Data Use Professional Development Series 301 Day 6

The contents of this slideshow were developed under a Race to the Top grant from the U.S. Department of Education. However, those contents do not necessarily represent the policy of the U.S. Department of Education, and you should not assume endorsement by the Federal Government. Rhode Island educators have permission to reproduce and share the material herein, in whole or in part, with other Rhode Island educators for educational and non-commercial purposes. © 2013 the Rhode Island Department of Education and Wireless Generation, Inc. 2

Welcome back! 3

Days 6, 7, and 8 Day 4 Data Conversations Inference Validation Data Analysis Questions Correlation/Causation Triangulation/Intersection Analysis Implementation Planning Adaptive Work and Collaborative Structures Data Conversations with parents Today Welcome/Overview Implementation Progress Data and Small Group Differentiation Assessment Literacy BREAK Aggregate Data and Sub- populations Intersection Analysis LUNCH Action Research Techniques for Data Conversations: Paraphrasing BREAK Data Conversations with Students Implementation Planning Wrap Up/Evaluations Day 7: On-Site Visit Agenda to be determined with your coach Day 8: Partial list of topics Expanded Assessment Literacy Revisit Data Inventory Action Research Continued Vertical Articulation 4

Data Use 301 Day 6 Agenda Welcome/Overview Implementation Progress Data and Small Group Differentiation Assessment Literacy BREAK Aggregate Data and Sub-populations Intersection Analysis LUNCH Action Research Techniques for Data Conversations: Paraphrasing BREAK Data Conversations with Students Implementation Planning Wrap Up/Evaluations 5

Objectives By the end of Day 6, SDLTs will be able to: Identify impacts of their data use implementation. Evaluate assessment items and create checks for understanding based on alignment to standards and Depth of Knowledge. Engage in Data Conversations with students. Articulate a plan for beginning an Action Research project. Articulate a plan for ongoing data use implementation. 6

Implementation Progress What impacts have you seen on teachers’ core instructional practices? What impacts have you seen on school culture? What role did our on-site visit play in advancing the work with teachers?

Integrating Initiatives How has connecting initiatives been going? How has using data impacted other initiatives? How have other initiatives impacted what you want to learn here? 8

Cycle of Inquiry 9

Data and Small Group Differentiation Types of flexible small groups: Short Term Long Term Spontaneous 10

Data and Small Group Differentiation 11

EXCEED RTI 12

Assessment Literacy Evaluating Assessments Creating Assessments 13

Assessment Literacy Summative: Assessment OF learning Formative: Assessment FOR learning Interim: Assessment OF or FOR learning 14

Assessment Literacy Dimensions of Formative Assessment: Clearly articulated learning progressions Identified learning goals and success criteria Descriptive feedback Self and peer assessment Collaboration 15

Assessment Literacy 16

Summary Impacts of the work look different at different schools. Differentiating for small groups of students can mean flexibly adjusting core instruction for clusters of students within a Cycle of Inquiry. It is important for educators to plan how they will assess student learning while creating their Instructional Action Plan. 17

BREAK 18

Evaluating Assessments Alignment to Standards Cognitive Complexity Data to inform instruction 19

Evaluating Assessment Items RL.6.2 Key Ideas and Details: Determine a theme or central idea of a text and how it is conveyed through particular details; provide a summary of the text distinct from personal opinions or judgments. ItemSkill/concept measuredDOKPart/All of standard? What are the themes of Little Women? Determine a theme or central idea of a text. 2Part Write a brief plot summary of Little Women, explaining the themes revealed throughout the text using specific examples from the text. Determine a theme or central idea of a text and how it is conveyed through particular details; provide a summary of the text. 3All 20

Evaluating Assessment Items Cognitive Complexity: Webb’s Depth of Knowledge Level 1: Recall identify, state, list, define, recognize, use, measure Level 2: Skill/Concept classify, organize, estimate, compare, infer, summarize Level 3: Strategic Thinking generalize, draw a conclusion, support, hypothesize, investigate Level 4: Extended Thinking make connections, synthesize, prove, analyze, design and carry out the project 21

Describe one cause of the War of Describe the similarities between the War of 1812 and the American Civil War. Describe the impact that the War of 1812 and the American Civil War have had on modern day America. Evaluating Assessment Items Cognitive Complexity 22

Creating an Effective Check for Understanding Measure only one standard, or one aspect of a standard. Determine the type of item that will be used. Keep in mind the format of the item. Design a question that helps diagnose common misperceptions on the topic. Use varying levels of cognitive complexity (DOK). Be aware of time constraints. Encourage student effort. 23

Creating Checks for Understanding 24

Cycle of Inquiry 25

Implementation Planning 26

Aggregate Data What is it? “Student performance data reported at the largest, aggregate- group level, such as by grade level and content area for a school, district, or state.” (p. 146) Why is it important? “It paints a broad brush picture of student achievement overall” and helps us “understand how students in their school perform in comparison to students in similar schools.”(p. 146) Love, N., Stiles, K.E., Mundry, S., & DiRanna, K. (2008). The Data Coach’s Guide to Improving Learning for All Students, 27

