1. Assessment and Design Strategies for Improving Student Learning: Utilizing Data with Technology Tools for Instructional Decisions University of Maryland Educational Technology Outreach Director: Davina Pruitt-Mentle EDUC 476/698V

2. Session 1 Assessment and Data CourseCOE ETO UMCP copyright 2004 2 Outcomes Understand the tie between data (school/district and classroom) and standards (and instructional design) Understand where and how to locate MSDE/school data and content standards Understand how to interpret and analyze data from mock case studies Become familiar with technology tools, like Excel and the vast features within the application Making instructional designs based on data analysis Apply new knowledge gained to your own classroom data

3. Session 1 Assessment and Data CourseCOE ETO UMCP copyright 2004 3 Graphical Overviews See Handouts

4. Session 1 Assessment and Data CourseCOE ETO UMCP copyright 2004 4 Raw Data Math FocusReading Focus Instructional Decisions are Guided by the Overall Mission

5. Session 1 Assessment and Data CourseCOE ETO UMCP copyright 2004 5 Decisions Guided by…. MSA Data http://www.mdk12.org/data/ msa_analyzing/index.asp http://www.mdk12.org/data/ msa_analyzing/index.asp Voluntary State Curriculum (VST) http://www.mdk12.or g/instruction/index.html http://www.mdk12.or g/instruction/index.html

6. Session 1 Assessment and Data CourseCOE ETO UMCP copyright 2004 6 Standards/Mission Overall Mission is a driver for all educational communities –K-12 (MD) http://www.msp.msde.state.md.us/http://www.msp.msde.state.md.us/ –UMCP http://www.oirp.umd.edu/WOCN/index.cfmhttp://www.oirp.umd.edu/WOCN/index.cfm –UMCP COE http://www.education.umd.edu/collegeinfo/ and http://www.edtechoutreach.umd.edu/http://www.education.umd.edu/collegeinfo/ http://www.edtechoutreach.umd.edu/ –UMCP Life Sciences http://www.life.umd.edu/college/StrategicPlanForWeb.pdf and http://www.life.umd.edu/college/initiatives.html#undergraduat e http://www.life.umd.edu/college/StrategicPlanForWeb.pdf http://www.life.umd.edu/college/initiatives.html#undergraduat e –Association of American Universities Data Exchange (AAUDE) http://www.pb.uillinois.edu/aaude/http://www.pb.uillinois.edu/aaude/ –Association of American Universities http://www.aau.edu/ http://www.aau.edu/

7. Session 1 Assessment and Data CourseCOE ETO UMCP copyright 2004 7 Instructional Management System Main Site http://www.mcps.k12.md. us/IMS/ http://www.mcps.k12.md. us/IMS/ User Request Form http://www.mcps.k12.md. us/IMS/IMSRequest2.pdf http://www.mcps.k12.md. us/IMS/IMSRequest2.pdf By default – each teacher has an account to see their students only (no request needed) LSS are also testing out IMS-only a few can afford them

8. Session 1 Assessment and Data CourseCOE ETO UMCP copyright 2004 8 Data Warehouse: MCPS example Data Warehouse http://www.mcps.k12.md.us/dep artments/technology/datawareh ouse.shtm http://www.mcps.k12.md.us/dep artments/technology/datawareh ouse.shtm Limited to central office staff and school administrators Many LSS are testing out online data warehouses

9. Session 1 Assessment and Data CourseCOE ETO UMCP copyright 2004 9 Why Excel? For those who do not have data warehouses Those who do have a data warehouse, but want to analyze outside the “standard” format –can download data entered in database into Excel –many collect in Excel and then have a central person enter into data warehouse

10. Session 1 Assessment and Data CourseCOE ETO UMCP copyright 2004 10 Templates MSDE http://mdk12.org/data/progress/developin g/m4w2/pr2/index.html http://mdk12.org/data/progress/developin g/m4w2/pr2/index.html UMCP COE http://www.edtechoutreach.umd.edu/stan dards.html http://www.edtechoutreach.umd.edu/stan dards.html

11. Session 1 Assessment and Data CourseCOE ETO UMCP copyright 2004 11 Identifying Desired Results  Scavenger Hunt  Data  Curriculum and Standards  Data  Looking at the Bigger Picture  State Needs University Needs  LSS College Needs  School Unit/Dept. Needs  Interpretation and analysis  Case Studies (LP elem school)  Collecting (tech group) Excel –Downloading and using templates –Analysis College High Elem. –Tools Basics Lookup Conditional Formatting Filters Graphs/Charts SD/Variance

12. Session 1 Assessment and Data CourseCOE ETO UMCP copyright 2004 12 Identifying Desired Results Different ways to look at and analyze data Easier with technology tools and procedures Consensus on interpretations Connect instructional decisions/changes based on interpretation

13. Session 1 Assessment and Data CourseCOE ETO UMCP copyright 2004 13 Instructional Choices Learning Styles Instructional Styles Background Info on target group/s Differentiated Instruction vs. Individualized Instruction

14. Session 1 Assessment and Data CourseCOE ETO UMCP copyright 2004 14 Instructional Choices 8.4/9.4 (apple unit); 8.3/9.3 (your own scenario of differentiated instruction); 10.1 (chemistry consultant); each of the case studies w/Excel (elem/high/college)

15. Session 1 Assessment and Data CourseCOE ETO UMCP copyright 2004 15 8.4/9.4 Apple Unit See Handouts

16. Session 1 Assessment and Data CourseCOE ETO UMCP copyright 2004 16 8.3/9.3 Scenario Various scenarios were used throughout this weeks readings sharing visions and examples of what differentiated instruction is (and in some cases is not). Come up with your own scenario that would illustrate an example of what differentiated instruction is. Continue to check back to see what others have posted and share your option as to if you feel their example is/is not "differentiated instruction"-and support your opinion.

17. Session 1 Assessment and Data CourseCOE ETO UMCP copyright 2004 17 10.1 Chemistry High School 10.1 4.2 Some results