Harnessing the Power of the Skill-Will Matrix

Brian Hurley

Article

Letting the Data Motivate and Delegate: Harnessing the Power of the Skill-Will Matrix

Purpose

This article aims to introduce a data tool that can nurture constructive educator conversations, help orchestrate interventions, and ultimately improve student achievement. The Skill-Will Data Tool can be created by any school or district with a digital learning management system (LMS), takes less than 30 minutes per week to update, and is easily disseminated via email. While the Skill-Will Data Tool was first created during the pandemic, it is a powerful tool that can help students anytime.

Developing Triggers

As a district instructional coach who worked primarily with teachers, I was part of the Multitiered Systems of Support (MTSS) team assigned to one of the schools in the district. I also worked closely with two academic interventionists on the MTSS team who worked primarily with students at the same school. Together, we developed intervention and coaching plans that could best support students and teachers. Once the order

for remote learning was given in March 2020, we knew we would need additional tools to help us design and implement effective interventions remotely. We also knew that the earlier we could identify students who could benefit from interventions, a trigger or triggers that could instantiate interventions, the greater the chance the intervention would be successful (Cotunga, Vickery, & Carpenter-Haefele, 2009).

Powerschool generated a weekly report sent to administrators in spreadsheet form with a running sum of absences per student per class, as well as the student’s percent grade in that class. We knew from previous analyses, one absence per week increased the chances of failing the class, so our first trigger was 3 or more absences at week 3, increasing that number by one every week until week 13 when the trigger became “greater than 13 absences.” Since we were concerned with failures, percent grade became our second trigger initially set to “less than 60%.”

Finding the “Will”

The first test of our trigger system identified students for intervention that exceeded the recommended caseload for our academic interventionists. We realized there were several students identified by the triggers that were on the border of passing, i.e., could probably be removed from the caseload if they submitted one missing assignment or earned a few more points on an assessment. These students stood in stark contrast to those who had less than 51% in each of their classes while exceeding the trigger-trigger-number of absences. It seemed to us students who were close to passing had the will to succeed but may have required some support to gain the skill, thus the Skill-Will matrix seemed a perfect tool to organize students for interventions. In our SkillWill Data Tool, attendance and percent grade placed students in a quadrant of the tool, and weekly GPA, added during a subsequent iteration of the Skill-Will Data Tool, differentiated students in Quadrant III by those that required counselor or social worker support.

The Skill Will Data Tool

Students in Quadrant I of the Skill-Will Matrix were passing the class (60% or higher), regardless of attendance. Interventions for Quadrant I students centered around praise and enrichment opportunities. Students in Quadrant II had less than the trigger-trigger-number of absences and greater than 51% but less than a 60% which indicated to us they were trying but needed a little help. Interventions could include additional practice, reteaching, or retaking a test (among others), including strategies that are a part of every teacher’s tool kit.

Students in Quadrant IV had greater than 51% but less than 60% with greater than the trigger-trigger-number of absences. Quadrant IV students were also students that teachers could help but required some additional diagnoses. Quadrant IV students completed some coursework as evidence by having greater than 51% grade, but were also truant, which led us to believe they could successfully complete some classwork despite missing classes. Examining the data, reflecting on our own practice, and talking to these students led us to believe Quadrant IV students were “selectively capable” meaning they had the skill to perform

well academically, but were choosing not to, for some reason. The interventions for these students were slightly more sophisticated, but if the assumption of “selectively capable” was accurate, then teachers could create alternative assignments, motivate students by talking about the value of school and learning, incorporate student choice into assignments and assessments, than the trigger-amount of absences were categorized as “Intervention C”. All students in Quadrant III were referred to academic interventionists via the MTSS referral system. Academic interventionists, administrators, and teachers worked together to determine root causes of class failures for students in intervention group A since students in intervention group A had a weekly GPA

In a word, it helped coordinate support across the school.

incorporate social emotional learning (SEL) lessons into class, include metacognition/ time management skill building, increase rigor, in addition to other options.

