Supporting Chemistry Learning with Adaptive Support for Connection Making Between Graphical Representations in a Cognitive Tutoring System
Supporting Chemistry Learning with Adaptive Support for Connection Making Between Graphical Representations in a Cognitive Tutoring System
批准号:
1611782
负责人:
Martina Rau
金额:
$59.38万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-09-01 至 2020-08-31
中文摘要
点击翻译按钮获取中文摘要
英文摘要
Success in science, technology, engineering, and mathematics (STEM) depends on the ability to learn with graphical representations that use visual features to depict information. Many instructors assume that visuals help students learn, but they can be confusing if students do not know how the visuals show information. The goal of this project is to design and study the effectiveness of an educational technology called Chem Tutor to help college chemistry students learn with visuals. The project will determine how Chem Tutor technology can help students learn about visuals in a way that enhances their ability to learn from visuals about complex chemistry knowledge. Specifically, the project will focus on supporting two representation skills: the ability to make sense of how particular visual features illustrate concepts (sense-making) and perceptual fluency with visuals (akin to fluency in a language). The project will investigate how best to combine supports for these two skills in learning about representations, and the technology will also be designed to adapt to individual student's learning progress. This project will be conducted in the context of undergraduate chemistry learning at two-year and four-year colleges, including Madison Area Technical College and the University of Wisconsin - Madison, and is also expected to inform the development of educational technologies for other STEM disciplines.The goal of this NSF Improving Undergraduate STEM Education (IUSE: EHR) project is to help chemistry students acquire the important representation skills of sense-making and perceptual fluency in using graphical representations without mental effort. This will be accomplished by designing and studying the Chem Tutor intelligent tutoring system that will adapt to individual student's learning progress. The development of Chem Tutor will rely on user-centered design techniques to create an effective educational technology for undergraduate chemistry students. A series of experiments will then be conducted to investigate how sense-making and perceptual-fluency skills interact, how support for these skills should be combined, and whether adaptive support for enhancing representation skills is an effective pathway to improve learning outcomes in chemistry. Further, the project will investigate effects on gender equality. Thus, the project will contribute to educational psychology and chemistry education research regarding the role of graphical representations in students' learning; yield principles for the design of adaptive educational technologies that support representation skills; and contribute to undergraduate chemistry education by freely disseminating the final version of Chem Tutor to students at two-year and four-year colleges.
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