CN110349063A - A kind of school work growth curve test method and system - Google Patents
A kind of school work growth curve test method and system Download PDFInfo
- Publication number
- CN110349063A CN110349063A CN201910640709.0A CN201910640709A CN110349063A CN 110349063 A CN110349063 A CN 110349063A CN 201910640709 A CN201910640709 A CN 201910640709A CN 110349063 A CN110349063 A CN 110349063A
- Authority
- CN
- China
- Prior art keywords
- scoring
- growth curve
- student
- school work
- examination
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000010998 test method Methods 0.000 title claims abstract description 13
- 238000012360 testing method Methods 0.000 claims abstract description 44
- 238000011156 evaluation Methods 0.000 claims abstract description 22
- 230000000694 effects Effects 0.000 claims abstract description 16
- 238000012545 processing Methods 0.000 description 13
- 230000002452 interceptive effect Effects 0.000 description 2
- 238000000034 method Methods 0.000 description 2
- 230000036651 mood Effects 0.000 description 2
- 238000012163 sequencing technique Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000000630 rising effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/20—Education
- G06Q50/205—Education administration or guidance
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/161—Detection; Localisation; Normalisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/168—Feature extraction; Face representation
- G06V40/171—Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
Abstract
The invention discloses a kind of school work growth curve test method and systems, including determine school work growth curve test period；The relevant information of evaluation factor of each student within test period is obtained, the relevant information of evaluation factor includes the daily scoring of student, examination scoring, expands activity score, communicative competence scoring and examination tendentiousness scoring；According to the weight coefficient of evaluation factor, score of the student within the test period is calculated, school work growth curve is fitted according to the score of each test period.The factor of the various aspects of the comprehensive student of the present invention carries out growth in all directions to student and tests.
Description
Technical field
The present invention relates to school work detection technique field, a kind of school work growth curve test method and system are particularly related to.
Background technique
In the prior art, detect student school work growth be mostly according to the achievement of student or the rising of marks sequencing or
Decline to judge, but this judgment criteria to the growth of each student judge be it is unilateral, be easy to ignore student in achievement
Except other factors growth judgement.
Summary of the invention
The present invention proposes a kind of school work growth curve test method and system, solves in existing judgment criteria according to student's
Achievement or marks sequencing rise or fall to judge, so as to cause the growth to each student judge it is unilateral, be easy to ignore
The problem of other factors of the student except achievement are grown up.
The technical scheme of the present invention is realized as follows:
A kind of school work growth curve test method, including
S1 determines school work growth curve test period；
S2 obtains the relevant information of evaluation factor of each student within test period, the relevant information packet of evaluation factor
It includes the daily scoring of student, examination scoring, expand activity score, communicative competence scoring and examination tendentiousness scoring；
S3 calculates score of the student within the test period, according to each test according to the weight coefficient of evaluation factor
The score in period fits school work growth curve.
Tendentiousness of taking an examination as a preferred embodiment of the present invention, in step S2 scoring refers specifically to student and is taking an examination
In correct topic tendentiousness, including but not limited to creativity, memory, imagination.
As a preferred embodiment of the present invention, commenting when the daily scoring of step S2 middle school student is listened to the teacher including student
The scoring of the scoring and ongoing operations that divide, are interacted with teacher.
It is further comprising the steps of as a preferred embodiment of the present invention
S4 according to daily scoring, examination scoring, expands activity score, communicative competence scoring and examination tendentiousness scoring point
It does not fit sub- growth curve individually, and is associated with school work growth curve.
It is further comprising the steps of as a preferred embodiment of the present invention:
S5 show that school work is reported according to school work growth curve and sub- growth curve.
A kind of school work growth curve test macro, including
Setting unit scores for school work growth curve test period and the evaluation factor within test period to be arranged
Factor includes the daily scoring of student, examination scoring, expands in activity score, communicative competence scoring and examination tendentiousness scoring
Two or multinomial；
Acquiring unit, for obtain in test period set evaluation factor relevant information, i.e., the daily scoring of student, examine
Two or multinomial in examination scoring, expansion activity score, communicative competence scoring and examination tendentiousness scoring；
Fitting unit calculates score of the student within the test period, root for the weight coefficient according to evaluation factor
School work growth curve is fitted according to the score of each test period.
