so that the situation that the message reminding is not timely or too much is reasonably avoided, the pertinence is stronger, a plurality of parameters are considered, and the online examination and homework application method is flexibly applied to different teaching scenes;
(3) the dependence on thought caused by artificial supervision is reduced, and the mode of on-line message reminding self-service sending enables students to learn to check messages in time and complete tasks, so that the independent learning consciousness of the students is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of an autonomous sending method for message alerts in a teaching management platform according to an embodiment of the present invention;
fig. 2 is a flow chart of autonomous sending of a message alert in an examination scenario according to an embodiment of the present invention;
fig. 3 is a flow chart of autonomous sending of a message alert in an operation scenario according to an embodiment of the present invention;
FIG. 4 shows the number X of knowledge points used according to the embodiment of the present invention1As a root node decision tree graph;
FIG. 5 shows a time length X of a video resource corresponding to a chapter2A decision tree graph as a root node;
FIG. 6 shows the average result X of the last operation according to the embodiment of the present invention3As a root node decision tree graph;
FIG. 7 is a usage student category X provided by an embodiment of the invention4A point decision tree graph as a root node;
FIG. 8 is a graph of usage chapter importance X according to an embodiment of the present invention5As a decision tree graph for the root node.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
As shown in fig. 1, the present invention provides an autonomous sending method for message alerts in a teaching management platform, where the method includes:
s1, acquiring a task scene type, task creation time and corresponding task parameters created by a teacher, and monitoring the task submission state of students in real time, wherein the task scene type comprises an examination scene and an operation scene;
s2, under an examination scene, determining examination notification time according to task creation time, determining a message reminding object according to a task submission state, determining examination advance notice and examination submission reminding time according to corresponding task parameters, determining the specific content of message reminding according to the type of the task scene and the message reminding time, and sending the examination notification, the examination advance notice and the examination submission reminding to the message reminding object;
s3, under the operation scene, determining operation notification time according to the task creating time, determining a message reminding object according to the task submitting state, extracting operation attribute characteristics, determining operation difficulty degree by using a random forest algorithm, determining operation submitting reminding time according to the operation difficulty degree, and sending operation notification and operation submitting reminding to the message reminding object.
In the embodiment, it is assumed that jobrepresents the type of a task scene, jobCreateTime represents task creation time, starttime represents task start time, endtime represents task end time, duration represents task duration (unit hour), level represents task difficulty, notice represents task forecast time, content represents specific content of message reminding, and isSubmit represents task submission state of a student and is used for representing whether the student submits a task.
After a teacher creates a specific task, the values of the parameters are determined, and specific message reminding times, time, objects and contents are obtained according to the message reminding autonomous sending method provided by the invention.
(1) Assuming the teacher created an exam, referring to FIG. 2, the task scenario type jobis assigned a value of 1. Task parameters such as examination title, start time, end time, examination duration and the like can be set in the examination creating process, and the examination creating time is recorded, so that the parameters start time, end time, duration and jobCreateTime can be determined, and the message reminding time and content can be determined according to the task scene type and the corresponding task parameters:
1) and (4) examination notification: at the first time when the examination is successfully created, examination notification information is issued to each student needing to take the examination, namely, examination notification reminding information is issued at jobCreateTime, and the content is information such as examination subject, examination starting time, examination ending time, examination duration and the like.
2) And (4) test forenotice: the starting time (in hours) of the examination is acquired, and the time length t is set0Will start time-t0Assign a task forecast time notice, and if the notice is later than the time of creating the test, assign a notice>The jobCreateTime issues examination forecast information to each student needing to take an examination at a task forecast time notice; if the time is earlier than the jobCreateTime, the test advance notice information is not issued. If t0When 1 hour, a test advance notice message is issued to each student who needs to take a test 1 hour before the test starts, and the content "please take in time one hour after the test starts".
