Date of Award:

2016

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Instructional Technology and Learning Sciences

Advisor/Chair:

Sheri Haderlie

Abstract

Teaching computational thinking has been a focus of recent efforts to broaden the reach of computer science (CS) education for today’s students who live and work in a world that is heavily influenced by computing principles. Computational thinking (CT) essentially means thinking like a computer scientist by using principles and concepts learned in CS as part of our daily lives. Not only is CT essential for the development of computer applications, but it can also be used to support problem solving across all disciplines. Computational thinking involves solving problems by drawing from skills fundamental to CS such as decomposition, pattern recognition, abstraction, and algorithm design.

The present study examined how Dr. Scratch, a CT assessment tool, functions as an assessment for computational thinking. This study compared strengths and weaknesses of the CT skills of 360 seventh- and eighth-grade students who were engaged in a Scratch programming environment through the use of Dr. Scratch. The data were collected from a publicly available dataset available on the Scratch website. The Mann-Whitney U analysis revealed that there were specific similarities and differences between the seventh- and eighth-grade CT skills. The findings also highlight affordances and constraints of Dr. Scratch as a CT tool and address the challenges of analyzing Scratch projects from young Scratch learners. Recommendations are offered to researchers and educators about how they might use Scratch data to help improve students’ CT skills.

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