Principal Investigator: Julie Linsey
CoPrincipal Investigator(s): Wayne Li
Organization: Georgia Tech Research Corporation
The Cyberlearning and Future Learning Technologies Program funds efforts that will help envision the next generation of learning technologies and advance what we know about how people learn in technology-rich environments. Cyberlearning Exploration (EXP) Projects explore the viability of new kinds of learning technologies by building examples and studying their possibilities for fostering learning as well as challenges to using them well. This project examines whether technology can support learning to freehand sketch. Sketching has been demonstrated to play an important role in a number of domains, including engineering, and the ability to quickly sketch has been shown to improve creativity by making it easier for engineers to generate ideas and communicate them. This project will modify artificial intelligence tools that support recognizing sketches to directly help teach undergraduate engineers how to sketch well. Research studies will examine whether the tool helps students learn sketching skills, and importantly how it influences their spatial reasoning ability. Thus, if successful this research will not only create tools to allow people to learn to sketch better, but also will advance our understanding of how spatial reasoning and sketching are linked, and could eventually lead to more effective engineering education.
The project proposes two interconnected strands of work: developing the software tool and conducting research studies in the context of undergraduate engineering courses. The software tool will use a heterogenous set of classifiers to help provide feedback to learners as they perform a sequence of sketching exercises on tablets. The design process will iterate on the tool to explore what types of feedback are most helpful and how different classifiers can be used to detect different levels of sketching skill. The program of research will include studying whether sketching training leads to advances in spatial reasoning skills, whether it affects design self-efficacy and attitudes towards sketching, transfer of spatial skillsets to design activities in other courses, and how sketching skills correlate to success on spatial reasoning tasks. In addition, through iterative development including user-centered design processes, design principles for sketching based tools will be derived. Data sources will include both qualitative and quantitative data such as pre- and post-test spatial reasoning tasks, structured interviews, surveys, and artifact analysis. Additionally, students (N=approximately 30-40) using the new tool in class will be compared to control cohorts of approximately 30 students who either use traditional engineering curricula (little free-hand sketching and some isometric drawing) and a sketching curriculum without the AI tool.