Game-Based Learning and AI Content Generation
Corresponding Author: Marcus Round
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Length: 90 minutes
Location:
Description:
The “Swipe Game” is an interactive discussion-based gameplay framework developed by Circus Street and QA. It allows corporate learners to engage in lively debates, centered around a dynamic workplace narrative that is connected through various hypothetical scenarios in a particular subject domain.
This gameplay framework is designed to provoke debates and diagnose levels of disagreement and uncertainty amongst the learners. To this end, the game takes place in an online session where a transcript of the discussion is recorded and can thereby be analysed by an AI to draw out insights.
The use of AI is further extended to the content generation process, where Large Language Models can be used to analyse PDFs of learning materials and extract relevant characters, metrics, and scenarios for a game based on these learning materials to be centred around.
This process has rapidly accelerated our workflow for generating new episodes of the Swipe Game, and provides useful insights on how AI can be used to strike a balance between open-ended generation of written content and the constraints of meeting the strict technical requirements of programming digital games.
Join us for a look at our journey of exploring the interaction between the fluid creative potential of LLM content generation, the creative constraints of digital game-based learning, and the use of open-ended learner discussions as an end goal for corporate learning; culminating in an interactive demonstration as we collaboratively use our AI tools to construct a learning game specifically designed to provoke meaningful debates.
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