Introductions. 2015: Measuring, Monitoring, and Managing What Matters: Part 2 Gathering, Organizing, and Using Data

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Utah State University Introductions Sarah Brasiel 18 year as a middle and high school teacher (math,

1 2015: Measuring, Monitoring, and Managing What Matters: Part 2 Gathering, Organizing, and Using Data Sarah Brasiel, Ph.D. Utah State University Introductions Sarah Brasiel 18 year as a middle and high school teacher (math, science, reading, special educadon) in CA and TX Utah State University Department of InstrucDonal Technology and Learning Science Researcher/Evaluator TwiPer: SarahBrasiel1 LinkedIn 1

2 Reflection and Discussion What kinds of data do teachers have access to? What kinds of data do leaders have access to that teachers do not have access to? What kind of data do you use currently? Why do some students in your school fail or have low achievement? What types of supports or opportuni1es do you provide to engage those students? Complete Handout SecDon WHAT DATA DID YOU BRING TODAY? OR HAVE ACCESS TO? 2

3 Objectives Understand data available to make data- driven decisions Determine root causes of poor performance and potendal solu1ons Develop a common language around indicators Use lagging/leading indicator data, determine students in high and medium need Triangulate data from mul1ple indicators Determine which high and medium need students are not currently receiving support Select students to target and determine measureable goals Develop a data collec1on/review plan Set measurable goals for the grade level Determine appropriate incen1ves for students/classes who reach the goal(s) Performance Management Building the capacity of educators at all levels to use data to priori5ze ac5vi5es that advance core goals, measure progress towards mee5ng those goals, and make informed decisions regarding the best ways of improving student achievement. Looking systemically at how all the components of the educa5on system work together to support student learning is the primary goal of this new management approach. 3

4 Principle 3 - Engaging Teachers in Performance Management Principle 3: Guide and support teachers in the use of data to meet the needs of students and to support them in reaching their goals Prac5ce 1: Provide targeted professional development and ongoing data support Prac5ce 2: Designate a school- based facilitator who meets with teachers to discuss data. Prac5ce 3: Dedicate structured 5me for staﬀ collabora5on. Prac5ce 4: Organize and prepare a variety of data about students and student learning. Prac5ce 5: Interpret data and develop theories about how to improve learning. Prac5ce 6: Modify instruc5on to test theories and increase student learning. Principle 3 Practice 1 Prac5ce 1: Provide targeted professional development and ongoing data support What structures are in place for PD Dme? Who currently provides teachers with data support? Discuss with your group 4

5 Recommendations Provide support for an eﬀecdve work group by se]ng clear expecta1ons and goals for the work. Focus on school- based data that relates to teachers and their classes to make the ac1vi1es more authen1c. Devote professional development Dme to working with each teacher s classroom data. Provide a forum for sharing ideas about using data to improve instrucdon among teachers, such a data teams. What Current Practices for PD around Data are in your School? On demand PD (online learning) Face to Face PD Team MeeDngs What is working? What are the challenges? Discuss with your Group 5

6 Leveraging Assets Grade level planning meedngs Department planning meedngs PosiDve school climate and culture Teachers focused on engaging and teaching all students Support for students (e.g., intervendon teachers) Principle 3 Practice 2 Prac5ce 2: Designate a school- based facilitator who meets with teachers to discuss data. 6

7 Role of a Data Facilitator Increase capacity of teachers to use data to idendfy student needs and develop appropriate acdon plans Schedule or organize monthly mee1ngs with teachers to discuss student performance data, idendfy trends, and consider appropriate responses. Model how to use data to gauge progress towards learning goals and drive instrucdonal decisions Support teachers undl they feel more conﬁdent in their own abilides as they develop a beper appreciadon of the value of using data to manage student performance. What About Your School? Do you have a data facilitator at your school? Yes How were they selected? How can you determine if they are eﬀecdve? No Who at your school might be able to have this role? Why? What are the constraints? Discuss with your Group 7

8 Principle 3 Practice 3 Prac5ce 3: Dedicate structured 5me for staﬀ collabora5on. Quality Time Structured meedngs where teachers and facilitators come prepared with data Suﬃcient 1me to think about teaching and learning, and then test their theories with the data End with pracdcal data- based ac1on steps they can take into the classroom Monitored by school leaders so that teachers not only talk about data, but also change their prac1ces 8

