Educational technology coaching can be instrumental in the introduction and integration of new products and programs across subjects and grade levels—especially when coaches forge relationships with teachers that are founded on collaboration and mutual respect.
The school district where I help lead a team of edtech coaches recently made coaching support available to any K–12 teacher interested in instructional technology integration, rather than following our previously limited, grant-funded cohort model. This presented an interesting challenge: How, in the face of increased demand, were we going to forge meaningful connections between coaches and teachers who would most benefit from our team’s expertise?
To tackle this inquiry, we created an interactive system for ensuring that teacher-coach pairings are productive. It’s one you might replicate in your own coaching context, outlined below.
Identifying Teacher Characteristics as Clues for Technology Coaching
As the school year started, we noticed that our coaches were doing a great job connecting with teachers across the district—and were interested to discover that most of the teachers with whom coaches connected were new to the profession and/or our latest curriculum adoptions.
The frequency of these pairings demonstrated that although our coaches were sympathetic to all teachers’ needs, there was an increased demand among certain teacher populations. To help our team of coaches identify which teachers would be great candidates for technology integration work, our leadership team created an activity to acquaint us with the different teacher personas we might encounter. Our goal was to create a list of characteristics to help guide coaches as they tailored their approach.
First, we made and shared a matrix using Figma that was split into four quadrants representing common teacher types: inexperienced educator with high pedagogical confidence; experienced educator with high pedagogical confidence; inexperienced educator with low pedagogical confidence; and experienced educator with low pedagogical confidence.
We divided our team of coaches into four groups and created poster-sized sticky notes, one per quadrant category, to attach to the walls of the room. From there, we shared the following prompts to drive our conversation:
- “Thinking about the vision of the Learning Technologies team of technology integration, which quadrant(s)/teacher types would most benefit from our coaching services?”
- “Thinking about teachers who fall into quadrants that may not be the best fit for our services, with whom would you connect them for support (e.g., building instructional coach, building climate coach, content curriculum coach, or a new teacher mentor)?”
- “How do we assess where an educator might fall in the quadrant?”
- “Thinking about ourselves as coaches, if we realize that we may not be the best fit for a teacher, how might we transition to another coaching opportunity related to instructional technology?”
- “What other professional learning opportunities around technology integration could we offer this teacher that may not involve a full coaching cycle?”
- “How might we end a coaching cycle upon realizing that the teacher would benefit from other types of coaching support at this time?”
Using sticky notes and markers, our coaches created a list of teacher characteristics or classroom “look-fors” for the quadrant they were assigned—for example, one group said that a teacher with limited teaching experience and high pedagogical confidence might “bring new ideas to the classroom,” have “excitement, passion, and eagerness to be a teacher (e.g., not burnt out),” but might demonstrate “inflexibility or inability to pivot/shift” in practice.
Alternatively, a teacher with experience but a low level of pedagogical confidence might demonstrate “comfort” but might be more “willing to have others do the work” in the classroom or might utilize “compliance-dependent learning” strategies with students.
When our coaching groups were done brainstorming, we created a physical impact matrix by placing all four poster sheets together to compare results—noticing similarities and differences across responses and quadrants.
After completing their collaborative brainstorms, our coaches were ready to reflect deeply on the different types of teachers they could encounter in our district. This exercise made it easier for them to identify the characteristics that represented different teachers’ identities and experiences and to plan action steps for providing a tailored, individualized approach.
Our team acknowledged that some teachers may fit into more than one of the quadrants and that each quadrant represents a spectrum. We agreed that coaches should take this variability into consideration when establishing a coaching relationship. We also agreed that, with so many coaches in our district, allowing ourselves time to evaluate a teacher’s professional needs gave us the opportunity to create best-fit matches between their needs and our team members’ coaching competencies.
Our most meaningful takeaway was that our team felt better able to determine what characteristics they should look for in a teacher-partner when pursuing technology integration projects, so that they could best align their expertise and/or make referrals to meet teachers’ instructional objectives. With a better understanding of whom our team could best serve, and how, we felt confident heading into the year with an organized, intentional system.