CDS Welcomes Acevedo-Garcia and Chang as Faculty Fellows

I am very excited about collaborating with CDS colleagues. Our team uses many large datasets from multiple sources to capture socioeconomic, educational, health, and environmental conditions, as well as policies, at different geographic scales and across time. We have a fantastic team of social scientists with expertise in data analysis, so we are in a great position to learn from and partner with data scientists.

We see potential not only for making our data pipelines more efficient but also for uncovering new patterns in the conditions that children experience. For example, our work has shown that although both Black and Hispanic children are disproportionately concentrated in lower-opportunity neighborhoods, their neighborhoods have different challenges and resources, which also depend on the region and state of residence. We could perhaps characterize these lower-opportunity neighborhoods in a more precise way to allow for more targeted interventions. While we can explore these differences with conventional analytic tools, we are eager to collaborate with CDS colleagues to explore new methods.

We are also eager to explore the connection between inequities in neighborhood opportunity and local, state, and national policies. There are new data tools such as national zoning regulation maps that we can combine with our Child Opportunity index to see, for instance, if areas where exclusionary zoning is more prevalent have wider inequities in child opportunity. I also see potential for exploring new data sources, such as cellular phone data, which has been used to study neighborhood segregation via patterns of social interaction between neighborhoods. Our project furthermore relies on data mapping and visualizations, and we look forward to learning about new techniques and processes with CDS. And I am sure our colleagues in CDS will have great ideas that we have not even considered.

Of course, data can also be used for negative purposes or in algorithms that inadvertently—or not—are biased. We proactively try to prevent these misuses of data. We believe that collaboration between data scientists and researchers who understand the social and policy issues embedded in data could help design applications that prevent bias and lead to positive social change.

I am looking forward to collaborating with colleagues who think differently, can help us approach problems differently, contribute new methods, and potentially facilitate simpler paths to working with stakeholders who can make data-informed decisions to improve children’s lives. I am excited about the possibility of creating a co-lab that will bring together different disciplines interested in equity in opportunities for healthy child development and data science, and to participate in training graduate and undergraduate students to work at the intersection of data science, social science, and social policy.

Our team works closely with foundations, non-profits, hospitals, and government agencies across the U.S. An important part of this work involves helping them leverage the massive amounts of data that are available across U.S. communities. This work requires in-depth content knowledge of the space that the organizations work in and what they are trying to accomplish, but crucially it also requires advanced programming, computing, and product design skills. The goal often is to make data accessible and actionable in an efficient way that meets the organization's requirements and helps organizations make more equitable decisions. We are thrilled to join the interdisciplinary CDS community and eager to collaborate with like-minded researchers, seeking to leverage their considerable technical skills for the greater social good.

AI for education is an incredibly hot topic particularly as tools like ChatGPT have served to instigate many conversations about what we hope transformative learning spaces can look like. However, rather than radically changing how we approach teaching and learning in schools, many of the most common uses of AI-Ed tools primarily seek to make existing instructional practices more efficient, individualized, and personalized.

I am interested in understanding (a) why it is hard to envision learning possibilities outside the status quo (b) how we create spaces where researchers (both computer science and education) can dream alongside stakeholders about hopeful, joyful learning possibilities, and (c) what it would take to make those dreams a reality within higher-ed and K-12 learning spaces. I believe that this approach offers a new way to think about the role of technology in building on a large body of educational research that argues that learning necessitates forefronting learners’ joy and well-being alongside more traditional disciplinary learning.

As a computer scientist who made a hard pivot into education after the completion of my PhD, I was amazed by how education researchers, teachers, youth, and families all spectacularly opened up and complicated how I thought about learning. I learned that building technical tools is an important part of the process, but by itself, they often underdeliver on their potential to revolutionize learning without paying attention to the learning context – which is wonderfully complicated! Based on my experiences, I believe that collaboration between Wheelock and CDS can open the door to new, joyful learning possibilities at BU and beyond, ones that enhance rather than replace the deep expertise that educators and students already bring to this process.

To realize this, we have to consider how to meaningfully incorporate educators and students into the end-to-end design process, from speculating about new, equitable learning possibilities to implementing and maintaining new learning tools supported by computing and data sciences. This opportunity can only be accomplished through deep, thoughtful collaboration between Wheelock and CDS, something that I feel very hopeful for as I join a number of my colleagues at Wheelock in building and deepening research partnerships with a variety of CDS faculty.