Making Competency-Based, Personalized Learning Real for Teachers

EdTech, Learning, PreK-12

When it comes to preparing teachers, development providers must build a collective infrastructure that connects learning happening everywhere and anytime. That’s why The Learning Accelerator, with a cohort of human capital providers including BetterLesson, Highlander Institute, and the Friday Institute decided to take action with support from Yet Analytics. This blog that first appeared on shares information on the collaboration to utilize systems for professional learning as learning becomes more personalized, competency-based, and data rich.

Beth Rabbitt & Margaret Roth

Across the country, teachers are trying to bring technology into their classrooms to better meet the needs of every student. The goal is to make learning more personalized, competency-based, and data rich.

As educators work to make the shifts necessary to make this a reality, we have to ask ourselves what our systems for professional learning can do to achieve similar ends.

  • Don’t teachers deserve training and continuous development opportunities that are customized to their unique goals?
  • Can we move beyond one-size-fits-all models of professional development to offer choice in how and when learning happens?
  • What would creating this “next generation” of educator learning take?
  • What would it look like for teachers?

Over the last year and a half, The Learning Accelerator (TLA) has been working through this problem with a cohort of human capital providers who have been developing supports for teachers as they implement blended learning. Throughout the process, TLA grantees have worked as a group to share approaches and prototype designs to develop a suite of open resources, launching new programs that, just now entering the beta stage, are already in use by tens of thousands of teachers across the nation. Together, we’re discovering a lot about how to replicate for educators what we hope they’ll enact in their classrooms– we’re creating tools and programs that are highly modular and accessible online as well as professionally networked and connected to authentic assessments that bring training into practice daily.

One of our key realizations as a team was that there was powerful collective work to be done.

Making learning components better organization-by-organization is great, but our adult learners need more. In the same way school systems are figuring out ways to offer students choice and providing means of learning across different and differentiated programs, our teachers need ways to make their own learning actionable and evident across multiple platforms too. And they need a way to figure out what it all means in a way that is both professionally and personally meaningful.

Further, as adult professionals, our teachers have the potential for enacting their learning across even more boundaries and with greater self direction. Therefore, teacher development providers — if they are really serious about offering resources that are truly more personalized — need to build together a common infrastructure that connects learning happening everywhere and anytime.

As a group of independent but aligned organizations, the TLA human capital cohort has moved forward to develop this common infrastructure, in partnership and with support from Yet Analytics.

This work has three parts:

1) Embracing the ideas of competency and mastery over seat time and credentials. Too many of our existing teacher supports lack direct alignment to a shared, clear picture of what teachers need to learn. This results in fragmented credentials, degrees, and continuous education hours that don’t really add up in an integrated way for learners. The TLA cohort grounded our conversations and mapped content to a common set of teacher competencies that we felt were a good start for blended learning environments—the iNACOL Blended Learning Educator Competency Framework. We expect this definition of competency to evolve as the field grows, but by linking resources and their related learning assessments asynchronously to a common set of standards rather than an arbitrary expectation of learning time, we believe we can help institutions and educators more clearly link development to clear objectives for learning and improvement.

2) Creating a shared language to connect learning across platforms. Nearly all of the learning content created through this project is open-access and available to any teacher in the country for free, but each of the cohort organizations own and locally host their content independently in the platform and format of their choice so that they can continue to grow and iterate upon it in the future. Teachers need ways to find content addressing the same learning topics across these platforms easily, so we co-developed a common tagging model for all of the resources. This model links directly to the learning competencies, but makes it possible to identify content by practice-based skill areas, making learning content searchable by topic as well as by more specific learning objectives.

3) Building in data interoperability to track progress and competency strengths across systems and content providers. Being able to define common objectives and link to content isn’t enough. We need teachers to be able to track their learning activities and progress as they go, amassing data so that they and their coaches can make better, smarter decisions about what is working and to develop a clear picture of where, competency-wise, to go next.

As a collective, we realized that to accomplish the three parts of this work, this ecosystem requires not the building of a singular learning platform but rather adopting a standard that allows for portability and interoperability across programs and platforms.

Working with Yet, the TLA cohort is linking our learning model through an open specification called the Experience API (xAPI). This xAPI integration will allow interoperable collection, management, and visualization of learning data through the use of Learning Record Stores and analytics technologies. Further, it will be able to integrate directly with learning management systems, software, and any other resources making it possible to collect data when are where learning occurs.

Ultimately, we envision a world where learning is linked behind the scenes through a smart infrastructure for competency-based personalized learning. By allowing teachers to have a truly personalized experience we believe the outcomes will be improved for all students.

We’re nearing the end of the definition phase and are beginning to test the learning infrastructure internally. We plan to share the first version this month— July 2015— to get broader feedback and to begin to explore critical next steps for making this vision a reality within and beyond the TLA portfolio.

To join us and get first access, give a shout @bethrabbitt.

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