CN116563068A - 5G network service platform type remote education system - Google Patents
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Abstract
The invention discloses a 5G network service platform type remote education system, which particularly relates to the technical field of remote education, and comprises a collection unit, a first processing unit, an optimization module, a lifting module and a optimizing module, wherein the collection unit is used for collecting data of student terminals to form collection information, and comprises a video learning collection module, an interaction information collection module and an online examination collection module; according to the invention, in the remote education system, the student terminal can detect the teaching process of the remote education system through the acquisition unit and the first processing unit, and quantitatively evaluate the learning result of the student terminal, based on the remote education evaluation value, the teacher terminal can conveniently judge whether the education scheme in the remote education system can continue learning, and if the education scheme cannot continue learning or has poor learning effect, corrective measures are taken for the education scheme, so that the learning effect of students is effectively improved.
Description
Technical Field
The invention relates to the technical field of distance education, in particular to a 5G network service platform type distance education system.
Background
The 5G network service platform is used for providing various telecommunication and data services, including telephone, video data messaging, etc., and the fifth generation (5G) mobile standard requires higher data transmission speed, more connection and wider coverage, and the 5G network has been used in many applications in people's work and life.
When the student terminal performs remote education learning through the 5G network service platform, if the education schemes in the remote education system are more, the student terminal optimizes various education schemes so as to be suitable for students in different learning stages.
In a plurality of groups of remote education schemes in the remote education system, as the learning time and learning effect of students are different, a teacher is required to conduct periodic remote education guidance according to student terminals, so that the difficulty of remote education of the teacher is increased, the remote education schemes in the existing remote education system are various and complex, students and teachers are difficult to conduct personalized education according to the self conditions of the students, cannot evaluate according to the learning stages of different students, and cannot conduct education scheme optimization on the students in different learning stages through different education schemes, the qualification rate of remote education of the students is reduced, and the remote education system of a 5G network service platform type is provided.
Disclosure of Invention
In order to overcome the above-mentioned drawbacks of the prior art, an embodiment of the present invention provides a 5G network service platform type distance education system to solve the above-mentioned problems set forth in the background art.
In order to achieve the above purpose, the present invention provides the following technical solutions: A5G network service platform type remote education system comprises an acquisition unit, a first processing unit, an optimization module, a lifting module and a optimizing module,
the acquisition unit is used for acquiring data of the student terminals to form acquisition information and comprises a video learning acquisition module, an interaction information acquisition module and an on-line examination acquisition module;
the video learning acquisition module is used for recording online video learning time of the student terminal to form learning time Xt;
the interaction information acquisition module acquires interaction information of the student terminal and the teacher terminal, acquires interaction duration in a current interaction period, and forms interaction duration Js by taking 45 minutes as the interaction period in an exemplary manner;
the on-line assessment acquisition module acquires education achievements of student terminals, takes one learning period or two learning periods or other proper assessment time as an acquisition period, and acquires average achievements in the period to form assessment achievements Sc;
the first processing unit is used for acquiring the acquired information, carrying out teaching evaluation on the acquired information, and forming a teaching adjustment scheme for the remote education mode of the student terminal according to the evaluation result;
the optimizing module is used for receiving the teaching adjustment scheme of the first processing unit, forming an optimizing instruction and optimizing at least one of the lifting module, the optimizing module and the second optimizing unit;
the teaching evaluation module is used for receiving the learning time Xt, the interaction time Js and the assessment score Sc, forming a collection information data set, and performing teaching evaluation to form a remote education evaluation value Jp;
the remote education evaluation value Jp conforms to the following method:
the learning time Xt, the interaction time Js and the assessment score Sc are acquired, subjected to non-dimensionality treatment and correlated through correlation analysis, and the learning time Xt, the interaction time Js and the assessment score Sc accord with the following expression:
in the formula, 0 < alpha 1 ≤1、0＜α 2 ≤1α 2 、0＜α 3 Less than or equal to 1, and alpha 1 +α 2 +α 3 ＝1，
Wherein alpha is 1 、α 2 Alpha and alpha 3 And P is the correlation coefficient of the learning duration and the assessment score, and is obtained by calculating a plurality of groups of learning duration and assessment score.