As a preferred embodiment of the present invention, tendentiousness of taking an examination scoring refers specifically to student and correctly inscribes in examination
Purpose tendentiousness, including but not limited to creativity, memory, imagination.
Scoring and teacher as a preferred embodiment of the present invention, when the daily scoring of student is listened to the teacher including student
The scoring of interactive scoring and ongoing operations.
As a preferred embodiment of the present invention, the fitting unit, be also used to be scored according to daily scoring, examination,
Expand activity score, communicative competence scoring and examination tendentiousness scoring and individually fit sub- growth curve, and with school work at
Long curve association.
Further include reporting unit as a preferred embodiment of the present invention, for according to school work growth curve and son at
Long curve show that school work is reported.
The beneficial effects of the present invention are: the factor of the various aspects of comprehensive student carries out growth in all directions to student
Test.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention without any creative labor, may be used also for those of ordinary skill in the art
To obtain other drawings based on these drawings.
Fig. 1 is a kind of flow chart of school work growth curve test method one embodiment of the present invention；
Fig. 2 is a kind of functional block diagram of school work growth curve test macro one embodiment of the present invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
As shown in Figure 1, the invention proposes a kind of school work growth curve test methods, including
S1 determines school work growth curve test period；Test period can be one week, two weeks, ten days, one month etc. phase
Limit, can carry out customized setting according to the demand of user.
S2 obtains the relevant information of evaluation factor of each student within test period, the relevant information packet of evaluation factor
It includes the daily scoring of student, examination scoring, expand activity score, communicative competence scoring and examination tendentiousness scoring；
S3 calculates score of the student within the test period, according to each test according to the weight coefficient of evaluation factor
The score in period fits school work growth curve.
Tendentiousness of taking an examination as a preferred embodiment of the present invention, in step S2 scoring refers specifically to student and is taking an examination
In correct topic tendentiousness, including but not limited to creativity, memory, imagination.According to taking an examination, tendentious scoring can be with
Judge student creativity, memory and in terms of strong and weak ability, it is possible thereby to excavate each student's
Strong point.
As a preferred embodiment of the present invention, commenting when the daily scoring of step S2 middle school student is listened to the teacher including student
The scoring of the scoring and ongoing operations that divide, are interacted with teacher.It can be arranged in classroom to obtain the scoring interacted with teacher
Camera, voice obtain module, speech analysis processing module, video analysis processing module；Voice obtains module and speech analysis
Processing module obtains student and is answering a question and/or actively puing question to related data, and voice obtains module and speech analysis handles mould
When block obtains illegal noisy speech, video acquiring module and video analysis processing module are waken up, video acquiring module obtains
Student's video, and student is obtained with the presence or absence of the order situation that disturbs the class, if so, note by video analysis processing module analysis
Record related data.
Scoring when student listens to the teacher can detect whether student appears in picture by Face datection algorithm, and statistics obtains
Whether each student appears in the number in picture, focus on, obtain when judging whether each student listens to the teacher and listen to the teacher with this
Scoring.
Camera obtains the video that student attends class, and exports successive frame video flowing, and video analysis processing module regards successive frame
Student's face key point in frequency stream is tracked, and judges whether the mood of student's upper class hour is conscientious actively.Specifically, based on
Track stable algorithm tracks the direction of motion and range ability of the face key point in front of and after frames face picture, mainly to people
The key point of eyes and mouth in face is tracked, and calculates the variation distance of eyes key point and mouth key point, if setting
The variation distance of the eyes key point of frame and mouth key point not up to or the change threshold beyond setting, then judges the student not
It focuses on.
It is further comprising the steps of as a preferred embodiment of the present invention
S4 according to daily scoring, examination scoring, expands activity score, communicative competence scoring and examination tendentiousness scoring point
It does not fit sub- growth curve individually, and is associated with school work growth curve.
