Learning Analytics and Artificial Intelligence in Education

Learning Analytics and Artificial Intelligence in Education: Human-centered design approaches towards increased teacher agency and compliance to FATE principles

Although Artificial Intelligence (AI) and Learning Analytics (LA) have shown their potential in Education, stakeholders’ agency seems to be threatened. On the other hand, multiple issues regarding FATE (Fairness, Accountability, Transparency and Ethics) have been raised when AI or LA-based solutions are designed and implemented. These issues have been especially acute since the emergence of Large Language Models and Generative AI.

This talk discusses the quest for an optimal balance between human and computational agents, when LA tools and services are employed in a Technology Enhanced Learning (TEL) ecosystem. Through the discussion of relevant conceptual models and examples, it argues for Human-Centered Learning Analytics (HCLA) and Human-Centered Artificial Intelligence (HCAI) approaches, where agency and FATE principles are essential design parameters.

The talk focuses especially on LA/AI solutions that may position teachers as designers of effective interventions and orchestration actions. Selected Human-Centered Design (HCD) principles are discussed and illustrated, and directions for future research and development are formulated to overcome the main obstacles for adoption of human-centered approaches for LA and AI in education.

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Yannis Dimitriadis