Computational Thinking as a Practice of Representation: A Proposed Learning and Assessment Framework

Abstract

This study proposes a research and learning framework for developing and assessing computational thinking under the lens of representational fluency. Representational fluency refers to individuals' ability to (a) comprehend the equivalence of different modes of representation and (b) make transformations from one representation to another. Representational fluency was used in this study to guide the design of a robotics lab. This lab experience consisted of a multiple step process in which students were provided with a learning strategy so they could familiarize themselves with representational techniques for algorithm design and the robot programming language. The guiding research question for this exploratory study was: Can we design a learning experience to effectively support individuals' computing representational fluency? We employed representational fluency as a framework for the design of computing learning experiences as well as for the investigation of student computational thinking. Findings from the implementation of this framework to the design of robotics tasks suggest that the learning experiences might have helped students increase their computing representational fluency. Moreover, several participants identified that the robotics activities were engaging and that the activities also increased their interest both in algorithm design and robotics. Implications of these findings relate to the use of representational fluency coupled with robotics to integrate computing skills in diverse disciplines.

Computational thinking in higher education: A review of the literature

“…Thus, there was far less than consensus among how to measure and assess computational thinking skills within the students. One complexity with computational thinking is that it is more related to the process of moving between representations than on the final product [31]. This means that currently educators are left without options for standardized ways of measuring computational thinking skills within their students.…”

“…The models and modeling perspective has been heavily studied concerning engineering education [7,8,33]. Discipline-based modeling and simulation has been shown to help students build both programming skills and disciplinary skills within engineering contexts [24,28,31] Thus, bringing this perspective to incorporating computational thinking within education engineering contexts may give key insights into how best to create computational thinking-enabled engineering professionals.…”