Artificial intelligence curriculum for primary and secondary schools
AI and the development of digital comptence
Media education IV
Machine Emotion Recognition
Machine Emotion Recognition
This activity focuses on machine detection of emotions from human face. The topic is mainly approached from an ethics perspective, but of course the lesson also explains how these systems work. The methodology also includes an extension activity of sentiment analysis from text. The lesson is not directly related to the previous one, but it is an important piece to the puzzle of understanding the contemporary world.
Information about lessons
Subsidies
45-90 minutes
Vintages or preconceptions
8. and 9. primary school grades and secondary school grades
Building stones
Machine Emotion Recognition
Aids
Teacher: Projection equipment, presentation.
Students: Computers or tablets with camera.
What pupils learn
Artificial intelligence systems can detect emotions in text, images, video, or voice with some accuracy.
Why is it taught
They think critically about the use of digital services and devices in everyday life.
How do we know if they've learned
Explain the principle of machine recognition of emotions from human faces. Describe the ethical aspects associated with this technology.
Outputs of the RVP
RVP Outcomes - Computer Science
I-9-4-05 can direct their actions to minimize the risk of data loss or misuse; describes the operation and discusses the limitations of security solutions
RVP Outcomes - Education for citizenship
VO-9-1-05 critically approaches media information, expresses his/her attitude towards the effect of propaganda and advertising on public opinion and people's behaviour
RVP Outcomes G - Computer Science and Information and Communication Technology
Organizes data effectively and protects it against damage or misuse.
RVP Outcomes G - Civic and social science foundation
Explains the nature of some contemporary social problems and describes the possible effects of socially pathological behaviour on individuals and society.
Bloom's taxonomy
Understanding: Students explain the principles of machine recognition of emotions in text, images, and voice.
Application: They use MorphCast to analyze emotions.
Analysis: They analyze the results of emotion recognition and discuss their accuracy and limitations.
Digital competences
Utilization and engagement
Benefit and development
Five Big Ideas
4-C-I Understanding emotions