Preferably, the comparison module comprises a first comparison sub-module and a second comparison sub-module, a remote education evaluation value Jp is obtained and compared with the first comparison sub-module and the second comparison sub-module, if the remote education evaluation value is larger than the first comparison sub-module, a first evaluation result is formed, if the remote education evaluation value Jp is between the first comparison sub-module and the second comparison sub-module, a second evaluation result is formed, and if the remote education evaluation value Jp is smaller than the second comparison sub-module, a third evaluation result is formed, and a corresponding teaching adjustment scheme is formed;
the comparison module transmits the first evaluation result, the second evaluation result and the third evaluation result to respectively obtain a first education scheme, a second education scheme and a third education scheme, and the lifting module, the optimizing module and the first detection unit are respectively optimized.
Preferably, the optimization module acquires a first education scheme to form a first teaching signal, and the remote education of the student terminal is revealed through the optimization module;
the optimizing module acquires a second education scheme to form a second teaching signal, the remote education of the student terminal is revealed by the optimizing module, the remote education is detected by the first detecting unit, and a detection result is output;
the optimizing module obtains a third education proposal, forms a third teaching signal, displays the third teaching signal through the lifting module, displays the remote education of the student terminal through the optimizing module, detects the remote education through the first detecting unit, outputs a detection result,
the detection method of the first detection unit comprises the following steps:
when a student terminal starts to display an education scheme, counting the matching rate Pb of teaching contents and course progress in the education scheme from the start of detection to the time of evaluation and detection;
in the detection period, counting the duty ratio Zb of abnormal teaching contents in a normal education scheme and the repetition rate Jc of the teaching contents;
carrying out normalization processing on the course progress matching rate Pb, the teaching content repetition rate Jc and the abnormal teaching content occupation ratio Zb, and synthesizing to form an abnormal detection value Yp, wherein the abnormal detection value Yp has a judging formula as follows:
in the formula, 0 < beta 1 ≤1、0＜β 2 ≤1、0＜β 3 Not more than 1 and beta 1 +β 2 +β 3 ＝1，
Wherein beta is 1 、β 2 Beta and beta 3 As the weight, lna is the correlation coefficient of course progress matching rate and abnormal teaching content duty ratio, and is calculated by a plurality of groups of course progress matching rate and abnormal teaching content duty ratio.
Comparing the abnormal detection value Yp with a preset abnormal detection value threshold, if the abnormal detection value is higher than the preset abnormal detection value threshold, judging that the education scheme is abnormal temporarily after other factors are considered, displaying the education scheme, if the abnormal detection value is lower than the preset abnormal detection value threshold, analyzing the factors to analyze whether the abnormality exists, and transmitting the abnormality factors to a second optimizing unit.
Preferably, the remote education evaluation value Jp is greater than the first comparison sub-module, and is detected by the first detection unit, and the detection result is output; the second optimizing unit obtains the detection result according to the first detecting unit, determines to select the corresponding remote education scheme, evaluates the corresponding remote education scheme, and outputs the corresponding remote education scheme with the highest evaluation value; and the third optimizing unit receives the corresponding remote education scheme output by the second optimizing unit, checks whether the corresponding remote education scheme is effective or not after the corresponding remote education scheme is subjected to remote education, and sends an early warning to the teacher end if the corresponding remote education scheme is ineffective, so that the teacher terminal is reminded to manually change the remote education scheme.
Preferably, the test module determines that the remote education evaluation value Jp is not greater than the first comparison sub-module, monitors the remote education scheme for one period, determines abnormal characteristics and outputs the abnormal characteristics; the abnormal characteristics are that the teaching resources are single and the content is repeated;
the abnormal database acquires abnormal characteristics and compares the abnormal characteristics with known abnormal characteristics in the abnormal database, whether the abnormal characteristics are known abnormal characteristics or not is determined, and if the abnormal characteristics are not known abnormal characteristics, the abnormal characteristics are recorded through the recording module.
Preferably, the second optimizing unit includes a teaching resource database, an output module and a second evaluation module, where the teaching resource database indexes the corresponding education scheme from the teaching resource database according to the corresponding abnormal characteristic when judging that the abnormal characteristic of the remote education scheme is a known abnormal characteristic, and outputs the education scheme through the output module.
