Learning Enviroments
My dissertation research centers on three core areas. Firstly, I emphasize the design of authentic learning environments, focusing on identity and learner-centered design choices. Secondly, I am in the process of developing a platform tailored to support the development of complex skills crucial in collaborative-oriented settings within these authentic learning environments. Thirdly, I employ a mixed-methods approach to characterize the learning processes, with a particular emphasis on context-relevant assessment tools. The primary context for this research is sports. Within the context of sports as authentic learning environments, I employ design-based research to describe how various components facilitate learning in computing, data science, and physical computing. Additionally, I am actively working on the development of a platform that caters to a wide range of team-oriented skill development, particularly in areas such as communication. Lastly, I place importance on ensuring that assessment tools are context-specific for these learning environments. In this domain, I am exploring the place of restructurations of sports knowledge and conduct analyses aimed at characterizing the dynamics of learning within sports teams.
Learning Experiences
I have co-designed and facilitated several versions of camp: bit (balls, information, and technology), a sports camp that authentically embeds computing to engage children with computational thinking, physical computing, and data literacy. We are writing a set of design principles that would be publish at the end of 2023.
Tools
I am developing a wearable device to support athletes communication skills.
I am also conducting user studies to evaluate prototyping tools' abilities to support creativity for student-athletes in bringing thier ideas to life.
methods: UX, rapid prototyping
tools: makecode platform; XIAO nRF52840,
Data Science
Modeling communication dynamics within sports teams. Learning Processes and Network Structures: Large group deliberation is complicated for several reasons, including limited communication among members and hubs that greatly influence other members through their social capital and influence. We modeled and simulated network structures to overcome these issues by breaking down large groups and shuffling them periodically. [Paper underview at Journal Nature Communications] methods: modeling and simulation tools: GitHub, VSC, Jupyter Notebook
Qualitative Methods
I conducted making sessions to identify how children’s learning constructs change after engaging with the making process. I used grounded theory and case study to analyze the data and published the results in Constructionism Conference 2023.
Previuos projects
Blockchains and governance.