CN113570208A - Dispatcher course management method and device based on artificial intelligence - Google Patents
Dispatcher course management method and device based on artificial intelligence Download PDFInfo
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Abstract
The application relates to a dispatcher course management method and device based on artificial intelligence, relating to the technical field of training course management, and the dispatcher course management method based on artificial intelligence comprises the following steps: distributing corresponding work subject courses according to the work subjects of the dispatcher; collecting test scores of a dispatcher after completing a learning course, and recording the learning duration corresponding to the learning course; when the test score of the learning course is lower than the preset qualified score and the corresponding learning duration is lower than the preset theoretical learning duration, improving the pushing frequency of the working subject course; and when the test score of the learning course is lower than the preset qualified score and the corresponding learning duration exceeds the preset theoretical learning duration, sending out a targeted guidance alarm. According to the training course arrangement in the earlier stage, the learning condition of training staff is collected and reason analysis is carried out, and then the training course is adjusted, so that the working efficiency of course adjustment work is improved.
Description
Technical Field
The application relates to the technical field of training course management, in particular to a dispatcher course management method and device based on artificial intelligence.
Background
At present, along with the discovery of network technology, an online education platform gradually develops and matures, the training of a plurality of technical posts also utilizes online education technology, and the convenience of online education is utilized to obtain better training effect.
The purpose of the training is to enable the trainee to develop more specialized levels of skill into the actual work. At the present stage, the arrangement work of post training courses of the online education platform is mainly carried out manually by working staff according to the specific conditions of the training staff, the training arrangement of the training staff at different posts is greatly different, and the actual training results of different training staff at the same post are also different, so that the working staff often need to manually adjust the courses, the workload is large, the course arrangement efficiency is low, and the learning effect of the training staff is not ideal.
Therefore, how to know the learning effect through an intuitive technical means and further intelligently adjust the courses is a problem which needs to be solved urgently at present.
Disclosure of Invention
The application provides a dispatcher course management method and device based on artificial intelligence, which are used for collecting the learning condition of training personnel and analyzing reasons according to the arrangement of training courses in the early stage, and further adjusting the training courses so as to improve the working efficiency of course adjustment work.
In a first aspect, the present application provides a dispatcher curriculum management method based on artificial intelligence, the method includes the following steps:
distributing corresponding work subject courses according to the work subjects of the dispatcher;
collecting the test scores of the dispatcher after completing the learning course, and recording the learning duration corresponding to the learning course;
when the test score of the learning course is lower than a preset qualified score and the corresponding learning duration is lower than a preset theoretical learning duration, improving the pushing frequency of the work subject course;
and when the test score of the learning course is lower than a preset qualified score and the corresponding learning duration exceeds a preset theoretical learning duration, sending out a targeted guidance alarm.
According to the training course arrangement in the earlier stage, the learning condition of training staff is collected, the course with the unsatisfactory learning result is subjected to reason analysis, and then the training course is adjusted based on the reason analysis result so as to improve the working efficiency of course adjustment work and provide convenience for online training work.
Further, the method comprises the following steps:
collecting the learning durations and the test scores of different dispatchers of the work subject course;
calculating the average learning duration of the work subject courses according to the learning durations of different dispatchers;
calculating the average test score of the work subject course according to the test scores of different dispatchers;
and when the average test score is lower than a preset test average first score and the average learning duration exceeds a preset theoretical average learning first duration, judging that the working subject course is unreasonable.
Further, the method comprises the following steps:
collecting the learning durations and the test scores of different dispatchers of the work subject course;
calculating the average learning duration of the work subject courses according to the learning durations of different dispatchers;
calculating the average test score of the work subject course according to the test scores of different dispatchers;
and when the average test score exceeds a preset test average second score and the average learning duration is lower than a preset theoretical average learning second duration, judging that the working subject course is unreasonable.
Further, the method comprises the following steps:
and when the test score of the learning course is higher than a preset qualified score and the corresponding learning duration is lower than a preset theoretical learning duration, the pushing frequency of the working subject course is reduced.
Specifically, the method for improving the pushing frequency of the work subject course comprises the following steps:
and pushing the study plan of the work subject course to a dispatcher by using preset intelligent wearable equipment.
In a second aspect, the present application provides an artificial intelligence based dispatcher lesson management apparatus, the apparatus comprising:
the course distribution module is used for distributing corresponding work subject courses according to the work subjects of the dispatcher;
the learning recording module is used for collecting the test scores of the dispatcher after the learning course is finished and recording the learning duration corresponding to the learning course;
the course pushing module is used for pushing the distributed work subject courses to the corresponding dispatchers;
the course pushing module is further used for increasing the pushing frequency of the working subject course when the test score of the learning course is lower than a preset qualified score and the corresponding learning duration is lower than a preset theoretical learning duration;
and the course alarm module is used for sending out a pertinence guidance alarm when the test score of the learning course is lower than a preset qualified score and the corresponding learning duration exceeds a preset theoretical learning duration.