Preferably, the third optimizing unit includes a fault question strengthening module, the fault question strengthening module receives the education scheme, and performs targeted optimization on the corresponding abnormal characteristics, after the fault question strengthening module optimizes the education scheme, the testing module scans the abnormal characteristics of the remote education, judges whether the abnormality of the education scheme is optimized, and according to the judging result, the second evaluating module evaluates the corresponding education scheme to determine whether the education scheme is feasible.
Preferably, the method of evaluating includes the following:
equidistant divisions are made in the direction of the time axis, and are labeled i=1, 2, 3,..n-1, n, and distance education evaluation values Jp are obtained, respectively n-1 ，Jp n Abnormality detection value Yp n-1 ，Yp n ；
Correlating the remote education evaluation value with the abnormality detection value to form a second evaluation coefficient Pg, wherein the second evaluation coefficient Pg accords with the following formula:
in which 0 < sigma 1 ≤1，0＜λ 2 Less than or equal to 1 and sigma 1 2 +σ 2 2 ＝1.25，
Educational regimens were evaluated at Pg (J, Y) in the following manner:
wherein sigma 1 Sigma (sigma) 2 The weight is specifically adjusted by a manager;
and acquiring a second evaluation coefficient Pg and comparing the second evaluation coefficient Pg with a preset second evaluation coefficient threshold value, if the second evaluation coefficient Pg is higher than the preset second evaluation coefficient threshold value, the education scheme is not abnormal, the student terminal continues to use the education scheme, if the second evaluation coefficient Pg is higher than the preset second evaluation coefficient threshold value, the education scheme is abnormal, and the abnormal characteristics are transmitted to the early warning module.
Preferably, the third optimizing unit further comprises an early warning module, and the early warning module sends early warning to the teacher terminal to remind the teacher to modify and optimize the remote education scheme after the testing module scans the abnormal features of the remote education and the abnormal features are not indexed in the abnormal database or the abnormal features are not indexed, but the corresponding education scheme is not found.
The invention has the technical effects and advantages that:
(1) According to the invention, in the remote education system, the student terminal can detect the teaching process of the remote education system through the acquisition unit and the first processing unit, and quantitatively evaluate the learning result of the student terminal, based on the remote education evaluation value, the teacher terminal can conveniently judge whether the education scheme in the remote education system can continue learning, and if the education scheme cannot continue learning or has poor learning effect, corrective measures are taken for the education scheme, so that the learning effect of students is effectively improved.
(2) According to the invention, when the first detection unit, the second optimization unit and the third optimization unit are arranged and the education scheme is judged to be corrected, the education scheme is detected firstly, the abnormal problem is found through detection, the abnormal characteristics are determined, so that comparison from an abnormal database is facilitated, and finally the corresponding education scheme is found from the teaching resource library, so that the repeated correction time of a teacher terminal is reduced, and correspondingly, the remote education system is periodically detected, so that the teaching qualification rate of students and the use rate of the remote education system are improved.
Drawings
Fig. 1 is a block diagram of a system architecture of the present invention.
FIG. 2 is a schematic diagram of the system optimization of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
Referring to fig. 1-2, the present embodiment provides a 5G network service platform-type remote education system as shown in fig. 1, including an acquisition unit, a first processing unit, an optimization module, a lifting module, and a optimizing module;
when a student terminal logs in a remote education system, the acquisition unit acquires data of the student terminal to form acquisition information, and specifically, the acquisition unit comprises a video learning acquisition module, an interaction information acquisition module and an online examination acquisition module;
the video learning acquisition module is used for recording online video learning time of the student terminal to form learning time Xt,
the interaction information acquisition module acquires interaction information of the student terminal and the teacher terminal, acquires interaction duration in a current interaction period, and forms interaction duration Js by taking 45 minutes as the interaction period in an exemplary manner;
the on-line assessment acquisition module acquires education achievements of student terminals, takes one learning period or two learning periods or other proper assessment time as an acquisition period, and acquires average achievements in the period to form assessment achievements Sc;
in this embodiment, the learning time Xt, the interaction time Js and the assessment score Sc are collected and summarized to form collected information of the learning terminal, the collected information is integrated, and the remote education state of the student terminal is monitored.