It is further comprising the steps of as a preferred embodiment of the present invention:
S5 show that school work is reported according to school work growth curve and sub- growth curve.
As shown in Fig. 2, the invention also provides a kind of school work growth curve test macros, including
Setting unit scores for school work growth curve test period and the evaluation factor within test period to be arranged
Factor includes the daily scoring of student, examination scoring, expands in activity score, communicative competence scoring and examination tendentiousness scoring
Two or multinomial；Test period can be one week, two weeks, ten days, one month etc. time limit, can carry out according to the demand of user
Customized setting.
Acquiring unit, for obtain in test period set evaluation factor relevant information, i.e., the daily scoring of student, examine
Two or multinomial in examination scoring, expansion activity score, communicative competence scoring and examination tendentiousness scoring；
Fitting unit calculates score of the student within the test period, root for the weight coefficient according to evaluation factor
School work growth curve is fitted according to the score of each test period.
As a preferred embodiment of the present invention, tendentiousness of taking an examination scoring refers specifically to student and correctly inscribes in examination
Purpose tendentiousness, including but not limited to creativity, memory, imagination.According to taking an examination, tendentious scoring may determine that
It is raw creativity, memory and in terms of strong and weak ability, it is possible thereby to excavate the strong point of each student.
Scoring and teacher as a preferred embodiment of the present invention, when the daily scoring of student is listened to the teacher including student
The scoring of interactive scoring and ongoing operations.To obtain the scoring interacted with teacher, camera, language can be set in classroom
Sound obtains module, speech analysis processing module, video analysis processing module；Voice obtains module and speech analysis processing module obtains
Student is taken to answer a question and/or actively puing question to related data, voice obtains module and the acquisition of speech analysis processing module does not conform to
When the noisy speech of method, video acquiring module and video analysis processing module are waken up, video acquiring module obtains student's video, and
Student is obtained with the presence or absence of the order situation that disturbs the class, if so, record related data by video analysis processing module analysis.
Scoring when student listens to the teacher can detect whether student appears in picture by Face datection algorithm, and statistics obtains
Whether each student appears in the number in picture, focus on, obtain when judging whether each student listens to the teacher and listen to the teacher with this
Scoring.
Camera obtains the video that student attends class, and exports successive frame video flowing, and video analysis processing module regards successive frame
Student's face key point in frequency stream is tracked, and judges whether the mood of student's upper class hour is conscientious actively.Specifically, based on
Track stable algorithm tracks the direction of motion and range ability of the face key point in front of and after frames face picture, mainly to people
The key point of eyes and mouth in face is tracked, and calculates the variation distance of eyes key point and mouth key point, if setting
The variation distance of the eyes key point of frame and mouth key point not up to or the change threshold beyond setting, then judges the student not
It focuses on.
As a preferred embodiment of the present invention, fitting unit is also used to according to daily scoring, examination scoring, expands
Activity score, communicative competence scoring and examination tendentiousness scoring individually fit sub- growth curve, and bent with school work growth
Line association.
Further include reporting unit as a preferred embodiment of the present invention, for according to school work growth curve and son at
Long curve show that school work is reported.
The factor of the various aspects of the comprehensive student of the present invention carries out growth in all directions to student and tests.
The above is merely preferred embodiments of the present invention, be not intended to limit the invention, it is all in spirit of the invention and
Within principle, any modification, equivalent replacement, improvement and so on be should all be included in the protection scope of the present invention.
Claims (10)
1. a kind of school work growth curve test method, which is characterized in that including
S1 determines school work growth curve test period；
S2, obtains the relevant information of evaluation factor of each student within test period, and the relevant information of evaluation factor includes learning
Raw daily scoring, examination scoring, expansion activity score, communicative competence scoring and examination tendentiousness scoring；
S3 calculates score of the student within the test period, according to each test period according to the weight coefficient of evaluation factor
Score fit school work growth curve.