3) Reminding of examination submission: acquiring a task submission state of a student, wherein an object to be reminded of submitting an examination is the student who does not submit the examination, namely the student who is isSubmit fast, notification time is determined according to examination duration, the duration is acquired when an online examination is established, the unit is hour, and the time to be reminded of submitting the examination is examination ending time advanced duration of 15 minutes; for example, the duration of the test is 2 hours, then the submission is reminded half an hour before the end time of the test, and the content is "there is a duration 15 minutes from the end of the test, please submit in time", where the expression duration 15 shall be a specific time.
(2) Assuming that the teacher creates a job, such as a plurality of types of preview jobs, post-lesson jobs, class jobs, and the like corresponding to chapters, please refer to fig. 3, and assign the task scene type joba to 2. In the process of creating the job, the job title, the job content and the submission time are set, and the job creation time is recorded, so that the parameters jobCreateTime, content and endtime are all determined, and the time and the content of the message reminder are determined as follows:
1) and (4) job notification: since a job is different from an examination and the creation time of the job is the start time of the job, i.e., jobCreateTime is the starting time, a job notification is issued to each student at the time of job creation, and the content is information such as a job title, job content, and submission time.
2) Job submission reminding: the notification object is a student who has not submitted the homework, namely a student who isSubmit is fast, the notification time of the homework submission reminding is determined according to the difficulty level of the homework,
the method for determining the difficulty level value of the operation comprises the following steps: dividing the difficulty of operation into three difficulty levels of difficulty, medium difficulty and easy difficulty, and correspondingly setting level values as 3, 2 and 1, wherein the greater the difficulty is, the greater the level value is; the invention adopts a random forest model to calculate the difficulty of the operation, wherein the random forest is a decision tree which is formed by randomly selecting k characteristics from decision trees with m characteristics, and then selecting a prediction result mode, firstly, the attribute characteristics of the operation are extracted, and the attribute characteristics comprise the number X of knowledge points contained in the operation1The duration X of the video resource of the chapter corresponding to the operation2Average result of previous work X3Class X of students4Chapter importance X5. When using the random forest algorithm, assuming that a class has n students, each student has the above five attribute feature data. Each student makes decision tree judgment on the five attribute characteristics, and the nodes of the decision tree use the five characteristics in turn. The five attribute characteristics are sequentially used as root nodes of the decision tree to construct the decision tree, and the method specifically comprises the following steps:
① first use knowledge point number X1As shown in fig. 4, the root node of the decision tree is determined as follows:
when X is present1>When 5, continuously judging the chapter importance degree X5If the chapter is important, the difficulty level is difficult, the chapter is general or not important, and the difficulty level is middle;
when X is more than or equal to 31When the number of the students is less than or equal to 5, continuously judging the class X of the students4If the studentThe difficulty level is medium if the category is Ben Ke Sheng, and the difficulty level is easy if the category is Special Sheng or Special student;
when X is present1<When the number of the jobs is 3, the average score X of the last job is continuously judged3If X is3More than or equal to 60 points, the difficulty is middle, if X is3<The difficulty is easy at 60 minutes; wherein the scores are all divided into 100.
