While the proliferation of data science is most commonly associated with fields such as finance, marketing, and the technology sector, data science has become increasingly important in a variety of disciplines, including health, medicine, and education.
Vasant Dhar, a professor at the Center for Data Science, began incorporating data science into his research in the 1990s. He was originally working in the financial sector, but over the course of his career, his research interests have expanded to a broad range of fields, including sports and health care.
Dhar is mostly known for his ongoing work in the financial sector, but he recently began to investigate the role of data science in tracking educational standards, specifically in his home country, India. One of his ongoing research projects is exploring the possibility of using educational smartphone games to assist in childhood education.
Dhar said, “It’s a big problem in India… good teachers are few and far between.”
While Dhar does not believe that educational smartphone games can replace a human teacher, he sees them as a way to supplement classroom experiences, and gain valuable data regarding how children are learning.
Dhar said, “We’re gathering lots of telemetry data from people interacting with their devices. Once you collect that data, you can infer something about what kids are looking at, what they’re playing, and how well they’re playing a given game.”
But Dhar also stressed that certain societal norms are key to understanding how data science can be implemented in a community.
“Games are one part of it… but you also have to account for social and cultural factors within the country that you’re dealing with. A lot of parents don’t think their kids are learning something when they’re playing games. They think: that’s not work, that’s play. So it’s a bit of a challenge to figure out how to seamlessly integrate the device and it’s usage,” Dhar said.
He continued, “It’s not just the technical issue, it’s the socio-ethical issue. What you’re doing is designing technology to be integrated with the way people work, and their social boundaries.”
Vasant Dhar’s dilemma captures an essential piece of knowledge concerning data science: while a solution to a problem might be theoretically sound, real-world effectiveness is crucial. As data science becomes increasingly prevalent, it is essential that domain expertise goes hand-in-hand with insight from those who are most knowledgeable about the communities that data scientists seek to serve.