Overarching Questions When Examining Aggregate Data Do aggregated groups of students meet or exceed district or state performance levels? -Pockets of success or need within student body Are we able to discern trends over time that would have implications rooted in student learning? -Analyze effectiveness of instruction, curriculum, and resources horizontally and vertically Love, N., Stiles, K.E., Mundry, S., & DiRanna, K. (2008). The Data Coach’s Guide to Improving Learning for All Students Aggregate Data 28

Mathematics – Grade 4 Average Scale Scores White Black Gap NAEP Proficient: 249 Aggregate Data and Sub-Populations 29

Triangulation and Intersection Analysis Triangulation is “analyzing other data to illuminate, confirm, or dispute what you learned through your initial analysis – you will be able to identify your problem with more accuracy and specificity.” Boudett, K. P., City, E. A., Murnane, R. J. (2007) Data Wise: A Step-by-Step Guide to Using Assessment Results to Improve Teaching and Learning. Intersection Analysis is investigating the different dimensions of data to “look more closely and understand each piece of information we gather about a school.” Bernhardt, V. L. (2004). Data Analysis for Continuous School Improvement. Larchmont, NY: Eye on Education 30

Intersection Analysis Demographic Attendance, grade level, ethnicity, gender, etc. Student Learning Standardized test results, GPA, curriculum assessments Perception Surveys, questionnaires, observations “People act in congruence with what they believe, perceive, or think about different topics.” (Bernhardt, 23) School Process Data that describe instructional practices, strategies, programs, scheduling Bernhardt, V. L. (2004). Data Analysis for Continuous School Improvement 31

Two-way Intersections IntersectionsCan Tell Us Demographics by Student Learning If subgroups of students perform differently on student learning measures Demographics by PerceptionIf subgroups of students are experiencing school differently Demographics by School Processes If all students are represented in the different programs offered by the school Student Learning by School Processes If different programs are achieving similar student learning results Student Learning by Perceptions If student perceptions of the learning environment have an impact on their results Perceptions by School Processes If people are perceiving programs and processes differently 32

IntersectionsCan Tell Us Demographics by Student Learning by Perceptions The impact of demographic factors and attitudes about the learning on student learning Demographics by Student Learning by School Processes The impact of specific programs on different subgroups of students, as measured by subgroup learning results Demographics by Perceptions by School Processes What programs different students like best, or the impact of different programs on student attitudes Student Learning by School Processes by Perceptions The relationship between the processes students prefer and learning results Three-way Intersections 33

Four-way Intersections IntersectionsCan Tell Us Demographics by Student Learning by Perceptions by School Processes What processes or programs have the greatest impact on different subgroups of students’ learning, according to student perceptions, and as measured by student learning results 34

For each intersection: Generate a question that targets the heart of each intersection. Determine what data we would need to answer these questions. Be ready to share your table’s best data question. Using Questions to Drive Intersection Analysis 35

Summary When evaluating and creating assessment items or checks for understanding, two criteria to use are standards alignment and Depth of Knowledge. It is important to be prepared for conversations about sub-groups when disaggregating large data sets. Intersection Analysis is useful when examining large aggregate data sets. 36

LUNCH 37

Action Research and Expanding Cycles of Inquiry 38

Action Research Practitioner Researcher Cycle of Inquiry Broad area of focus Commitment to documenting progress 39

Rhode Island Growth Model 40

Implementation Planning 41

Summary Engaging in Action Research is a way to examine broad areas of focus that are important to our school. Planning an Action Research project for my school will allow me to examine school-wide issues closely and in a structured way. 42

BREAK 43

Techniques for Data Conversations Positive Presumptions Paraphrasing 44

Principles of Paraphrasing Attend fully Listen with the intention to understand Capture the essence of the message Reflect the essence of voice, tone, and gestures Paraphrase BEFORE asking a question Use the pronoun “you” instead of “I” Center for Cognitive Coaching,

Data Conversations with Students 46

Data Conversations with Students You and Ms. Jackson both teach Antonio. The student is well behaved and is performing well in Ms. Jackson’s class. In your class, Antonio has become disruptive and his performance on weekly quizzes has declined over the last month. How would you plan for your Data Conversation with Antonio? What questions would you ask? 47

Finding Solutions Is the soccer team getting in the way of your school work?versus Gathering Information Did you forget to do your homework again? versus Guiding Improvement Are you going to be ready for the test Friday? versus Presuming Positive Intent 48

Student Data Conversations Role Plays Choose a role play card Plan your Data Conversation: – What is your goal for the conversation? – How will you begin? Ask questions using Positive Presumptions – Open ended questions to promote thinking and reflection Paraphrase as you go 49

Planning for Student Data Conversations Think about Data Conversations that teachers currently have with students. How could these conversations be structured to incorporate more data? How could questioning techniques such as using positive presumptions and open ended questions, and paraphrasing be incorporated more often? 50

Day 8 Some of the topics to be covered Day 8: Expanded Assessment Literacy Revisit Data Inventory Action Research continued Vertical Articulation Rhode Island Growth Model continued 51

Wrap Up 52