② duration X of second use of video resource corresponding to chapter2As shown in fig. 5, the root node of the decision tree is determined as follows:
when X is present2>At 20 minutes, the chapter importance level X is continuously judged5If the chapter is important, the difficulty level is difficult, the chapter is general or not important, and the difficulty level is middle;
when X is more than or equal to 102When the time is less than or equal to 20 minutes, continuously judging the class X of the student4If the student category is the president, the difficulty level is middle, and if the student category is the special promotion or the president, the difficulty level is easy;
when X is present2<When 10 minutes, the number X of the knowledge points contained in the homework or the examination is continuously judged1If X is1More than or equal to 3, the difficulty is medium, X1<3, the difficulty is easy;
③ average score X of the last operation used for the third time3As shown in fig. 6, the root node of the decision tree is determined as follows:
when X is present3>At 80 minutes, continuously judging the class X of the student4If the student category is the president, the difficulty level is difficult, and if the student category is the special promotion or the president, the difficulty level is medium;
when X is more than or equal to 603When the degree of importance X of the chapters is less than or equal to 80, continuing to judge the degree of importance X of the chapters5If the chapter is important, the difficulty level is middle, the chapter is general or not important, and the difficulty level is easy;
when X is present3<When 60, continuously judging the number X of the knowledge points contained in the current homework or examination1If X is1More than or equal to 3, the difficulty is medium, X1<3, the difficulty is easy;
④ fourth use student class X4As shown in fig. 7, the root node of the decision tree is determined as follows:
when the student category is the student, continuously judging the chapter importance degree X5If the chapter is important, the difficulty level is difficult, the chapter is general or not important, and the difficulty level is middle;
when the class of the student is the special notebook, continuously judging the duration X of the video resource2If X is2More than or equal to 10 minutes, the difficulty is medium, X2<The difficulty level is easy within 10 minutes;
when the class of the student is a specialist student, the number X of the knowledge points contained in the homework or the examination is continuously judged1If X is1More than or equal to 3, the difficulty is medium, X1<3, the difficulty is easy;
⑤ fifth use chapter importance X5As shown in fig. 8, the root node of the decision tree is determined as follows:
when the chapter importance degree is important, the student category X is continuously judged4If the student category is the president, the difficulty level is difficult, and if the student category is the special promotion or the president, the difficulty level is medium;
when the chapter importance degree is general, continuously judging the number X of the knowledge points contained in the current homework or examination1If X is1More than or equal to 3, the difficulty is medium, X1<3, the difficulty is easy;
when the chapter importance degree is unimportant, continuously judging the duration X of the video resource2If X is2More than or equal to 10 minutes, the difficulty is medium, X2<The hardness is easy within 10 minutes.
And 5 decision results are obtained through the five rounds of decision trees, and the result with the highest ticket number is the value of the difficulty level.
The time of job submission reminding is level 30 minutes before submission time endtime, for example, if the difficulty is medium, the reminding message is sent 60 minutes before submission time endtime. The content of the reminder is "level 30 minutes away from the submission time, please complete the job and submit in time", wherein the expression level 30 shall be the specific time.
The invention adopts the random forest model to evaluate the difficulty level of each homework, determines the time for submitting the homework for reminding according to the difficulty level of the homework, fully considers the actual situation of each student in the homework writing process, avoids untimely and excessive message reminding or too early message reminding time, can effectively follow the actual learning situation of the student, and timely supervises and urges the student to complete the learning task on time.
Corresponding to the embodiment of the method, the invention also provides a message reminding autonomous sending system in the same teaching management platform, and the system comprises:
a parameter acquisition module: the system comprises a task management system, a task management system and a task management system, wherein the task management system is used for acquiring a task scene type, task creation time and corresponding task parameters created by a teacher and monitoring the task submission state of students in real time, and the task scene type comprises an examination scene and an operation scene;
the examination reminding module comprises: the system comprises a task creating module, a processing module and a display module, wherein the task creating module is used for creating task time according to the task creating module; determining a message reminding object according to the task submission state, determining examination advance notice and examination submission reminding time according to corresponding task parameters, determining specific content of the message reminding according to the task scene type and the message reminding time, and sending the examination advance notice and the examination submission reminding to the message reminding object;
operation reminding module: the system comprises a task creating module, a task setting module and a task sending module, wherein the task creating module is used for creating task time according to the task creating time; determining a message reminding object according to the task submitting state, extracting the attribute characteristics of the operation, sequentially using the attribute characteristics as root nodes of the decision tree to construct the decision tree, determining the difficulty level of the operation by using a random forest algorithm, determining the time of the job submitting reminding according to the difficulty level of the operation, and sending the job submitting reminding to the message reminding object.
