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Diagnostic Tools for Academic Performance and Social Behavior (Chapter 3) Name Here Institutional Affiliation Here.

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Presentation on theme: "Diagnostic Tools for Academic Performance and Social Behavior (Chapter 3) Name Here Institutional Affiliation Here."— Presentation transcript:

1 Diagnostic Tools for Academic Performance and Social Behavior (Chapter 3) Name Here Institutional Affiliation Here

2 Today’s Objectives Provide a purpose, rationale, and description of what constitutes a diagnostic tool for academic performance and social behavior Discuss how diagnostic tools may differ as a function of the problem area and/or level of service delivery (i.e., tier) Describe how to make data-based decisions with diagnostic tools to identify specific deficiencies to target with intervention Provide examples of working with a diagnostic tool for both academic and behavior problems

3 Universal Core Curriculum Universal Screening Measures Identification of At-Risk Students Standard Educational Diagnostic Tool Tier II Standard Protocol Instruction Progress Monitoring Individualized Diagnostic Assessment Tier III Individualized Instruction Progress Monitoring Special Education Entitlement Progress Monitoring

4 3 Purposes of Diagnostic Tools  Follow up with any student identified on the USM as potentially needing additional support  Identify a specific skill or subset of skills for which students need additional instructional support  Assist in linking students with skill deficits to empirically supported intervention

5 Rationale for Diagnostic Tools Measures  Rule out any previous concerns flagged by a universal screening measure  Find an appropriate diagnosis  Identify an effective treatment

6 Characteristics of Diagnostic Tools  Might be administered in a one-to-one format  Require more time to administer than a USM  Generally contain a larger sample of items than a USM  Generally have a wider variety of items than a USM

7 Examples of Diagnostic Tools for Academic Skills (DT-A) at Tier II Standard Protocol

8 Diagnostic Tools Chosen [Note to presenter: fill in your own info on this slide] [Provide examples of suggestions/ alternatives/adopted diagnostic tools to be used in your building and/or district at the Tier II level.] [Point out how this fills a gap in your curriculum and/or why these diagnostic tools were chosen.]

9 Examples of Diagnostic Tools for Academic Skills (DT-A) at Tier III and Special Education Curriculum Based Evaluation

10 Curriculum-Based Evaluation 1.Answer this: What does the student need in addition to what is already being provided (i.e., intensification of service)? 2.Conduct an analysis of student responding – Record review: Work samples – Observation: Independent work time – Interview: Ask the student why he or she struggles 3.Develop a hypothesis based on the above 4.Formulate a “test” of this hypothesis

11 Data-Based Decision Making with DT-A

12 Example of CBE: Tammy Fourth-grade student Did not make adequate progress with the Tier II standard protocol intervention in winter School psychologist administered an individual probe (i.e., diagnostic tool) and observed Tammy’s completion of this probe An analysis of responding yielded a diagnosis of the problem This diagnosis of the problem informs intervention selection

13 1. What seems to be the problem? 2. What should the intervention target? 3. Describe something a teacher could do to target this problem. 4. Do you have to buy an expensive program just for Tammy?

14 Revisiting the 3 Purposes of Diagnostic Tools: Tammy  Follow up with any student identified on the USM as potentially needing additional support  Identify a specific skill or subset of skills for which students need additional instructional support  Assist in linking students with skill deficits to empirically supported intervention

15 Revisiting the Characteristics of Diagnostic Tools: Tammy  Might be administered in a one-to-one format  Require more time to administer than a USM  Generally contain a larger sample of items than a USM  Generally have a wider variety of items than a USM

16 Data-Based Decision Making with Diagnostic Tools for Social Behavior (DT-B)

17 Screening: Teacher Nomination And Office Discipline Referrals Confirmation: Rating Scales Descriptive Functional Assessment: Interviews, Record Review, Observations Experimental Functional Analysis: FBA plus Manipulation of the environment to note effects

18 Office Discipline Referrals Good as a stand-alone screening tool for externalizing behavior problems Also good for analyzing schoolwide data – Discussed later See example teacher nomination form – Chapter 2 of book and on CD

19 Teacher Nomination Teachers are generally good judges Nominate three students as externalizers Nominate three students as internalizers Trust your instincts and make decision – There will be more sophisticated process to confirm your choices

20 Confirming Teacher Nominations with Other Data Teacher, Parent, and Student Rating Scales – BASC – CBCL (Achenbach)

21 Example: Systematic Screening for Behavior Disorders (SSBD) Critical Events Inventory: – 33 severe behaviors (e.g., physical assault, stealing) in checklist format – Room for other behaviors not listed Adaptive Scale: Assesses socially appropriate functional skills (e.g., following teacher directions) Maladaptive Scale: Assesses risk for developing antisocial behavior (e.g., testing teacher limits)

22 Functional Assessment and/or Experimental Functional Analysis Set of procedures that requires extensive training Functional Assessment: Results in a testable hypothesis about reason for behaviors (e.g., social attention, escape, tangible reinforcement, sensory reinforcement) Functional Analysis: Results in empirical support for the tested hypothesis

23 Functional Assessment: Remember to RIOT Record review – ODRs, antecedent-behavior-consequence (A-B-C) logs, teacher narratives Interview – Teacher, child, parent, key personnel Observation – A-B-C logs, frequency counts – Classroom observations Test (not done): This is what the experimental functional analysis is all about

24 Data-Based Decision Making Using DT-B: Antecedent-Behavior-Consequence Logs

25 1. What patterns do you see here? 2. What is the likely function of behavior?

26 Data-Based Decision Making Using DT-B: Frequency Counts

27 1.What day does the behavior most often occur? What day is it least likely to occur? 2.What time of day does the behavior most often occur? Least often? 3.When should someone come to visit if they wanted to witness the behavior? Note: It is just as important to look at when the behavior occurs as it is to look at when it doesn’t.

28 Data-Based Decision Making Using DT-B: Direct Behavioral Observations

29 1.What can you get from this? 2.Are all of these behaviors severe enough to warrant individualized intervention?

30 Experimental Functional Analysis Experimentally testing a hypothesis about why a behavior occurs: – Social attention – Escape – Tangible reinforcement – Sensory reinforcement Requires expertise, cooperation, and time Strongest empirically supported method available today for identifying cause(s) of behavior

31 Example of Experimental Functional Analysis: Talking Out in Class Potential FunctionTest Condition Tangible reinforcementContingent access to reinforcement AttentionContingent reprimand EscapeContingent break upon talking out after demand Sensory stimulationLeave isolated in room Control conditionFree time with attention and no demands

32 What is the primary function of behavior?

33 Review of Important Points Three Purposes for Diagnostic Tools – As a follow-up to USM – To identify a specific skill that needs additional support – To assist in linking students to intervention Four Characteristics of Diagnostic Tools – Might be administered in a one-to-one format – Require more time to administer than a USM – Generally contain a larger sample of items than a USM – Generally have a wider variety of items than a USM

34 Review of Important Points DT-A procedures may differ at Tiers II and III DT-B procedures may differ at Tiers II and III DT data are not the only data to consider when developing an intervention

35 Questions


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