Lecturer: Logan Bentley, Harriet Crisp
Fields: Education, Artificial Intelligence, Machine Learning
Content
Join us for an interactive, hands-on workshop where you’ll design AI-powered interventions to tackle real-world challenges in early childhood education. In this course we will merge academic expertise with industry-driven insights – equipping and inspiring you to create solutions addressing the global learning crisis.
The course will begin with foundational instruction in core concepts and practices of early childhood education, emphasizing its critical importance in shaping equitable futures. Then we’ll explore the transformative potential of AI in education, presenting case studies from EIDU (https://www.eidu.com/) where traditional pedagogical interventions have been augmented with AI. These will include:
– Structured Pedagogy: How we leverage large language models (LLMs) to generate unique and relevant lesson plans that empower teachers.
– Personalized Learning: The use of machine learning to tailor individual students’ learning paths and maximize their learning outcomes.
With this foundation, we’ll move into an immersive design workshop where you prototype practical, AI-driven interventions targeting improvement for early learners’ literacy and numeracy. You’ll be guided with instruction on best practices, proven frameworks, and lessons from our own experience.
The learning crisis is a global challenge; solving it demands collaboration across disciplines, industries, and borders. Let’s explore together how we all can make a lasting impact.
Literature
- Friedberg, A (2023). Can A/B Testing at Scale Accelerate Learning Outcomes in Low- and Middle-Income Environments? (https://link.springer.com/chapter/10.1007/978-3-031-36336-8_119)
- Sun, C, Major, L, Moustafa, N, Daltry, R, and Freidberg, A (2024) Learner Agency in Personalised Content Recommendation: Investigating Its Impact in Kenyan Pre-primary Education. (https://link.springer.com/chapter/10.1007/978-3-031-64312-5_25)
- Sun, C, Major, L, Moustafa, N, Daltry, R, and Freidberg, A (2024) Teacher-AI Collaboration in Content Recommendation for Digital Personalised Learning among Pre-primary Learners in Kenya (https://dl.acm.org/doi/10.1145/3657604.3664662)
Lecturer
Logan is an accomplished software engineer with over a decade of experience in the education and gaming industries. He is an engineering manager at EIDU, where for the last years his team has been focused on improving learning outcomes for EIDU\’s EdTech interventions in low-income countries.
Affiliation: EIDU GmbH
Homepage: https://www.eidu.com/
Harriet received her Master’s degree in Engineering from the University of Cambridge. She began her career as a Machine Learning Engineer at a data consultancy, where she worked for two years. She then joined EIDU as a Data Scientist, bringing her expertise to the field of educational technology.
Affiliation: EIDU GmbH
Homepage: https://www.eidu.com/