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Pedagogical Strategies for Teaching AI & ML

Rita Ferreira

Created on September 19, 2024

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7. Pedagogical Strategies for Teaching AI & ML

Inquiry-based learning approaches

Vast amounts of Data

Online Educational Systems

Data analysis by AI

Digital Learning Enhancement

Dropout predictions

Intelligent tutoring

Performance predictions

Analytics

Data

Applications of Machine Learning and Deep Learning algorithms to Educational Themes

Adaptative learning

Commonly used algorithms

AI evolution in Education

Web-based platforms

Computer-based systems

Intelligent systems

ChatbotsHumanoid robots

INFO

Advancements relevance for teachers

Chatbots Humanoid robots

Machine learning

Deep learning

Personalised recomendations Grading assistance Methods adjustments based on student performance

Administrative tasks Curricula adaptation Content tailoring & improved learning outcomes

Pattern analysis using techniques such as decision tree learning, clustering, and reinforcement learning

Project-based learning (PBL) approaches

Multimodal interaction tools

PBL enhancement through AI

Learning outcomes improvement

High level of differentiation and tailored experiences

AI-driven platforms

Allow customization of instructional design, testing and feedback

AI-powered tools

AI-powered tools

Visualization

Enhance learning content

Simulation

Web-based environments

AI advantages

Personalized approach to project-based learning Routines optimization Enhanced efficiency Improved accessibility Processes scaling

Thank you!

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