Students in Quadrant III were categorized three ways: 1) Students that were failing a class, had greater than the trigger-number of absences, and had a weekly GPA of greater than 1.0 were categorized as “Intervention A” 2) Students that had little to no academic evidence (less than or equal to 51%) and had less than the triggernumber of absences were categorized as “Intervention B” 3) Students that had little to no academic evidence (less than or equal to 51%) and had higher above a 1.0 indicating they were passing other classes. Students in intervention group B were referred to social workers and students in intervention group C were referred to school counselors.

Impact of the Skill-Will Data Tool

The Skill-Matrix was able to do several things. First, it efficiently predicted students that would benefit from interventions which energized administrators, interventionists, and teachers to provide supports to students early enough so they could pass classes before progress reports.

Second, it helped teachers separate chronic issues such as truancy which required assistance from administration,

interventionists, counselors, or social workers, from acute learning struggles experienced by students in Quadrants II and IV which teachers could address. In a word, it helped coordinate support across the school. In a district that serves almost exclusively students of color, it is important to remember that COVID-19 is three times more likely to infect people of color and kill twice as many infected with the disease than Whites (Oppel, et al., 2020); and that teachers of students from communities of color dealt with significantly less engagement from their students and faced greater adversity during the pandemic (Kraft, Simon, & Lyon, 2020). Sporadic attendance, virtual classrooms filled with initials and avatars instead of smiling faces of students, added to an already adverse teaching context so having support from professionals throughout the school helped relieve some of the stress on teachers who were worried about the health and welfare of their students.

Third, it facilitated constructive, supportive conversations between teachers and administrators. Administrators working with teachers could show the Skill-Will Data Tool and say, “Look at the great work you are doing here for students in Quadrant I. Despite what you may be feeling, you are reaching students, you are helping students in this crisis. I know how worried you are about these students in Quadrant III, but you have called and emailed home several times for several weeks, you have made the MTSS referral, so let’s focus on students in Quadrants II and IV, the students we know you can move.”

In the throes of the pandemic, it was easy to lose sight of the good work being done. Administrators using the Skill-Will Data Tool centered the conversation around teaching successes while providing an entry point for troubleshooting learning issues experienced by students in Quadrants II and IV with the teacher. Celebrating successes, serving as a compassionate partner in helping students achieve, and coordinating the workload across professionals in the school was not only motivating for teachers, but also efficient. The Skill-Will Data Tool helped facilitate the kind of communication and coordination that Kraft, Simon, and Lyon (2020) suggest leads to successful schools, whether during a global pandemic or thereafter.

References

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Buffum, A. G., Mattos, M. W., & Malone, J. (2018). Taking action: A handbook for

RTI at work. Solution Tree Press.

Cotunga, N., Vickery, C.E., CarpenterHaefele, K.M. (2009). Evaluation of literacy level of education. Journal of

Community Health, 30(3), 213 – 219

Kraft, M. A., Simon, N. S., & Lyon, M. A. (2020, February). Sustaining a

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Teacher Working Conditions during the COVID-19 Pandemic (Working Paper No. 20-279). https://www.

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Oppel Jr., R. A., Gebeloff, R., Lai, K. K. R., Wright, W., & Smith, M. (2020, July 5). The fullest look yet at the racial inequity of coronavirus. The

New York Times. Brian Hurley has been coaching teachers in various contexts since 2011 where he first worked education graduate students at Northwestern University. Since then, Brian has helped teachers earn their National Board Certification, mentored teachers new to the profession, designed district inductional programs, developed training for more than 14,000 STEM teachers in the Republic of Georgia, and worked as a STEM coach and district instructional coach. He has published research on using disciplinary literacy in high school physics classrooms and has presented locally and internationally on inquiry, STEM topics, data driven instruction, and teacher education.