Over the past decade, “personalized learning” has evolved from being a buzzword to fueling a multi-million dollar EdTech industry and becoming a focus for philanthropy. Personalized learning is much more than just a trend now: In December 2015, Mark and Priscilla Zuckerberg announced their investment in the development of a software “that understands how you learn best and where you need to focus.” Not to be outdone, the Gates Foundation has three initiatives based on personalized learning models: Next Generation Learning Challenges (NGLC), Charter School Growth Fund’s Next Generation School Investments, and the Gates Foundation’s Personalized Learning Pilots.
At NWEA, we’re often asked for our position on personalized learning, which can be a complicated question to answer: there are simply no pat definitions that capture the various approaches, tools, and methods of personalized learning in practice. However, recently the Gates Foundation funded a series of research reports executed by RAND that examined the efficacy of personalized learning models in foundation-funded schools. When reviewing the second report in the series, “Continued Progress: Promising Evidence on Personalized Learning,” I was struck by a few things I think are worth sharing.
RAND researchers analyzed learning outcomes for about 11,000 students from 62 schools and examined the implementation of personalized learning in 32 of the 62 schools. The sample of schools included elementary and high schools, were mostly urban (except for two rural schools), had a diverse student population (school-level median of 75% students of color), and a high percentage of free or reduced lunch (school-level median of 80%). They used MAP Growth assessments from NWEA in Reading and Math as the outcome measures to evaluate whether the personalization models resulted in accelerated student achievement and growth during the 2014-2015 school year (though researchers use MAP Growth as an outcome measure regularly, I still get excited whenever I come across mention of it used for this purpose—I’m proud that we’re trusted by folks who are paid to be skeptical, rigorous, and demanding of their instruments).
The findings, as the report’s title suggests, were indeed promising. “Achievement analyses find that there were positive effects on student mathematics and reading performance and that the lowest-performing students made substantial gains relative to their peers.” This is encouraging news that bears further scrutiny! Without going into too much detail, I’d like to discuss two key findings: “a large proportion of students with lower starting achievement levels experienced greater growth rates than peers, particularly in mathematics,” and the results were “widespread, with a majority of schools having statistically positive results.”
(Pane, J. et al, 2015)
It’s worth noting again here that personalized learning as an approach doesn’t have any implementation standards or official methodology. In fact, in the 32 schools examined by RAND researchers, there were 32 unique implementations.
Though personalized learning looks different in different contexts, RAND researchers articulated five strategies that occurred in various degrees across the school sites:
- data-informed learner profiles
- personalized learning paths
- competency-based progression
- flexible learning environments
- focus on career and college readiness
For detailed explanations of these five strategies, please refer to the study.
When it comes to NWEA and personalized learning, it’s important to understand while many of NWEA’s offerings strongly support many personalized learning strategies, our applications and data-driven resources go even further to create a holistic set of educational tools. Our quality data, norms, linking studies, reports, tools like the College Explorer tool, professional learning offerings, and instructional resources combine to create a well-stocked toolbox for our partners to create personalized learning implementations that work for them. We don’t believe in being prescriptive or limiting our partners’ options around personalized learning to a single application; we offer them a palette. In doing so, we honor each student’s unique context and their ability to create solutions for themselves.
My favorite finding from the RAND study was this: the implementation strategy that had the single greatest impact on student achievement was using data for instructional grouping. I love that personalized learning can lead to successful instructional grouping—especially since the concept is one NWEA has been promoting and supporting for years. Helping teachers meet students where they are with instruction, create thoughtful and flexible instructional groupings, and encourage each student to grow along their own learning path is part of our DNA.
Personalized learning isn’t going anywhere anytime soon. The EdTech industry will likely continue to produce new tools that help teachers “optimize” around personalized learning, and hordes will keep descending on SXSWedu and ISTE looking for the “next big thing.” Hopefully, a lot of good will come of it: students always benefit when they have educators advocating for their individual needs. At the same time, it’s important to remember that personalized learning is most effective when it’s part of a learning strategy, and not the only approach taken. And as educators, we must apply a wide array of tools grounded in strategies that work for all students, and not just for the affluent.