9 Ask Important Questions Boston s McCormack Middle School decided to ask the quesdon: Are par'cular middle school math teachers especially eﬀec've at teaching certain topics? Some teachers 8th grade students outperformed the state average on a subset of quesdons Teachers shared their speciﬁc strategies for teaching the topics related to these quesdons Principle 3 Practice 4 Prac5ce 4: Organize and prepare a variety of data about students and student learning. 9

10 WHAT ASSETS CAN YOU LEVERAGE? Dimensions of Data Available 10

11 Beginning with the End in Mind What are the instruc1onal ques1ons you would like data to answer? What types of professional learning do you need to support your eﬀecdve use of the data to strengthen your instrucdonal pracdces? Which instruc1onal prac1ces will the data enable you to strengthen? Complete Handout SecDon REVIEW OF LEADING AND LAGGING INDICATORS 11

12 Leading and Lagging Indicators Lagging What are some examples of data you have that would be lagging indicators? Leading What are some examples of data you have that would be leading indicators? WHAT DATA DID YOU BRING TODAY THAT WOULD BE CONSIDERED LEADING DATA? LAGGING DATA? COMPLETE HANDOUT 12

13 Reviewing Student Data for Lagging Indicators Review all data available for students in your grade level that are considered lagging data (e.g., prior year assessment) For each data source, determine the benchmark Color high need student scores in red Color medium need student scores in yellow Color low need student scores in green Compare the scores (colors) across data source to determine paperns in strength/weakness Consider the change in performance since the last assessment Complete with Data Brought to Session Reviewing Student Data for Leading Indicators Add data on absences (average per week) Can consider period level absences Color high need students red (2+ absences per week) Color medium need students yellow (1 absence/week) Color low need students in green Add data on course grades (consider benchmarks and color coding) Add data on behavior (consider benchmarks and color coding Complete with Data Brought to Session 13

14 Triangulating Data from Multiple Indicators Analysis by Gender Analysis by Race/Ethnicity Analysis by Class Period Discuss what you no1ce/wonder with your Group Complete Handout Determining who is in need of additional support Determine supports each student is already receiving Document what you know about the whole student Set a measurable goal for medium/high need students Create an interven1on or strategy to meet their needs Determine plan for progress monitoring Determine how you will know the students are progressing Discuss with your Group 14

15 Principle 3 Practice 5 Prac5ce 5: Interpret data and develop theories about how to improve learning. Root Causes of Poor Performance Lack of self- eﬃcacy or beliefs in ability Lack of mo1va1on (no real goal) Mismatch between the goals of students and the goals of educators Unrealis1c messages Diﬀerent priori1es Skill gaps Lack of padence and persistence 15

16 Principle 3 Practice 6 Prac5ce 6: Modify instruc5on to test theories and increase student learning. Possible Solutions Become a coach and your student s #1 cheerleader Use data tell you how to set up the class or design your instrucdon (e.g., videos from the last game in sports) Reframe the goal to be more measureable and achievable (standards, skills, checklist- not grades) Reframe tests as skills assessments Plan for opportuni1es to show mastery of skills (e.g., retake tests, test correcdons) Make hearvelt connec1ons with the students 16

17 ACTION PLAN Complete Handout Targeting Medium to High Need Students Currently not supported by IntervenDon or ESOL teacher 5 students per teacher/administrator Make a folder with chart to have discussions with students Goal Baseline Measurement Diﬀerence Goal Met? Next Steps 17

18 Setting Goals for Your Grade Level Measureable CelebraDng Individual and Class Success Long Term Goals Student data folders Personalized learning so(ware with real Dme data for teachers Parent involvement in tracking student data Changes in the Classroom Look at ways to integrate low scoring content areas throughout the year. Spend less Dme on content areas where students score well. Create student learning groups based on student- level data. Individualize assignments based on student- level data. Use data to create peer tutoring pairs (comprised of a low- and high- performing student in an area) 18

19 Data Management Systems Principle 5: Ensure that school- level and student data needs are incorporated into districtwide data management system planning and implementa1on. 19

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