CN107958351A - Teaching quality assessment cloud service platform - Google Patents
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Abstract
The present invention relates to instruction management platform technical field, specially a kind of Teaching Quality Assessment cloud service platform, including cloud server and classroom terminal, classroom terminal is arranged in each classroom, classroom terminal includes classroom data acquisition module, terminal control module and network communication module, terminal control module passes through network communication module and cloud server network connection, terminal control module can control classroom data collecting module collected classroom data and by the classroom data sending of classroom data collecting module collected to cloud server according to the control signal of cloud server, classroom data include video data；Cloud server includes data memory module, assessment management module, data analysis module, data evaluation module.Teaching Quality Assessment cloud service platform provided by the invention, it is cumbersome time-consuming can to solve the problems, such as to exist during existing Teaching Quality Assessment very big randomness and subjectivity, statistic processes.
Description
Technical field
The present invention relates to instruction management platform technical field, is put down in particular to a kind of Teaching Quality Assessment cloud service
Platform.
Background technology
With advances in technology, multimedia teaching assistant system is applied in modern classroom teaching more and more widely,
Make the originally dull richer diversity of teaching and interest.
For a long time, on how to tracking the teaching quality of teacher, how to understand student in depth to different courses or same
The interest-degree of course difference knowledge point and the effect that different teachers give lessons same course how is grasped and compares, many researchs
Mechanism and personnel have carried out substantial amounts of research work.
In general, the basic data in these research work rely primarily on selective examination enquirement, questionnaire survey, teacher or
The personnel such as teaching supervisor carry out with the mode such as hall observation and subjective statistics, statistic processes is loaded down with trivial details time-consuming, it is necessary to special messenger listens to the teacher, effect
Rate is low, and after assessment, and student or teacher can not see the course of other prominent teachers, is unfavorable for excellent course and outstanding
The popularization of teaching method.
The content of the invention
The invention is intended to provide a kind of Teaching Quality Assessment cloud service platform, existing Teaching Quality Assessment process can be solved
In there are statistic processes it is cumbersome time-consuming the problem of.
In order to solve the above-mentioned technical problem, this patent provides following basic technology scheme：
Teaching Quality Assessment cloud service platform, including cloud server, classroom terminal and student terminal, wherein：
The classroom terminal is arranged in each classroom, and the classroom terminal includes classroom data acquisition module, terminal control
Molding block and network communication module, the terminal control module pass through network communication module and cloud server network connection, institute
Classroom data collecting module collected classroom data can be controlled simultaneously according to the control signal of cloud server by stating terminal control module
By the classroom data sending of classroom data collecting module collected to cloud server；
Student terminal and cloud server network connection, student terminal are used to check course ranking and recommendation class for student
Journey, viewing classroom instruction is live and is scored online for course；
The cloud server includes data memory module, assessment management module, data analysis module, data assessment mould
Block, course ranking module, course recommending module and live teaching broadcast module；
The data memory module is stored with lesson data, and the lesson data includes course master data, identification
Data, classroom assessment data record, Curriculum Evaluation result；
The lesson data control that the assessment management module is used in memory module teaches indoor classroom whole accordingly
End carries out the collection and transmission of classroom data；
The data analysis module is used to analyze the data that classroom data collecting module collected arrives, and generates analysis result；
The data evaluation module is used to quality of instruction is assessed to obtain according to the analysis result of data analysis module
Score under course line, the data evaluation module be additionally operable to according to student terminal score online to scoring on course line, and
According to the Emergent Curriculum assessment result that scores on scoring under course line and course line；
The course ranking module is used to carry out ranking according to Curriculum Evaluation result to course, and course recommending module is used for root
Recommend course to student terminal according to course ranking, live teaching broadcast module is used for attending class to other live teachers of student terminal
Journey.
