Artificial intelligence curriculum for primary and secondary schools

AI and the development of digital comptence

Music education I

Sound transformations

Sound transformations

In the lesson, students learn to recognize unique tonal characteristics and timbre while using an app that can transform any sound into a musical instrument through artificial intelligence. The goal of the lesson is to show students that each musical instrument has its own unique sound characteristics and that these characteristics can not only be recognized but also replicated through machine learning.

Information about lessons

Subsidies

45-90 minutes

Vintages or preconceptions

Students already know the difference between sound and noise. They know the properties of sound (pitch, length, colour, loudness). Primary 5-9 and Secondary School

Aids

Teacher: projection equipment, presentation, computer, speakers.
Students: one or more melodic instruments and percussion instrument, equipment, external microphone.

What pupils learn

Each musical instrument has its own unique sound characteristics.
Machine learning helps us to not only recognize these features, but also mimic them.

Why is it taught

They creatively use modern technology in their work.

How do we know if they've learned

When listening to music, identify the different instruments.
After listening, verbally characterize the timbre of the different instruments.

Outputs of the RVP

Music Education
HV-9-1-05 navigates the stream of sounding music, approaches a piece of music as a logically formed whole
HV-9-1-01 uses their individual musical abilities and skills in musical activities

Bloom's taxonomy

Memorization: Students learn concepts related to properties of sound and the basics of machine learning.
Analysis: They analyze the sound of musical instruments and compare original and transformed sounds.
Creation: They create musical works using AI.

Digital competences

Utilization and engagement
Creation and expression

Five Big Ideas

5-D-I AI for social good (democratization of artificial intelligence)

Methodological material

Version: 04
Number of pilots: 02
Last update: 01/25

Authors: Ondra Hrách and Vláďa Novotný
Methodological consultant: Pet'a Dovhunová
Expert guarantors: Pavel Kordík, Eva Nečasová
Language proofreading: Marcela Wimmerová