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Abstract
In this this dissertation study, I develop visual prompts for robotics education with the Bee-Bot for three kindergartners with suspected Attention-Deficit/Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) in three independent settings. Employing Latour’s (2005) Actor-Network Theory (ANT) and design-based research methodology (DBR) founded by Brown (1992) and Collins (1992), I pay attention to these three participating children’s responses to visual prompts in order to create, refine, and evaluate the visual prompts as instructional materials for robotics education. For this study, I systematically conducted a microanalysis of video data and an artifact analysis of visual prompts in Cycles 1, 2, and 3. The findings of this study show the agentic roles of the visual prompts in robotics education: 1) the role of the prompts, along with a pre-teaching strategy, in letting the child find the command cards and program the Bee-Bot using those cards in order, 2) the role of the prompts, along with the annotation strategy, in teaching the order of command button cards and the way to correct errors on the cards along with the path the child drew, and 3) the role of visual prompts, adopting both pre-teaching and annotating strategies, in guiding the child to identify the incorrect command cards when the Bee-Bot made wrong movements. This study highlights the agentic roles of visual prompts in teaching concepts and skills as mediators in these children’s robotics education. In addition, this study shows the importance of the iterative process of developing visual prompts to address the participating children’s diverse challenges in robot programming procedures.