CAREER: Intelligent Representations: How to Blend Physical and Virtual Representations by Adapting to the Individual Student's Needs in Real Time

适应性教育技术可以极大地提高学生在科学、技术、工程和数学 (STEM) 领域的学习。这些技术的一个特殊优势是它们可以提供可视化复杂概念的交互式模型。教育技术通常使用学生通过鼠标或键盘操作的虚拟模型。然而，学生用手操作的物理模型可以更直观，因为它们将抽象概念与学生联系起来？现实世界中的身体体验。该职业项目研究如何最好地将物理模型整合到适应性教育技术中。该项目将重点关注模型在教学中发挥关键作用的领域：本科生化学。两年制和四年制大学的一系列实验将测试物理模型或虚拟模型对于特定概念是否最有效，以何种顺序呈现它们，以及如何帮助学生在它们之间建立联系。此外，该团队还将开发一种技术，可以评估学生如何操作物理模型。结果将被整合到物理​​和虚拟模型如何影响学生学习的综合理论中。结果将帮助教师为学生选择最佳模型。该团队将在研究结果的基础上开发一种教育技术，根据学生的学习进度，自适应地选择对学生最有帮助的物理和虚拟模型。这项研究将产生一种新型的教育技术，它融合了物理和虚拟模型，并且可以适应个别学生的身体互动。此类技术可以使具有不同背景的学生更容易理解 STEM 概念。此外，通过吸引那些经常缺乏技术创新机会的两年制大学的学生和教师，该项目将扩大 STEM 的参与并增强社会经济平等。学生在视觉表达方面的思考困难会危及他们在化学等科学、技术、工程和数学 (STEM) 领域的学习。物理（有形）和虚拟表征模式对于学生的学习具有互补的优势。然而，当学生学习抽象内容时，还没有关于表征模式如何相互补充的全面理论。这个职业项目的目标就是发展这样的理论。由于物理和虚拟表示的有效组合是特定于概念、行动和学生的，因此对于教师来说，如果没有支持，它们可能太复杂而无法实现。教育技术可以提供此类支持，但它们无法与物理表征交互。因此，这个职业项目的另一个目标是将有关表征模式的理论转化为自适应教育技术，智能地融合物理和虚拟表征。两年制和四年制大学化学的一系列实验将研究物理和虚拟表征如何相互补充，如何最好地对它们进行排序，以及如何最好地帮助学生在它们之间建立联系。与教师和学生一起进行的用户研究将调查教育技术设计如何解决真实学习环境中的教育需求和系统约束，以及如何支持教师有效地结合表征模式。进一步的项目活动将把智能混合框架扩展到 K-12 环境中的 STEM 领域。该项目将贡献关于物理和虚拟表征如何相互补充的新理论。它将为适应学生个体身体互动的教育技术设计提供实用的建议。具体的交付成果将是针对两年制和四年制大学化学的适应性教育技术，免费提供并向不同人群传播。通过将两年制大学纳入其中，并使这项研究适用于 K-16 背景下的 STEM 教育，该项目可能会扩大许多 STEM 领域的参与并增强社会经济平等。

Adaptive educational technologies can much improve students' learning in science, technology, engineering, and mathematics (STEM) domains. A particular strength of these technologies is that they can provide interactive models that visualize complex concepts. Educational technologies typically use virtual models that students manipulate via mouse or keyboard. Yet, physical models that students manipulate with their hands can be more intuitive because they relate abstract concepts to students? bodily experiences in the real world. This CAREER project examines how best to integrate physical models into adaptive educational technologies. The project will focus on a domain where models play a crucial role in instruction: undergraduate chemistry. A series of experiments at 2-year and 4-year colleges will test whether physical or virtual models are most effective for particular concepts, in which order to present them, and how to help students make connections among them. Further, the team will develop a technology that can assess how students manipulate physical models. Results will be consolidated in a comprehensive theory of how physical and virtual models affect student learning. The results will help instructors select the best model for their students. The team will build on the results to develop an educational technology that adaptively selects physical and virtual models that is most helpful to the individual student given his/her learning progress. This research will yield a new type of educational technologies that blend physical and virtual models and that can adapt to individual students' bodily interactions. Such technologies can make STEM concepts more accessible to students with diverse backgrounds. Further, by involving students and instructors from 2-year colleges who often lack access to technology innovations, the project will broaden participation and enhance socioeconomic equality in STEM.Students' difficulties in thinking in terms of visual representations jeopardize their learning in science, technology, engineering, and math (STEM) domains such as chemistry. Physical (tangible) and virtual representation modes have complementary benefits for students' learning. Yet, there is no comprehensive theory of how representation modes complement one another when students learn abstract content. The goal of this CAREER project is to develop such theory. Because effective combinations of physical and virtual representations are concept-, action-, and student-specific, they are likely too complex for instructors to achieve without support. Educational technologies can offer such support, but they cannot interface with physical representations. Hence, another goal of this CAREER project is to translate theory about representation modes into adaptive educational technologies that intelligently blend physical and virtual representations. A series of experiments in 2- and 4-year college chemistry will investigate how physical and virtual representations complement one another, how best to sequence them, and how best to help students make connections among them. User studies with instructors and students will investigate how educational technology design can address educational needs and systemic constraints in real learning contexts and how to support instructors in combining representation modes effectively. Further project activities will expand the intelligent blending framework to STEM domains in K-12 contexts. The project will contribute new theory about how physical and virtual representations complement one another. It will yield practical recommendations for the design of educational technologies that adapt to individual students' body-based interactions. A concrete deliverable will be an adaptive educational technology for 2- and 4-year college chemistry, available for free and disseminated to diverse populations. By including 2-year-colleges and by making this research applicable to STEM education in K-16 contexts, this project may broaden participation and enhance socioeconomic equality in many STEM domains.