The above method embodiments correspond to the system embodiments one to one, and the brief description of the system embodiments is provided with reference to the method embodiments.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (6)
1. An autonomous message prompt sending method in a teaching management platform is characterized by comprising the following steps:
s1, acquiring a task scene type, task creation time and corresponding task parameters created by a teacher, and monitoring the task submission state of students in real time, wherein the task scene type comprises an examination scene and an operation scene;
s2, under an examination scene, determining examination notification time according to task creation time, determining a message reminding object according to a task submission state, determining examination advance notice and examination submission reminding time according to corresponding task parameters, determining the specific content of message reminding according to the type of the task scene and the message reminding time, and sending the examination notification, the examination advance notice and the examination submission reminding to the message reminding object;
s3, under the operation scene, determining operation notification time according to the task creating time, determining a message reminding object according to the task submitting state, extracting operation attribute characteristics, determining operation difficulty degree by using a random forest algorithm, determining operation submitting reminding time according to the operation difficulty degree, and sending operation notification and operation submitting reminding to the message reminding object.
2. The message prompt autonomous sending method in the teaching management platform according to claim 1, wherein in an examination scene, the corresponding task parameters include examination question, examination start time, examination end time, and examination duration; in a job scenario, the corresponding task parameters include a job title, job content, and submission time.
3. The autonomous method for sending message alerts in a teaching management platform as claimed in claim 2, wherein said step S2 specifically is:
taking the time for creating the examination as examination notification time, issuing examination notification information to each student needing to take the examination, wherein the specific content of the message prompt is the question, the starting time, the ending time and the examination duration of the examination;
acquiring the starting time of the examination and setting the duration t0If starttime-t0The examination forecast information is released to each student needing to take the examination later than the examination creating time;
acquiring the task submission state of each student before the examination ending time, wherein the object for reminding the submission of the examination is the student who does not submit the examination, determining the time for reminding the submission of the examination according to the duration of the examination, and the time for reminding the submission of the examination is 15 minutes before the duration of the examination ending time.
4. The autonomous method for sending a message alert in a teaching management platform according to claim 1, wherein the step S3 specifically comprises:
when the homework is created, a homework notice is issued to each student, and the notice content is a homework title and submission time;
acquiring the task submission state of each student before the job submission time, wherein the object of job submission reminding is the student who does not submit the job; determining the difficulty level value of the operation, wherein the time for reminding the operation submission is 30 minutes before the time for submitting the operation;
the method for determining the difficulty level value of the operation comprises the following steps: dividing the difficulty level of the operation into three difficulty levels of difficulty, medium difficulty and easy difficulty level, taking the corresponding level values as 3, 2 and 1, and extracting operation attribute characteristics, wherein the attribute characteristics comprise the number X of knowledge points contained in the operation1The duration X of the video resource of the chapter corresponding to the operation2Average result of previous work X3Class X of students4Chapter importance X5(ii) a The five attribute characteristics are sequentially used as root nodes of the decision tree to construct a decision tree, each student judges the five attribute characteristics through the decision tree, 5 decision results are obtained through five rounds of decision tree judgment, and the result with the highest ticket number is the difficulty level leThe value of vel.
