Check-In/Check-Out (CICO) in Schools: Tier 2 PBIS Guide for BCBAs®

You’re Called When the Fire’s Already Burning

The Pattern You Know

It’s 2:07 p.m. and the email hits: “Three office referrals this week—can you help?” As a BCBA®, you arrive with reinforcement plans and calm coaching—but you’re entering after escalation. Teachers are exhausted, students are discouraged, and leaders need something doable tomorrow, not a 30-page plan next month.

You don’t have to wait for chronic behavior to recommend scalable supports. Within district procedures, you can help teams set up Check-In/Check-Out (CICO) so it’s ready to launch quickly, with clear goals, simple data, and predictable reinforcement. Your role: recommend, train briefly, and data-check (Hawken, Crone, Bundock, & Horner, 2020).

Key Takeaways

• CICO = Tier 2 support implemented within your school’s referral process.

• BCBAs® recommend, train, and data-check; they don’t bypass referrals.

• Core pieces: AM check-in → DPR (2–5 Tier 1–aligned goals, 0–2 scale, ≥4 ratings/day) → PM check-out + same-day reinforcement → home sign-off.

• Start with 3–5 days of baseline, then shape toward ~80% success.

• Review data every 2 weeks using a simple dashboard (daily %, by period, fidelity).

• Front-load reinforcement (Weeks 1–2) with student choice; then fade to Tier 1.

• Best for mild–moderate, multi-setting concerns where adult attention is reinforcing; use function-mods or Tier 3 when needed.

• Protect fidelity: ≤ 3 CICO students/teacher, semi-private check-in/out, standardized goals/forms.

• Flat data? Check fidelity → upgrade reinforcers → shorten intervals → verify function; escalate per policy if needed.

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What Is Check-In/Check-Out (CICO)?

CICO is a Tier 2 routine that gives students predictable bookends (brief morning check-in and afternoon check-out), a simple Daily Progress Report (DPR) tied to Tier 1 expectations, and frequent, behavior-specific teacher feedback. Schools use it to boost engagement, reduce disruptions, and generate actionable data with minimal staff time (Drevon, Hixson, Wyse, & Rigney, 2018; Maggin, Zurheide, Pickett, & Baillie, 2015; Park & Blair, 2020).

Why it works (ABA in action): reinforcement and specific praise, motivating operations (anticipation of praise/access), stimulus control (AM/PM routines), rule-governed behavior (clear, simple rules), and differential reinforcement of alternatives—powered by consistent teacher feedback. Component analyses highlight the importance of feedback cadence as an active ingredient (Weber, Rich, Gann, Duhon, & Kellen, 2019).

Core Components (Done Right)

• Morning check-in (1–2 min): Warm greeting, prime expectations, quick materials check (secondary), hand the DPR.

• DPR + teacher feedback: Use 2–5 concrete goals aligned to Tier 1 (e.g., “follow directions the first time,” “on task,” “keep hands/feet to self”). Score ≥4 rating periods/day with a 0–2 rubric printed on the form for consistency.

• Afternoon check-out (1–2 min): Total points, give specific praise, and deliver same-day reinforcement when goals are met.

• Home communication: Paper or digital signature to connect school and home and maintain accountability.
  These are the standard elements as described in the CICO/BEP manual (Hawken et al., 2020).

How to Implement CICO (Within Your Referral Process)

1) Build the team

Include an administrator, coordinator (any trained, trusted adult), teacher rep, and behavior support/BCBA®. Clarify referral flow and caregiver communication (Hawken et al., 2020).

2) Standardize goals → design the DPR

Translate Tier 1 expectations into 2–5 observable behaviors and print a 0–2 rubric on a half-page DPR. Plan ≥4 rating periods/day (intervals ≤75 minutes; younger students benefit from shorter intervals) (Hawken et al., 2020).

3) Train fast (keep it practical)

Model behavior-specific praise, consistent scoring with examples, neutral scripts for lower ratings, and logistics (semi-private, easy access). Coordinator—not the classroom teacher—delivers end-of-day reinforcement (Hawken et al., 2020).

4) Establish baseline (3–5 days)

Teachers score DPRs without student feedback to set an achievable starting goal (often shaped toward ≈80%) and share baseline with caregivers (Maggin et al., 2015; Park & Blair, 2020).

5) Launch + review biweekly

Start CICO and review data every two weeks to decide whether to continue, modify, fade, or add supports (Drevon et al., 2018; Todd, Campbell, Meyer, & Horner, 2008).

Data & Decision Rules (One Simple Dashboard)

Track five essentials so the team can access insights in under a minute:
(a) Daily % (overall), (b) by period/class (hot spots), (c) a 5–10 day moving average (trend), (d) attendance/tardy flags, and (e) fidelity checks (rating periods completed? same-day reinforcement?). Use these to guide fading or intensifying supports (Hawken et al., 2020; Weber et al., 2019).

Decision rules you can standardize:

• Continue: moving average ≥80% with steady trend.

• Modify: 60–79% or class-period dips → tighten rubric, strengthen reinforcement, adjust intervals.

• Intensify: <60% despite fidelity → increase prompts, shorten intervals, check function.

• Fade: 2–3 weeks ≥80% → reduce rating periods, thin reinforcement, reduce check-ins → return recognition to Tier 1 (Hawken et al., 2020).