Further, the learning record module is further configured to collect the learning durations and the test scores of different dispatchers of the work subject course;
the learning recording module is further used for calculating the average learning duration of the work subject course according to the learning durations of different dispatchers;
the learning recording module is further used for calculating the average test score of the work subject course according to the test scores of different dispatchers;
the course alarm module is further used for judging that the course of the work subject is unreasonable when the average test score is lower than a preset test average first score and the average learning duration exceeds a preset theoretical average learning first duration.
Further, the learning record module is further configured to collect the learning durations and the test scores of different dispatchers of the work subject course;
the learning recording module is further used for calculating the average learning duration of the work subject course according to the learning durations of different dispatchers;
the learning recording module is further used for calculating the average test score of the work subject course according to the test scores of different dispatchers;
the course alarm module is further used for judging that the course of the work subject is unreasonable when the average test score exceeds a preset test average second score and the average learning duration is lower than a preset theoretical average learning second duration.
Furthermore, the course propelling movement module is also used for working as study course the test score is higher than the predetermined qualified score, and corresponding study duration is less than predetermined theoretical study duration, reduces the propelling movement frequency of work subject course.
Further, the device also comprises intelligent wearable equipment;
the course pushing module is further used for pushing a learning plan of the work subject course to a dispatcher by using the intelligent wearable device.
The beneficial effect that technical scheme that this application provided brought includes:
according to the training course arrangement in the earlier stage, the learning condition of training staff is collected, the course with the unsatisfactory learning result is subjected to reason analysis, and then the training course is adjusted based on the reason analysis result so as to improve the working efficiency of course adjustment work and provide convenience for online training work.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a flowchart illustrating steps of a method for managing dispatcher courses based on artificial intelligence provided in an embodiment of the present application;
fig. 2 is a block diagram of an artificial intelligence based dispatcher lesson management device provided in 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, and it is obvious that the described embodiments are some embodiments of the present application, but 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.
Embodiments of the present application will be described in further detail below with reference to the accompanying drawings.
The embodiment of the application provides a dispatcher course management method and device based on artificial intelligence, the training condition of training personnel is collected according to training course arrangement in an earlier stage, reason analysis is carried out on courses with unsatisfactory learning results, and then the training courses are adjusted based on the reason analysis results, so that the working efficiency of course adjustment work is improved, and convenience is brought to online training work.
In order to achieve the technical effects, the general idea of the application is as follows:
a dispatcher curriculum management method based on artificial intelligence comprises the following steps:
s1, distributing corresponding work subject courses according to the work subjects of the dispatcher;
s2, collecting test scores of the dispatcher after completing the learning course, and recording the learning duration corresponding to the learning course;
s3, when the test score of the learning course is lower than the preset qualified score and the corresponding learning duration is lower than the preset theoretical learning duration, improving the pushing frequency of the working subject course;
and S4, when the test score of the learning course is lower than the preset qualified score and the corresponding learning duration exceeds the preset theoretical learning duration, sending out a targeted guidance alarm.
Embodiments of the present application will be described in further detail below with reference to the accompanying drawings.
In a first aspect, referring to fig. 1, an embodiment of the present application provides an artificial intelligence based dispatcher curriculum management method, which includes the following steps:
s1, distributing corresponding work subject courses according to the work subjects of the dispatcher;
s2, collecting test scores of the dispatcher after completing the learning course, and recording the learning duration corresponding to the learning course;
s3, when the test score of the learning course is lower than the preset qualified score and the corresponding learning duration is lower than the preset theoretical learning duration, improving the pushing frequency of the working subject course;
and S4, when the test score of the learning course is lower than the preset qualified score and the corresponding learning duration exceeds the preset theoretical learning duration, sending out a targeted guidance alarm.
In the embodiment of the application, the training condition of the training staff is collected according to the arrangement of the training courses in the previous period, the course with the unsatisfactory learning result is subjected to reason analysis, and then the training course is adjusted based on the reason analysis result so as to improve the working efficiency of course adjustment work and provide convenience for online training work.
Further, the method comprises the following steps:
collecting learning duration and test scores of different dispatchers of work subject courses;
calculating the average learning duration of the work subject courses according to the learning durations of different dispatchers;
calculating the average test score of the work subject course according to the test scores of different dispatchers;
and when the average test score is lower than the preset test average first score and the average learning duration exceeds the preset theoretical average learning first duration, judging that the course of the work subject is unreasonable.