In technical solution of the present invention, classroom terminal is arranged in each classroom, the data memory module of cloud server
In be stored with the lesson data with assessment course, including course master data, such as class period, place of attending class, the teacher that attends class, learn
Stranger's number etc., assessment management module can automatically control according to class period and place of attending class and teach indoor classroom terminal accordingly
The collection of classroom data is carried out, is then analyzed by data analysis module, data evaluation module is further according to data analysis module
Analysis result Emergent Curriculum assessment result.Background system can control the classroom terminal automatic collection note where course to be assessed
The classroom data of each class are recorded, specially go to listen to the teacher without special messenger, the workload in the evaluation process that cuts down the curriculum；
To student terminal recommended according to Curriculum Evaluation result Emergent Curriculum ranking and according to ranking, student can lead to
The teaching quality that student terminal learns each teacher is crossed, by live teaching broadcast module, student can be allowed to learn the excellent of other teachers
Matter course, can also allow the teaching form and method of other teachers of teacher learning, allow student can on line to quality of instruction into
Row scoring, can allow teacher to receive the ballot of the student of full platform, number of samples bigger, more truly, on platform, Xue Shenghe
Do not known each other between teacher, therefore evaluation result is more just.
Further, the classroom data include video data, and the data analysis module includes analysis module, described
Analysis module includes recognition of face submodule and action recognition submodule, and the recognition of face submodule is used for according to identity
The identity of personnel in identification data identification video data, the action recognition submodule are used to identify that video data middle school student act
Or posture；The data evaluation module includes：
Attendance evaluation module, the attendance evaluation module are used for recognition result and course base according to recognition of face submodule
Notebook data generates student attendance data；
Interactive evaluation module, the interactive evaluation module are used to count teachers and students according to the recognition result of action recognition submodule
Interactive number data；
Enthusiasm evaluation module, the enthusiasm evaluation module are used for recognition result and class according to action recognition submodule
Journey master data generates Students' enthusiasm data；
Online scoring statistical module, for the online scoring of statistic terminal-pair course, scores on Emergent Curriculum line；
Statistical module is assessed, the assessment statistical module is used to comment in the classroom of classroom assessment data update to memory module
Estimate in data record, while generated according to classroom assessment data record and scored under the course line of the course, and according on course line
The Emergent Curriculum assessment result that scores under scoring and course line simultaneously updates storage mould Curriculum Evaluation in the block as a result, the classroom assessment
Data include student attendance data, student's action discipline data, interactive number data and Students' enthusiasm data.
Classroom data include video data, and data analysis module recognition of face can be carried out to video data and action is known
Not, so as to identify the student and teacher in video data, attendance evaluation module can be according to the recognition result of recognition of face
The attendance datas such as the rate of attendance of this class, late rate, rate of leaving early are calculated, interactive evaluation module is according to action recognition as a result, can
To filter out the action that student raises one's hand, classroom, can be divided into more by the time interval that interactive evaluation module is raised one's hand according to student
A different interaction time section, and then classroom interactions' number data can be obtained, enthusiasm evaluation module is raised one's hand according to student
Quantity, then by calculating accordingly, such as calculate the accounting for the student that raises one's hand, you can obtain Students' enthusiasm data, assessment statistics
Above-mentioned several data have been counted the classroom assessment data for being used as this class by module together, and this is assessed data record
Into the classroom assessment data record of data memory module, then all classroom assessments in classroom assessment data record are recorded
Added up, ultimately generate the Curriculum Evaluation result of whole subject and be synchronized in data memory module.
By attendance evaluation module, interactive evaluation module and enthusiasm evaluation module from student attendance, interactive number, ask
Three aspect generation classroom assessment data of enthusiasm are answered, student attendance shows the ability in terms of the class management of teacher, interactive
Number then embodies the teaching method of teacher and the control ability of classroom atmosphere, and question and answer enthusiasm then embodies the teaching side of teacher
Ability in terms of method and teaching efficiency, and by assessing statistical module by these three aggregation of data, it is all raw to each class
It is simple and convenient efficient into classroom assessment as a result, without manually being evaluated, it is more objective and just, and finally add up every
One section can obtain classroom assessment result and generate final Curriculum Evaluation as a result, the classroom performance of each class of teacher is all included final
In Curriculum Evaluation, sample range is big, and randomness is small, can more really and accurately react the teaching level and teaching matter of teacher
Amount.
Further, the interactive evaluation module includes raise one's hand action record submodule, division submodule, interactive record submodule
Block, the action record submodule of raising one's hand are used to video data middle school student's action are raised one's hand on time according to the result of action recognition
Between record successively, it is described division submodule be used for according to adjacent two raise one's hand action between time differences by whole class journey draw
Be divided into different interactive sections, the interaction record sub module be used for the number for counting interactive section and using the result of statistics as
Classroom interactions' number data.
