Data can, and should, help K-12 leaders offer personalized professional development as well
For more than 20 years, educators and ed-tech companies have pursued the promise that technology and personalized instruction can raise student achievement. Sophisticated educational software now can adapt to students’ content knowledge, language skills, and engagement preferences to provide truly unique learning experiences.
So why has so little work been done, similarly, in professional development for adults?
Personalized instruction—often technology-enabled or supported—is a proven approach for students that builds competencies by allowing kids to work on the things they need to work on first, then build on those successes by setting ever higher goals.
But when it comes to teachers, so much of what passes as professional development is not even tailored to the school, let alone each educator. There are a plethora of pre-packaged workshops, content libraries, free online resources, and reams of materials to be used. And while the quality of the content is sometimes high, the tools are too often provided as “one-offs” rather than as part of a system to address teachers’ initial or ongoing development needs.
One thing that all high-performing schools have in common is a culture of high expectations—not only for students, but also for teachers and school leaders. In these schools, principals are instructional leaders who foster a collaborative environment. They believe in, and invest in, sustained, job-embedded professional development.
Schools that have made this cultural shift empower their teachers to own their professional development. These schools do not “hand down” the plan to the teacher; instead, teachers collaborate around student data and evidence collected from direct observations. They use these data to help build the plan and engage with mentors, coaches, and the school leadership to grow as individual educators and collectively as a faculty.
Some of the initial efforts in offering personalized professional development are too simplistic and prescriptive. To summarize that approach: Consider the evaluation data, then prescribe content to read or videos to watch.
(Next page: What’s wrong with this approach)