Investigating the Decision-Making of Response to Intervention (RtI) Teams Within the School Setting Dr. Scott Thur Dr. Kathleen Marshall OSEP Project Directors’ Conference, 2016 OSEP Project Directors' Conference, 2016 OSEP Project Directors' Conference, 2016 1

I. Nature and Significance of the Problem OSEP Project Directors' Conference, 2016 OSEP Project Directors' Conference, 2016 2

A. Summary Review of Literature Table 1: RtI Components RtI Component RtI Aspect Sample Resources Measures and Tools Assessment Screening, CBM Monitoring Curriculum / Intervention Fuchs & Fuchs (2006) Deno et al., (2009); Stuart & Rinaldi (2009) Duhon et al. (2009); Wanzek & Cavanaugh (2012) Data-Driven Decisions Evidence-based practice Determining risk Tiers / Special Education Gresham (2004) Mellard et al. (2004); Gersten et al. (2009); VanDerHayden (2010) Fuchs et al. (2012); Shapiro & Clemens (2009) Process and Procedures RtI model approach Fidelity of implementation Logistics and Resources Fuchs et al. (2004); White, et al. (2010) Glover & Diperna (2007); Keller-Margulis (2012) Jenkins et al. (2013); Prewett et al. (2012) OSEP Project Directors' Conference, 2016 OSEP Project Directors' Conference, 2016 3

B. Study’s Purpose There is a need to: Determine the decision-making processes and influences of RtI teams within each of the three RtI areas. A paucity of quantifiable data Measure who serves on RtI teams, examine the multiple factors that impact their decision-making, and study whether involvement differs between team members within each of the three RtI areas. Examine the decision-making between RtI team levels (i.e. elementary versus middle) to have a better understanding of differences in implementation. OSEP Project Directors' Conference, 2016 OSEP Project Directors' Conference, 2016 4

Discussion Questions In what ways will the data presented in this breakout session help to explain how and why the decisions that are made impact a school and district's RtI model? How are certain types of RtI decisions related to a team member’s position and school level, and what are some targeted and constructive practices schools and districts can implement as a result? Does a RtI team member's role on their team influence their decision-making, and how does that affect the purpose and effectiveness of the RtI process?  OSEP Project Directors' Conference, 2016 OSEP Project Directors' Conference, 2016 5

II. Methodology OSEP Project Directors' Conference, 2016

A. Overview of Study’s Procedures Recruiting district participation Recruiting school teams, personnel Setting 5 South Carolina school districts Participants Core members of team – directly, consistently involved OSEP Project Directors' Conference, 2016 OSEP Project Directors' Conference, 2016 7

B. Summary of Demographics Participation Overview (in totals): School districts = 5 Range of schools within districts (i.e. district size) = 3–35 School teams participating = 37 Surveys sent = 259 Surveys with discernable data = 178 Fully completed surveys = 135 Completion percentage = 52% Demographic Aspects (range, mean) Team Size: 2–25; 7.2 Years Serving on RtI team: 1–23; 3.6 RtI Experience (in years): 1–23; 5.6 Years in education: 1–46; 16.8 Schools’ RtI model (in years): 1–9; 2.3 OSEP Project Directors' Conference, 2016 OSEP Project Directors' Conference, 2016 8

C. Research Design IV. Instrumentation - RtI Team Decision-Making Questionnaire Survey Design Electronic survey – Qualtrics © Survey Software 30 total questions – with sub-items Likert-like responses Open-ended response items Multiple choice Four sections: Measures and Tools - 11 total questions Data-Driven - 8 total questions Process and Procedures - 11 total questions General Demographics – 8 demographic questions Section provided at end of survey 5 additional for RtI Leads OSEP Project Directors' Conference, 2016 OSEP Project Directors' Conference, 2016 9

III. Results and Interpretation OSEP Project Directors' Conference, 2016 OSEP Project Directors' Conference, 2016 10

A. Data Analysis Descriptive statistics – categorical data measuring frequency and percentages Inferential statistics – test of associations Variable 1 – Level of Decision-Making Involvement within each aspect Variable 2 - Team Member’s Position on the RtI team Variable 3 – School Level Fisher’s Exact Test with a Monte Carlo estimate approach (Variable 1, 2) Confidence Interval (99% level) Significance (p=.05) Cramer’s V coefficient Fisher’s Exact Test (Variable 1, 3) Phi correlation coefficient OSEP Project Directors' Conference, 2016 OSEP Project Directors' Conference, 2016 11

B. Findings and Interpretation Influential factors (Team) Using evidence-based practices most influential across all RtI areas Greatest within Data-Driven Decisions (63.3%) Pressure from parents is the least influential across all RtI areas (only 2-3%) Pressure from teammates is not a significant team influence Comparison differences within Process and Procedures Pressure from teammates, school position, role on team Amount of time spent making Data-Driven Decisions Majority of time spent making Data-Driven decisions (>31 minutes) Least time spent making Measures and Tools decisions (<15 minutes) OSEP Project Directors' Conference, 2016

