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Creating or Improving the Effectiveness of Data Teams. Dan Hyson HVED Data Management Coordinator. Agenda. Introductions Review agenda and objectives Questions to add? What should the data teaming process look like? What data or information should data teams be looking at?
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Creating or Improving the Effectiveness of Data Teams Dan Hyson HVED Data Management Coordinator
Agenda • Introductions • Review agenda and objectives • Questions to add? • What should the data teaming process look like? • What data or information should data teams be looking at? • Who should be involved in data teams? • How can we make time for data teams to meet? • Questions? • Next steps for creating/refining data teams
Objectives • Use summative and benchmark screening overall and strand data to identify whether most of your students are meeting standards and which students may be in need of supplemental instruction • Review technology tools available to view data to accomplish Objective 1 (e.g., AIMSweb, Cognos) • Introduce one model for creating or improving the effectiveness of data teams in your school or district • Plan for followup face-to-face or virtual coaching sessions to sustain effectiveness of data teams
4. What should the data teaming process look like? • Many models, but all some form of Problem Solving Model, at the systems level • Kovaleski offers a useful script with guiding questions for walking through that model during planning meetings at the beginning of the year and other meetings throughout the year
5. What data or information should data teams be looking at? • Should be comprehensive - multiple measures, serving multiple functions • Review primary functions of assessment • Share Bernhardt multiple measures diagram • Some possible sources of data/information • Summative and some diagnostic – Data Book Power Point • Benchmark screening • AIMSweb – Tier Transition report • Cognos – AIMSweb/MAP Proficiency Change Across Norm Periods • Progress monitoring • AIMSweb • Can use other technology tools like Microsoft Excel and Chart Dog to progress monitor on skills not measured by AIMSweb
Primary functions of assessment • Summative • Did students meet standards? (e.g., MCA) • Formative • Benchmark screening • Are all students meeting standards or growing at a rate that will make them more likely to meet standards in the future? If not, which students are not meeting standards or not growing at the necessary rate? (e.g., AIMSweb, NWEA MAP, classroom formative assessments) • Progress monitoring • Are those identified students responding to additional intervention we’re providing? (e.g., AIMSweb, Chart Dog, Microsoft Excel) • Diagnostic • If students are not responding, what specific areas of weakness are getting in the way? (e.g., MCA and NWEA MAP sub-skill strands, classroom formative assessments) 7
6. Who should be involved in data teams? • Multiple possible levels of teams – e.g., district, building, grade/content area • Could be already created team(s), BUT important to clearly refocus team on goals of data teaming • Onsite data coaches critical to making data teaming part of system • Love et al. handout on characteristics and job description of data coaches
7. How can we make time for data teams to meet? • Should at least meet at beginning of year or end of previous year to plan and after each benchmark screening • Preferably more often to examine progress monitoring data to see how at-risk students responding to supplemental instruction • See Resources slide at end for links to 2 documents with ideas for making time • BUT highly recommend that you form a staff team in your building to brainstorm options that will work in YOUR school, present them to the rest of the staff
9. Next steps for creating/refining data teams • What do you think you need to do next to create or refine the use of data teams within YOUR building? • What can I do or what can we do as a group to help?
Resources Kovaleski, J.F., Roble, M., & Agne, M. (2008). The RTI Data Analysis Teaming Process. Retrieved February 15, 2012 from http://www.hved.org/documents/DataManagement/RTI-Action-Network-Data-Analysis-Teaming-Process.htm. Love, N., Stiles, K.E., Mundry, S., & DiRanna, K. (2008). The data coach’s guide to improving learning for all students. Thousand Oaks, CA: Corwin Press. Making time for collaboration handout from allthingsplc.info – http://www.allthingsplc.info/pdf/articles/MakingTimeforCollaboration.pdf MDE secondary level scheduling Power Point - http://www.hved.org/documents/DataManagement/MDE-Middle-and-High-School-Intervention-Scheduling-Power-Point.ppt