CN111091733A - Auxiliary detection system for real-time teaching achievements of teachers - Google Patents
Auxiliary detection system for real-time teaching achievements of teachers Download PDFInfo
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Abstract
The invention discloses a teacher real-time teaching result auxiliary inspection system which comprises a teaching following unit, a content acquisition module, a comprehensive analysis unit, an audience monitoring module, a data analysis unit, a processor, a display unit, a storage unit, an intelligent terminal, a score acquisition unit, a management unit and an auxiliary analysis unit, wherein the content acquisition module is used for acquiring the content of a teacher; the method comprises the steps of analyzing each teaching knowledge point of a teacher through a teaching following unit to obtain the specific knowledge point of the current teacher teaching, informing an audience monitoring module to monitor the specific listening condition of a student at the current finished knowledge point when the next knowledge point is taught, judging whether the student is distracted or not, and obtaining whether the student is distracted or not through data analysis to obtain the corresponding distracted proportion; and meanwhile, according to the analysis of the two data, the concrete conditions of students listening to the class corresponding to each knowledge point are obtained.
Description
Technical Field
The invention belongs to the field of teaching inspection, relates to a teaching achievement auxiliary inspection technology, and particularly relates to a real-time teaching achievement auxiliary inspection system for teachers.
Background
The patent with publication number CN108597280A discloses a teaching system and a teaching method based on learning behavior analysis, which comprises a teaching server, a teacher terminal and student terminals, wherein the teaching server comprises a teaching resource server, a knowledge point testing server, an answering interaction server, a learning behavior data acquisition server, a learning behavior analysis server and a data visualization server, and the learning behavior data acquisition server is used for acquiring various behavior data generated by the student terminals accessing the teaching resource server, the knowledge point testing server and the answering interaction server; the learning behavior analysis server carries out classification analysis on various behavior data collected by the learning behavior data collection server and displays classification analysis results on the data visualization server.
The invention collects various learning behavior data of students in the learning process in real time, evaluates the learning behavior data of each student in a multidimensional quantification manner, dynamically adjusts the teaching content according to the learning behavior analysis result, and develops personalized teaching design for the students.
However, it does not disclose how to effectively analyze the vague nerves of students, and at the same time, it does not provide an analysis method for a single knowledge point of a student, and whether the single knowledge point is mastered, and it can analyze whether the reason of not mastering is because of a teacher teaching method problem, or the reason of not listening to a class by the student; to achieve this technical idea, a solution is now provided.
Disclosure of Invention
The invention aims to provide an auxiliary inspection system for real-time teaching results of teachers.
The purpose of the invention can be realized by the following technical scheme:
a teacher real-time teaching result auxiliary inspection system comprises a teaching following unit, a content acquisition module, a comprehensive analysis unit, an audience monitoring module, a data analysis unit, a processor, a display unit, a storage unit, an intelligent terminal, a score acquisition unit, a management unit and an auxiliary analysis unit;
the teaching following unit is used for acquiring teaching character information of teaching contents of a teacher;
the teaching following unit is used for transmitting teaching character information to the content acquisition module, and the content acquisition module is used for carrying out content analysis on the teaching character information to obtain a teaching knowledge point group and corresponding teaching duration information; the teaching duration information comprises a start time, an end time and an interval time;
the content acquisition module is used for transmitting the teaching knowledge point group and the corresponding teaching duration information to the comprehensive analysis unit, and the comprehensive analysis unit receives the teaching knowledge point group and the corresponding teaching duration information transmitted by the content acquisition module;
the content acquisition module transmits the teaching knowledge points and the corresponding teaching duration information to the audience monitoring module when generating a stage ending signal, and the audience monitoring module automatically acquires the audience image according to the teaching duration information to obtain stage image information when receiving the stage ending signal transmitted by the content acquisition module;
