Abstract

The increased presence of technology in all aspects of daily life makes computational thinking a necessary skill. Predictions say that the rising need for computational thinkers will be unmet by computer science graduates. An e-textile learning module, based on principles of constructionism, was designed as a method to develop computation thinking skills and encourage interest and confidence in the computing fields in both male and female graduate education students. The module leveraged the affordances of the LilyPad Arduino, a technology that allows for the creation of projects that integrate textiles and electronics without soldering. The creation of the learning module relied on design-based research methodologies and followed the use-modify-create principle for the included activities. Multiple data sources were analyzed using The Computational Thinking Rubric for Examining Students' Project Work to examine artifacts and interactions for indications of computational thinking concepts, practices, and perspectives. Students participated in debugging activities and created their own projects as part of the learning module. Analysis of the learning module activities showed students using computational thinking concepts, engaged in computational thinking practices, and exhibiting computational thinking perspectives. During the coding process, several new computational thinking concepts, practices, and perspectives emerged. There was evidence of both an increase and decrease in confidence among the student participants. Improvements for the next iteration of the learning module were presented and the implications for the study of computational thinking explored. the study helps contradict the shrinking pipeline metaphor by showing that it is possible to encourage interest in computation in university students, not just middle-school students.

Library of Congress Subject Headings

Dissertations (EdD) -- Learning technologies; Computational learning theory -- Education, Higher; Electronic textiles -- Education, Higher; Graduate students

Date of Award

2019

School Affiliation

Graduate School of Education and Psychology

Department/Program

Education

Degree Type

Dissertation

Degree Name

Doctorate

Faculty Advisor

Polin, Linda;

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