The first processing unit is used for acquiring the acquired information, carrying out teaching evaluation on the acquired information, and forming a teaching adjustment scheme for the remote education mode of the student terminal according to the evaluation result;
the optimizing module is used for receiving the teaching adjustment scheme of the first processing unit, forming an optimizing instruction, and optimizing at least one of the lifting module, the optimizing module and the second optimizing unit so as to optimize the teaching adjustment scheme.
Referring to fig. 1, the first processing unit includes a teaching evaluation module, a comparison module and an analysis module,
the teaching evaluation module is used for receiving the learning time Xt, the interaction time Js and the assessment score Sc, forming a collection information data set, and performing teaching evaluation to form a remote education evaluation value Jp;
wherein the remote education evaluation value Jp conforms to the following method:
the learning time Xt, the interaction time Js and the assessment score Sc are acquired, subjected to non-dimensionality treatment and correlated through correlation analysis, and the learning time Xt, the interaction time Js and the assessment score Sc accord with the following expression:
in the formula, 0 < alpha 1 ≤1、0＜α 2 ≤1α 2 、0＜α 3 Less than or equal to 1, and alpha 1 +α 2 +α 3 ＝1，
Wherein alpha is 1 、α 2 Alpha and alpha 3 And P is the correlation coefficient of the learning duration and the assessment score, and is obtained by calculating a plurality of groups of learning duration and assessment score.
The comparison module comprises a first comparison sub-module and a second comparison sub-module, a remote education evaluation value Jp is obtained and compared with the first comparison sub-module and the second comparison sub-module, if the remote education evaluation value is larger than the first comparison sub-module, a first evaluation result is formed, if the remote education evaluation value Jp is between the first comparison sub-module and the second comparison sub-module, a second evaluation result is formed, and if the remote education evaluation value Jp is smaller than the second comparison sub-module, a third evaluation result is formed;
the analysis module receives the evaluation results of the comparison module, wherein the evaluation results comprise a first evaluation result, a second evaluation result and a third evaluation result, and a corresponding teaching adjustment scheme is formed.
And the three evaluation results transmitted by the comparison module, namely the first evaluation result, the second evaluation result and the third evaluation result, respectively obtain a first education scheme, a second education scheme and a third education scheme, and respectively optimize the lifting module, the optimizing module and the first detection unit.
In this embodiment, through evaluating the remote education scheme of the student terminal, and comparing and analyzing with the first comparing sub-module and the second comparing sub-module in the comparing module, the remote education scheme of the student terminal is roughly judged, and the teacher terminal can accurately judge the remote education scheme of the student terminal according to the comparing result.
1-2, further disclosure is made of the first educational regimen, the second educational regimen, and the third educational regimen;
the optimization module acquires a first education scheme to form a first teaching signal, and the remote education of the student terminal is displayed through the optimizing module;
the optimizing module acquires a second education scheme to form a second teaching signal, the remote education of the student terminal is revealed by the optimizing module, the remote education is detected by the first detecting unit, and a detection result is output;
the optimizing module acquires a third education scheme to form a third teaching signal, the third teaching signal is displayed through the lifting module, the remote education of the student terminal is displayed through the optimizing module, the first detecting unit detects the remote education, and the detection result is output;
the detection method of the first detection unit comprises the following steps:
when a student terminal starts to display an education scheme, counting the matching rate Pb of teaching contents and course progress in the education scheme from the start of detection to the time of evaluation and detection;
in the detection period, counting the duty ratio Zb of abnormal teaching contents in a normal education scheme and the repetition rate Jc of the teaching contents;
carrying out normalization processing on the course progress matching rate Pb, the teaching content repetition rate Jc and the abnormal teaching content occupation ratio Zb, and synthesizing to form an abnormal detection value Yp, wherein the abnormal detection value Yp has a judging formula as follows:
in the formula, 0 < beta 1 ≤1、0＜β 2 ≤1、0＜β 3 Not more than 1 and beta 1 +β 2 +β 3 ＝1，
Wherein beta is 1 、β 2 Beta and beta 3 As the weight, lna is the correlation coefficient of course progress matching rate and abnormal teaching content duty ratio, and is calculated by a plurality of groups of course progress matching rate and abnormal teaching content duty ratio.
