This year, BCNM initiated its undergraduate research fellowships, which offer undergraduates the chance to engage in direct research experience with BCNM graduates. MacKenzie Alessi was selected to work with John Scott (Education) on his research into online education.
What if we could map learning in the social realm? How would classroom engagement appear and shift over time? And how could we use this data to improve teaching?
These are the questions at the heart of John Scott’s dissertation research at the School of Education, where he investigates the role of art and storytelling. Fascinated by the digital context for learning in formal and informal spaces, John seeks to understand how these activities lead to knowledge production. This year, he had some help on the project, thanks to the inaugural BCNM Undergraduate Research Fellowships. MacKenzie Alessi, a senior in interdisciplinary studies, was selected to work on data visualizations for this study.
A former political science major, MacKenzie turned to interdisciplinary studies to explore her varied interests — while still graduating on time! As part of her program, she was able to take such influential courses as the History of Information with Geoffrey Nunberg and Concepts of Information with Paul Duguid, discovering her passion for data in the process.
MacKenzie built on this foundation by interning with BCNM Director Greg Niemeyer over the summer through a Digital Humanities grant. Blending art and computer science, she learned how to code data representations — a skill that would prove invaluable when she partnered with John Scott to question the effectiveness of data visualizations in education.
The project, a partnership with Greg Niemeyer, is an analysis of the data produced by the Suite C software pack, a set of three applications planned to be integrated into bCourses. The research focuses primarily on the data produced by the Engagement Index app, through pilot courses taught by Greg Niemeyer and Glynda Hull.
Contemporary theories of learning integrate how social behavior affects knowledge production, and the project explores that space. John and MacKenzie consider learning in the social dimension — including those spaces between input and output.The research seeks to highlight the engagement pathways created by student interactions, which are not reflected in tracking discrete one-to-one outcomes. By modeling how students move through a system, and how the students’ engagement leads to organic learning communities, the project develops opportunities for professors to leverage the data and improve their students’ learning experience.
Collaboration is key to this project. In meeting every Monday to update the team on progress, they’ve created a powerful creative and supportive space. Since no one is perfectly versed in the genre of data visualization, they’ve explored all measures of possibilities, including 3-D prints of their work, which encouraged new perspectives thanks to the added tactility of the change in medium. The sheer amount of open source software available also allows for a playful methodology involving trial and reevaluation, as well as collaborations with experts from across campus, including Zachary Pardos from the I-School and Nicolaas Matthijs, head engineer on Campus Analytics.
Their emphasis on diverse perspectives further shines through in their working group, the Berkeley Learning Analytics Group. The team brings together undergraduates, graduate students and professors to collaborate. By not having a hierarchical structure, the group mobilizes expertise efficiently.
This model has been particularly valuable for students such as MacKenzie. In a university where undergraduate class sizes can range above a thousand students, the project offers opportunities for students to engage with their professors and gain real research experience.
Check out their work in May at Data Edge, when they’ll be showcasing some 3D and immersive data visualizations of student engagement in the Suite C tools.
For more information, find their group at dlab.berkeley.edu/working-groups/berkeley-learning-analytics-group