2. school work growth curve test method according to claim 1, which is characterized in that tendentiousness of taking an examination in step S2 is commented
Divide the tendentiousness for referring specifically to student's correct topic in examination, including but not limited to creativity, memory, imagination.
3. school work growth curve test method according to claim 1, which is characterized in that the daily of step S2 middle school student is commented
The scoring of scoring, the scoring and ongoing operations that are interacted with teacher when point listening to the teacher including student.
4. school work growth curve test method according to claim 1, which is characterized in that further comprising the steps of
S4, according to daily scoring, examination scoring, expansion activity score, communicative competence scoring and tendentiousness scoring list respectively of taking an examination
Sub- growth curve is solely fitted, and is associated with school work growth curve.
5. school work growth curve test method according to claim 4, which is characterized in that further comprising the steps of:
S5 show that school work is reported according to school work growth curve and sub- growth curve.
6. a kind of school work growth curve test macro, which is characterized in that including
Setting unit, for school work growth curve test period and the evaluation factor within test period, evaluation factor to be arranged
Two in daily scoring, examination scoring, expansion activity score, communicative competence scoring and examination tendentiousness scoring including student
Or it is multinomial；
Acquiring unit, for obtaining the relevant information for setting evaluation factor in test period, i.e. the daily scoring, examination of student is commented
Be divided to, expand activity score, communicative competence scoring and examination tendentiousness scoring in two or multinomial；
Fitting unit calculates score of the student within the test period, according to each for the weight coefficient according to evaluation factor
The score of a test period fits school work growth curve.
7. school work growth curve test macro according to claim 6, which is characterized in that examination tendentiousness scoring refers specifically to
Be student's correct topic in examination tendentiousness, including but not limited to creativity, memory, imagination.
8. school work growth curve test macro according to claim 6, which is characterized in that the daily scoring of student includes learning
The scoring of scoring, the scoring and ongoing operations that are interacted with teacher when life is listened to the teacher.
9. school work growth curve test macro according to claim 6, which is characterized in that
The fitting unit is also used to according to daily scoring, examination scoring, expands activity score, communicative competence scoring and examination
Tendentiousness scoring individually fits sub- growth curve, and is associated with school work growth curve.
10. school work growth curve test macro according to claim 9, which is characterized in that further include
Reporting unit, for showing that school work is reported according to school work growth curve and sub- growth curve.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910640709.0A CN110349063A (en) | 2019-07-16 | 2019-07-16 | A kind of school work growth curve test method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910640709.0A CN110349063A (en) | 2019-07-16 | 2019-07-16 | A kind of school work growth curve test method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110349063A true CN110349063A (en) | 2019-10-18 |
Family
ID=68176397
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910640709.0A Pending CN110349063A (en) | 2019-07-16 | 2019-07-16 | A kind of school work growth curve test method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110349063A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112085631A (en) * | 2020-09-04 | 2020-12-15 | 上海松鼠课堂人工智能科技有限公司 | Intelligent analysis method for student memory curve |
| CN112419112A (en) * | 2020-11-30 | 2021-02-26 | 郑兰 | Academic growth curve generation method and device, electronic device and storage medium |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040180317A1 (en) * | 2002-09-30 | 2004-09-16 | Mark Bodner | System and method for analysis and feedback of student performance |
| CN102663659A (en) * | 2012-03-27 | 2012-09-12 | 上海爱友科技有限公司 | Education system based on academic achievement development index |
| US8465288B1 (en) * | 2007-02-28 | 2013-06-18 | Patrick G. Roers | Student profile grading system |
