In software engineering, psychological safety is the shared belief that team members feel safe to take interpersonal risks in the workplace. Psychological safety plays an essential role in communication, especially in tightly coupled team activities like mob programming (i.e., mobbing), in which three or more team members develop software together. Mobbing requires members to play different roles while suggesting and digesting new ideas, which makes them particularly vulnerable to interpersonal risk. Autistic software engineers can struggle with mob programming, as they experience high levels of anxiety and stress when communicating with others due to their different cognitive and communication styles. A collaborative space that allows autistic team members to flexibly communicate in neurodiverse teams can increase the psychological safety and accessibility of collaborative software development.

To identify tools and practices that foster psychological safety in neurodiverse collaborative mob programming, I will conduct a series of mixed-method, design-based studies. First, I conduct a survey and interview study to uncover the relationship between neurodivergent cognitive and communication traits and psychological safety in teams. Second, I generate design principles for psychological safety through the iterative design and evaluation of a neuroinclusive digital collaboration space. Third, I evaluate the impact of these design principles through an experiment with majority, minority and all neurodivergent teams.

My work makes the following contributions to accessible software engineering education and practice: 1) Novel descriptions of psychological safety relating to neurodivergent cognitive and communication attributes; 2) design principles for fostering psychological safety in collaborative software development teams; 3) a software development tool that scaffolds psychologically safe mobbing in neurodiverse software teams.

I am a Ph.D. student in Human-Computer Interaction at Carnegie Mellon University.

I research psychologically safe collaboration in neurodiverse AI engineering teams. I aim to discover design principles for software development tools that support psychological safety among engineers with social and emotional differences. This can foster team learning, well-being, and productivity.

I have worked with Deloitte, Google, and the Caribbean Science Foundation.

Mon 4 Aug

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14:50 - 15:40
14:50
50m
Talk
Transfer Student Success in CS: Modeling Pathways and Outcomes
Doctoral Consortium
Nawar Wali Virginia Tech
14:50
50m
Talk
Supporting Structured Problem-Solving in Machine Learning Education
Doctoral Consortium
Clemens Witt TUD Dresden University of Technology
14:50
50m
Talk
Leveraging Large Language Models to Integrate Culturally Responsive Problems in Computer Science Theory Classes
Doctoral Consortium
Erica Goodwin University of Chicago
14:50
50m
Talk
Understanding and Developing Educational Tools in the LLM Era
Doctoral Consortium
Jason Weber University of California, Irvine
14:50
50m
Talk
Fostering Psychological Safety for Learning in Neurodiverse Software Teams
Doctoral Consortium
Ren Butler Carnegie Mellon University
14:50
50m
Talk
Socioeconomic Disparity Factors in Computer Science Education
Doctoral Consortium
14:50
50m
Talk
Justice-Centered Computing Education in Refugee Support Organizations
Doctoral Consortium
Megumi Kivuva University of Washington, Seattle
14:50
50m
Talk
Modeling Students’ Emotions in Computing Education: A Context-Specific Multi-Modal Approach
Doctoral Consortium
FNU Rakhi The Ohio State University
14:50
50m
Talk
Towards Digital Sovereignty and Self-Determination: A Community-Driven Framework for CS Education in the Tibetan Diaspora
Doctoral Consortium
Yeshi Paljor University at Buffalo
14:50
50m
Talk
Understanding the Effects of AI Literacy Lessons on Student Usage and Understanding of LLMs
Doctoral Consortium
Grace Li University of Chicago