Artificial intelligence curriculum for primary and secondary schools
AI and the development of digital comptence
Media education I
Recommendation systems on social networks
Recommendation systems on social networks
The topic of the lesson is recommender systems, which use machine learning methods to recommend content - on social media, streaming platforms, in search, etc. The lesson aims to help students understand how content in the online space is recommended to them and what the positives and negatives associated with this are.
Information about lessons
Subsidies
90 minutes
Vintages or preconceptions
8th and 9th grades of primary and secondary schools
Building stones
Social networks, recommendation systems.
Aids
Educator: projection equipment and presentation to projection, worksheet
Students: stationery or mobile phone with internet connection
What pupils learn
Recommender systems track user behaviour and offer content based on that. There are different models for recommending content on social networks.
Why is it taught
Based on their understanding of how recommendation systems work, they critically assess the content offered on social media.
How do we know if they've learned
They will describe models of how recommender systems work.
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-9-1-03 takes a critical approach to media information, expresses his/her attitude towards the effect of propaganda and advertising on public opinion and people's behaviour
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.
RVP Outcomes G - Computer Science and Information and Communication Technology
Organizes data effectively and protects it against damage or misuse.
Bloom's taxonomy
Memorization: Students learn the basic concepts related to recommender systems and their models on social media.
Application: They apply their knowledge of how these systems work to analyze the content they are offered on social media.
Creation: They create arguments for and against recommender systems, weighing their advantages and disadvantages based on their knowledge.
Digital competences
Usage and wiring
Five Big Ideas
5-A-III Ethical AI
5-B-I AI and Culture (AI in everyday life)
5-B-II AI and Culture (Trust and Responsibility)
