Learning science concepts through metaphor comprehension, production, and conversation: Behavioral, neural and artificial intelligence measures

科学教师经常使用隐喻来教授科学概念。本项目研究隐喻学习如何在头脑和大脑中工作，在使用专家创造、自我生成或人工智能引导的隐喻时，这种学习效果是如何比较的，以及隐喻学习是否以及如何提高对所学概念的记忆保留。这项研究将促进我们对人们如何更有效地学习，以及个体差异如何影响学习过程的理解。这项研究的结果将为干预措施提供信息，以加强整个生命周期的学习和教育，它将拉丁裔和其他背景的高中生纳入其中，将扩大来自代表性不足的少数民族的不同学生在科学领域的参与和培训。研究人员将通过行为测量、人工智能、脑电波（EEG）和脑成像（fMRI）技术来解决上述问题。研究1将使用行为范式来评估隐喻推理在几天内对科学概念的学习和记忆的影响。研究2将对比被动和主动的隐喻学习（专家教授和计算机辅助自我生成），其中语义关联将由人工智能提供。研究1和研究2都通过对学生对目标概念（如分子）的知识进行多方面的前后测试来评估学习成果，并通过比较测量前和前一天学习的概念来测试所学知识的保留情况。研究3和研究4检验了概念学习背后的认知-神经机制假说，比较了隐喻和字面指导前后的科学概念神经表征（研究3）和实时导师与学生对话时的脑电图（研究4）。研究3和研究4都将在神经和行为数据之间进行跨水平分析。除了这四项研究外，该项目还将通过一个面向大学生的脑电图训练营来教育学习者研究方法，并通过七次以科学展览机会结束的访问来训练高中生进行研究。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Science teachers often use metaphors to teach science concepts. This project investigates how metaphoric learning works in the mind and in the brain, how such learning effects compare when using expert-created, self-generated, or artificial intelligence guided metaphors, and whether and how metaphoric learning improves memory retention of the learned concepts. This research will advance our understanding of how people learn more effectively, and how individual differences affect the learning process. The findings from this study will inform interventions to enhance learning and education throughout the lifespan, and its inclusion of high school students from Latinx and other backgrounds will broaden participation and training of diverse students from underrepresented minorities in science.The investigators will address the above mentioned questions with behavioral measures, artificial intelligence, brainwave (EEG), and brain imaging (fMRI) techniques. Study 1 will use behavioral paradigms to assess the effect of metaphoric reasoning on the learning and retention of science concepts over several days. Study 2 will contrast passive vs active learning of metaphor (expert-taught vs computer-aided self-generation), where semantic associates will be provided by artificial intelligence. Both study 1 and 2 assess learning outcomes with multi-faceted pre- and post- tests on student knowledge of target concepts (e.g., molecule) and test retention of learned knowledge by comparing concepts learned immediately before measurement vs. a day prior. Study 3 and 4 test hypotheses about the cognitive-neural mechanisms underlying concept learning, comparing the neural representations of science concepts before and after metaphoric and literal instructions using fMRI (Study 3) and in real-time tutor-student conversation using EEG (Study 4). Both study 3 and 4 will conduct cross-level analyses between neural and behavioral data. Alongside these four studies, the project will educate learners in research methodology through an EEG boot camp for university students, and training of high-school students to conduct research through seven visits that end with a science fair opportunity.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.