The interval difference raised one's hand by video data detection between action, will be greater than preset value and raises one's hand to be divided into not twice
Same interaction, the interactive number of automatic record are simple and quick without other sensors.
Further, the enthusiasm evaluation module includes raise one's hand number statistic submodule, enthusiasm data calculating sub module,
The number statistic submodule of raising one's hand can count student on classroom according to the action of raising one's hand for action record submodule record of raising one's hand
Total number of raising one's hand, the enthusiasm calculating sub module is based on according to student total raise one's hand number and classroom interactions' number data
Calculate the number of raising one's hand that is averaged interactive every time, the enthusiasm calculating sub module, which is additionally operable to calculate number of averagely raising one's hand, accounts for total people that turns out for work
Several ratios, and Students' enthusiasm data are used as using the ratio.
The ratio that total number of persons of turning out for work is accounted for by calculating number of averagely raising one's hand is used as Students' enthusiasm data, can eliminate difference
The image that course is brought due to the difference of course number of student itself, it is more fair.
Further, the classroom data further include voice data, and the data analysis module further includes audio analysis submodule
Block, the audio analysis module are used for the speech content for identifying Faculty and Students；Data evaluation module further includes teacher and comments in violation of rules and regulations
Estimate module, teacher's violation assessment module is used to unite to violation language described in teachers according to teacher's speech content
Count and generate language violation data, the classroom assessment data further include language violation data.
By gathering audio and analysis audio, the speech content of Faculty and Students can be obtained, can be further sharp
Teachers ' teaching quality is evaluated with voice data, increases the accuracy of evaluation.
The content of teachers is screened by violation assessment module, and counts the violation language of teacher, prevents teacher to student
Conduct incorrect thought, for example, abuse student, jump on someone, complaint of complaining, propagate incorrect values, anti-government,
It is antihuman etc..Sense of responsibility, political, outlook on life, the values of teacher can be embodied by language violation data, can be more complete
Appraise the teacher in face.
Further, the data evaluation module further includes classroom discipline evaluation module, and the classroom discipline evaluation module is used
Discipline data are acted in generating student according to the recognition result of action recognition submodule, the audio analysis module is additionally operable to from sound
Frequency obtained the noise of student's upper class hour in, and the classroom discipline evaluation module is additionally operable to be given birth to according to the noise of student's upper class hour
Into student's sound discipline data, the classroom assessment data further include student and act discipline data and student's sound discipline data.
Classroom discipline evaluation module can show that student acts discipline by counting the student's quantity slept, bow, walked about
Data, can reflect classroom discipline, and then embody the managerial ability of teacher, can also be from the opposing party by the noise of upper class hour
Classroom discipline is reacted in face, both combine, and can react the discipline situation in classroom comprehensively, and then can more comprehensive scientificity
Quality of instruction.
Further, the classroom terminal further includes display module, and the control module can be obtained from cloud server
Lesson data simultaneously controls display module to show.
Show that lesson data checks course content easy to student by display module.
Brief description of the drawings
Fig. 1 is data analysis module and data evaluation module in Teaching Quality Assessment cloud service platform embodiment of the present invention
Logic diagram.
Embodiment
Below by embodiment, the present invention is described in further detail：
The present embodiment Teaching Quality Assessment cloud service platform includes cloud server, classroom terminal and student terminal, wherein：
Classroom terminal is arranged in each classroom, classroom terminal include classroom data acquisition module, terminal control module and
Network communication module, terminal control module pass through network communication module and cloud server network connection, terminal control module energy
It is enough that classroom data collecting module collected classroom data are controlled and by classroom data acquisition module according to the control signal of cloud server
The classroom data sending of block collection is to cloud server.
Classroom data include video data and voice data, and classroom data acquisition module includes video data acquiring submodule
With audio data collecting submodule, the video data and voice data being respectively used in collection teacher, video data acquiring module
Can be the high-definition camera being arranged in classroom, in order to comprehensively obtain the indoor video data of religion, camera can be with
Set multiple, the algorithm then synthesized by image gets up the image mosaic of each camera, similarly audio data collecting mould
Block can also be to be evenly distributed on religion indoor microphone composition, synthesize final voice data by audio algorithm, at audio
Adjustment method and the Processing Algorithm of video image can use existing technology, as long as can ensure that video acquisition module can
The scope in whole classroom is covered, collects the face and limb action of all students and teacher in classroom, audio collection mould
Block can collect the normal one's voice in speech of any one student in classroom, and details are not described herein.
