CN108230200A - A kind of user behavior data acquisition method for online education platform - Google Patents
A kind of user behavior data acquisition method for online education platform Download PDFInfo
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- CN108230200A CN108230200A CN201611198386.7A CN201611198386A CN108230200A CN 108230200 A CN108230200 A CN 108230200A CN 201611198386 A CN201611198386 A CN 201611198386A CN 108230200 A CN108230200 A CN 108230200A
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- server
- camera
- behavior data
- user behavior
- online education
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- 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
- G06V40/161—Detection; Localisation; Normalisation
- G06V40/165—Detection; Localisation; Normalisation using facial parts and geometric relationships
-
- 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
- G06V40/167—Detection; Localisation; Normalisation using comparisons between temporally consecutive images
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
Abstract
The present invention relates to a kind of user behavior data acquisition methods for online education platform, include the following steps：S 1, camera start, and server obtains camera data, the image that player real-time display takes in real time；S2, server handle and analyze in real time camera data, detect the face of appearance activity before camera；S3, server calculate face before camera after stay time setting value, to player send start play instruction, player since server obtain teaching resource and play teaching resource；S4, in teaching resource playing process, server calculates the frequency of wink of people and mouth profile size, and generates change curve respectively, as user behavior data, is analyzed for the attention of user.Compared with prior art, the present invention can analyze to obtain user's attention change trend, compensate for the deficiency that online education can not achieve good Real-time Feedback, may advantageously facilitate the improvement of curriculum quality.
Description
Technical field
The present invention relates to one kind, more particularly, to a kind of user behavior data acquisition method for online education platform.
Background technology
The progress of Internet technology and the limitation of traditional education mode, promote online education to send out rapidly in recent years
Exhibition.And along with the universal of internet and smart mobile phone, mobile Internet related tool and network environment obtain greatly improve with
It is promoted, online education especially mobile terminal online education also accelerated development.
Compared with traditional education mode, online education have many advantages, such as flexibility it is high, it is at low cost, do not limited by place, so
And its it is bad be in course learning interactive missing, can not learn lecture content to user whether attractive, user whether
It focuses on, the platform of online education and the end user of product are learners, if not customer-centric, it is impossible to meet
The demand of learner, it is impossible to bring good user experience, it is impossible to realize good learning effect, then even if how high it is
On big, also eventually abandoned by learner.
For online education evaluation and feedback aspect, existing there are as below methods：
1. embedded testing.Embedded testing is added in instructional video, test topic can be jumped out at regular intervals.It is embedded
Formula is tested based on the relatively low objective item of difficulty, is assisted mainly in learner and is focused on, grasps important knowledge point.
2. it tests after class.It tests after class based on objective item, supplemented by subjective item, learner can immediately obtain just after answering
Accidentally feedback and explanation.
Both the above method is still a passive process for the reception of test result, lacks real-time, cannot
Know whether learner focuses in learning process, and each learner's level is different, unilaterally according to test into
Achievement has limitation to assess teaching efficiency.
With good grounds camera shooting train driver face, calculating frequency of wink are used as driver, the method at present
Whether focus in analysis driver, there is larger feasibility.
Invention content
It is an object of the present invention to overcome the above-mentioned drawbacks of the prior art and provide one kind is used for online education
The user behavior data acquisition method of platform.
The purpose of the present invention can be achieved through the following technical solutions：
A kind of user behavior data acquisition method for online education platform includes the following steps：
S1, camera start, and server obtains camera data, the image that player real-time display takes in real time；
S2, server handle and analyze in real time camera data, detect the face of appearance activity before camera；
S3, server calculate face before camera after stay time setting value, and starting broadcasting to player transmission refers to
Enable, player since server obtain teaching resource and play teaching resource；
S4, in teaching resource playing process, server calculates the frequency of wink of people and mouth profile size, and generates respectively
Change curve as user behavior data, is analyzed for the attention of user.
In teaching resource playing process, content that camera takes is shown in player in the form of floating frame and shown
On screen.
The camera be equipped with it is multiple, be separately positioned on different angle, and pass through network and connect with server.
The teaching resource is divided into two parts, and forepart is divided into short-sighted frequency, and latter half is the curriculum video of user's selection,
In short video display process, the frequency of wink and mouth profile size of people is as the reference value in attention analysis.
The short video playback time is 10~30s.