| CN106851216A (en) * | 2017-03-10 | 2017-06-13 | 山东师范大学 | A kind of classroom behavior monitoring system and method based on face and speech recognition |
| CN108734364A (en) * | 2017-04-21 | 2018-11-02 | 北京泛鹏天地科技股份有限公司 | Employee individual's feedback on performance method based on growth curve |
| CN109359521A (en) * | 2018-09-05 | 2019-02-19 | 浙江工业大学 | The two-way assessment system of Classroom instruction quality based on deep learning |
| CN109872587A (en) * | 2019-01-07 | 2019-06-11 | 北京汉博信息技术有限公司 | The processing system of multidimensional teaching data |
-
2019
- 2019-07-16 CN CN201910640709.0A patent/CN110349063A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040180317A1 (en) * | 2002-09-30 | 2004-09-16 | Mark Bodner | System and method for analysis and feedback of student performance |
| US8465288B1 (en) * | 2007-02-28 | 2013-06-18 | Patrick G. Roers | Student profile grading system |
| CN102663659A (en) * | 2012-03-27 | 2012-09-12 | 上海爱友科技有限公司 | Education system based on academic achievement development index |
| CN106851216A (en) * | 2017-03-10 | 2017-06-13 | 山东师范大学 | A kind of classroom behavior monitoring system and method based on face and speech recognition |
| CN108734364A (en) * | 2017-04-21 | 2018-11-02 | 北京泛鹏天地科技股份有限公司 | Employee individual's feedback on performance method based on growth curve |
| CN109359521A (en) * | 2018-09-05 | 2019-02-19 | 浙江工业大学 | The two-way assessment system of Classroom instruction quality based on deep learning |
| CN109872587A (en) * | 2019-01-07 | 2019-06-11 | 北京汉博信息技术有限公司 | The processing system of multidimensional teaching data |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112085631A (en) * | 2020-09-04 | 2020-12-15 | 上海松鼠课堂人工智能科技有限公司 | Intelligent analysis method for student memory curve |
| CN112419112A (en) * | 2020-11-30 | 2021-02-26 | 郑兰 | Academic growth curve generation method and device, electronic device and storage medium |
| CN112419112B (en) * | 2020-11-30 | 2024-03-05 | 郑兰 | Method and device for generating academic growth curve, electronic equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104637350B (en) | One kind adult's hearing speech rehabilitation system | |
| Wong | Acoustic characteristics of three-year-olds' correct and incorrect monosyllabic Mandarin lexical tone productions | |
| US8708702B2 (en) | Systems and methods for learning using contextual feedback | |
| US11786171B2 (en) | Method and system for articulation evaluation by fusing acoustic features and articulatory movement features | |
| CN102930866A (en) | Evaluation method for student reading assignment for oral practice | |
| CN101419795B (en) | Audio signal detection method and device, and auxiliary oral language examination system | |
| Fairgray et al. | Effects of auditory-verbal therapy for school-aged children with hearing loss: An exploratory study | |
| CN102436812A (en) | Conference recording device and conference recording method using same | |
| CN110349063A (en) | A kind of school work growth curve test method and system | |
| CN108229441A (en) | A kind of classroom instruction automatic feedback system and feedback method based on image and speech analysis | |
| CN107844762A (en) | Information processing method and system | |
| CN109166068A (en) | Discussion learning method and device | |
| JP2002258729A (en) | Foreign language learning system, information processing terminal for the same and server | |
| Medrado et al. | Voice-over: perceptual and acoustic analysis of vocal features | |
| CN108596159A (en) | A kind of teaching method and system based on Internet education | |
| CN105513612A (en) | Language vocabulary audio processing method and device | |
| CN114971975B (en) | Learning abnormity prompting method and system for online education platform | |
| CN115223029A (en) | Intelligent monitoring system based on intelligent breeding support robot | |
| CN106557914A (en) | A kind of alarm clock prompting method and device | |
| Altinkaya et al. | A dynamic, self supervised, large scale audiovisual dataset for stuttered speech | |
| CN114067433A (en) | Language and image understanding system based on multiple protocols | |
| CN113593326A (en) | English pronunciation teaching device and method | |
| Perigoe | Generalization of speech skills in hearing-impaired children | |
| Trijatmiko et al. | Voice Classification of Children with Speech Impairment Using MFCC Kernel-Based SVM | |
| CN115311606B (en) | Classroom recorded video validity detection method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20191018 |