Student terminal and cloud server network connection, student terminal are used to check course ranking and recommendation class for student
Journey, viewing classroom instruction is live and is scored online for course；
Cloud server includes data memory module, assessment management module, data analysis module, data evaluation module, class
Journey ranking module, course recommending module and live teaching broadcast module；
Data memory module is stored with other data and the lesson data of course to be assessed, and it is basic that lesson data includes course
Data, identification data, classroom assessment data record, Curriculum Evaluation result, course content data etc.；Course fundamental packets
Course class period, place of attending class, the lecturer that attends class, number of student of attending class etc. are included, identification data owns including the students and faculty
The facial recognition data of people, course content data include course set point keyword, emphasis knowledge point keyword etc., other data
Including violation language keyword.
Assessment management module can teach indoor accordingly according to the lesson data control of course to be assessed in memory module
Classroom terminal carries out the collection and transmission of classroom data；
As shown in Figure 1, data analysis module includes analysis module and audio analysis module.
Analysis module includes recognition of face submodule and action recognition submodule, and recognition of face submodule is used to identify
Locate the Faculty and Students in video data, action recognition submodule is used to identify video data middle school student action or posture, this reality
Apply in example, action recognition module is mainly used for identifying student's heads-down posture, student's sleeping position, student action and student on foot
Raise one's hand to act, the technical solution of face recognition technology scheme and action recognition is the prior art.
Audio analysis module includes vocal print code division ion module, semantics recognition submodule and noise extracting sub-module, sound
Line code separation module is used to be divided the audio of Faculty and Students from voice data according to the vocal print code characteristic of teacher
From semantics recognition submodule is used for the speech content for identifying Faculty and Students, it uses existing recognizer, noise extraction
Module is used for the extraction from voice data and teaches indoor noise data.
Audio analysis specifically includes following steps：
Step 1：Audio analysis module divides the audio of teacher in voice data and the audio of student according to vocal print code feature
From；
Step 2：Audio analysis module carries out speech recognition conversion to the audio of teacher and the audio of student；
Step 3：Audio analysis module obtained the environmental noise data of student's upper class hour from voice data.
Data evaluation module includes attendance evaluation module, classroom discipline evaluation module, interactive evaluation module, enthusiasm assessment
Module, knowledge point evaluation module, master degree evaluation module, teacher's violation assessment module and assessment statistical module.
Attendance evaluation module includes teacher's attendance submodule and student attendance submodule, is respectively used to according to recognition of face
The recognition result generation student attendance data and teacher's attendance data of module, specifically, student attendance data student is late rate, arrive
Whether diligent rate, rate of leaving early, teacher's attendance data include whether to be late, leave early.
Classroom discipline evaluation module is used to generate student's action discipline data according to the recognition result of action recognition submodule,
It is additionally operable to generate student's sound discipline data according to the noise data of student's upper class hour；
Interactive evaluation module, which is used to detecting student according to the recognition result of action recognition submodule, raises one's hand behavior, and according to
Raw action statistics classroom interactions' number data of raising one's hand.
The step of interactive evaluation module is assessed specifically includes following steps：
Step 1：Action recognition module identification student's raises one's hand to act, and interactive evaluation module obtains and raises one's hand to act each time
At the beginning of between；
Step 2：The action of raising one's hand that time started difference is less than preset value by interactive evaluation module is divided into once mutual
Dynamic, the action of raising one's hand that time started difference is more than to preset value is divided into different interactions；
Step 3：The interactive total degree of interactive evaluation module statistics is as classroom interactions' number data.
Enthusiasm evaluation module is used to raise one's hand what is answered a question according to the recognition result statistic of action recognition submodule
Number, and the percentage that the number accounts for total class size is calculated, and Students' enthusiasm data are used as using the percentage.
The appraisal procedure of enthusiasm evaluation module specifically includes following steps：
Step 1：The number raised one's hand in each interaction of enthusiasm evaluation module statistics；
Step 2：Enthusiasm evaluation module calculates the number of raising one's hand that is averaged interactive every time according to classroom interactions' number data；
Step 3：Enthusiasm evaluation module calculates the averagely number of raising one's hand and accounts for class's total number of persons ratio, and using the ratio as
Students' enthusiasm data.
