Key Takeaways:
From India to Harvard: Site Director Palak Chandak’s career spans teaching, policy, and leadership–shaping her work at Saga Education.
AI-Powered Coaching: Palak leverages Saga’s AI insights to provide holistic, trend-based feedback to her team of tutors, shifting coaching away from single-session observations to a more complete, data-driven picture.
In this Q&A, we dive into Palak Chandak’s journey to the education field, day-to-day work as a site director for Saga Education at a Maryland high school, the program model, and her tech-powered approach to coaching—specifically, how she leverages Saga’s AI insights to provide holistic, trend-based feedback to her team of seven tutors.
Can you start by telling us about your role at Saga Education?
I am a site director at Reginald F. Lewis High School (located in northeast Baltimore, Maryland), where my team and I support over 80 students at the school with high-impact math tutoring.
The program pairs classroom instruction with next-day targeted tutorials, creating alignment with the classroom curriculum that deepens mastery of core Algebra I skills and reduces unfinished learning.
Your path to education began in India. Can you share a bit about that journey?
I grew up in Biaora, a quaint town in the central state of Madhya Pradesh in India, where I did not have enough opportunities to access quality education that could allow me to unleash my full potential during my school years. Later, I studied business, specializing in finance, at Narsee Monjee Institute of Management Studies in India. During my studies, I learned about Teach for India. Two months into the fellowship, COVID hit India and schools shut down. I started a mentoring business with a friend, but then returned to the fellowship to focus on teaching.
After my two years at Teach for India, I worked in a policy and project management role with my home state’s government, focused on a project that impacted 2.5 million children on foundational literacy and numeracy.
Then, I applied for my Master’s and was accepted into Harvard University’s Graduate School of Education. Through a class called “Measuring Impact at Scale through Equity, Evidence, and Ecosystem,” I found Saga. At the time, I saw a wave of AI tutors emerging, and I was skeptical, but my hypothesis was that we need tech to enable humans in the equation, and Saga was actually doing that pretty well.
Walk us through a day in the life of a Site Director.
I manage the logistical and operational tasks that ensure the tutorial program runs smoothly at the school. The day begins with a morning check-in with the team of tutors. During this meeting we discuss instructional practices and how to improve tutorials for the students. While tutoring happens, I manage the administration of tutoring, making sure students are logged into Saga’s tutoring platform and conducting observations. After school ends, the focus is on data. I make sure grades, attendance, and engagement data are up to date so we can track student progress and adjust instruction. I also coach and mentor a team of tutors, share student achievement reports with stakeholders, and manage stakeholders relations.
How has AI changed the way you coach and support your team of tutors?
The primary way AI helps is by allowing me to give more comprehensive feedback to my tutors. When I observe a tutorial in real time, I make my own detailed notes, but then I compare those to the AI-generated insights.
The AI provides a high-level summary and factual view, generating ‘glows and grows’ for multiple sessions. The key is that I don’t have the bandwidth to observe every single lesson for my seven tutors, but I can read the trends through those ‘glows and grows’ across multiple sessions. This lets me see if a tutor is consistent, or if a particular session was a function of the students or other dynamics.
As a former teacher, I know one observation is never enough to give the right kind of feedback. So, AI insights are incredibly helpful because they let me have a conversation with a tutor that’s based on more than just a single snapshot. Metrics like the student-to-talk ratio are also useful quantitative data points that help drive those conversations.
That is one of the AI insights we use quite often with coaching conversations. One tutor brought it up on their own that they started at a low of 17 percent on student-to-tutor talk time. They were able to achieve a 44 percent student-to-tutor talk ratio and the tutor brought this up as a point of improvement in their reflection. It’s very easy for someone who is tutoring to not realize it unless there is some deep reflection. That’s an example of how AI provides insights that augments the work of a coach to nurture a tutor’s learning.
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