In the step S4, after player receives pause instruction, which is sent to server, server pause
The instruction after player receives continue-to-play instruction, is sent to server, server continues to draw curve by Drawing of Curve.
Setting value in the step S3 is 3s~5s.
Compared with prior art, the present invention has the following advantages：
(1) existing analysis is passed through by the frequency of wink and mouth profile size, formation curve figure that calculate user in real time
Method can be analyzed to obtain user's attention change trend, compensate for online education and can not achieve good Real-time Feedback not
Foot.
(2) player is mostly mobile phone or tablet computer, carries camera, and camera function is easily achieved；Server can lead to
It crosses network to connect with player and camera, big data resource can be obtained, the different data of same course is subjected to comprehensive analysis,
Be conducive to the improvement of curriculum quality.
(3) in teaching resource playing process, the content that camera takes is shown in player in the form of floating frame
On display screen, user can adjust floating frame position, not influence teaching efficiency.
(4) teaching resource includes the short-sighted frequency for being used as user behavior data reference, and short-sighted frequency can be from historical statistics point
The video resource with higher attraction obtained is analysed, higher user's attention can be caused, thus obtained analysis result is more
Closing to reality, it is with a high credibility.
(5) short video playback time is 10~30s, does not influence teaching process, when can meet the minimum for calculating frequency of wink
It is long.
(6) during video pause, suspend the drafting of curve, it is contemplated that the time of user's bait, data really may be used
It leans on.
(7) setting value in step S3 is 3s~5s, is essentially ensures that user has been enter into study preparation state at this time.
Description of the drawings
Fig. 1 is the flow chart of the method for the present invention.
Specific embodiment
The present invention is described in detail with specific embodiment below in conjunction with the accompanying drawings.The present embodiment is with technical solution of the present invention
Premised on implemented, give detailed embodiment and specific operating process, but protection scope of the present invention is not limited to
Following embodiments.
Embodiment
As shown in Figure 1, a kind of user behavior data acquisition method for online education platform, includes the following steps：
S1, camera start, and server obtains camera data, the image that player real-time display takes in real time；
S2, server handle and analyze in real time camera data, detect the face of appearance activity before camera；
S3, server calculate face before camera after stay time setting value (3s~5s), are opened to player transmission
Beginning play instruction, player since server obtain teaching resource and play teaching resource；Teaching resource is divided into two parts, preceding
Part is the short-sighted frequencies of 10~30s for reference, and latter half is the curriculum video of user's selection, in short video display process,
The frequency of wink and mouth profile size of people is as the reference value in attention analysis；
S4, in teaching resource playing process, server calculates the frequency of wink of people and mouth profile size, and generates respectively
Change curve as user behavior data, is analyzed for the attention of user.In teaching resource playing process, camera shooting
To content be shown in the form of floating frame on player display screen.
Camera be equipped with it is multiple, be separately positioned on different angle, and pass through network and connect with server.
In step S4, after player receives pause instruction, which is sent to server, server pause curve is painted
The instruction after player receives continue-to-play instruction, is sent to server, server continues to draw curve by system.
Horizontal axis in change curve is time or video node, and the longitudinal axis is frequency of wink and mouth profile size, is led to first
It crosses study and obtains the frequency of wink and mouth profile when user's attention is concentrated, when frequency of wink is substantially reduced, illustrate that user notes
Power of anticipating declines, possibly into tired state；Mouth profile significantly becomes larger, and illustrates that user may have the behavior yawned, shows to note
Meaning power is not concentrated.
When user is absent minded, Resource Manager is needed to draw attention, takes steps to keep user's attraction,
To promote the sustained improvement of curriculum quality.
Claims (7)
1. a kind of user behavior data acquisition method for online education platform, which is characterized in that include the following steps：
S1, camera start, and server obtains camera data, the image that player real-time display takes in real time；
S2, server handle and analyze in real time camera data, detect the face of appearance activity before camera；
S3, server calculate face before camera after stay time setting value, are sent to player and start play instruction, broadcast
Put device since server obtain teaching resource and play teaching resource；
S4, in teaching resource playing process, server calculates the frequency of wink of people and mouth profile size, and generation variation respectively
Curve as user behavior data, is analyzed for the attention of user.
2. a kind of user behavior data acquisition method for online education platform according to claim 1, feature exist
In in teaching resource playing process, the content that camera takes is shown in the form of floating frame on player display screen.