Knowledge point evaluation module includes knowledge point matched sub-block, knowledge point quantity statistics submodule, emphasis assessment submodule
Block and ranging assessments submodule, knowledge point matched sub-block are used to match default knowledge point key from the content of teachers
Word, knowledge point quantity statistics submodule are able to record the number for the knowledge point told about during teachers and each knowledge
The frequency that point occurs, the frequency that emphasis assessment submodule can occur according to knowledge point generate data of giving prominence to the key points, ranging assessments
Submodule can generate knowledge point range data according to the number of knowledge point；Specifically, in the present embodiment, data memory module
In be stored with the emphasis knowledge point keyword of the course, emphasis assessment submodule can choose the knowledge point frequency of occurrences highest five
A knowledge point vocabulary is matched with emphasis knowledge point keyword, and the number of record matching is as data of giving prominence to the key points, scope
Estimate that submodule can be using the percentage of the knowledge point Zhan Zong knowledge points occurred as knowledge point range data.
Knowledge point assessment specifically includes following steps：
Step 1：Knowledge point evaluation module carries out the knowledge point keyword of teacher's speech content and the curricular standard
Match somebody with somebody, the frequency number of the number of statistical knowledge point and the appearance of each knowledge point；
Step 2：Knowledge point evaluation module is by the emphasis knowledge point of first five highest knowledge point of frequency and the curricular standard
Keyword is matched, and the number of record matching simultaneously will record result as data of giving prominence to the key points；
Step 3：The knowledge point number that knowledge point evaluation module calculates the appearance of this course accounts for the course set point number
Percentage, and using the percentage as knowledge point range data.
Master degree evaluation module includes problem matched sub-block, answer verification submodule and accuracy statistic submodule, asks
Topic matched sub-block can match default key to the issue word from teacher's speech content, and answer verification submodule, which is used to match, to be learned
It is used for statistic question and answer with the relevant answer vocabulary of the key to the issue word, accuracy statistic submodule in the raw answer answered
Accuracy.
Teacher's violation assessment module includes violation language matched sub-block, violation word statistic submodule and the life of language violation data
Into submodule, violation language matched sub-block is used for according to teacher's speech content to violation language progress described in teachers
Match somebody with somebody, violation word statistic submodule counts the quantity of violation language, language violation data generate submodule according to the quantity of violation language and
Each the corresponding score value of violation language calculates final language violation data.
Statistical module is assessed, student attendance data, student are acted discipline data, student's sound discipline by assessment statistical module
Data, language violation data, teacher's attendance data, question and answer accuracy, knowledge point data, classroom interactions' number and Students' enthusiasm
Aggregation of data is the classroom assessment data of this course, and assessment statistical module is capable of all classroom assessment data of Statistics Course,
And the average value of each item data in classroom assessment data is calculated, and according to default weight and score value, obtain each item data
Mean scores, finally obtain the total scores of all data item, the Curriculum Evaluation result using the fraction as the course.
The course ranking module is used to carry out ranking according to Curriculum Evaluation result to course, and course recommending module is used for root
Recommend course to student terminal according to course ranking, live teaching broadcast module is used for attending class to other live teachers of student terminal
Journey.
Student grouping division module is further included, video data acquiring module is additionally operable to review one's lessons indoor video in collection student
Data, analysis module can also analytics be born from course described in the textbook seen during habit, student grouping division module energy
It is enough according to analysis module recognition of face and the analysis result for the course reviewed one's lessons, time for individual study of student in record room for individual study,
Duration, the course reviewed one's lessons etc., and the student that take part in course to be assessed is found out from the student reviewed one's lessons, with according to these students from
Duration is practised, filters out the student for reviewing one's lessons duration that time for being spent on the course weekly exceedes preset value, it is (pre- in the present embodiment
If when it is a length of weekly 4 it is small when), these students are the student diligently made great efforts, and obtain these students usually course detection
Fraction (achievement of such as interim test, the achievement of usually classroom test), if the detection fraction of the student course usually not
Can be up to standard, Passing Criteria takes full class's mean scores in the present embodiment, then illustrates these students although diligent effort, but study side
Method is there are problem, Ontario Scholar that usual performance that student grouping division module selects the course is before full class 20%, and at random
These preferred students and learning method student of problems are divided into the same movable group of the course, such as preferred student has
20 people, learning method student of problems have 20 people, then can be according to the specific rules of course, point 4 people, one group or 6 people
One group, and ensure there is preferred student and learning method student of problems in every group, make on their courses afterwards
Some discussion or problem activity are participated in jointly, so that the classmate succeeded in school can be aprowl by of problems of learning method
Skill in terms of raw offer course learning.