Comparing the abnormal detection value Yp with a preset abnormal detection value threshold, if the abnormal detection value is higher than the preset abnormal detection value threshold, judging that the education scheme is abnormal temporarily after other factors are considered, displaying the education scheme, if the abnormal detection value is lower than the preset abnormal detection value threshold, analyzing the factors to analyze whether the abnormality exists, and transmitting the abnormality factors to a second optimizing unit.
In this embodiment, after the evaluation of the remote education scheme of the student terminal is completed through the first processing unit, an evaluation result is formed, a corresponding remote education scheme is formed, the remote education scheme output by the first processing unit is received through the optimizing module, and the lifting module, the optimizing module and the first detecting unit are adjusted and detected.
When the remote education evaluation value Jp is larger than the first comparison sub-module, the remote education scheme of a certain student terminal is better than expected, and the next remote education scheme is continued to be carried out on the remote education system of the student terminal, so that the remote education scheme of the student terminal is displayed by using the optimizing module;
when the remote education evaluation value Jp is between the first comparison sub-module and the second comparison sub-module, the current remote education scheme of the student terminal is only proved to achieve the accepted education effect, and the student terminal can continue learning, but the student terminal needs to learn and promote the student terminal;
when the remote education evaluation value Jp is smaller than the second comparison sub-module, it is indicated that the current student terminal remote education program is lower than the education effect expectation, and the remote education program needs to be reset, so that the education program adjustment is performed on the current student terminal remote education.
According to the different remote education schemes, the education schemes are optimized in a targeted manner in consideration of the existence of a plurality of education schemes in the remote education system, and the operation efficiency of the remote education system is improved under the condition that the influence is minimum in the remote education schemes of the student terminals.
Please refer to fig. 1-2 for further disclosure:
when the remote education evaluation value Jp is larger than the first comparison sub-module, detecting by a first detection unit, and outputting a detection result; the second optimizing unit obtains the detection result according to the first detecting unit, determines to select the corresponding remote education scheme, evaluates the corresponding remote education scheme, and outputs the corresponding remote education scheme with the highest evaluation value; and the third optimizing unit receives the corresponding remote education scheme output by the second optimizing unit, checks whether the corresponding remote education scheme is effective or not after the corresponding remote education scheme is subjected to remote education, and sends an early warning to the teacher end if the corresponding remote education scheme is ineffective, so that the teacher terminal is reminded to manually change the remote education scheme.
Referring to fig. 1-2, further disclosure is made based on the foregoing, the first detection unit includes a testing module, an anomaly database and a recording module, wherein,
the test module determines that the remote education evaluation value Jp is not more than the first comparison sub-module, monitors the remote education scheme for one period, determines abnormal characteristics and outputs the abnormal characteristics; the abnormal characteristics refer to single teaching resources, wrong content editing and the like;
the abnormal database acquires abnormal characteristics and compares the abnormal characteristics with known abnormal characteristics in the abnormal database, whether the abnormal characteristics are known abnormal characteristics or not is determined, and if the abnormal characteristics are not known abnormal characteristics, the abnormal characteristics are recorded through the recording module.
In this embodiment, if it is determined that the remote education evaluation value Jp is not greater than the value of the first comparison sub-module, correction of the remote education scheme of the student terminal needs to be considered, and the existing abnormality can be rapidly judged by setting the abnormality feature, so that the workload of modifying the education scheme by the teacher terminal is reduced.
Referring to fig. 1-2, the second optimizing unit includes a teaching resource database, an output module and a second evaluation module,
and when the teaching resource database judges that the abnormal characteristics of the remote education scheme are known abnormal characteristics, the corresponding education scheme is indexed from the teaching resource database according to the corresponding abnormal characteristics, and is output through the output module.
In the embodiment, when the remote education scheme is determined to be abnormal, the difficulty of modifying the education scheme for the remote education scheme by the teacher terminal is facilitated through the index in the teaching resource database, and high-quality remote education service is provided for the student terminal in time.