3. a kind of user behavior data acquisition method for online education platform according to claim 1, feature exist
It is equipped in, the camera multiple, is separately positioned on different angle, and pass through network and connect with server.
4. a kind of user behavior data acquisition method for online education platform according to claim 1, feature exist
In the teaching resource is divided into two parts, and forepart is divided into short-sighted frequency, and latter half is the curriculum video of user's selection, short-sighted
In frequency playing process, the frequency of wink and mouth profile size of people is as the reference value in attention analysis.
5. a kind of user behavior data acquisition method for online education platform according to claim 4, feature exist
In the short video playback time is 10~30s.
6. a kind of user behavior data acquisition method for online education platform according to claim 1, feature exist
In in the step S4, after player receives pause instruction, which being sent to server, server pause curve
It draws, after player receives continue-to-play instruction, which is sent to server, server continues to draw curve.
7. a kind of user behavior data acquisition method for online education platform according to claim 1, feature exist
In the setting value in the step S3 is 3s~5s.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201611198386.7A CN108230200A (en) | 2016-12-22 | 2016-12-22 | A kind of user behavior data acquisition method for online education platform |
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| CN201611198386.7A CN108230200A (en) | 2016-12-22 | 2016-12-22 | A kind of user behavior data acquisition method for online education platform |
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| CN108230200A true CN108230200A (en) | 2018-06-29 |
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| CN201611198386.7A Pending CN108230200A (en) | 2016-12-22 | 2016-12-22 | A kind of user behavior data acquisition method for online education platform |
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109087221A (en) * | 2018-07-27 | 2018-12-25 | 安徽豆智智能装备制造有限公司 | Game type learning system |
| CN109754661A (en) * | 2019-03-18 | 2019-05-14 | 北京一维大成科技有限公司 | A kind of on-line study method, apparatus, equipment and medium |
| CN110213654A (en) * | 2019-05-18 | 2019-09-06 | 杭州当虹科技股份有限公司 | A kind of streaming media video effectively watches the detection device and method of content |
| CN111402096A (en) * | 2020-04-03 | 2020-07-10 | 广州云从鼎望科技有限公司 | Online teaching quality management method, system, equipment and medium |
| CN111402439A (en) * | 2020-03-12 | 2020-07-10 | 郝宏志 | Online training class arrival rate statistical management method and system based on face recognition |
| CN115250379A (en) * | 2021-04-25 | 2022-10-28 | 花瓣云科技有限公司 | Video display method, terminal, system and computer readable storage medium |
| CN115733998A (en) * | 2022-10-19 | 2023-03-03 | 江苏科技大学 | Live broadcast content transmission method based on online course live broadcast system |
-
2016
- 2016-12-22 CN CN201611198386.7A patent/CN108230200A/en active Pending
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109087221A (en) * | 2018-07-27 | 2018-12-25 | 安徽豆智智能装备制造有限公司 | Game type learning system |
| CN109754661A (en) * | 2019-03-18 | 2019-05-14 | 北京一维大成科技有限公司 | A kind of on-line study method, apparatus, equipment and medium |
| CN110213654A (en) * | 2019-05-18 | 2019-09-06 | 杭州当虹科技股份有限公司 | A kind of streaming media video effectively watches the detection device and method of content |
| CN110213654B (en) * | 2019-05-18 | 2021-04-06 | 杭州当虹科技股份有限公司 | Method for detecting effective watching content of streaming media video |
| CN111402439A (en) * | 2020-03-12 | 2020-07-10 | 郝宏志 | Online training class arrival rate statistical management method and system based on face recognition |
| CN111402096A (en) * | 2020-04-03 | 2020-07-10 | 广州云从鼎望科技有限公司 | Online teaching quality management method, system, equipment and medium |
| CN115250379A (en) * | 2021-04-25 | 2022-10-28 | 花瓣云科技有限公司 | Video display method, terminal, system and computer readable storage medium |
| CN115250379B (en) * | 2021-04-25 | 2024-04-09 | 花瓣云科技有限公司 | Video display method, terminal, system and computer readable storage medium |
| CN115733998A (en) * | 2022-10-19 | 2023-03-03 | 江苏科技大学 | Live broadcast content transmission method based on online course live broadcast system |
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Application publication date: 20180629 |