More than be only the embodiment of the present invention, the general knowledge such as known concrete structure and characteristic is not made excessively herein in scheme
Description, all common of technical field that the present invention belongs to before one skilled in the art know the applying date or priority date
Technological know-how, can know the prior art all in the field, and with using normal experiment means before the date
Ability, one skilled in the art can improve under the enlightenment that the application provides and implement we with reference to self-ability
Case, some typical known features or known method should not become the barrier that one skilled in the art implement the application
Hinder.It should be pointed out that for those skilled in the art, without departing from the structure of the invention, if can also make
Dry modification and improvement, these should also be considered as protection scope of the present invention, these all without influence effect that the present invention implemented and
Practical applicability.The scope of protection required by this application should be based on the content of the claims, the specific reality in specification
Apply the content that the records such as mode can be used for explaining claim.
Claims (7)
1. Teaching Quality Assessment cloud service platform, including cloud server, classroom terminal and student terminal, it is characterised in that：
The classroom terminal is arranged in each classroom, and the classroom terminal includes classroom data acquisition module, terminal control mould
Block and network communication module, the terminal control module pass through network communication module and cloud server network connection, the end
Control module is held to control classroom data collecting module collected classroom data according to the control signal of cloud server and by class
The classroom data sending of hall data collecting module collected is to cloud server；
Student terminal and cloud server network connection, student terminal are used to check course ranking for student and recommend course, see
See that classroom instruction is live and is scored online for course；
The cloud server includes data memory module, assessment management module, data analysis module, data evaluation module, class
Journey ranking module, course recommending module and live teaching broadcast module；
The data memory module is stored with lesson data, the lesson data include course master data, identification data,
Classroom assessment data record, Curriculum Evaluation result；
It is described assessment management module be used in memory module lesson data control teach accordingly indoor classroom terminal into
The collection and transmission of row classroom data；
The data analysis module is used to analyze the data that classroom data collecting module collected arrives, and generates analysis result；
The data evaluation module is used to quality of instruction is assessed to obtain course according to the analysis result of data analysis module
Score under line, the data evaluation module be additionally operable to according to student terminal score online to scoring on course line, and according to
Scoring and the Emergent Curriculum assessment result that scores on course line under course line；
The course ranking module is used to carry out ranking according to Curriculum Evaluation result to course, and course recommending module is used for according to class
Journey ranking recommends course to student terminal, and live teaching broadcast module is used for the process of attending class to other live teachers of student terminal.
2. Teaching Quality Assessment cloud service platform according to claim 1, it is characterised in that：The classroom data include regarding
Frequency evidence, the data analysis module include analysis module, the analysis module include recognition of face submodule and
Action recognition submodule, the recognition of face submodule are used for the body that personnel in video data are identified according to identification data
Part, the action recognition submodule is used to identify video data middle school student action or posture；The data evaluation module includes：
Attendance evaluation module, the attendance evaluation module are used for recognition result and course basic number according to recognition of face submodule
According to generation student attendance data；
Interactive evaluation module, the interactive evaluation module are used to count classroom interactions according to the recognition result of action recognition submodule
Number data；
Enthusiasm evaluation module, the enthusiasm evaluation module are used for recognition result and course base according to action recognition submodule
Notebook data generates Students' enthusiasm data；
Online scoring statistical module, for the online scoring of statistic terminal-pair course, scores on Emergent Curriculum line；
Statistical module is assessed, the assessment statistical module is used for the classroom assessment number of classroom assessment data update to memory module
According in record, while generated according to classroom assessment data record and scored under the course line of the course, and scored according on course line
With scoring under course line Emergent Curriculum assessment result and mould Curriculum Evaluation in the block is updated storage as a result, the classroom assessment data
Discipline data, interactive number data and Students' enthusiasm data are acted including student attendance data, student.
