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© NEC Asia Pacific Pte Ltd 2021 Commercial-in-Confidence
NEC Emotion and Attentiveness Analytics
for Online & Onsite Learning
MOE SLS Pitch Day Submission
NEC Asia Pacific Pte Ltd
Presenter:
Tapas Das (tapaskumar_das@nec.com.sg)
COMPULSORY
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NEC's face recognition technology ranks first in NIST testing
•Press release: https://www.nec.com/en/press/202108/global_20210823_01.html
NEC facial recognition technology is deployed widely around the globe (1000
major systems in more than 70 countries) and is also able to detect age &
gender, and track gaze.
Examples of some recent deployments
In Gurugram India: Surveillance & traffic management system
In Tigre Argentia: Integrated video analytics solution for urban safety
In Singapore: Solution to detect suspicious behavior at Orchard Rd & Jurong Island
In Indonesia: Solution to detect suspicious activities and abandoned objects during
Asian games
In Japan: Disaster response management solution through Crowd Behavior analytics
NEC is currently a leader in facial recognition and video analytics
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NEC’s emotion and attentiveness analytics solution for online and onsite learning is built on
NEC’s video analytics platform (Vantage+) combined with NEC’s facial recognition
(NeoFace) and other AI driven emotion recognition engines.
The solution utilizes face images from photos and videos to track students’ eye
movements, facial expressions etc to measure the intensity of concentration. The
system reveals when students are bored, happy, anxious, interested, angry or surprised.
Such information can be aggregated and viewed w.r.t. age, gender breakdown and in
the timescale.
The Vantage+ platform enables integration of any home grown, custom or 3rd party
analytics engines, ingestion of various video and image data sources in real-time or batch
processing, and subsequently correlation and discovery of meaningful associations
between the data sources.
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1 SLIDE . Product Summary
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Use Cases Diagram for Illustration
NEC
Vantage+
SessionId,
LessonId,
Timing,
Emotion,
Attentiveness
MOE
Backend
Application
Teachers,
Parents,
Content Providers
Emotion/Attention &
FR analytics
Self-directed learning
Virtual classroom
Collaborative learning
Onsite learning
Learner Images or videos over course of lesson
Conferencing videos over
course of lesson
Home Based
Learning
Application
Content
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Example: Visualization of Emotion Data Combined with Other LMS Information
Example: Visualization of Emotion Data in Classroom Scenario
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Makes online learning through SLS platform more effective. Enables SLS team to:
Understand which content is more receptive to the target students, and which tends to cause
frustration, stress or loss of attention.
Adjust curriculum and test responses from students to study which curriculum is more effective.
Design curriculum personalized and adaptive as the solution can track individual student’s
attentiveness level and responses to the contents.
Enables the teachers to keep a pulse on the students during remote learning using
SLS platform as it can track student’s engagement level & monitor student’s stress level.
Helps teachers to receive real-time feedback of the students’ engagement level in
a virtual classroom and thus enables teachers to take measure to boost online
participation & attentiveness through various means, e.g., quiz, video, breakout room.
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2. Alignment to SLS Partnerships Areas of
Interest (25%)
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Correlate students’ emotions/attentiveness with teaching methods and
contents to get better insights of learning effectiveness for an individual student or
for a class.
Emotion/Attentiveness analytic results can be integrated and utilized by MOE’s
Learning Platform to improve on the Self-Directed, Personalized, Connected and
Human-centered learning.
Emotions could be utilized to measure the participants’ levels of attention span
and the motivation level towards their academic activities.
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3. Alignment to EdTech 2.0 Themes (25%) SLIDE
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Teachers and Educators able to
Understand which topics or which aspects of presentation are more receptive to the target
students, and which tends to cause frustration or loss of attention.
Associate students’ receptiveness to online course with their subject exam performance – to assess
if the course is effective for a class or group of students.
Help under-performing students better through relevant adjustment.
Content Providers able to
Continually enhance course content – using feedback on students’ receptiveness.
Tailor online courses to students with different learning capabilities.
Students able to
Attend online courses with interesting content and engaging delivery.
Be incentivised to stay attentive during online lessons through instant feedback.
Parents able to
Have a feel of a younger child’s reception to online lessons, type of subjects or contents.
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4. Benefits to Stakeholders (25%) SLIDE
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Empowers stakeholders to get data driven insights of students’ emotions promptly
Extensible for future needs as it is built on a platform enabling MOE to integrate home
grown, and other 3
rd party analytics in future easily to meet additional requirements
Flexible – can be integrated with LMS, allows exporting emotion data for other usage
Highest accuracy - NEC face recognition ranks 1st repeatedly in terms of accuracy and
speed.
Privacy and security by design:
Face images transferred over encrypted channels; not stored on server (configurable)
Provision to get consent from student (or parent) or teacher prior to capturing face
images and lesson meta-data for submission and processing
Adaptable analytics & can be fine-tuned
“Test” mode that allows a specific SLS session or “test” student to be recorded
Provides means to review and fine-tune the analytic engine outputs
5. Efficiency/ Effectiveness of Solution (25%)
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