Date of Award

2020

Degree Type

Thesis

Degree Name

Doctor of Philosophy

School

School of Arts & Humanities

First Advisor

Associate Professor Stuart Medley

Second Advisor

Dr Greg Baatard

Field of Research Code

129999, 130201, 130212

Abstract

The thesis will explore the implications of teaching computer science through visual communication. This study aims to define a framework for using pictures within learning computer science. Visual communication materials for teaching computer science were created and tested with Year 8 students. Along with a recent commercial and political focus on the introduction of coding to adolescents, it appears that the computer industry has a large shortfall of programmers. Accompanying this shortfall is a rise among adolescents in the preference for visual communication (Brumberger, 2011; Coats, 2006; Oblinger et al., 2005; Prensky, 2001; Tapscott, 1998) while textual communication currently dominates the teaching materials in the computing discipline. This study looks at the learning process and utilises the ideas of Gibson, Dewey and Piaget to consider the role of visual design in teaching programming. According to Piagetian theory Year 8 is the time a child begins to understand abstract thought. This research investigated through co-creation and prototyping how to creatively support cognition within the learning process. Visual communication theories, comprising the fields of graphic and information design, were employed to communicate computer science to approximately 60 junior high school students across eight schools. Literature in a range of visual communication fields is reviewed along with the psychology of perception and cognition to help create a prototype lesson plan for the target audience of Year 8 students. The history of computer science is reviewed to illustrate the mental imagery within the discipline and also to explore computational thinking concepts. These concepts are ". . . the metaphors and structures that underlie all areas of science and engineering" (Guzdial, 2008). The participants’ attitudes increased toward learning programming through visual communication. Quantitative questionnaires were used to gather data on cognition and measure the effectiveness of the learning process. Thirteen hypotheses were established concerning learning programming through pictures from the quantitative data. Focus groups further triangulated data gathered in the quantitative stage. Approximately seventy percent of the participants understood seventy percent of the information within the instrumentation. Models of intent to learn programming through pictures were established using structural equation modelling (SEM). Outcomes of the exegesis are a framework for using pictures that demonstrates computational thinking and explains the research.

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