3. Teaching Quality Assessment cloud service platform according to claim 2, it is characterised in that：The interactive evaluation module bag
Action record submodule of raising one's hand, division submodule, interactive record sub module are included, the action record submodule of raising one's hand is used for basis
The result of action recognition temporally records the action of raising one's hand of video data middle school student successively, and the division submodule is used for basis
Whole class journey is divided into different interactive sections, interactive record by the time difference that adjacent two raise one's hand between acting
Module is used to count the number in interactive section and is used as classroom interactions' number data using the result of statistics.
4. Teaching Quality Assessment cloud service platform according to claim 2, it is characterised in that：The enthusiasm evaluation module
Including number statistic submodule of raising one's hand, enthusiasm data calculating sub module, the number statistic submodule of raising one's hand can be according to act
What submodule of noting down manually recorded raises one's hand to act the number of raising one's hand that student is total on statistics classroom, the enthusiasm calculating sub module
It is described positive for raise one's hand number and each interactive number of raising one's hand that is averaged of classroom interactions' number data calculating according to student always
Property calculating sub module be additionally operable to calculate number of averagely raising one's hand and account for the ratio for total number of persons of turning out for work, and Students' enthusiasm is used as using the ratio
Data.
5. Teaching Quality Assessment cloud service platform according to claim 2, it is characterised in that：The classroom data further include
Voice data, the data analysis module further include audio analysis submodule, the audio analysis module be used to identifying teacher and
The speech content of student；Data evaluation module further includes teacher's violation assessment module, and teacher's violation assessment module is used for root
Violation language described in teachers is counted according to teacher's speech content and generates language violation data, the classroom assessment
Data further include language violation data.
6. Teaching Quality Assessment cloud service platform according to claim 5, it is characterised in that：The data evaluation module is also
Including classroom discipline evaluation module, the classroom discipline evaluation module is used to be generated according to the recognition result of action recognition submodule
Student acts discipline data, and the audio analysis module was additionally operable to obtain the noise of student's upper class hour from voice data, described
Classroom discipline evaluation module is additionally operable to generate student's sound discipline data, the classroom assessment number according to the noise of student's upper class hour
Discipline data and student's sound discipline data are acted according to student is further included.
7. Teaching Quality Assessment cloud service platform according to any one of claims 1 to 6, it is characterised in that：The classroom
Terminal further includes display module, and the control module can obtain lesson data from cloud server and control display module to show
Show to come.
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|---|---|---|---|---|
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130224716A1 (en) * | 2012-02-24 | 2013-08-29 | Jerry Chih-Yuan SUN | Cloud-based multimedia teaching system, development method and interaction method thereof |
| CN103345719A (en) * | 2013-07-03 | 2013-10-09 | 青岛大学 | System and method for evaluating experiment teaching achievement |
| CN106845320A (en) * | 2015-12-03 | 2017-06-13 | 杭州海康威视系统技术有限公司 | Detect the method and its system of classroom efficiency |
| CN107085721A (en) * | 2017-06-26 | 2017-08-22 | 厦门劢联科技有限公司 | A kind of intelligence based on Identification of Images patrols class management system |
| CN107316257A (en) * | 2017-06-06 | 2017-11-03 | 南京信息工程大学 | A kind of Method of Teaching Quality Evaluation analyzed based on classroom students ' behavior and system |
-
2017
- 2017-12-26 CN CN201711438016.0A patent/CN107958351A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130224716A1 (en) * | 2012-02-24 | 2013-08-29 | Jerry Chih-Yuan SUN | Cloud-based multimedia teaching system, development method and interaction method thereof |
| CN103345719A (en) * | 2013-07-03 | 2013-10-09 | 青岛大学 | System and method for evaluating experiment teaching achievement |
| CN106845320A (en) * | 2015-12-03 | 2017-06-13 | 杭州海康威视系统技术有限公司 | Detect the method and its system of classroom efficiency |
| CN107316257A (en) * | 2017-06-06 | 2017-11-03 | 南京信息工程大学 | A kind of Method of Teaching Quality Evaluation analyzed based on classroom students ' behavior and system |
| CN107085721A (en) * | 2017-06-26 | 2017-08-22 | 厦门劢联科技有限公司 | A kind of intelligence based on Identification of Images patrols class management system |
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Application publication date: 20180424 |