Data-based Decision Making for Instruction and Professional Development

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Principle 3 Provide eﬀec+ve demonstra+ons, professional development, and

1 Data-based Decision Making for Instruction and Professional Development Jeanne Wanzek, Ph.D. Principle 3 Provide eﬀec+ve demonstra+ons, professional development, and leadership support to teachers on the necessity of using data to inform, plan, and adjust instruc+on, in addi+on to other areas. 1

2 Principle 5 Implement ongoing, intensive professional development that targets what teachers are expected to teach; that aligns with district, state, and na+onal standards; and that matches teacher and student needs. Evidence for Data-based Decision Making Teachers who monitor the eﬀec=veness of instruc=on tend to achieve signiﬁcantly higher rates of student learning than teachers who rely on more tradi=onal assessments (Conte & Hintze, 2000; Fuchs, Fuchs, HamleM, & Allinder, 1991; Stecker, Lembke, & Foegen, 2008) Teachers using progress- monitoring measures tend to be more realis=c when es=ma=ng a student's rate of progress and are able to adjust instruc=onal goals accordingly (Fuchs, Deno, & Mirkin, 1984; Fuchs, Fuchs, HamleM, & Stecker, 1991) 2

3 Evidence for Data-based Decision Making (cont d) Make data part of an ongoing cycle of instruc=onal improvement Teach students to examine their own data set learning goals Establish a clear vision for schoolwide data use Provide supports that foster a data- driven culture within the school Develop and maintain a districtwide data system Hamilton et al., 2009 Common Pitfalls Overwhelmed by data Overreliance on using tes=ng for instruc=on Lack of knowledge for using the available data Use of data for evalua=ve purposes only 3

4 Leadership Leaders play a crucial role in: What data are collected How data are used Culture for the use of data Resources for using data Practices Using Data Provide eﬀec2ve demonstra2ons, professional development, and support to teachers on the necessity of using data to inform, plan, and adjust instruc2on. Lead teachers and school staﬀ members through the process of using data to iden2fy and plan for changes in the instruc2onal program. 4

5 Practices (cont d) Professional Development Ins2tute frequent and ongoing site- based professional development. Provide 2me and resources for professional development that focuses on the subject maber content teachers are expected to teach and that aligns with district, state, and na2onal standards. Provide targeted professional development in an intensive format that is con2nuous throughout the year. Monitor implementa2on of the prac2ces from professional development and related teacher and student outcomes for at least 2 years to determine the associa2on between them. Addressing Needs Determine sources of data available Iden=fy what is collected and why Reduce duplica=on or data that are not useful Skalski & Romero,

6 Ongoing Cycle of Instructional Improvement Collect and prepare a variety of data about student learning Hamilton et al., 2009 Interpret data and develop hypotheses about how to improve student learning Modify instruc=on to test hypotheses and increase student learning Multiple Types of Data Student achievement measures Teacher prac=ce measures Demographic informa=on Percep=ons, beliefs, and aetudes 6

7 Consider the Student Assessment Data You Have or Need for Decision-Making Screening Diagnos=c Progress Monitoring Outcome HELPING TEACHERS UNDERSTAND THE DATA FOR DECISION-MAKING 7

8 Know Your Assessment What is the assessment designed to measure? What types of decisions can be made with the assessment? How has this assessment typically been used in research or prac=ce? What is our conﬁdence in the assessment and the decisions we are making? How does this assessment relate to instruc=on? Know The Meaning of the Assessment Scores What types of scores are available? How is the score calculated? What on the assessment causes change in a score? 8

9 Instructional Decisions Current Instruc=on What instruc=on is currently happening? What areas of instruc=on could be adapted? There is no point in tes=ng if you don t look at the data, don t understand it, and don t change. Chuck Watson, Principal Kennewick School District Fielding, Kerr, & Rosier,

