Cayla Risinger
Cayla Risinger
Home Institution
The University of Illinois at Urbana-Champaign
Year Participated
2022
Year in School
Undergraduate
REU Faculty Mentor
Colleen Lewis
Research Area Interest
Computers and Education
Biography & Research Abstract
Abstract:
Physical representations are pedagogical tools used to build an understanding of abstract concepts in computer science (CS), which is important to making CS education more accessible. The use of everyday objects within physical representations can help students with less privilege and prior knowledge succeed and feel qualified to continue in the field by challenging the stereotype that CS is only for intellectual elites. Similar to how math uses physical representations, we have worked on developing physical models of coding concepts (e.g. objects/references, inheritance, method calls, linked data structures, arrays/arraylists, and conditional/loop execution). We have written an activity that uses physical objects to teach students about arrays. We received feedback on clarity and effectiveness from both high school students and AP CS A teachers. The activity uses an instructional strategy known as process oriented guided inquiry learning (POGIL), which is focused on building students’ conceptual understanding through collaboration. The effectiveness of these physical models will be tested through interviews with students where they are given either a 3D or 2D representation and are asked to work through a series of tasks. Through the design and distribution of these physical representations, we hope to make CS education more accessible and broaden participation in CS.
Bio:
I am a rising junior at the University of Illinois Urbana-Champaign majoring in Computer Science. I am currently interested in being a professor and teaching Computer Science. In addition to taking CS classes for my major, I have also taken a class on digital learning environments and have been a Course Assistant for CS 128, Intro to Computer Science II, for two semesters. I want to work on improving CS education by finding new ways to teach material more effectively and efficiently for different learning styles.