the audience monitoring module is used for transmitting the stage image information to the data analysis unit, and the data analysis unit receives the stage image information transmitted by the audience monitoring module and carries out concentration analysis on the stage image information to obtain a vague mean value with cognitive identification;
the data analysis unit is used for transmitting the vague mean value with the cognitive identifier to the comprehensive analysis unit, and the comprehensive analysis unit receives the vague mean value with the cognitive identifier transmitted by the data analysis unit;
the comprehensive analysis unit is used for carrying out efficiency analysis on the vagus mean value, the teaching knowledge point group and the corresponding teaching duration information to obtain teaching knowledge points Zj and corresponding dropout ratios Scj;
the comprehensive analysis unit is used for transmitting the teaching knowledge points Zj and the corresponding loss ratio Scj to the processor, and the processor receives the teaching knowledge points Zj and the corresponding loss ratio Scj transmitted by the comprehensive analysis unit;
the score acquisition unit is used for acquiring examination paper information of students, wherein the examination paper information is examination paper of corresponding students and corresponding knowledge points and score information; and transmitting the test paper information to an auxiliary analysis unit, wherein the auxiliary analysis unit is used for carrying out probability analysis on the test paper information to obtain the correct probability of each knowledge point, and the acquisition method comprises the following steps:
the method comprises the following steps: acquiring each knowledge point of the test paper information, acquiring whether each corresponding knowledge point is mastered or not, and evaluating whether the mastered knowledge point is mastered or not by means of the score of a student at the knowledge point;
step two: when the proportion of the score to the total score of the knowledge points exceeds a preset proportion X3, marking the knowledge points as mastered, otherwise, marking the knowledge points as not mastered; x3 is a preset value;
step three: acquiring the proportion of students mastering the knowledge points in all students in the total students, marking the students as the mastering proportion of the corresponding knowledge points, and endowing the cognitive identification of the corresponding knowledge points;
the auxiliary analysis unit is used for transmitting the mastery proportion with the cognitive identification to the processor;
the processor is used for carrying out mastering analysis on the mastering proportion with the cognitive identification, the teaching knowledge points Zj and the corresponding lost difference ratio Scj, and the mastering analysis steps are as follows:
step SS 001: acquiring a mastered proportion with cognitive identification, and marking the mastered proportion as Zwj, j =1.. l; zwj are in one-to-one correspondence with Zj and Scj;
step SS 002: calculating the grasping value according to a formula
When Zwj > X4, marking the corresponding knowledge point Zj as a mastered knowledge point;
when Zwj is less than or equal to X4, if Scj is less than or equal to X5, marking the corresponding knowledge points as quality-enhanced knowledge points;
when Zwj is less than or equal to X4, if Scj > X5 is satisfied, the corresponding knowledge point is marked as an added-effect knowledge point;
the processor is also used for transmitting the mastered knowledge points, the quality-enhancing knowledge points and the effect-adding knowledge points to an intelligent terminal corresponding to the teacher, and the intelligent terminal is a mobile phone;
the management unit is used for recording all preset values X1, X2, X3, X4, X5 and T1.
Further, the method for acquiring the teaching text information comprises the following steps:
the method comprises the following steps: pre-storing voiceprint information corresponding to a teacher, and performing voiceprint matching when the teacher performs teaching to obtain teaching voice of the teacher;
step two: and performing character conversion processing on the teaching voice to obtain teaching character information consisting of characters.
Further, the content analysis comprises the following specific steps:
the method comprises the following steps: all knowledge points corresponding to the teaching subjects of the teacher are preset in the content acquisition module, the knowledge points are key knowledge points of the corresponding subjects pre-recorded by the teacher, and the key knowledge points are marked as reference knowledge information;
step two: the teaching character information who acquires the teacher refines teaching character information, and the process of refining is:
step S1: acquiring teaching character information in real time, and performing word segmentation processing on the teaching character information to obtain teaching character information consisting of a plurality of split words;
step S2: marking the splitting words as Ci, i =1.. n, n being a positive integer greater than zero; acquiring the occurrence frequency of each split word, and when the occurrence frequency reaches a preset frequency X1, marking the corresponding split word as an annotation word Bi, wherein i =1.
