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Research and games both require the participant to make a series of choices. Active learning is a process borrowed from machine learning for algorithmically making choices that has become increasingly used to accelerate materials research. While this process may seem opaque to researchers outside the field of machine learning, examining active learning in games provides an accessible way to showcase the process and its virtues. Here, we examine active learning through the lens of the game Wordle to both explain the active learning process and describe the types of research questions that arise when using active learning for materials research.
