Publication Date

5-2021

Date of Final Oral Examination (Defense)

4-8-2021

Type of Culminating Activity

Dissertation

Degree Title

Doctor of Education in Educational Technology

Department

Educational Technology

Supervisory Committee Chair

Youngkyun Baek, Ph.D.

Supervisory Committee Member

Yu-Hui Ching, Ph.D.

Supervisory Committee Member

Yu-Chang Hsu, Ph.D.

Abstract

As a tangible and motivating medium for students to engage in computational thinking, robotics has drawn interest from educators and researchers as K-12 schools continue to integrate STEM into curriculum. Through this mixed methods study, the researcher sought to explore the effects of robotics instructional methods (task-based and project-based) on the computational thinking skills of middle school students, including the problem-solving strategies used and the role of peer collaboration. The quantitative results of this study indicated no significant difference in the computational thinking skills of students participating in task-based or project-based robotics instruction. Interviews consisted of open-ended questions in which problem-solving and collaboration in robotics were explored from the perspectives of the participants. In both groups, problem-solving strategies encompassed all aspects of computational thinking as students took an iterative approach to problem-solving in both tasks and projects. Peer collaboration was naturally occurring and frequent among both groups. In task-based robotics instruction, peer collaboration and problem-solving strategies were primarily focused on the programming of the robot. In project-based robotics, peer collaboration and problem-solving strategies were applied throughout the entire design process, including the building and the programming of the robot. Through this study, the researcher hoped to provide a roadmap for the implementation of robotics in schools for K-8 students. As schools are increasingly seeking ways to integrate robotics into school curriculum, further research in this area on a larger scale is recommended.

DOI

10.18122/td.1817.boisestate

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