Step S3: comparing the labeled words with the labeled reference knowledge information to obtain labeled reference knowledge information corresponding to the labeled words, and obtaining knowledge points at the moment, and marking the corresponding labeled reference knowledge information as teaching knowledge points;
step three: continuously repeating the step two when the teaching knowledge point is obtained, generating a stage ending signal when a new teaching knowledge point is identified, and acquiring teaching duration information corresponding to the teaching knowledge point, wherein the teaching duration information comprises a starting time, an ending time and an interval time, the starting time is the starting time corresponding to the teaching knowledge point, the ending time is the ending time corresponding to the teaching knowledge point, and the interval time is the teaching duration of the teaching knowledge point; until the teacher finishes teaching;
step four: and repeating the third step to obtain a teaching knowledge point group formed by all teaching knowledge points learned by the teacher and corresponding teaching duration information.
Further, the audience image acquisition specifically includes:
step S100: when a stage ending signal is received, automatically acquiring the starting time and the ending time in the teaching duration information;
step S200: acquiring real-time image information of students between the starting time and the ending time of the students in a teacher by using image acquisition equipment in the audience monitoring module, and marking the image information as stage image information;
step S300: and matching the stage image information with the corresponding teaching knowledge points, and endowing the stage image information and the corresponding teaching knowledge points with the same cognitive identification.
Further, the specific steps of the concentration analysis are as follows:
step S010: acquiring stage image information, and carrying out next operation on each student in the stage image information;
step S020: selecting image information of any student;
step S030: acquiring characteristic point lines of students, wherein the characteristic point lines are connecting lines of lowest points of earlobes on the left side and the right side of a user;
step S040: acquiring a desktop transverse line of a student desk, wherein the desktop transverse line refers to a line parallel to the characteristic point line when a student looks at a blackboard and sits up;
step S050: acquiring an included angle between the characteristic point line and the desktop transverse line, and marking the included angle as a characteristic included angle; and the characteristic included angle is an acute angle value;
step S060, when the characteristic included angle is less than or equal to α and the duration is longer than T1, determining that the student is in the vague state, wherein α and T1 are preset values;
if the switching frequency of the student between the vague side and the conventional side is more than or equal to X2, judging that the student is vague;
step S070: acquiring the vague time of the student according to the principle of the step S060;
step S080: acquiring the vague time of all students, calculating an average value, and marking the average value as a vague mean value;
step S090: and marking the vagus nerve mean value with the cognitive mark which is the same as the image information of the corresponding stage.
Further, the specific steps of the efficiency analysis are as follows:
step SS 01: marking all teaching knowledge points in the teaching knowledge point group as Zj, j =1.. l, wherein l is a positive integer larger than zero;
step SS 02: any teaching knowledge point is taken to obtain a corresponding nerve mean value and interval time in the teaching duration information;
step SS 03: dividing the mean vagal value by the interval time to obtain the loss ratio;
step SS 04: taking the next teaching knowledge point, and repeating the steps SS02-SS04 until all teaching knowledge points are analyzed;
step SS 05: and marking the error ratios corresponding to all the teaching knowledge points Zj as Scj, j =1.. l, wherein Scj and Zj are in one-to-one correspondence.
Further, the processor is configured to transmit the learned knowledge points, the qualitative knowledge points, and the effective knowledge points to the display unit, and the display unit receives the learned knowledge points transmitted by the processor and displays "substantially completely learned knowledge points + learned knowledge points".
Further, when the display unit receives the quality-enhancing knowledge points transmitted by the processor, the display unit automatically displays 'change of the current knowledge points to be noticed in the teaching mode + the quality-enhancing knowledge points'; the display unit receives the adding effect knowledge points transmitted by the processor and automatically displays the teaching time length which needs to be supplemented and the adding effect knowledge points of the current knowledge points due to the distraction of students.
Further, the processor is used for transmitting the mastered knowledge points, the quality-enhancing knowledge points and the effective knowledge points to the storage unit for real-time storage.