Referring to fig. 1-2, the third optimizing unit includes a fault question strengthening module and an early warning module,
the error question strengthening module receives the education scheme, carries out targeted optimization on the corresponding abnormal characteristics, carries out abnormal characteristic scanning on remote education after the error question strengthening module completes the optimization on the education scheme, judges whether the abnormality of the education scheme is optimized or not, and evaluates the corresponding education scheme through the second evaluation module according to the judging result to determine whether the education scheme is feasible or not;
the method of evaluating includes the following:
equidistant divisions are made along the direction of the time axis and are labeled i=1, 2, 3,..n-1, n,obtaining remote education evaluation values Jp, respectively n-1 ，Jp n Abnormality detection value Yp n-1 ，Yp n ；
Correlating the remote education evaluation value with the abnormality detection value to form a second evaluation coefficient Pg, wherein the second evaluation coefficient Pg accords with the following formula:
in which 0 < sigma 1 ≤1，0＜λ 2 Less than or equal to 1 and sigma 1 2 +σ 2 2 ＝1.25，
Educational regimens were evaluated at Pg (J, Y) in the following manner:
wherein sigma 1 Sigma (sigma) 2 The weight is specifically adjusted by a manager;
acquiring a second evaluation coefficient Pg and comparing the second evaluation coefficient Pg with a preset second evaluation coefficient threshold value, if the second evaluation coefficient Pg is higher than the preset second evaluation coefficient threshold value, the education scheme is not abnormal, the student terminal continues to use the education scheme, if the second evaluation coefficient Pg is higher than the preset second evaluation coefficient threshold value, the education scheme is abnormal, the abnormal characteristics are transmitted to the early warning module,
after the abnormal features of the remote education are scanned based on the testing module, the early warning module does not index the abnormal features in the abnormal database or index the abnormal features, but sends early warning to the teacher terminal when the corresponding education scheme is not found, and the teacher is reminded to modify and optimize the remote education scheme.
In this embodiment, through the application of the wrong question strengthening module and the early warning module, when the remote education scheme generates abnormal characteristics and when the education scheme is temporarily unavailable, an early warning is sent to the teacher terminal, so that the teacher can conveniently correct and promote the education scheme, and if the teacher has a proper education scheme, the education scheme is recorded in the teaching resource database.
In summary, the invention has the following beneficial effects:
in the remote education system, the student terminal can detect the teaching process of the remote education system through the acquisition unit and the first processing unit, and quantitatively evaluate the learning result of the student terminal, based on the remote education evaluation value, the teacher terminal is convenient to judge whether the education scheme in the remote education system can continue learning, and if the education scheme cannot continue learning or has poor learning effect, corrective measures are taken for the education scheme, so that the learning effect of students is effectively improved.
When the first detection unit, the second optimization unit and the third optimization unit are arranged and the education scheme is judged to be corrected, the education scheme is detected firstly, abnormal problems are found through detection, abnormal characteristics are determined, comparison is conducted from an abnormal database, and a corresponding education scheme is found from a teaching resource library finally, so that the repeated modification time of a teacher terminal is reduced, and accordingly, the remote education system is detected periodically, and the teaching qualification rate of students and the use rate of the remote education system are improved.
It is noted that relational terms such as first and second, and the like, if any, 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. Moreover, 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 one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element. It should be noted that the above-described working procedure is merely illustrative, and does not limit the scope of the present invention, and in practical application, a person skilled in the art may select part or all of them according to actual needs to achieve the purpose of the embodiment, which is not limited herein.
Other embodiments or specific implementations of a 5G network service platform-type remote education system may refer to the above method embodiments, and are not described herein.
