Behavior Data for Real-World Success

Lyndsay Palach Shelton, MA, LBSII — 4 minute read
As a transition specialist, I love a good data graph. Show me progress-monitoring charts, benchmark trends, and growth percentiles—I’m in. But here’s what I’ve learned over time: academic data alone does not predict adult success.
When our students leave high school, their outcomes hinge just as much on emotional regulation, coping skills, persistence, and autonomy skills as they do on reading levels or algebra credits.

And the research backs that up.
The Council for Exceptional Children emphasizes that research-backed special education practice requires using data to inform decisions across academic, behavioral, and functional domains—not just content areas. Similarly, the Division on Career Development and Transition (DCDT) highlights self-determination, social competence, and career readiness as critical predictors of post-school success.
So the real question isn’t whether we should use mental and behavioral health data. It’s: how do we coach our staff to actually do it?
So the real question isn’t whether we should use mental and behavioral health data. It’s: how do we coach our staff to actually do it?
Lyndsay Palach Shelton, MA, LBSII

Redefine What “Counts” as Data

Most educators are very comfortable tracking reading fluency, math benchmarks, credit accrual, and graduation progress. But when you start talking about time to return to baseline, coping strategy use, work stamina, attempts at independence, and avoidance patterns, you can feel the hesitation.

Here’s the shift: if it impacts adult independence, it counts as data.

DCDT’s transition-focused research consistently indicates that self-determination and adaptive behavior are strong predictors of employment and postsecondary outcomes. If we aren’t measuring those skills, we’re leaving major predictors off the table.

Coaching move: Start small. Ask your team to identify two non-academic skills that most interfere with adult success for a particular student. Track them consistently for four weeks. Then analyze patterns together.

Once staff see patterns emerge, it becomes real.

Anchor It in Transition Requirements

Under the IDEA, transition services must be based on measurable postsecondary goals related to employment, education, and independent living.

That word—measurable—matters.
Ask your team:
  • Can a student maintain employment if they cannot regulate frustration?
  • Can they request accommodations in college without practicing it now?
  • Can they navigate local settings if anxiety shuts them down?

The Council for Exceptional Children’s High-Leverage Practices reinforce the importance of using data to guide behavioral and social-emotional supports—not as an add-on, but as a core instructional practice.

When staff see that behavioral data collection is both research-supported and legally aligned, the conversation shifts from “extra” to “essential.”
But coaching staff means helping them move from documenting incidents to analyzing patterns. This is the perfect role for job coaches or paraeducators. 
Lyndsay Palach Shelton, MA, LBSII

Shift from Incident Reports to Pattern Recognition

In many buildings, behavioral data gets attention only after something explodes.
But coaching staff means helping them move from documenting incidents to analyzing patterns. This is the perfect role for job coaches or paraeducators. 

Instead of: “What happened?”
Try:
  • “What pattern do we see?”
  • “What time of day does this occur?”
  • “What adult response seems to escalate or de-escalate?”
  • “What skill is missing here?”

The Council for Exceptional Children emphasizes data-based decision-making as a cornerstone of effective special education. That includes identifying variables and adjusting instruction—not just recording events.

Coaching move: During team meetings, build in five minutes for hypothesis testing. Treat behavioral data like academic data: something we analyze and adjust based on, not just file away.

Build Comfort with Mental Wellness Metrics

Let’s be honest—some staff feel nervous about measuring psychological health indicators.

You’ll hear:
  • “I’m not a counselor.”
  • “I don’t want to label anxiety.
  • “I don’t know how to quantify that.”


Reassure them: we are not diagnosing. We are observing the impact of function.

DCDT’s work on self-determination highlights the importance of teaching and measuring goal-setting, self-monitoring, and self-regulation. Those are instructional skills—not clinical diagnoses.

Start simple:
  • 1–5 regulation scales
  • Frequency of independent break requests
  • Duration of sustained task engagement
  • Self-monitoring checklists

If we can graph reading fluency, we can graph coping strategy use.

Coaching move: Model it yourself. Collect one behavioral variable for a student in a work-based learning placement. Show the team how that data led to adjusting supports. Nothing builds buy-in like visible impact.

Make Sure the Data Leads Somewhere

If staff collect data and nothing changes, motivation disappears quickly.

The Council for Exceptional Children’s professional standards emphasize using assessment results to adapt instruction and improve outcomes. That means every data conversation should end with action.

After reviewing behavioral data, ask:
  1. What will we stop?
  2. What will we start?
  3. What will we adjust?
  4. How will we measure impact?

For transition-age students, this might mean:
  • Modifying worksite expectations
  • Teaching explicit feedback-response routines
  • Increasing structured autonomous opportunities
  • Adjusting environmental supports before known stress points

When staff see data directly shaping programming decisions, its value becomes obvious.

Keep Adult Outcomes Front and Center

As a transition specialist, I constantly bring teams back to one grounding question: “Will this matter after graduation?” Reading growth matters. But so does arriving on time, managing supervisor feedback, handling frustration without quitting, sustaining effort on non-preferred tasks, and navigating unfamiliar environments.

DCDT’s research repeatedly reinforces that post-school success is strongly linked to social competence, self-determination, and work behaviors. If we are not measuring those, we are not truly preparing students for adulthood.
If we only use data to measure academics, we prepare students for tests. But if we use data to measure regulation, resilience, and self-determination, we prepare them for life.
Lyndsay Palach Shelton, MA, LBSII

Final Thought

If we only use data to measure academics, we prepare students for tests. But if we use data to measure regulation, resilience, and self-determination, we prepare them for life.

The Council for Exceptional Children and the Division on Career Development and Transition both reinforce what many of us see every day: postsecondary success depends on more than content mastery. Coaching staff to use mental and behavioral health data isn’t about adding more to their plates. It’s about aligning our data practices with what truly predicts independence. And from a transition perspective, that alignment changes everything.

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written by

Lyndsay Palach Shelton

Lyndsay Palach Shelton is a transition specialist who specializes in determining realistic and fulfilling individual goals while working with families to inform, support, and guide them through the complex world of special education. She has been a special educator and transition specialist in the public education sector. Outside of her professional work, she enjoys running marathons around the country, traveling with her family, and enjoying delicious vegan dishes. 

Lyndsay is a Transition Specialist, Certified Vocational Coordinator, and Founder of Future SLTP with her Bachelors in Special Education, Master of Arts in Transition Education and Services, and certification in Cooperative Education.

EDITED BY Heather Volchko

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