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   <dim:field mdschema="dc" element="contributor" qualifier="advisor">Abelson, Harold</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author">Granquist, Ashley</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science</dim:field>
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   <dim:field mdschema="dc" element="description" qualifier="abstract">The recent revolutionary advancements in Artificial Intelligence (AI) have presented im- mense opportunities and challenges in computer science education. This thesis presents the development of an AI-powered tool built on top of MIT App Inventor to help students in- crementally design mobile applications. The tool allows students to describe desired changes to their MIT App Inventor mobile applications in natural language and have those changes be implemented automatically. Students can alternate between manually editing their app and using this tool, enabling them to collaborate with AI and incrementally develop apps with a degree of assistance from AI that meets their needs and is appropriate for their skill level and workflow preferences. This thesis also explores the benefits and detriments of such a tool, as well as observations and lessons learned from studying the ways students interact with the tool during a pilot study.</dim:field>
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   <dim:field mdschema="dc" element="title">AI-Augmented Interface for Incremental App Development in MIT App Inventor</dim:field>
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   	&lt;Title>AI-Augmented Interface for Incremental App Development in MIT App Inventor&lt;/Title>
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   	&lt;Abstract>The recent revolutionary advancements in Artificial Intelligence (AI) have presented im- mense opportunities and challenges in computer science education. This thesis presents the development of an AI-powered tool built on top of MIT App Inventor to help students in- crementally design mobile applications. The tool allows students to describe desired changes to their MIT App Inventor mobile applications in natural language and have those changes be implemented automatically. Students can alternate between manually editing their app and using this tool, enabling them to collaborate with AI and incrementally develop apps with a degree of assistance from AI that meets their needs and is appropriate for their skill level and workflow preferences. This thesis also explores the benefits and detriments of such a tool, as well as observations and lessons learned from studying the ways students interact with the tool during a pilot study.&lt;/Abstract>
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