Q&A with Learning Analytics alum Anjali Yadav

The Master’s in Educational Psychology: Learning Analytics program at UW–Madison is a skills-based degree designed for working professionals.

Completely online and asynchronous, students in this program learn balanced analytical methods, design strategies, and communication skills in the seven-course curriculum. These students work with a world-class teaching team to perform and present analyses, and learn how to improve educational outcomes in a range of learning environments. In addition, students collaborate with their peers in the cohort and build professional relationships.

According to James Wollack, who chairs the highly ranked Department of Educational Psychology, the Learning Analytics program at UW–Madison “provides a truly world-class education, and an educational experience unlike that of any other program available.”

Following is a Q&A with Anjali Yadav, who recently received her master’s degree from the program.

Anhali Ann Yadav

I understand you’ve received a fellowship with Harvard’s Strategic Data Project. Can you tell me a little more about this fellowship, how it came about, and what you’ll be doing as part of this fellowship? Is there a particular data project you’ll be working on and what can you tell me about that? The Strategic Data Project is a two-year fellowship program that helps education agencies use data to drive strategic decision-making and build sustainable data cultures. They accomplish this by placing data analysts in education organizations to complete a long-term data project related to educational improvement that will lead to better outcomes for students. The SDP team supports this work by providing relevant training and resources to the fellow as they work on their project. I was nominated by my current employer, CommonLit, to study how to best connect data from our standalone products to support teacher decision-making in the classroom. The fellowship will kick off later this year in October. 

How did you get interested in this field of work and what are you hoping to learn from your data project? As our literacy program has grown and reached more classrooms, it has become even more essential that teachers are supported in understanding and applying their students’ data. Given this, the goal of our project is to create effective connections between data sources, providing teachers with clear, actionable, and pedagogically-sound recommendations that will save them time and positively impact their students’ learning. As our research progresses, the project outcomes may evolve and potentially point toward innovative AI-driven applications that can support how teachers make decisions with their class data.

How, if at all, has the Learning Analytics program at UW–Madison helped you get to where you are today? Completing the Learning Analytics program enabled me to transition to the data science and research team at CommonLit, which in turn made me eligible to apply for the SDP fellowship. A big motivation behind pursuing the Learning Analytics program was my interest in exploring opportunities to contribute to educational research, so I’m excited to be making meaningful progress toward this goal. 

What are your career or future goals? I am enjoying the work I’m getting to do on the data science team at CommonLit, and this fellowship is the perfect complement for me to continue advancing my data skills and dive into a long-term educational research project. I’m looking forward to connecting with other fellows, pushing myself to learn new skills, and seeing where the next two years take me.

Anything else that’s important to you about yourself or your studies or anything else? I want to extend my sincerest appreciation to the team behind the Learning Analytics program. The curriculum and community they have created have had a significant positive impact on my life. Additionally, I am grateful for the support and encouragement I have received from my friends and colleagues at CommonLit throughout my master’s and during my transition to the data team. I consider myself very lucky to work someplace where my professional interests are valued and my development is encouraged.

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