LearnLM: Improving Gemini for Learning

Understand

Today's generative AI systems are tuned to present information by default, rather than engage users in service of learning as a human tutor would.

• To address the wide range of potential education use cases for these systems, we reframe the challenge of injecting pedagogical behavior as one of \textit{pedagogical instruction following}, where training and evaluation examples include system-level instructions describing the specific pedagogy attributes present or desired in subsequent model turns.
• This framing avoids committing our models to any particular definition of pedagogy, and instead allows teachers or developers to specify desired model behavior.
• It also clears a path to improving Gemini models for learning -- by enabling the addition of our pedagogical data to post-training mixtures -- alongside their rapidly expanding set of capabilities.