Introduction to Artificial Intelligence in Education

Study Notes

AI systems are used by learners and educators throughout Europe, often without their knowledge.
These systems are present in search engines, smart assistants, chatbots, translation services, navigation apps, online games, and other everyday applications.
AI systems rely on data collected from various sources like sound, images, text, posts, and clicks, which contribute to our digital footprint.
AI has the potential to enhance education and training for learners, educators, and school leaders.
AI systems assist educators in identifying individual learning needs, providing personalized learning experiences, and aiding schools in making informed decisions for resource allocation.
The impact of evolving AI systems and increasing data usage on the world, particularly in education, requires understanding and critical engagement.
Educators and school leaders need a basic understanding of AI and data usage for ethical and effective use of this technology.

The draft AI Act defines an AI system as software developed using specific techniques and approaches.
These systems are designed to generate outputs like content, predictions, recommendations, or decisions that influence the environments they interact with.
AI Techniques and Approaches are:
- Machine Learning: Supervised, unsupervised, and reinforcement learning using methods like deep learning.
- Logic and Knowledge-Based Approaches: Knowledge representation, inductive programming, knowledge bases, inference and deductive engines, reasoning, and expert systems.
- Statistical Approaches: This includes Bayesian estimation, search, and optimization methods.