Reinforcement That Actually Works

• Front-load Weeks 1–2: Provide dense, same-day reinforcement to build momentum; if goals aren’t met with fidelity, lower the initial criterion (set from baseline) and increase value/immediacy (Todd et al., 2008; Sottilare & Blair, 2023).

• Use student choice menus: Low-cost privileges (lotteries, school store coupons, brief preferred activities, “buddy” passes) outperform adult guesses; verify impact in the data (Maggin et al., 2015).

• Then thin: Reduce rating periods, move to intermittent reinforcement, and taper check-ins (daily → M/W/F → weekly → graduation) so students transition back to Tier 1 systems (Hawken et al., 2020).

Eligibility & Referral Pathways (Who It’s For—and Not)

Good fit (via your school’s referral/identification process): mild–moderate concerns across multiple settings (e.g., off-task, low initiation, mild disruption, transition difficulties); positive response to adult attention, predictable structure, and frequent feedback; capacity to follow simple, explicit rules (Drevon et al., 2018; Maggin et al., 2015).

Not a fit (consider function-matched or Tier 3 pathways per policy): severe/chronic safety risks; concerns only in unstructured settings; student finds adult attention aversive; or the primary function is escape from specific academic demands—traditional CICO is strongest when attention is the maintaining variable (Hawken, O’Neill, & MacLeod, 2011; Klingbeil, Dart, & Schramm, 2019). Function-modified CICO can extend effects when aligned to function (e.g., providing brief, earned breaks for escape-maintained behavior) (Kilgus, Fallon, & Feinberg, 2016).

Common Pitfalls & Fast Fixes

• No data or slow access → Build a 1-page dashboard; schedule biweekly 10-minute reviews (Hawken et al., 2020).

• Inconsistent scoring → Print the 0–2 rubric on every DPR; practice with examples in staff training (Hawken et al., 2020).

• Overloaded teachers → Cap at ≤3 CICO students per teacher; standardize goals/forms so one coordinator can support many students efficiently (Weber et al., 2019).

• Flat data → Re-check function, increase reinforcer value/immediacy, shorten intervals, and verify fidelity; teacher feedback is a key active ingredient (Weber et al., 2019; Maggin et al., 2015).

• Privacy concerns → Use semi-private, easy-access locations—especially in middle/high school (Hawken et al., 2020). (

Want the Full Playbook?

Check-In/Check Out A Tier 2 Intervention: Turning Small Moments into Big Behavior Gains gives you 1.5 CEUs and walks through grade-band DPR examples, reinforcement menus, fidelity tools, and troubleshooting non-responders—so you can recommend CICO confidently within referral procedures and help teams run it with fidelity.

References (APA)

Drevon, D. D., Hixson, M. D., Wyse, R. D., & Rigney, A. M. (2018). A meta-analytic review of the evidence for check-in check-out. Psychology in the Schools, 56(3), 393–412. https://doi.org/10.1002/pits.22195 (PMC)

Hawken, L. S., Crone, D. A., Bundock, K., & Horner, R. H. (2020). Responding to problem behavior in schools: The check-in, check-out intervention (3rd ed.). Guilford Press. (Guilford Press)

Hawken, L. S., O’Neill, R. E., & MacLeod, K. S. (2011). An investigation of the impact of function of problem behavior on effectiveness of the Behavior Education Program (BEP). Education and Treatment of Children, 34(4), 551–574. https://doi.org/10.1353/etc.2011.0031 (PMC)

Kilgus, S. P., Fallon, L. M., & Feinberg, A. B. (2016). Function-based modification of check-in/check-out to influence escape-maintained behavior. Preventing School Failure, 60(4), 302–310. https://doi.org/10.1080/15377903.2015.1084965 (Taylor & Francis Online)

Klingbeil, D. A., Dart, E. H., & Schramm, A. L. (2019). A systematic review of function-modified check-in/check-out. Journal of Positive Behavior Interventions, 21(2), 77–92. https://files.eric.ed.gov/fulltext/EJ1207376.pdf

Maggin, D. M., Zurheide, J., Pickett, K. C., & Baillie, S. J. (2015). A systematic evidence review of the Check-In/Check-Out program for reducing student challenging behaviors. Journal of Positive Behavior Interventions, 17(4), 197–208. https://doi.org/10.1177/1098300715573630 (SAGE Journals)

Park, E.-Y., & Blair, K.-S. C. (2020). Check-in/check-out implementation in schools: A meta-analysis of group design studies. Education and Treatment of Children, 43(4), 361–375. https://doi.org/10.1007/s43494-020-00030-2 (PMC)

Sottilare, A. L., & Blair, K.-S. C. (2023). Implementation of check-in/check-out to improve classroom behavior of at-risk elementary school students. Behavioral Sciences, 13(3), 257. https://doi.org/10.3390/bs13030257 (PMC)

Todd, A. W., Campbell, A. L., Meyer, G. G., & Horner, R. H. (2008). The effects of a targeted intervention to reduce problem behaviors: Elementary school implementation of check in–check out. Journal of Positive Behavior Interventions, 10(1), 46–55. https://doi.org/10.1177/1098300707311369 (PMC)

Weber, M. A., Rich, S. E., Gann, C. J., Duhon, G. J., & Kellen, S. S. (2019). Can less be more for students at risk for emotional and behavioral disorders? Evaluating components of check-in/check-out. Education and Treatment of Children, 42(4), 469–488. https://doi.org/10.1353/etc.2019.0022 (scholars.okstate.edu)