Finally: the foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (9)
1. A5G network service platform type remote education system is characterized in that: comprises a collecting unit, a first processing unit, an optimizing module, a lifting module and a optimizing module,
the acquisition unit is used for acquiring data of the student terminals to form acquisition information and comprises a video learning acquisition module, an interaction information acquisition module and an on-line examination acquisition module;
the video learning acquisition module is used for recording online video learning time of the student terminal to form learning time Xt;
the interaction information acquisition module acquires interaction information of the student terminal and the teacher terminal, acquires interaction duration in a current interaction period, and forms interaction duration Js by taking 45 minutes as the interaction period in an exemplary manner;
the on-line assessment acquisition module acquires education achievements of student terminals, takes one learning period or two learning periods or other proper assessment time as an acquisition period, and acquires average achievements in the period to form assessment achievements Sc;
the first processing unit is used for acquiring the acquired information, carrying out teaching evaluation on the acquired information, and forming a teaching adjustment scheme for the remote education mode of the student terminal according to the evaluation result;
the optimizing module is used for receiving the teaching adjustment scheme of the first processing unit, forming an optimizing instruction and optimizing at least one of the lifting module, the optimizing module and the second optimizing unit;
the teaching evaluation module is used for receiving the learning time Xt, the interaction time Js and the assessment score Sc, forming a collection information data set, and performing teaching evaluation to form a remote education evaluation value Jp;
the remote education evaluation value Jp conforms to the following method:
the learning time Xt, the interaction time Js and the assessment score Sc are acquired, subjected to non-dimensionality treatment and correlated through correlation analysis, and the learning time Xt, the interaction time Js and the assessment score Sc accord with the following expression:
in the formula, 0 < alpha 1 ≤1、0＜α 2 ≤1α 2 、0＜α 3 Less than or equal to 1, and alpha 1 +α 2 +α 3 ＝1，
Wherein alpha is 1 、α 2 Alpha and alpha 3 And P is the correlation coefficient of the learning duration and the assessment score, and is obtained by calculating a plurality of groups of learning duration and assessment score.
2. The 5G web service platform based distance education system of claim 1 wherein: the comparison module comprises a first comparison sub-module and a second comparison sub-module, a remote education evaluation value Jp is obtained and compared with the first comparison sub-module and the second comparison sub-module, if the remote education evaluation value is larger than the first comparison sub-module, a first evaluation result is formed, if the remote education evaluation value Jp is between the first comparison sub-module and the second comparison sub-module, a second evaluation result is formed, and if the remote education evaluation value Jp is smaller than the second comparison sub-module, a third evaluation result is formed, and a corresponding teaching adjustment scheme is formed;
the comparison module transmits the first evaluation result, the second evaluation result and the third evaluation result to respectively obtain a first education scheme, a second education scheme and a third education scheme, and the lifting module, the optimizing module and the first detection unit are respectively optimized.
3. The 5G web service platform based distance education system of claim 1 wherein: the optimization module acquires a first education scheme to form a first teaching signal, and the remote education of the student terminal is displayed through the optimizing module;
the optimizing module acquires a second education scheme to form a second teaching signal, the remote education of the student terminal is revealed by the optimizing module, the remote education is detected by the first detecting unit, and a detection result is output;
the optimizing module obtains a third education proposal, forms a third teaching signal, displays the third teaching signal through the lifting module, displays the remote education of the student terminal through the optimizing module, detects the remote education through the first detecting unit, outputs a detection result,
the detection method of the first detection unit comprises the following steps:
when a student terminal starts to display an education scheme, counting the matching rate Pb of teaching contents and course progress in the education scheme from the start of detection to the time of evaluation and detection;
in the detection period, counting the duty ratio Zb of abnormal teaching contents in a normal education scheme and the repetition rate Jc of the teaching contents;
carrying out normalization processing on the course progress matching rate Pb, the teaching content repetition rate Jc and the abnormal teaching content occupation ratio Zb, and synthesizing to form an abnormal detection value Yp, wherein the abnormal detection value Yp has a judging formula as follows:
in the formula, 0 < beta 1 ≤1、0＜β 2 ≤1、0＜β 3 Not more than 1 and beta 1 +β 2 +β 3 ＝1，
Wherein beta is 1 、β 2 Beta and beta 3 As weight, lna is course progress matching rate and abnormalityThe correlation coefficient of the teaching content duty ratio is calculated by a plurality of groups of course progress matching rates and abnormal teaching content duty ratios.
