Leveling Up Education: Harnessing Generative AI for Game-Based Learning

Ashish Amresh
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Abstract

Generative AI has exploded in popularity over the past few years and is showing no signs of slowing down. There is skepticism among educators and institutions on the best ways to harness its power without ignoring ethical and equitable challenges that arise with its use. One area where there is emerging consensus is in building personalized learning solutions that can provide equitable access to a wide range of learners without compromising on ethical challenges. Simultaneously game-based learning has proven to be a viable paradigm to engage learners and the ability of games to be able to adapt to the player/learner provides significant opportunities to build equitable and accessible personalized learning solutions. In this talk, we will discuss ways in which game-based learning and generative AI can synergistically be combined to take advantage of each other’s capabilities and create educational interventions that can be offered at scale. By combining the interactive and motivational aspects of games with the adaptability and intelligence of generative AI, educators can unlock new opportunities to cater to individual learning needs and cultivate a more effective and enjoyable learning process. In this keynote, we will look at experimental software frameworks that can drive and level up education in multiple contexts and showcase some exemplars that demonstrate the promise that this integration provides.
提升教育水平:利用生成式人工智能进行游戏式学习
生成式人工智能在过去几年里大受欢迎,而且没有放缓的迹象。教育工作者和教育机构对如何以最佳方式利用人工智能的力量,同时又不忽视在使用过程中出现的道德和公平方面的挑战持怀疑态度。正在形成共识的一个领域是建立个性化学习解决方案,既能为广泛的学习者提供公平的学习机会,又不影响道德挑战。与此同时,基于游戏的学习已被证明是吸引学习者的一种可行范式,而游戏能够适应玩家/学习者的能力,为建立公平、无障碍的个性化学习解决方案提供了重要机会。在本讲座中,我们将讨论如何将基于游戏的学习与生成式人工智能协同结合起来,以利用彼此的能力,创建可大规模提供的教育干预措施。通过将游戏的互动性和激励性与生成式人工智能的适应性和智能性相结合,教育工作者可以开启新的机遇,满足个人的学习需求,培养更有效、更愉快的学习过程。在本主题演讲中,我们将探讨可在多种情况下推动和提升教育水平的实验性软件框架,并展示一些范例,以证明这种整合所带来的前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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