SUMMARY

As science and technology advances, the importance of creativity in engineering design increases, but it seems harder to come up with novel or creative ideas. Also, the number of workplace and education environments that are encouraging and utilizing more virtual workspaces and virtual collaboration is increasing. Global trends indicate that future workplace and education environments will require virtual collaboration and interfacing with technology and artificial intelligence. However, working and learning in virtual environments reduces productivity and efficiency due to difficulties in communication, low level of media richness, and frequent multitasking during team collaboration. By augmenting cognitive skills for collaboration in virtual environments, problem solvers and designers can improve their creativity, problem solving, communication, and documentation of their outcomes. The work presented in this dissertation addresses these challenges by presenting the first unsupervised speech-based automated mindmapping technology, Speech2Mindmap and AIRT Speech2Mindmap to address following research goals and questions: Research Goals 1) Augment human cognition through the advancement and automation of mindmapping technology, supporting the expansion of human creativity by lowering cognitive load. 2) Design a tool to better support virtual and in-person collaboration using automated mindmapping technology. Research Questions 1) How can mindmapping technology be enhanced using computational automation techniques? 2) How similarly and reliably can the automated mindmapping technology represent the human thought process or human-generated mindmaps? 3) How does artificial intelligence incorporated real-time automated mindmapping technology affect human creativity and productivity in design problem solving? 4) How usable and well received is this A.I. assisted real-time mindmapping technology as an ideation tool for designers? This dissertation is composed of four main research tasks; 1) developing an unsupervised mindmapping software (Speech2Mindmap) that uses recorded audio data, 2) investigating how accurate and reliable the unsupervised Speech2Mindmap tool is, 3) developing a real-time responsive and AI-assisted speech-based Speech2Mindmap software, 4) and investigating the usability and effects of using the real-time AI-assisted Speech2Mindmap software.