B. Findings and Interpretation (2) Influential factors (Personal) Using evidence-based practices most influential across all 3 areas Greatest within Data-Driven decisions (66%) Pressure from parents had the least amount of influence (<2%) There were distinct, area-specific influences that impacted team member’s personal decision-making: District mandates (29% for Measures and Tools, 13% for Process and Procedures) School culture – specific to Process and Procedures (15.1%) Incorporating previous experiences – specific to Measures and Tools Considering and analyzing multiple and varied data sources (29% for Data Driven). OSEP Project Directors' Conference, 2016

B. Findings and Interpretation (3) Tier involvement, Team v. Personal Greatest amount of team members - Tier 2 decisions (75.3%-90%) Least amount of team members - Tier 1 decisions (63% - 69%). The greatest amount of on-going, informative feedback – Tier 2 decisions (79% - 89.1%) Least amount of feedback in tier 1 decisions (66.2% - 74.8%) Tier 3 roughly 10% greater than tier 1 Comparison data: Team versus Personal Generally slightly greater degree of influence with teams as compared to personal across areas Most pronounced within Measures and Tools Between RtI areas Greatest amount of team members - Data-Driven Decisions Evidence-based practices Least involved with decisions - Measures and Tools OSEP Project Directors' Conference, 2016

B. Findings and Interpretation (4) Influence based on perception of position Team members associate their position to be the greatest with providing consistent, continued feedback and follow-up. Application of the results There appears to be many decisions within Measures and Tools that are one-time decisions, and so follow-up is not applicable. Particular personnel are more responsible for the decisions across RtI areas and tiers than others. Administrators, leads, and coaches Some types of decisions seem to be mandated to teams without room for them to deviate. District mandates within Measures and Tools If there are limited resources, teams seem to focus on tier 2, Data-Driven Decisions. OSEP Project Directors' Conference, 2016

B. Findings and Interpretation (5) Level of involvement in decision-making aspects There are clear and distinct aspects that team member‘s are and are not involved in. Entire teams do not collectively make all decisions. A large majority of all team members clearly spend the greatest amount of their time making Data-Driven Decisions. Process and Procedures – least overall The data clearly shows that only a few individuals are generally involved making certain types of decisions, and that some decisions are beyond the control of the school team level. OSEP Project Directors' Conference, 2016

B. Findings and Interpretation (6) Level of involvement based on position Many significant associations between position and involvement. Specific position-dependent decisions are made in each area. Administrators, leads, coaches / interventionists All aspects of Measures and Tools are dependent on position, and most are for Data-Driven and Process and Procedures. Top aspects: Deciding, planning which SW curriculum to implement Determining students’ ROI for movement between tiers Determining the locations of the intervention Lack of significant associations for some aspects: Determining student responsiveness to intervention Selecting number of tiers; selecting model type Reasons for independence: Large majority and/or extremely select few Prescribed, standardized manner (i.e. less variation) OSEP Project Directors' Conference, 2016

B. Findings and Interpretation (7) Involvement based on school level School level appears to affect some types of decisions. Examples: Measures and Tools – Determining Screening Instruments (elementary - 60.3% v. middle - 87.5%) Process and Procedures – Analyzing Fidelity of Implementation (elementary – 53.4% v. middle – 87.5%) Supports previous research Sources of data (Burns, 2008; Shapiro & Clemens, 2009) Middle level logistics, focus (Dulaney, 2012; Fuchs, Fuchs, & Compton, 2012) Universal screenings - Vaughn & Fletcher (2010) Fidelity of implementation Processes established Variation between programs Priority of school teams Data-Driven Decisions OSEP Project Directors' Conference, 2016

IV. Implications OSEP Project Directors' Conference, 2016 19

OSEP Project Directors' Conference, 2016 A. Limitations Less than intended sample size There were only eight total middle school participants Data collected was exclusively from my survey At least one RtI Lead indicated on the survey that their school was within its first year in RtI South Carolina only – differences with other states? 5 school districts Generalizable with other types of models OSEP Project Directors' Conference, 2016

OSEP Project Directors' Conference, 2016 B. Implications I. Future Research District level of involvement and influence in decision-making within their schools’ RtI model mandates and policies to schools and teams. Involvement on school teams State mandates; district variation Team members’ understanding of evidence-based practices. OSEP Project Directors' Conference, 2016

OSEP Project Directors' Conference, 2016 B. Implications (2) II. Practical Teams can more efficiently allocate time and resources targeted district involvement professional development Certain decisions are dependent on position Increasing additional perspectives and feedback Explain how and why decisions are actually made in an RtI school. emphasis and priority planned sharing of responsibility Develop strategies to address specific team needs team functioning, members’ understandings and awareness allows for enhanced team functioning district support, feedback, guidance School level differences – function, purpose, goals OSEP Project Directors' Conference, 2016

Discussion Questions (2) In what ways will the data presented in this breakout session help to explain how and why the decisions that are made impact a school and district's RtI model? How are certain types of RtI decisions related to a team member’s position and school level, and what are some targeted and constructive practices schools and districts can implement as a result? Does a RtI team member's role on their team influence their decision-making, and how does that affect the purpose and effectiveness of the RtI process?  OSEP Project Directors' Conference, 2016 OSEP Project Directors' Conference, 2016 23