10 6/4/14 HELPING TEACHERS USE ASSESSMENT TO INFORM INSTRUCTION VIDEO 10

11 Key Questions When Examining Data In what areas are students on track? In what areas do students need addi=onal instruc=on? What speciﬁc skills or prac=ces have been mastered? What instruc=on can be provided? Which students have similar instruc=onal needs and will form an appropriate group for instruc=on? Reading First Initiative: Secretary s Leadership Academy Types of Decisions Using Data District, School, or Grade Level Decisions Classroom Decisions Individual Student Decisions 11

12 District or School Level Decisions Need data from all students in the school or district (separated by grade level) Key areas: Are more students geeng on track in reading? Are signiﬁcant numbers of students in at- risk or categories? Are signiﬁcant numbers of students on the bubble for risk? Are par=cular students not doing well? ONE SCHOOL 12

13 Historical Sixth Grade Data Total Score Fall 15 Spring Computa=on Concepts and Applica=ons Classroom Observations and Interviews: Sixth Grade Math Ra+os and Propor+onal Rela+onships: ra=o concepts The Number System: focus on accuracy, focus on complex problems, frac=on mul=plica=on and division procedures Expressions and Equa+ons: algebraic expressions and equality with an unknown variable Geometry: procedures for determining area and volume Sta+s+cs and Probability: limited instruc=on, focus on comple=ng ac=vi=es in the program 13

14 Concerns Instruc+onal Components Fluency of procedural knowledge in the number system and computa=on Consistent applica=on of knowledge to problem solving, real world situa=ons, and use of mathema=cs language Sta=s=cs instruc=on Instruc+onal Delivery Modeling of procedural ﬂexibility Explicit connec=ons between previous knowledge and new knowledge (e.g. extending understanding of mul=plica=on and division) Prac=ce opportuni=es for students to verbalize decisions and solu=ons to math problems with feedback Instructional Decisions Professional Development for Sixth Grade Teachers Sta=s=cs Instruc=on Organizing Knowledge Across Concepts in Math Instruc=on Teaching for Accuracy and Fluency Progress Monitoring Diﬀeren=a=ng Instruc=on 14

15 Fall Data: Sixth Grade Score 25 Historical 20 Cohort I Computa=on Concepts and Applica=ons Spring Data: Sixth Grade Score 25 Historical 20 Cohort I Computa=on Concepts and Applica=ons 15

16 Sixth Grade Historical Math Data Percent of Students At Risk OnTrack Computation Concepts and applications Sixth Grade Cohort I 100 Percent of Students At Risk On Track Computations Concepts and Applications 16

17 CLASSROOM DECISIONS Classroom Decisions Need data for all students in the class Key Areas: Is most of the class at or above grade level? What areas are low for many students in the class? What areas are high for many students in the class? Who is falling behind? 17

18 Mr. Valenzuela Fall Data Student Oral Reading Fluency Maze Comprehension Spelling ESSENCE ANTONIA ESTHER PHILUP LILLIAN JONATHAN MARIA JESSICA SHYDESHIA SADIE KAYLA ONICA TRE RYAN ALEJANDRO JAMES DEVIN 110 Instructional Decisions Oral Reading Fluency Prac=ce reading connected text Instruc=on in ﬂuency Instruc=on in decoding mul=syllabic words Integrate decoding and spelling of mul=syllabic words Targeted word recogni=on work for students with signiﬁcant accuracy work Reading Comprehension Sentence comprehension and inferencing buildups Integrated vocabulary with decoding of mul=syllabic words Reading strategy work for comprehension monitoring 18

19 Mr. Valenzuela: Winter Student Oral Reading Fluency Maze Comprehension Spelling ESSENCE ANTONIA ESTHER PHILUP LILLIAN JONATHAN MARIA JESSICA SHYDESHIA SADIE KAYLA ONICA TRE RYAN ALEJANDRO JAMES DEVIN 134 Classroom Observations Majority of instruc=onal =me on word study, ﬂuency, and independent work. Limited integra=on of text reading comprehension instruc=on Comprehension instruc=on consists mainly of asking students ques=ons and comple=ng worksheets Explicit vocabulary instruc=on including games/incen=ves throughout the day for using and applying new words Individual students in the class receive mul=ple opportuni=es to read connected text with feedback each day. Targeted instruc=on incorporated for students needing instruc=on in skills the rest of class has mastered 19