Comparing the abnormal detection value Yp with a preset abnormal detection value threshold, if the abnormal detection value is higher than the preset abnormal detection value threshold, judging that the education scheme is abnormal temporarily after other factors are considered, displaying the education scheme, if the abnormal detection value is lower than the preset abnormal detection value threshold, analyzing the factors to analyze whether the abnormality exists, and transmitting the abnormality factors to a second optimizing unit.
4. A 5G web services platform based distance education system according to claim 3 wherein: the remote education evaluation value Jp is larger than the first comparison sub-module, and is detected by the first detection unit, and a detection result is output; the second optimizing unit obtains the detection result according to the first detecting unit, determines to select the corresponding remote education scheme, evaluates the corresponding remote education scheme, and outputs the corresponding remote education scheme with the highest evaluation value; and the third optimizing unit receives the corresponding remote education scheme output by the second optimizing unit, checks whether the corresponding remote education scheme is effective or not after the corresponding remote education scheme is subjected to remote education, and sends an early warning to the teacher end if the corresponding remote education scheme is ineffective, so that the teacher terminal is reminded to manually change the remote education scheme.
5. The 5G web service platform based distance education system of claim 1 wherein: the test module determines that the remote education evaluation value Jp is not more than the first comparison sub-module, monitors the remote education scheme for one period, determines abnormal characteristics and outputs the abnormal characteristics; the abnormal characteristics are that the teaching resources are single and the content is repeated;
the abnormal database acquires abnormal characteristics and compares the abnormal characteristics with known abnormal characteristics in the abnormal database, whether the abnormal characteristics are known abnormal characteristics or not is determined, and if the abnormal characteristics are not known abnormal characteristics, the abnormal characteristics are recorded through the recording module.
6. The 5G web service platform based distance education system of claim 1 wherein: the second optimizing unit comprises a teaching resource database, an output module and a second evaluation module, wherein when the teaching resource database judges that the abnormal characteristics of the remote education scheme are known abnormal characteristics, the teaching resource database indexes the corresponding education scheme from the teaching resource database according to the corresponding abnormal characteristics and outputs the teaching scheme through the output module.
7. The 5G web service platform based distance education system of claim 1 wherein: the third optimizing unit comprises a wrong question strengthening module, the wrong question strengthening module receives the education scheme and carries out targeted optimization on the corresponding abnormal characteristics, after the wrong question strengthening module completes optimization on the education scheme, the testing module carries out abnormal characteristic scanning on remote education, whether the abnormality of the education scheme is optimized or not is judged, and according to a judging result, the second evaluating module evaluates the corresponding education scheme to determine whether the education scheme is feasible or not.
8. The 5G web service platform based distance education system of claim 7 wherein: the method of evaluating includes the following:
equidistant divisions are made in the direction of the time axis, and are labeled i=1, 2, 3,..n-1, n, and distance education evaluation values Jp are obtained, respectively n-1 ，Jp n Abnormality detection value Yp n-1 ，Yp n ；
Correlating the remote education evaluation value with the abnormality detection value to form a second evaluation coefficient Pg, wherein the second evaluation coefficient Pg accords with the following formula:
in which 0 < sigma 1 ≤1，0＜λ 2 Less than or equal to 1 and sigma 1 2 +σ 2 2 ＝1.25，
Educational regimens were evaluated at Pg (J, Y) in the following manner:
wherein sigma 1 Sigma (sigma) 2 The weight is specifically adjusted by a manager;
and acquiring a second evaluation coefficient Pg and comparing the second evaluation coefficient Pg with a preset second evaluation coefficient threshold value, if the second evaluation coefficient Pg is higher than the preset second evaluation coefficient threshold value, the education scheme is not abnormal, the student terminal continues to use the education scheme, if the second evaluation coefficient Pg is higher than the preset second evaluation coefficient threshold value, the education scheme is abnormal, and the abnormal characteristics are transmitted to the early warning module.
9. The 5G web service platform based distance education system of claim 1 wherein: the third optimizing unit further comprises an early warning module, wherein the early warning module is used for sending early warning to a teacher terminal to remind the teacher of modifying and optimizing the remote education scheme after the testing module scans the abnormal characteristics of the remote education and the abnormal characteristics are not indexed in the abnormal database or are not indexed in the abnormal database, but the corresponding education scheme is not found.
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