Applying chaos theory to the classroom: Hopkins PhD student tries to predict teacher turnover
Before she entered the Johns Hopkins School of Education, Ashley Grant taught for three years at a Catholic elementary school in northeast Philadelphia. She says she and her colleagues faced demanding, exhausting, and often isolating work days teaching kids from some of the city's poorest neighborhoods.
Frustration and burnout ultimately led Grant to leave the profession. And she's not alone: Various studies estimate that half of new teachers resign within their first five years, with the rates climbing even higher for those working in poor urban communities.
Through her doctoral studies at JHU, Grant wants to develop a better understanding of those high turnover rates. She's turned to the chaos theory—which posits that seemingly random events are actually predictable—to study how working conditions in schools—including class size, hours, and classroom disruptions—can affect the social and emotional health of teachers. Going further, she hopes to use this information to predict teacher turnover.
"I want my research to work toward policies and programs that will address challenges that teachers, especially in struggling schools, are up against," Grant says.
It's a novel application for the chaos theory, which hasn't yet played a large role in educational research despite its previous uses studying childhood development patterns.
"It is still very early in the game, but I would theorize that chaos would be prevalent in higher-need, lower-performing schools and would be predictive of staff turnover," Grant says.
She notes that the teacher retention issue is worthy of attention due to the number of systemic problems it creates.
"We know more experienced teachers are, on average, better at raising student achievement levels than new ones," she says, "and high turnover can be costly to school systems in terms of recruitment and training."Read more from School of Education