Much is emerging and still to be learned about how to effectively personalize learning for every student. The research on student learning is solid and reliable direction for educators on how to put together the personalized learning pieces. For example, we know students succeed when learning in their Zone of Proximal Development (Vygotsky) – sometimes referred to as “the sweet spot of learning.” This learning theory, coupled with setting objectives and providing feedback (Marzano, Hattie), and linked with autonomy, mastery and purpose (Pink) makes for a compelling trifecta. These elements start to triangulate our thinking around the idea of how to truly personalize learning uniquely for each student. Indeed, the proposition of achieving that learning trifecta poses a tremendous opportunity for students, teachers and parents, balanced with weighty reality of this being an educational feat. Schools today are striving to achieve personalized learning for every one of their students - everyday, in every content area, and to high levels. I wrote about one such example from my school in the September 2014 issue of Educational Leadership: Motivation Matters. It was an anecdotal style reflection of how personalization can happen for a student with a wide range of needs, and illustrated that personalization positively changes the trajectory of a student’s education. Personalization causes magnitude on learning. It is how educators effectively change the direction and rate of a student's learning in individualized ways, and it is those very factors that magnetize me again and again to this learning approach. It’s a challenge worth taking on - but how?
Data as an Inquiry Tool
Data has a “must mention” here. It’s the tool that makes the “just right learning theory,” feedback strategies, and motivation trio work so harmoniously. Data is an engine of inquiry, fueled by formative assessment day in and day out. Pre-assessment, observations, checks for understanding, conferring, self-reflection and exit slips are just some of the tools of a master teacher that inform teaching and learning on a daily basis. These assessment practices must be audible and visible in the school environment on a daily basis, in order for data to hold meaning.
Data Questions to Consider
• To what degree does formative assessment exist in every teacher’s instructional practice?
Formative assessment (“assessment for” learning) is crucial in understanding each learner’s unique needs and progress. We cannot begin to talk about data, without discussing the underpinnings of formative assessment and how rooted it is in daily instructional practice.
• Are there supportive structures in the school where data is the centerpiece of teaching and learning conversations?
Data is not an event; it’s an ongoing practice that requires pillars of support. Start the culture with basic structures, such as a data notebook and or a simple spreadsheet. Look at authentic work samples across the grade level and organize the information simply with sticky notes, charts or basic spreadsheets. By doing this, educators can begin to look at how students are performing relative to the expected standards and engage in meaningful conversations. Leaders should also create common meeting times, ideally during the school day, that support teachers to collaborate in looking at student work. Professional learning communities, grade level meetings, peer mentoring, coaching opportunities and department meetings are structures where teachers should be working on data together, as a central and routine part of their collaboration.
• Is data being used for inquiry purposes?
All data tells a story. It should be used for looking at growth, not just achievement levels. By starting all data inquiry with an important question, and collaborating with team members in an inquiry-based process, data fuels a meaningful conversation around the “why” - not the “what.”
• Do you hear students, teachers and parents using a data lexicon? How is it being used to inform learning?
Data is a tool that has its own language and concepts. It is not jargon; rather it is an educational vocabulary that we must possess. It is our professional responsibility to become data literate. Educators must understand data concepts (such as growth measures, and “assessment of” and “assessment for”) and data language (such as standards, rubrics, cut scores), in order to build our collective capacity in our shared work together.
• Is the culture passionate about using data?
A culture that relies on data, in fact, generates and seeks data on its own. Data literate schools are data curious schools. When the leader models formative data use, sets a high expectation around formative data use, provides clear structures to support data, and empowers the school to be data literate; this is the litmus test of being a truly data informed school. Leaders should ask themselves,“Does data inspire our culture to strive to high levels of learning, and promote innovative forms of teaching and learning?” Just as teachers, students and parents become urgent when data inquiry unfolds a story of need, they also celebrate when collective effort around data has promoted student success.
It is essential that a leader makes data heard and seen in all aspects of a school’s life, and uses these efforts as a springboard to grow the academic and pro-social well-being of student success. When students say, “This is the goal I set for myself today, after reflecting on my self-assessment;” or teachers say, “I devised different ways to help my students learn the concepts, so they can choose their preferred learning modality and have the opportunity to learn at different rates;” or parents say, “I can see how much progress my child has made [here], but I want to know how to help them [there],” then a leader knows that data literacy and practices are taking hold within the school culture.
Realizing Personalized Learning Through Data
Effective data practices are necessary for personalization to fully come to life for each student. Data is the means to how educators to inform, guide and adjust learning. When data is partnered with the cornerstones on educational research around personalized learning (Vygotsky’s seminal theory on the Zone of Proximal Development; Hattie’s and Marzano’s compelling findings on feedback; and Pink’s argument on autonomy, mastery and purpose); data is the unsung hero among these giants. It is our professional responsibility to understand this educational research, and also make it actionable through proficient data literacy and practices. It is only then that personalized learning can effectively come to life for every student in a lasting way.
Sandra A. Trach, Principal
Cross-posted from my blog sandratrach.blogspot.com to ASCDEdge, Connected Principals and Microsoft Educator Network