Innovating more tailored approaches to teaching
Growing up in the Indian village of Sasthan, where resources were scarce and problems were plentiful, finding solutions came naturally to Akshatha Kamath. “Hey, this motor pump that irrigates our field isn’t working, and we have to fix it or the plants will die,” she says. “So you figure out a hack.”
Kamath is applying that spirit of innovation to her scholarship as an incoming master’s student in the GSE’s new program in education data science, where she plans to combine her deep love of technology with a desire to help children for whom established structures and programs are a poor fit.
She saw firsthand the need for a customized approach when she worked with children with learning differences in an orphanage near her home in India. Curriculum and teaching methods “have to be tailored” for these children, Kamath says, and data can be part of the means to develop effective new models.
Recently named a 2021 Knight-Hennessy Scholar at Stanford, Kamath’s path has been disrupted by the Covid-19 surge in India, where all visa offices have closed temporarily. Her family has remained safe, she says, but several of her friends have lost parents and other loved ones to the virus. She has met the rest of her Knight-Hennessy cohort remotely, and after an initial bout of anxiety before the interview (“I was so intimidated, I cried for an hour afterward”), she’s eager to join them. “It’s an amazing group of people.”