What representations am I using in my courses? Here’s an “app” for that!

As engineering educators, we are equipping technical experts with the skills to succeed in their profession, as well as make significant contributions to society. Problem solving and critical thinking skills are the foundation of engineering. These require not only technical (content) skills, but also fluency in engaging with a variety of information. Consequently, students who are comfortable with engaging multiple representations of information are likely also more robust problem solvers and critical thinkers. We are engaged in a multi-phase investigation to study whether exposure to diverse representations results in statistically significant differences in student problem solving, critical thinking, or communication skills. To accomplish this, it is useful for educators to be able to identify and track the representations used in their individual classes, as well as throughout degree programs. The current work was conceived following a study conducted in the chemical engineering department at a large Midwestern university. Observations from this study demonstrated that different instructors for the same course exhibited similar tendencies on exam problem representations. Furthermore, students were less successful on concept inventory problems using representations that were under-utilized by their instructors. Instructors involved in the study were also interested in further utilizing the “representations rubric” developed for this study, and curious as to whether these representation biases persisted through other courses in their degree program. To this end, we are developing an “app” that allows instructors to track the diversity of course experiences they are exposing students to by recording the “experience type” (e.g., lecture, homework problem, exam question) and the representation used (e.g., active, intuitive, visual). The “app” will record this information, and present longitudinal summaries of representations favored by the instructor, highlighting which representations students may not be exposed to frequently. When used across a course or a degree program, this technology can serve as both a formative and summative assessment of instructional strategies. In this work-in-progress paper, we will describe the “app”, its features, and plans for beta-version testing. We will also highlight how this “app” will be used to study prevalent representations in chemical engineering across institutions, and whether diversifying course experiences leads to greater problem solving capabilities in students. Purpose and Scope of Paper The described “app” is part of a long-term project to study the effects of exposure to diverse representations on chemical engineering student problem solving, critical thinking, and communication skills. The “app” is being developed primarily as a data-collection tool, but we also foresee potential implications for classroom use (depending on study results) as later described. At the time of this work-in-progress publication the “app” is in initial stages of development. Thus, we outline the framework for the “app” idea in detail, and describe some “app” features prior to broad dissemination of the “app” for beta-testing next year. Introduction and Motivation Engineering is often equated with problem solving. Critical thinking and communication are also essential skills for the professional engineer. The ability to think about problems critically is essential to being able to solve them, and the ability to communicate is also essential. Communication is important not only to share solutions, but also for understanding the problem and gathering the necessary information to solve it. If diversifying course experiences is shown to increase student problem-solving, critical thinking, and communication skills, we must focus our attention on how this diversity can be achieved in a manner that is low cost with respect to both time and money for the instructor. We believe that the “app” described may result in a viable new instructional and curricular planning tool for use in engineering education. As mentioned, the work described here is Phase I of a long-term project to study the effects of exposure to diverse representations on chemical engineering student problem solving, critical thinking, and communication skills. Rigorous curricular and disciplinary biases may limit students’ natural exposure to different representations in the ordinary course of their degree program. This may be hindering our students in their ability to tackle the increasingly difficult challenges of modern society. Our best attempts to re-create “real-world” experiences in our classrooms are still moderately controlled proxies, and in the “real world,” students will encounter problems, data, and information presented in all sorts of ways. It is our responsibility as educators to prepare them for these encounters. While multiple representations are promoted for their ability to engage different types of learners and diversify teaching styles, there is little research available on their effect on problem solving and critical thinking skills. Furthermore, the work that is available often focuses on a single representation (e.g., visualization). Because exposure to diverse representations will theoretically allow students to be more versatile thinkers, we believe this will result in greater development of problem solving and critical thinking skills. To be able to study this, we must first develop a framework to categorize representations, and assess what the “standard” representations for a given curriculum or course are. Having originated in the discipline of chemical engineering, this work will initially focus on that discipline before expanding to others. Over the course of this project, we will: 1) Develop a framework for categorizing representations (Phase I) 2) Adopt this framework into a user-friendly web-based electronic tool (the “app”) that will allow instructors to categorize the representations used in their course, track these representations over time, and see summaries of their representation biases (Phase II) 3) Test the “app” for usability, validity, and reliability (Phase II) 4) Use the “app” to study representations used in chemical engineering courses at institutions of interest (Phase III) 5) Report on institutional or course trends seen in Phase III, and identify “standard” representation experience (Phase III) 6) Use data from Phase III to select courses of interest for comparative study. Use preand post-semester problem solving and critical thinking analyses to compare a “standard” section of course with one which has been redesigned to expose students to a balanced variety of representations (Phase IV) Focus of the current work-in-progress publication will be on Phase I (complete, reported elsewhere) and Phase II (in progress) with some description of the vision for upcoming Phases III and IV.