Skip Navigation

Home Blogs Understanding Personalized Learning Implementation with Data

Understanding Personalized Learning Implementation with Data

Northeast & Islands | November 03, 2023

Two students learning on a tablet with another student learning via a miniature windmill

Personalized learning is an instructional approach that empowers students to take ownership of their learning. It is designed to meet students' individual learning needs, engage their interests, and provide flexibility in the pace and pathway students take to content mastery. While the research base is still emerging, early evidence for personalized learning is promising.1 And, as districts are taking steps to recover from the pandemic, many have doubled down on personalized learning as a strategy to re-engage students in learning and focus on their individual needs.

Wayne-Finger Lakes Board of Cooperative Educational Services (BOCES) in New York, for example, has been implementing personalized learning as a strategy to address student inequities since 2016. After investing significant resources toward these efforts over the years, they had questions about the extent to which implementation had taken root in their 25 districts and how these efforts were making a difference for students. To find answers, REL Northeast & Islands partnered with Wayne-Finger Lakes BOCES and several of their districts last fall, forming the New York Partnership to Strengthen Personalized Learning for Equity. In this blog, we describe the partnership's activities and discuss lessons learned about tracking personalized learning implementation.

Taking Stock of the Data

As a first step, our team helped districts develop logic models that described their key implementation strategies for personalized learning and the outcomes they hoped to achieve. Next, we worked with districts to conduct an inventory of data related to these strategies and outcomes to establish a clear picture of available data to track personalized learning implementation and understand how it might relate to student learning.

Districts used a common technology-based service for assessing and tracking students' academic progress and had similar strong routines for analyzing that data at regular intervals. However, districts' data practices varied considerably in how they gathered and used information about teachers' personalized learning practices and other relevant student outcomes of interest, such as students' engagement and investment in learning.

Data Practices Lessons Learned

During our time collaborating with Wayne-Finger Lake BOCES, we learned valuable lessons about tracking personalized learning implementation that might be useful to other districts. The following are some recommended best practices for tracking personalized learning implementation:

  • Leverage validated measurement tools when possible.
    Due to the significant and often intentional variation in how personalized learning practices are defined and implemented, it is exceptionally hard for states and districts to track and evaluate the effectiveness of these practices. However, there are a growing number of validated tools for measuring personalized learning implementation and outcomes. For example, RAND's Measuring and Improving Student-Centered Learning Toolkit provides a set of instruments designed to help educators measure and understand student-centered learning implementation in high schools. The toolkit includes surveys for students, instruction staff, and school and district leaders, protocols for classroom walkthroughs and student focus groups, and a reflection guide to support practitioners in interpreting the data and making improvements.

  • Take advantage of the data you already collect.
    Each Wayne-Finger Lakes BOCES district we worked with conducts an annual student survey as part of their efforts to monitor school culture and inform their SEL work. Although this survey wasn't designed to measure personalized learning, it provides valuable data about student engagement and self-efficacy—outcomes that are central to personalized learning efforts. Districts can use this data as part of their plan to track personalized learning implementation and outcomes.

  • Align data collection instruments to a common set of high-leverage practices.
    It may be necessary to supplement existing validated measures with district-developed tools to ensure the data being collected is targeted to the priorities and needs of that district. Participating districts had previously developed walkthrough tools, teacher surveys, and teacher self-assessment tools to gather important information about teacher practices. Aligning these tools to a common set of high-leverage instructional practices that are the focus of implementation efforts will ensure that data collection yields information about your priorities. In addition, using multiple data sources to triangulate findings can provide a more robust view of personalized learning practice.

  • Examine data over time to understand how implementation might be changing.
    Looking at different data sources over time will help to differentiate between long-term trends and short-term variation. Data that provides a snapshot of teacher practice, such as data from a walkthrough, can be especially useful when these snapshots are looked at over time alongside other related data. We recommend establishing a one-time baseline measurement and then committing to a consistent measurement tool to use at regular time intervals. Examining data over time can allow educators to understand how implementation might be changing and provides insight on how well professional development efforts are working and where there may be areas for improvement.

Aiming for Continuous Improvement

Tracking implementation and evaluating which personalized learning practices are working best for students is key to continuous improvement. Wayne-Finger Lakes BOCES district leaders benefited from learning about the different approaches their colleagues were taking to collecting data about personalized learning implementation and problem solving together around shared data challenges. Moving forward, they are using this knowledge to further strengthen their data practices and inform their personalized learning efforts. Educators interested in learning about continuous improvement may find the tools and resources included in Continuous Improvement in Education: A Toolkit for Schools and Districts helpful in supporting those efforts.

Additional Personalized Learning Resources from the REL Program

1 Pane, J. F., Steiner, E. D., Baird, M. D., Hamilton, L. S., & Pane, J. D. (2017). Informing progress: Insights on personalized learning implementation and effects. Santa Monica, CA: RAND Corporation.


Nicole Breslow

Nicole Breslow

Connect with REL Northeast & Islands