Problem solving, critical thinking, and communication are essential engineering skills that are difficult to explicitly teach and assess. My research projects aim to better understand how students develop these skills as they transition from novice to expert engineers, and subsequently develop data-driven, easy-to-implement, classroom practices for engineering educators. Here I will focus on two areas of interest: (1) engineering intuition and (2) multiple representations.
Intuition is considered by some to be an integral factor in achieving expertise. We are particularly interested in student intuition with respect to assessing technology-aided problem solutions, as these best represent how students will be solving problems in the “real world.”
Multiple representations refers to engaging with information in a variety of forms (written, visual, etc.). Some prior work suggests that faculty may bring significant representation biases to their instruction. This work seeks to better understand whether disciplinary representation biases exist, and implications of these biases for students’ development of the essential skills of problem solving, critical thinking, and communication skills.
As a new faculty in the beginning of my tenure, I am presenting this work in its early stages. I will share my motivation for approaching the problem from these perspectives, my theoretical framework, past and current results, and future directions.
teaching, engineering education, representativeness, biases, heuristics