Further, the method comprises the following steps:
collecting learning duration and test scores of different dispatchers of work subject courses;
calculating the average learning duration of the work subject courses according to the learning durations of different dispatchers;
calculating the average test score of the work subject course according to the test scores of different dispatchers;
and when the average test score exceeds a preset test average second score and the average learning duration is shorter than a preset theoretical average learning second duration, judging that the course of the work subject is unreasonable.
Further, the method comprises the following steps:
and when the test score of the learning course is higher than the preset qualified score and the corresponding learning duration is lower than the preset theoretical learning duration, the pushing frequency of the working subject course is reduced.
Specifically, the method for improving the pushing frequency of the working subject courses comprises the following steps:
and pushing a learning plan of a work subject course to a dispatcher by using preset intelligent wearable equipment.
It should be noted that the intelligent wearable device can be an intelligent bracelet with a heartbeat monitoring function, a blood pressure monitoring function or a body temperature monitoring function.
In a second aspect, referring to fig. 2, an embodiment of the present application provides an artificial intelligence based dispatcher lesson management apparatus based on the artificial intelligence based dispatcher lesson management method of the first aspect, the apparatus including:
the course distribution module is used for distributing corresponding work subject courses according to the work subjects of the dispatcher;
the learning recording module is used for collecting the test scores of the dispatcher after completing the learning course and recording the learning duration corresponding to the learning course;
the course pushing module is used for pushing the distributed work subject courses to the corresponding dispatchers;
the course pushing module is further used for improving the pushing frequency of the working subject courses when the test scores of the learning courses are lower than the preset qualified scores and the corresponding learning duration is lower than the preset theoretical learning duration;
and the course alarm module is used for sending out a targeted guidance alarm when the test score of the learning course is lower than the preset qualified score and the corresponding learning duration exceeds the preset theoretical learning duration.
In the embodiment of the application, the training condition of the training staff is collected according to the arrangement of the training courses in the previous period, the course with the unsatisfactory learning result is subjected to reason analysis, and then the training course is adjusted based on the reason analysis result so as to improve the working efficiency of course adjustment work and provide convenience for online training work.
Furthermore, the learning recording module is also used for collecting the learning duration and the test score of different dispatchers of the work subject course;
the learning recording module is also used for calculating the average learning duration of the working subject courses according to the learning durations of different dispatchers;
the learning recording module is also used for calculating the average test score of the working subject course according to the test scores of different dispatchers;
the course alarm module is further used for judging that the course of the work subject is unreasonable when the average test score is lower than the preset average test first score and the average learning duration exceeds the preset average theoretical learning first duration.
Furthermore, the learning recording module is also used for collecting the learning duration and the test score of different dispatchers of the work subject course;
the learning recording module is also used for calculating the average learning duration of the working subject courses according to the learning durations of different dispatchers;
the learning recording module is also used for calculating the average test score of the working subject course according to the test scores of different dispatchers;
the course alarm module is further used for judging that the course of the work subject is unreasonable when the average test score exceeds a preset test average second score and the average learning duration is shorter than a preset theoretical average learning second duration.
Furthermore, the course pushing module is further configured to reduce the pushing frequency of the work subject course when the test score of the learning course is higher than the preset qualified score and the corresponding learning duration is lower than the preset theoretical learning duration.
Further, the device also comprises intelligent wearable equipment;
the course pushing module is further used for pushing a learning plan of the course of the work subject to the dispatcher by using the intelligent wearable device.
It should be noted that the intelligent wearable device can be an intelligent bracelet with a heartbeat monitoring function, a blood pressure monitoring function or a body temperature monitoring function.
It is noted that, in the present application, relational terms such as "first" and "second", and the like, are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The foregoing are merely exemplary embodiments of the present application and are presented to enable those skilled in the art to understand and practice the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A dispatcher curriculum management method based on artificial intelligence is characterized by comprising the following steps:
distributing corresponding work subject courses according to the work subjects of the dispatcher;
collecting the test scores of the dispatcher after completing the learning course, and recording the learning duration corresponding to the learning course;
when the test score of the learning course is lower than a preset qualified score and the corresponding learning duration is lower than a preset theoretical learning duration, improving the pushing frequency of the work subject course;
and when the test score of the learning course is lower than a preset qualified score and the corresponding learning duration exceeds a preset theoretical learning duration, sending out a targeted guidance alarm.
