Home Blogs Understanding Personalized Learning Implementation with Data
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.
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.
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:
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.
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. https://doi.org/10.7249/RR2042
Author(s)
Nicole Breslow
Connect with REL Northeast & Islands