The invention has the beneficial effects that:
the method comprises the steps of analyzing each teaching knowledge point of a teacher through a teaching following unit to obtain the specific knowledge point of the current teacher teaching, informing an audience monitoring module to monitor the specific listening condition of a student at the current finished knowledge point when the next knowledge point is taught, judging whether the student is distracted or not, and obtaining whether the student is distracted or not through data analysis to obtain the corresponding distracted proportion; meanwhile, according to the analysis of the two, the concrete conditions of students corresponding to each knowledge point during listening are obtained;
then, the score of the student is analyzed through a score acquisition unit and an auxiliary analysis unit to obtain the mastering conditions of each knowledge point of the student, and the comprehensive analysis is performed on the corresponding knowledge points according to the mastering conditions of each knowledge point and the class listening quality of the student at each knowledge point, so that the situation of each knowledge point is not reasonably mastered; the invention is simple, effective and easy to use.
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In order to facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
FIG. 1 is a system block diagram of the teacher real-time teaching result auxiliary inspection system of the present invention.
Detailed Description
As shown in fig. 1, a teacher real-time teaching result auxiliary inspection system includes a teaching following unit, a content acquisition module, a comprehensive analysis unit, an audience monitoring module, a data analysis unit, a processor, a display unit, a storage unit, an intelligent terminal, a score acquisition unit, a management unit, and an auxiliary analysis unit;
the teaching following unit is used for acquiring teaching contents of a teacher, and the acquisition method comprises the following steps:
the method comprises the following steps: pre-storing voiceprint information corresponding to a teacher, and performing voiceprint matching when the teacher performs teaching to obtain teaching voice of the teacher;
step two: performing text-to-text processing on the teaching voice to obtain teaching text information consisting of characters;
the teaching following unit is used for transmitting teaching character information to the content acquisition module, the content acquisition module is used for carrying out content analysis on the teaching character information, and the specific steps of the content analysis are as follows:
the method comprises the following steps: all knowledge points corresponding to the teaching subjects of the teacher are preset in the content acquisition module, the knowledge points are key knowledge points of the corresponding subjects pre-recorded by the teacher, and the key knowledge points are marked as reference knowledge information;
step two: the teaching character information who acquires the teacher refines teaching character information, and the process of refining is:
step S1: acquiring teaching character information in real time, and performing word segmentation processing on the teaching character information to obtain teaching character information consisting of a plurality of split words;
step S2: marking the splitting words as Ci, i =1.. n, n being a positive integer greater than zero; acquiring the occurrence frequency of each split word, and when the occurrence frequency reaches a preset frequency X1, marking the corresponding split word as an annotation word Bi, wherein i =1.
Step S3: comparing the labeled words with the labeled reference knowledge information to obtain labeled reference knowledge information corresponding to the labeled words, and obtaining knowledge points at the moment, and marking the corresponding labeled reference knowledge information as teaching knowledge points;
step three: continuously repeating the step two when the teaching knowledge point is obtained, generating a stage ending signal when a new teaching knowledge point is identified, and acquiring teaching duration information corresponding to the teaching knowledge point, wherein the teaching duration information comprises a starting time, an ending time and an interval time, the starting time is the starting time corresponding to the teaching knowledge point, the ending time is the ending time corresponding to the teaching knowledge point, and the interval time is the teaching duration of the teaching knowledge point; until the teacher finishes teaching;
step four: repeating the third step to obtain a teaching knowledge point group formed by all teaching knowledge points learned by the teacher and corresponding teaching duration information;
the content acquisition module is used for transmitting the teaching knowledge point group and the corresponding teaching duration information to the comprehensive analysis unit, and the comprehensive analysis unit receives the teaching knowledge point group and the corresponding teaching duration information transmitted by the content acquisition module;
when the content acquisition module generates a stage end signal, the teaching knowledge point and the corresponding teaching time length information are transmitted to the audience monitoring module, when the audience monitoring module receives the stage end signal transmitted by the content acquisition module, the audience image acquisition is automatically carried out according to the teaching time length information, and the specific acquisition step is as follows:
step S100: when a stage ending signal is received, automatically acquiring the starting time and the ending time in the teaching duration information;
step S200: acquiring real-time image information of students between the starting time and the ending time of the students in a teacher by using image acquisition equipment in the audience monitoring module, and marking the image information as stage image information;
step S300: matching the stage image information with the corresponding teaching knowledge points, and endowing the stage image information and the corresponding teaching knowledge points with the same cognitive identification;
audience monitoring module is used for transmitting stage image information to data analysis unit, data analysis unit receives the stage image information that audience monitoring module transmitted to concentrate on the analysis to it, and the concrete step of concentrating on the analysis is:
step S010: acquiring stage image information, and carrying out next operation on each student in the stage image information;
step S020: selecting image information of any student;
step S030: acquiring characteristic point lines of students, wherein the characteristic point lines are connecting lines of lowest points of earlobes on the left side and the right side of a user;
step S040: acquiring a desktop transverse line of a student desk, wherein the desktop transverse line refers to a line parallel to the characteristic point line when a student looks at a blackboard and sits up;
step S050: acquiring an included angle between the characteristic point line and the desktop transverse line, and marking the included angle as a characteristic included angle; and the characteristic included angle is an acute angle value;
step S060, when the characteristic included angle is less than or equal to α and the duration is longer than T1, determining that the student is in the vague state, wherein α and T1 are preset values;
if the switching frequency of the student between the vague side and the conventional side is more than or equal to X2, judging that the student is vague;
step S070: acquiring the vague time of the student according to the principle of the step S060;
step S080: acquiring the vague time of all students, calculating an average value, and marking the average value as a vague mean value;
step S090: marking the vague mean value with a cognitive identifier which is the same as the image information of the corresponding stage;
the data analysis unit is used for transmitting the vague mean value with the cognitive identifier to the comprehensive analysis unit, and the comprehensive analysis unit receives the vague mean value with the cognitive identifier transmitted by the data analysis unit;
the comprehensive analysis unit is used for carrying out efficiency analysis on the vagus mean value, the teaching knowledge point group and the corresponding teaching duration information, and the specific steps of the efficiency analysis are as follows:
step SS 01: marking all teaching knowledge points in the teaching knowledge point group as Zj, j =1.. l, wherein l is a positive integer larger than zero;
step SS 02: any teaching knowledge point is taken to obtain a corresponding nerve mean value and interval time in the teaching duration information;
step SS 03: dividing the mean vagal value by the interval time to obtain the loss ratio;
step SS 04: taking the next teaching knowledge point, and repeating the steps SS02-SS04 until all teaching knowledge points are analyzed;
step SS 05: marking the loss difference ratios corresponding to all the teaching knowledge points Zj as Scj, wherein j =1.. l, and the Scj and the Zj are in one-to-one correspondence;
the comprehensive analysis unit is used for transmitting the teaching knowledge points Zj and the corresponding loss ratio Scj to the processor, and the processor receives the teaching knowledge points Zj and the corresponding loss ratio Scj transmitted by the comprehensive analysis unit;
the score acquisition unit is used for acquiring examination paper information of students, wherein the examination paper information is examination paper of corresponding students and corresponding knowledge points and score information; and transmitting the test paper information to an auxiliary analysis unit, wherein the auxiliary analysis unit is used for carrying out probability analysis on the test paper information to obtain the correct probability of each knowledge point, and the acquisition method comprises the following steps:
the method comprises the following steps: acquiring each knowledge point of the test paper information, acquiring whether each corresponding knowledge point is mastered or not, and evaluating whether the mastered knowledge point is mastered or not by means of the score of a student at the knowledge point;
step two: when the proportion of the score to the total score of the knowledge points exceeds a preset proportion X3, marking the knowledge points as mastered, otherwise, marking the knowledge points as not mastered; x3 is a preset value;
step three: acquiring the proportion of students mastering the knowledge points in all students in the total students, marking the students as the mastering proportion of the corresponding knowledge points, and endowing the cognitive identification of the corresponding knowledge points;
the auxiliary analysis unit is used for transmitting the mastery proportion with the cognitive identification to the processor;
the processor is used for carrying out mastering analysis on the mastering proportion with the cognitive identification, the teaching knowledge points Zj and the corresponding lost difference ratio Scj, and the mastering analysis steps are as follows:
step SS 001: acquiring a mastered proportion with cognitive identification, and marking the mastered proportion as Zwj, j =1.. l; zwj are in one-to-one correspondence with Zj and Scj;
step SS 002: calculating the grasping value according to a formula
When Zwj > X4, marking the corresponding knowledge point Zj as a mastered knowledge point;
when Zwj is less than or equal to X4, if Scj is less than or equal to X5, marking the corresponding knowledge points as quality-enhanced knowledge points;
when Zwj is less than or equal to X4, if Scj > X5 is satisfied, the corresponding knowledge point is marked as an added-effect knowledge point;
the processor is used for transmitting the mastered knowledge points, the quality-enhancing knowledge points and the effect-adding knowledge points to the display unit, and the display unit receives the mastered knowledge points transmitted by the processor and displays 'knowledge points which are basically and completely mastered + knowledge points which are mastered';
when the display unit receives the quality-enhancing knowledge points transmitted by the processor, the display unit automatically displays the 'change of the current knowledge point which needs to pay attention to the teaching mode + the quality-enhancing knowledge points';
the display unit receives the adding effect knowledge points transmitted by the processor and automatically displays the teaching time length which needs to be supplemented and the adding effect knowledge points of the current knowledge points due to the distraction of students.