2. The artificial intelligence based dispatcher lesson management method as recited in claim 1, further comprising the steps of:
collecting the learning durations and the test scores of different dispatchers of the work subject course;
calculating the average learning duration of the work subject courses according to the learning durations of different dispatchers;
calculating the average test score of the work subject course according to the test scores of different dispatchers;
and when the average test score is lower than a preset test average first score and the average learning duration exceeds a preset theoretical average learning first duration, judging that the working subject course is unreasonable.
3. The artificial intelligence based dispatcher lesson management method as recited in claim 1, further comprising the steps of:
collecting the learning durations and the test scores of different dispatchers of the work subject course;
calculating the average learning duration of the work subject courses according to the learning durations of different dispatchers;
calculating the average test score of the work subject course according to the test scores of different dispatchers;
and when the average test score exceeds a preset test average second score and the average learning duration is lower than a preset theoretical average learning second duration, judging that the working subject course is unreasonable.
4. The artificial intelligence based dispatcher lesson management method as recited in claim 1, further comprising the steps of:
and when the test score of the learning course is higher than a preset qualified score and the corresponding learning duration is lower than a preset theoretical learning duration, the pushing frequency of the working subject course is reduced.
5. The artificial intelligence based dispatcher lesson management method as claimed in claim 1, wherein said increasing the frequency of pushing said work subject lessons comprises the steps of:
and pushing the study plan of the work subject course to a dispatcher by using preset intelligent wearable equipment.
6. An artificial intelligence based dispatcher lesson management apparatus, the apparatus comprising:
the course distribution module is used for distributing corresponding work subject courses according to the work subjects of the dispatcher;
the learning recording module is used for collecting the test scores of the dispatcher after the learning course is finished and recording the learning duration corresponding to the learning course;
the course pushing module is used for pushing the distributed work subject courses to the corresponding dispatchers;
the course pushing module is further used for increasing the pushing frequency of the working subject course when the test score of the learning course is lower than a preset qualified score and the corresponding learning duration is lower than a preset theoretical learning duration;
and the course alarm module is used for sending out a pertinence guidance alarm when the test score of the learning course is lower than a preset qualified score and the corresponding learning duration exceeds a preset theoretical learning duration.
7. The artificial intelligence based dispatcher lesson management device as recited in claim 6, wherein:
the learning recording module is further used for collecting the learning duration and the test score of different dispatchers of the work subject course;
the learning recording module is further used for calculating the average learning duration of the work subject course according to the learning durations of different dispatchers;
the learning recording module is further used for calculating the average test score of the work subject course according to the test scores of different dispatchers;
the course alarm module is further used for judging that the course of the work subject is unreasonable when the average test score is lower than a preset test average first score and the average learning duration exceeds a preset theoretical average learning first duration.
8. The artificial intelligence based dispatcher lesson management device as recited in claim 6, wherein:
the learning recording module is further used for collecting the learning duration and the test score of different dispatchers of the work subject course;
the learning recording module is further used for calculating the average learning duration of the work subject course according to the learning durations of different dispatchers;
the learning recording module is further used for calculating the average test score of the work subject course according to the test scores of different dispatchers;
the course alarm module is further used for judging that the course of the work subject is unreasonable when the average test score exceeds a preset test average second score and the average learning duration is lower than a preset theoretical average learning second duration.
9. The artificial intelligence based dispatcher lesson management device as recited in claim 6, wherein:
the course pushing module is further used for reducing the pushing frequency of the working subject course when the test score of the learning course is higher than a preset qualified score and the learning duration is correspondingly lower than a preset theoretical learning duration.
10. The artificial intelligence based dispatcher lesson management apparatus as recited in claim 6, wherein said apparatus further comprises an intelligent wearable device;
the course pushing module is further used for pushing a learning plan of the work subject course to a dispatcher by using the intelligent wearable device.
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| CN101650809A (en) * | 2009-09-10 | 2010-02-17 | 上海一佳一网络科技有限公司 | Method and system for managing post capability training |
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2021
- 2021-07-09 CN CN202110781987.5A patent/CN113570208A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN101650809A (en) * | 2009-09-10 | 2010-02-17 | 上海一佳一网络科技有限公司 | Method and system for managing post capability training |
| TW201437952A (en) * | 2013-03-20 | 2014-10-01 | Univ Nat United | A method for designing and then assessing training courses for a professional organization with a supplementary method for observing and assessing the competence growth of its members through the courses and a learning system integrating computer devices |
| CN104616120A (en) * | 2015-02-27 | 2015-05-13 | 广东小天才科技有限公司 | Method and system for drawing up learning plan based on curriculum schedule |
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Application publication date: 20211029 |