Developing Computational Thinking Assessments From Learning Trajectories: Design Approach and Preliminary Validity Evidence

• In Event: Assessment of Engineering and Computer Science Skills and Attitudes

Abstract

Computational thinking (CT) assessment tasks were developed to assess students' CT knowledge, skills, and abilities. These tasks were developed from hypothesized learning trajectories for several CT topics (e.g., sequence, repetition). The tasks were administered to elementary students who were taught using an integrated math + CT curriculum. To evaluate the assessments we (1) analyzed student responses to one of the CT assessment instruments and (2) conducted a think-aloud protocol in which students responded to tasks sampled across all CT trajectories. Results suggested the tasks are appropriate for students with varying CT competencies, and also that students approach some of the CT assessment tasks as math tasks, emphasizing the final answer rather than listing out the steps in a computational logic.

Authors

• Brian Douglas Gane, University of Illinois at Chicago

• Noor Elagha, University of Illinois at Chicago

• Feiya Luo, The University of Alabama

• Ruohan Liu, University of Florida

• Wei Yan, University of Florida

• Carla Strickland, University of Chicago

• Diana Franklin, University of Chicago

• Kathryn Rich, Michigan State University

• James W. Pellegrino, University of Illinois at Chicago

• Maya Israel, University of Florida