AI 中文总结
该研究针对网络错误信息及数字素养教育问题，通过举办“捕捉叙事”多校竞赛，让学生团队构建大语言模型驱动的机器人影响模拟选举，分析竞赛情况及学生反馈，为教育工作者提供建议并提出改进方向。
AI 中文摘要
错误信息在网络话语中根深蒂固，全球事件期间近五分之一的帖子由机器人生成，它们放大虚假内容。近年来，生成式人工智能的使用进一步降低了制造可信错误信息的门槛，但大多数数字素养教育仍依赖于为早期媒体环境构建的静态清单和单人接种游戏。本文描述了我们如何通过“捕捉叙事”来填补这一教育差距，这是一项为期四周的多所大学竞赛，学生团队构建由大语言模型驱动的机器人来影响模拟选举。我们报告了我们定制的社交媒体平台、竞赛环境及其4000个由人工智能驱动的非玩家角色公民的设计，以及大规模运行“捕捉叙事”实际涉及的内容。在首次迭代中，来自18所澳大利亚大学的108个团队产生了7068206条玩家-机器人帖子，约占所有平台内容的60%。我们在竞赛前后分别对256名和83名学生进行了调查，以了解他们对错误信息和游戏本身的看法，发现学生在识别机器人方面并没有变得更自信，这与接种理论的预测相反。由于参与度会得到奖励，大多数团队将大量发帖置于细微影响之上，这反映了现实世界平台的动态。我们最后为考虑类似干预措施的教育工作者提供了建议，并提出了未来的改进方向，比如增加蓝队防守阶段。
英文摘要
Misinformation is deeply embedded in online discourse, with nearly one in five posts during global events generated by bots that amplify false content. In recent years, the use of Generative AI has further lowered the barrier to producing convincing misinformation, yet most digital literacy education still relies on static checklists and single-player inoculation games built for an earlier media landscape. This paper describes how we addressed this educational gap through Capture the Narrative, a four-week multi-university competition in which student teams build LLM-powered bots to influence a simulated election. We report on our custom social-media platform, the competition environment and design of its 4,000 AI-driven Non-Player Character (NPC) citizens, and what running Capture the Narrative at scale actually involved. In our first iteration, 108 teams from 18 Australian universities produced 7,068,206 player-bot posts, approximately 60% of all platform content. We surveyed 256 students before and 83 after the competition to understand their perceptions of misinformation and the game itself and found that students did not become more confident at spotting bots, contrary to what inoculation theory predicts. Because engagement was rewarded, most teams prioritised high-volume posting over nuanced influence, mirroring real-world platform dynamics. We close with recommendations for educators considering similar interventions, and propose future improvements, such as including a blue-team defensive phase.
Comments7 pages, 1 figure. Paper is under review
