Supporting Chemistry Learning with Adaptive Support for Connection Making Between Graphical Representations in a Cognitive Tutoring System

The ability to make connections among graphical representations is key to students' learning in science, technology, engineering, and math (STEM) domains. For instance, to learn about bonding in chemistry, students need to make connections among representations such as Lewis structures and ball-and-stick models. Traditional chemistry instruction often focuses on one type of connection-making ability: the ability to make sense of connections. However, chemistry expertise also involves a second type of connection-making ability: perceptual fluency—the ability to rapidly translate among representations based on their perceptual characteristics. Perceptual fluency enhances learning because it frees up students’ cognitive resources that students can invest in understanding complex concepts.

The goal of this project is to investigate how best to combine support for sense-making ability and perceptual fluency, using an adaptive educational technology. Such technologies have been shown to significantly enhance learning in STEM. They can adapt instruction to an individual student’s needs based on real-time diagnostics of his/her current knowledge level. As part of the project, we will develop Chem Tutor, an adaptive educational technology for undergraduate chemistry learning. Chem Tutor will adapt connection-making support to the individual student’s level of sense-making ability and perceptual fluency in real time. We hypothesize that such adaptive connection-making support will significantly enhance undergraduate chemistry learning.



Martina Rau


Active through August 31, 2019

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Martina Rau