The Impact of Intelligent Pedagogical Agents’ Interventions on Student Behavior and Performance in Open-Ended Game Design Environments

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2023-01-04 DOI:https://dl.acm.org/doi/10.1145/3578523
Özge Nilay Yalçın, Sébastien Lallé, Cristina Conati
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Abstract

Research has shown that free-form Game-Design (GD) environments can be very effective in fostering Computational Thinking (CT) skills at a young age. However, some students can still need some guidance during the learning process due to the highly open-ended nature of these environments. Intelligent Pedagogical Agents (IPAs) can be used to provide personalized assistance in real-time to alleviate this challenge. This paper presents our results in evaluating such an agent deployed in a real-word free-form GD learning environment to foster CT in the early K-12 education, Unity-CT. We focus on the effect of repetition by comparing student behaviors between no intervention, 1-shot, and repeated intervention groups for two different errors that are known to be challenging in the online lessons of Unity-CT. Our findings showed that the agent was perceived very positively by the students and the repeated intervention showed promising results in terms of helping students make less errors and more correct behaviors, albeit only for one of the two target errors. Building from these results, we provide insights on how to provide IPA interventions in free-form GD environments.

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开放式游戏设计环境中智能教学主体干预对学生行为和表现的影响
研究表明,自由形式的游戏设计(GD)环境可以非常有效地培养儿童的计算思维(CT)技能。然而,由于这些环境的开放性,一些学生在学习过程中仍然需要一些指导。智能教学代理(IPAs)可用于实时提供个性化帮助,以缓解这一挑战。本文介绍了我们在一个真实世界的自由形式的GD学习环境中评估这种智能体的结果,以促进早期K-12教育中的CT, Unity-CT。针对Unity-CT在线课程中已知具有挑战性的两种不同错误,我们通过比较无干预组、单次干预组和重复干预组的学生行为来关注重复的影响。我们的研究结果表明,学生对代理的感知非常积极,反复干预在帮助学生减少错误和更正确的行为方面显示出有希望的结果,尽管只针对两个目标错误中的一个。基于这些结果,我们提供了如何在自由形式的GD环境中提供IPA干预的见解。
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