20 Instructional Decisions Oral Reading Fluency Reduce =me on ﬂuency instruc=on Maintain connected text reading integrated with comprehension instruc=on Con=nue instruc=on and prac=ce in decoding and spelling of mul=syllabic words Reading Comprehension Increase emphasis on comprehension instruc=on Explicit instruc=on in prac=ces for monitoring and understanding text with modeling and supported prac=ce prior to independent work Increase review on newly taught comprehension prac=ces Explicit instruc=on in independent vocabulary strategies Mr. Valenzuela: Spring Student Oral Reading Fluency Maze Comprehension Spelling JAMES ESSENCE ANTONIA ESTHER PHILUP LILLIAN JONATHAN MARIA JESSICA SHYDESHIA SADIE KAYLA ONICA TRE RYAN ALEJANDRO DEVIN

21 INDIVIDUAL STUDENT DECISIONS When we want improvements and we keep doing the same things and keep geeng the same results who, really, are the slow learners? Dave Montague, Principal Kennewick School District Fielding, Kerr, & Rosier,

22 Individual Student Decisions Need data for speciﬁc students who are below grade level expecta=ons (use screening and progress monitoring assessments) Key areas: In what instruc=onal areas is this student progressing well? In what instruc=onal areas is this student progressing inadequately? Are the instruc=onal changes or interven=on eﬀec=ve? Derek Derek's Writing Correct Word Sequences Weeks 22

23 Amy Amy s Oral Reading Fluency Weeks Instructional Decisions Instruc=onal Components Provide prac=ce reading regular and irregular words mixed prior to text reading Strategies for decoding mul=syllabic words Include ﬂuency prac=ce with modeling of ﬂuent reading Instruc=onal Delivery Decrease group size to increase opportuni=es to prac=ce Break instruc=on into smaller steps and increase pace of instruc=on to increase opportuni=es to prac=ce Goal seeng focused on overall reading (not speed) 23

24 Amy s Oral Reading Fluency Weeks 24

25 Activity Use the class data to: Iden=fy assessment informa=on teachers need to consider to work with the data Iden=fy suppor=ng data that could further inform decision making Iden=fy key areas/concepts you want teachers to consider with these data (how you will model) Iden=fy 3 (or more) ques=ons you would ask teachers when discussing these data Guidelines When using data to measure a school s academic achievement goals, principals should: Model examples on how to use data to make instruc=onal decisions. Ensure that mul=ple sources of data are collected and used to assess student performance (i.e., forma=ve and summa=ve assessments, observa=ons, surveys, and test scores). Engage the en=re staﬀ and other stakeholders in analyzing data to make decisions about future instruc=onal planning, professional development, resource allotment, and curriculum adjustments. Make teachers and other stakeholders accountable to regularly iden=fy the data they use in making an instruc=onal decision or curriculum change. Evaluate the assessment competencies of teachers to accurately use data in their instruc=onal planning and support gaps with eﬀec=ve professional development. 25

26 Additional Resources Middle School MaMers Field Guide (and listed resources) The Research Ins=tute on Student Progress Monitoring's (RIPM) website hmp:// Interven=on Central hmp:// Hamilton et al., 2009 Using student achievement data to support instruc=onal decision making, IES Prac=ce Guide hmp://ies.ed.gov/ncee/wwc/prac=ceguide.aspx?sid=12 Goals Three goals you have around data- based decision making/professional development implementa=on in your school One ac=on for each goal 26

A14 Tier II Readiness, Data-Decision, and Practices

Na#onal PBIS Leadership Forum October 27 & 28, 2016 O www.pbis.org A14 Tier II Readiness, Data-Decision, and Practices Tim Lewis & Barbara Mitchell Key Words: Tier II; PBIS Founda6ons; Training Tier II