Chatbot Memory: Uncovering How Mental Effort and Chabot Interactions Affect Short-Term Learning.

Alexandre Marois, Isabelle Lavallée, Gabrielle Boily, Jonay Ramon Alaman, Bérénice Desrosiers, Noémie Lavoie
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Abstract

Developments in artificial intelligence (AI) are transforming everyday tasks, including accessing information, learning, and decision making. Generative AI is representative of these changes as it can generate content traditionally reserved for humans with increased efficiency and reduced effort. This includes technologies like ChatGPT and other tools that exploit large language models, typically taking the form of conversational agents (chatbots). These technologies can be useful for self-regulated learning as is the case for Web browsing. It is, however, unclear whether learning with chatbots may be efficient as opposed to other Web-based approaches given the reduced effort related to chatbot interactions. This study assessed how interacting with a chatbot may affect short-term learning and the role of mental effort. Memory performance was equivalent across participants who either interacted with a chatbot or browsed the Internet to find information for answering essay questions. Differences in self-reported workload were, however, found across conditions.

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聊天机器人记忆:揭示脑力劳动和聊天机器人互动如何影响短期学习。
人工智能(AI)的发展正在改变日常任务,包括获取信息、学习和决策。生成式人工智能是这些变化的代表,因为它可以以更高的效率和更少的努力生成传统上为人类保留的内容。这包括像ChatGPT这样的技术和其他利用大型语言模型的工具,通常采用会话代理(聊天机器人)的形式。这些技术对于自我调节学习很有用,就像Web浏览一样。然而,目前尚不清楚的是,与其他基于网络的方法相比,使用聊天机器人学习是否更有效,因为与聊天机器人交互相关的工作量减少了。这项研究评估了与聊天机器人的互动如何影响短期学习和脑力劳动的作用。无论是与聊天机器人互动,还是浏览互联网以寻找回答论文问题的信息,参与者的记忆力表现都是一样的。然而,在不同条件下,自我报告的工作量存在差异。
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