The processor is used for transmitting the mastered knowledge points, the quality-enhancing knowledge points and the effect-adding knowledge points to the storage unit for real-time storage.
The processor is further used for transmitting the mastered knowledge points, the quality-enhancing knowledge points and the effect-adding knowledge points to an intelligent terminal corresponding to the teacher, and the intelligent terminal is a mobile phone.
The management unit is used for recording all preset values X1, X2, X3, X4, X5 and T1.
A teacher real-time teaching achievement auxiliary inspection system is characterized in that during working, each teaching knowledge point of a teacher is analyzed through a teaching following unit to obtain the specific knowledge point taught by the teacher at present, and when the next knowledge point is taught, an audience monitoring module is informed to monitor the specific teaching listening condition of a currently finished knowledge point student and determine whether the student is distracted or not, and whether the student is distracted or not is obtained through data analysis to obtain the corresponding distracted proportion; meanwhile, according to the analysis of the two, the concrete conditions of students corresponding to each knowledge point during listening are obtained;
then, the score of the student is analyzed through a score acquisition unit and an auxiliary analysis unit to obtain the mastering conditions of each knowledge point of the student, and the comprehensive analysis is performed on the corresponding knowledge points according to the mastering conditions of each knowledge point and the class listening quality of the student at each knowledge point, so that the situation of each knowledge point is not reasonably mastered; the invention is simple, effective and easy to use.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (9)
1. A teacher real-time teaching result auxiliary inspection system is characterized by comprising a teaching following unit, a content acquisition module, a comprehensive analysis unit, an audience monitoring module, a data analysis unit, a processor, a display unit, a storage unit, an intelligent terminal, a score acquisition unit, a management unit and an auxiliary analysis unit;
the teaching following unit is used for acquiring teaching character information of teaching contents of a teacher;
the teaching following unit is used for transmitting teaching character information to the content acquisition module, and the content acquisition module is used for carrying out content analysis on the teaching character information to obtain a teaching knowledge point group and corresponding teaching duration information; the teaching duration information comprises a start time, an end time and an interval time;
the content acquisition module is used for transmitting the teaching knowledge point group and the corresponding teaching duration information to the comprehensive analysis unit, and the comprehensive analysis unit receives the teaching knowledge point group and the corresponding teaching duration information transmitted by the content acquisition module;
the content acquisition module transmits the teaching knowledge points and the corresponding teaching duration information to the audience monitoring module when generating a stage ending signal, and the audience monitoring module automatically acquires the audience image according to the teaching duration information to obtain stage image information when receiving the stage ending signal transmitted by the content acquisition module;
the audience monitoring module is used for transmitting the stage image information to the data analysis unit, and the data analysis unit receives the stage image information transmitted by the audience monitoring module and carries out concentration analysis on the stage image information to obtain a vague mean value with cognitive identification;
the data analysis unit is used for transmitting the vague mean value with the cognitive identifier to the comprehensive analysis unit, and the comprehensive analysis unit receives the vague mean value with the cognitive identifier transmitted by the data analysis unit;
the comprehensive analysis unit is used for carrying out efficiency analysis on the vagus mean value, the teaching knowledge point group and the corresponding teaching duration information to obtain teaching knowledge points Zj and corresponding dropout ratios Scj;
