MSPnet Blog: “Personalized: What questions to ask?”
posted March 20, 2017 – by Brian Drayton
Personalized learning, and its close companion, “competency based learning,” are now the wave of the future, and indeed the very near future. The Obama administration, in Race To The Top and ESSA (Every Student Succeeds Act), supports it; so do high-tech voices such as the Chan Zuckerberg Foundation, the Gates Foundation, and Eli Broad; so also major business interests such as Pearson, McGraw-Hill, Hewlett-Packard, and others. It is a favorite focus for the Nellie Mae Foundation, whose vision combines personalized education, competency-based learning, student control of learning, and the claim that learning takes place anytime, anywhere. Many states are moving in this direction; New England is a hotbed of personalization (see here and here for very fresh news from Massachusetts, for example. Tip of the hat to the blog Wrench in the Gears).
i have written before about the abundant use of “straw man” arguments (such as the “factory model“) to create a sense of urgency and indeed inevitability — now is our chance to break the chains of tradition, so that we can meet the demands of the 21st century economy, and “unleash greatness” (though we also need to move from “great” to “excellent,” as Michael Fullan puts it. ). Apparently, never before have we realized that learning can take place anytime, anywhere, nor has it been possible….
Because “personalization” is a current nexus for many different strands of policy, rhetoric, marketing, and technical development, it is worth attending to from various angles. One of these angles is the state of the evidence. Of course, what “personalized” means varies a lot, but still one can identify some claims, and ask what evidence there is to warrant large investments of public and private funds and large shifts in education policy to adopt the new approach.
The state of research in any field is a moving target, but here is a reasonable read-out on the research base on personalized learning as of 2016, thanks to Data & Society. The report, authored by Monica Bulger, puts the aspirations for personalized learning thus (page 2):
New technology is promised to level the playing field, effectively creating equal access to learning opportunities by democratizing information and instruction. Advocates hope that a technology- enabled shift (e.g., from teacher-based classroom interventions to personalized tablets and data-driven individualized learning plans) can provide a new incarnation of the one-teacher-one-student model— tailoring the learning experience to individual progress, interests, and goals. Classrooms could then be spaces in which advanced students and struggling students alike not only have their needs met, but are supported in the curious and creative pursuit of their own paths. Through personalized learning, these lofty goals seem within reach.
It’s nice to read a discussion of such a topic that acknowledges some history — that good teachers have always personalized their teaching a lot, for example — but Bulger focuses on the recent vision, which is inextricably linked with technology. Technology is intrinsic to this movement both as justification (the New Economy is high-tech, and so education must prepare our children to compete), and as mechanism (the goals of the new education can’t really be realized without lots of technology for content delivery, for student expression, and for massive data collection through which smart systems can inform students, teachers, and administrators or policy makers about How It’s Going, and how to do better).
The report also notes that “personalized learning” has become woven together with other ed ideas (also more and more tech-implicated):
The promise of personalized learning is often bundled within competency-based education and/or Common Core, making it difficult to separate the performance of one from the other, or truly distinguish personalized learning from associated assessments or teaching of competencies. At the same time, the controversies surrounding Common Core and competency-based education also tend to shape impressions of personalized learning.
Bulger goes on to describe and illustrate various ideas or approaches embraced by this increasingly comprehensive approach to “21st century” education — adaptive technologies, big-data and data-driven instruction, and so on.
She then examines what evidence there is for the promised benefits of personlization, differentiation, data-driven instruction, and a few other typical claims. The basic message is, the promises are being made, and policies are being adopted, on the basis of very little evidence, but rather on the basis of inferences, hopes, and anecdotes. As with so many innovations in education in recent decades, we are beginning another round of large-scale social engineering, with schools, teachers, students, parents as experimental subjects.
There are some basic underlying assumptions that need to be clarified, as well, before ever the edu-technological interventions could actually be properly evaluated.
Underlying adaptive personalized learning systems are algorithms—analyses driving programs to serve content that increases the likelihood of reaching a desired end goal. But which goals are being encoded in the design of personalized learning systems? Multiple goals are described in marketing materials (e.g., improved scores on quizzes or preparation for Common Core), yet optimizing for multiple goals is ineffective. It is currently unclear from descriptions of personalized learning systems, what goals each are optimizing for, and how they are differentiating between interim goals (e.g., testing to represent mastery) and larger end goals (progressing to the next grade level).
There are other questions — student privacy is a big one — still wide open. One of the biggest is, as always, equity — what resources will get diverted to make the massive investments that the new vision will require? What human or other resources will be reduced or eliminated, in these times of austerity thinking, to make the investments possible? What outcomes will we watch for, and which will we not know to measure, until after we’re already committed to surfing the new wave?
No doubt one or another aspect of this newly favored approach is taking shape near you. How does it look? What difference is it making in policy, in teaching, in students’ experience, in actual learning?
Because there is so little research on many aspects of Personalized Learning, some of the most interesting thinking is to be found in the gray literature, the world of reports, presentations — and blogs: the hunting ground of the Bloghaunter.
Note: Opinions expressed in this blog are those of the writer alone, and are not to be attributed to MSPnet, TERC, or the National Science Foundation.