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。这个项目调查了隐喻学习如何在大脑和大脑中发挥作用，当使用专家创建的、自我生成的或人工智能指导的隐喻时，这种学习效果如何比较，以及隐喻学习是否以及如何改善对所学概念的记忆保持。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。这项研究的发现将提供干预措施，以加强终身学习和教育，它包括来自拉美裔和其他背景的高中生将扩大来自未被充分代表的少数族裔的不同学生在科学领域的参与和培训。调查人员将通过行为测量、人工智能、脑电波(EEG)和脑成像(FMRI)技术解决上述问题。研究一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保持的影响。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的自我生成)，其中语义联系将由人工智能提供。研究1和研究2通过对学生的目标概念(例如，分子)的多方面前后测试来评估学习结果，并通过比较测量前一天和前一天学到的概念来测试对所学知识的保留。研究3和4测试了关于概念学习的认知-神经机制的假设，使用fMRI比较了隐喻和文字指导前后科学概念的神经表征(研究3)，并使用脑电比较了实时师生对话中科学概念的神经表征(研究4)。研究3和研究4都将在神经和行为数据之间进行交叉水平的分析。除了这四项研究，该项目还将通过大学生脑电训练营教育学习者研究方法，并培训高中生通过七次访问进行研究，最终获得科学博览会的机会。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.