the comprehensive analysis unit is used for transmitting the teaching knowledge points Zj and the corresponding loss ratio Scj to the processor, and the processor receives the teaching knowledge points Zj and the corresponding loss ratio Scj transmitted by the comprehensive analysis unit;
the score acquisition unit is used for acquiring examination paper information of students, wherein the examination paper information is examination paper of corresponding students and corresponding knowledge points and score information; and transmitting the test paper information to an auxiliary analysis unit, wherein the auxiliary analysis unit is used for carrying out probability analysis on the test paper information to obtain the correct probability of each knowledge point, and the acquisition method comprises the following steps:
the method comprises the following steps: acquiring each knowledge point of the test paper information, acquiring whether each corresponding knowledge point is mastered or not, and evaluating whether the mastered knowledge point is mastered or not by means of the score of a student at the knowledge point;
step two: when the proportion of the score to the total score of the knowledge points exceeds a preset proportion X3, marking the knowledge points as mastered, otherwise, marking the knowledge points as not mastered; x3 is a preset value;
step three: acquiring the proportion of students mastering the knowledge points in all students in the total students, marking the students as the mastering proportion of the corresponding knowledge points, and endowing the cognitive identification of the corresponding knowledge points;
the auxiliary analysis unit is used for transmitting the mastery proportion with the cognitive identification to the processor;
the processor is used for carrying out mastering analysis on the mastering proportion with the cognitive identification, the teaching knowledge points Zj and the corresponding lost difference ratio Scj, and the mastering analysis steps are as follows:
step SS 001: acquiring a mastered proportion with cognitive identification, and marking the mastered proportion as Zwj, j =1.. l; zwj are in one-to-one correspondence with Zj and Scj;
step SS 002: calculating the grasping value according to a formula
When Zwj > X4, marking the corresponding knowledge point Zj as a mastered knowledge point;
when Zwj is less than or equal to X4, if Scj is less than or equal to X5, marking the corresponding knowledge points as quality-enhanced knowledge points;
when Zwj is less than or equal to X4, if Scj > X5 is satisfied, the corresponding knowledge point is marked as an added-effect knowledge point;
the processor is also used for transmitting the mastered knowledge points, the quality-enhancing knowledge points and the effect-adding knowledge points to an intelligent terminal corresponding to the teacher, and the intelligent terminal is a mobile phone;
the management unit is used for recording all preset values X1, X2, X3, X4, X5 and T1.
2. The system for assisting in the examination of the teaching achievement of a teacher in real time as claimed in claim 1, wherein the teaching text information acquisition method is as follows:
the method comprises the following steps: pre-storing voiceprint information corresponding to a teacher, and performing voiceprint matching when the teacher performs teaching to obtain teaching voice of the teacher;
step two: and performing character conversion processing on the teaching voice to obtain teaching character information consisting of characters.
3. The system for assisting in the examination of the teaching performance of teachers in real time as claimed in claim 1, wherein the content analysis comprises the specific steps of:
the method comprises the following steps: all knowledge points corresponding to the teaching subjects of the teacher are preset in the content acquisition module, the knowledge points are key knowledge points of the corresponding subjects pre-recorded by the teacher, and the key knowledge points are marked as reference knowledge information;
step two: the teaching character information who acquires the teacher refines teaching character information, and the process of refining is:
step S1: acquiring teaching character information in real time, and performing word segmentation processing on the teaching character information to obtain teaching character information consisting of a plurality of split words;
step S2: marking the splitting words as Ci, i =1.. n, n being a positive integer; acquiring the occurrence frequency of each split word, and when the occurrence frequency reaches a preset frequency X1, marking the corresponding split word as an annotation word Bi, wherein i =1.