5. The autonomous method for sending message alerts in a teaching management platform as claimed in claim 4, wherein in step S4, the step of sequentially using the five attribute features as root nodes of a decision tree to construct the decision tree specifically comprises:
① first use knowledge point number X1As the root node of the decision tree, the judgment is based on the following:
when X is present1>When 5, continuously judging the chapter importance degree X5If the chapter is important, the difficulty level is difficult, the chapter is general or not important, and the difficulty level is middle;
when X is more than or equal to 31When the number of the students is less than or equal to 5, continuously judging the class X of the students4If the student category is the president, the difficulty level is middle, and if the student category is the special promotion or the president, the difficulty level is easy;
when X is present1<When the number of the jobs is 3, the average score X of the last job is continuously judged3If X is3More than or equal to 60 points, the difficulty is middle, if X is3<The difficulty is easy at 60 minutes;
② duration X of second use of video resource corresponding to chapter2As the root node of the decision tree, the judgment is based on the following:
when X is present2>At 20 minutes, the chapter importance level X is continuously judged5If the chapter is important, the difficulty level is difficult, the chapter is general or not important, and the difficulty level is middle;
when X is more than or equal to 102When the time is less than or equal to 20 minutes, continuously judging the class X of the student4If the student category is the president, the difficulty level is middle, and if the student category is the special promotion or the president, the difficulty level is easy;
when X is present2<When 10 minutes, the number X of the knowledge points contained in the homework or the examination is continuously judged1If X is1More than or equal to 3, the difficulty is medium, X1<3, the difficulty is easy;
③ average score X of the last operation used for the third time3As root node of decision tree, judge according toThe following is provided:
when X is present3>At 80 minutes, continuously judging the class X of the student4If the student category is the president, the difficulty level is difficult, and if the student category is the special promotion or the president, the difficulty level is medium;
when X is more than or equal to 603When the degree of importance X of the chapters is less than or equal to 80, continuing to judge the degree of importance X of the chapters5If the chapter is important, the difficulty level is middle, the chapter is general or not important, and the difficulty level is easy;
when X is present3<When 60, continuously judging the number X of the knowledge points contained in the current homework or examination1If X is1More than or equal to 3, the difficulty is medium, X1<3, the difficulty is easy;
④ fourth use student class X4As the root node of the decision tree, the judgment is based on the following:
when the student category is the student, continuously judging the chapter importance degree X5If the chapter is important, the difficulty level is difficult, the chapter is general or not important, and the difficulty level is middle;
when the class of the student is the special notebook, continuously judging the duration X of the video resource2If X is2More than or equal to 10 minutes, the difficulty is medium, X2<The difficulty level is easy within 10 minutes;
when the class of the student is a specialist student, the number X of the knowledge points contained in the homework or the examination is continuously judged1If X is1More than or equal to 3, the difficulty is medium, X1<3, the difficulty is easy;
⑤ fifth use chapter importance X5As the root node of the decision tree, the judgment is based on the following:
when the chapter importance degree is important, the student category X is continuously judged4If the student category is the president, the difficulty level is difficult, and if the student category is the special promotion or the president, the difficulty level is medium;
when the chapter importance degree is general, continuously judging the number X of the knowledge points contained in the current homework or examination1If X is1More than or equal to 3, the difficulty is medium, X1<3, the difficulty is easy;
when the chapter importance degree is unimportant, continuously judging the duration X of the video resource2If X is2More than or equal to 10 minutes, the difficulty is medium, X2<The hardness is easy within 10 minutes.
6. An autonomous message reminder sending system in a teaching management platform, the system comprising:
a parameter acquisition module: the system comprises a task management system, a task management system and a task management system, wherein the task management system is used for acquiring a task scene type, task creation time and corresponding task parameters created by a teacher and monitoring the task submission state of students in real time, and the task scene type comprises an examination scene and an operation scene;
the examination reminding module comprises: the system comprises a task creating module, a processing module and a display module, wherein the task creating module is used for creating task time according to the task creating module; determining a message reminding object according to the task submission state, determining examination advance notice and examination submission reminding time according to corresponding task parameters, determining specific content of the message reminding according to the task scene type and the message reminding time, and sending the examination advance notice and the examination submission reminding to the message reminding object;
operation reminding module: the system comprises a task creating module, a task setting module and a task sending module, wherein the task creating module is used for creating task time according to the task creating time; determining a message reminding object according to the task submitting state, extracting the attribute characteristics of the operation, sequentially using the attribute characteristics as root nodes of the decision tree to construct the decision tree, determining the difficulty level of the operation by using a random forest algorithm, determining the time of the job submitting reminding according to the difficulty level of the operation, and sending the job submitting reminding to the message reminding object.
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