Step S3: comparing the labeled words with the labeled reference knowledge information to obtain labeled reference knowledge information corresponding to the labeled words, and obtaining knowledge points at the moment, and marking the corresponding labeled reference knowledge information as teaching knowledge points;
step three: continuously repeating the step two when the teaching knowledge point is obtained, generating a stage ending signal when a new teaching knowledge point is identified, and acquiring teaching duration information corresponding to the teaching knowledge point, wherein the teaching duration information comprises a starting time, an ending time and an interval time, the starting time is the starting time corresponding to the teaching knowledge point, the ending time is the ending time corresponding to the teaching knowledge point, and the interval time is the teaching duration of the teaching knowledge point; until the teacher finishes teaching;
step four: and repeating the third step to obtain a teaching knowledge point group formed by all teaching knowledge points learned by the teacher and corresponding teaching duration information.
4. The system for assisting in the examination of the results of real-time teacher's teaching according to claim 1, wherein the audience image acquisition comprises the following specific steps:
step S100: when a stage ending signal is received, automatically acquiring the starting time and the ending time in the teaching duration information;
step S200: acquiring real-time image information of students between the starting time and the ending time of the students in a teacher by using image acquisition equipment in the audience monitoring module, and marking the image information as stage image information;
step S300: and matching the stage image information with the corresponding teaching knowledge points, and endowing the stage image information and the corresponding teaching knowledge points with the same cognitive identification.
5. The system for assisting in the examination of the results of real-time teacher's teaching according to claim 1, wherein said specific steps of focusing on the analysis are:
step S010: acquiring stage image information, and carrying out next operation on each student in the stage image information;
step S020: selecting image information of any student;
step S030: acquiring characteristic point lines of students, wherein the characteristic point lines are connecting lines of lowest points of earlobes on the left side and the right side of a user;
step S040: acquiring a desktop transverse line of a student desk, wherein the desktop transverse line refers to a line parallel to the characteristic point line when a student looks at a blackboard and sits up;
step S050: acquiring an included angle between the characteristic point line and the desktop transverse line, and marking the included angle as a characteristic included angle; and the characteristic included angle is an acute angle value;
step S060, when the characteristic included angle is less than or equal to α and the duration is longer than T1, determining that the student is in the vague state, wherein α and T1 are preset values;
if the switching frequency of the student between the vague side and the conventional side is more than or equal to X2, judging that the student is vague;
step S070: acquiring the vague time of the student according to the principle of the step S060;
step S080: acquiring the vague time of all students, calculating an average value, and marking the average value as a vague mean value;
step S090: and marking the vagus nerve mean value with the cognitive mark which is the same as the image information of the corresponding stage.
6. The system for assisting in the examination of the results of real-time teacher's teaching according to claim 1, wherein the specific steps of the efficiency analysis are as follows:
step SS 01: marking all teaching knowledge points in the teaching knowledge point group as Zj, j =1.. l, wherein l is a positive integer larger than zero;
step SS 02: any teaching knowledge point is taken to obtain a corresponding nerve mean value and interval time in the teaching duration information;
step SS 03: dividing the mean vagal value by the interval time to obtain the loss ratio;
step SS 04: taking the next teaching knowledge point, and repeating the steps SS02-SS04 until all teaching knowledge points are analyzed;
step SS 05: and marking the error ratios corresponding to all the teaching knowledge points Zj as Scj, j =1.. l, wherein Scj and Zj are in one-to-one correspondence.
7. The system of claim 1, wherein the processor is configured to transmit the learned knowledge points, the enriched knowledge points, and the enhanced knowledge points to the display unit, and the display unit receives the learned knowledge points transmitted from the processor and displays "substantially fully learned knowledge points + learned knowledge points".
8. The system for assisting in examining results of real-time teaching by teachers as claimed in claim 1, wherein the display unit, upon receiving the enriched knowledge points transmitted from the processor, automatically displays "change of teaching mode to be noticed at current knowledge point + enriched knowledge points";
the display unit receives the adding effect knowledge points transmitted by the processor and automatically displays the teaching time length which needs to be supplemented and the adding effect knowledge points of the current knowledge points due to the distraction of students.
9. The system of claim 1, wherein the processor is configured to transmit the learned knowledge points, the enriched knowledge points, and the validated knowledge points to the storage unit for real-time storage.
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