1. Developing Teachers’ Understanding of Statistics Tim Jacobbe University of Florida jacobbe@coe.ufl.edu DRL-1118168

2. Overview of Today’s Session Overview of the LOCUS Assessments Teachers’ Performance on LOCUS Some Materials for Teacher Development

3. LOCUS Assessment Project Principal Investigator: Tim Jacobbe, University of Florida Co-Principal Investigators –Bob delMas, University of Minnesota –Jeff Haberstroh, Educational Testing Service (ETS) –Brad Hartlaub, Kenyon College External Evaluator: Jim Hammerman, TERC Research Fellows: Catherine Case, Steven Foti, Douglas Whitaker, University of Florida

4. An Amazing Team Advisory Board: David Miller, Dick Scheaffer, Mike Shaughnessy, Jane Watson Beginning/Intermediate Items (Grades 6-9): Chris Franklin, Brad Hartlaub, Gary Kader, Mary Lindquist, and Jerry Moreno Intermediate/Advanced Items (Grades 10- 12): Bob delMas, Roxy Peck, Mike Perry, and Josh Tabor

5. LOCUS: Three Broad Goals Develop instruments to assess levels of statistical understanding as initially defined in the CCSS and the Guidelines for Assessment & Instruction in Statistics Education (GAISE) framework (Change the way statistics is assessed) Provide a characterization of the level of understanding of statistical topics Provide a tool for researchers and teachers to assess growth in statistical understanding

6. Evidence-Centered Design: 5 Layers Domain Analysis: GAISE, CCSS, learning trajectories from statistics education research Domain Modeling: Advisory Board provide feedback on mapping of CCSS and GAISE Conceptual Assessment Framework: Evidence Model derived from domain analysis Assessment Implementation: Develop and pilot assessment tasks Assessment Delivery: Final forms of assessments & dissemination of results

7. Design of Experiments Final Evidence Model LEVELDESCRIPTION EVIDENCE STATEMENTWORK PRODUCTS A.2.3Students understand how to conduct simple experiments with assignment of treatments. Students demonstrate the understanding that an experiment can be designed to measure the effect of treatments … … Students should be able to identify the experimental units, treatment groups, response variable and other variables. B.2.2Students understand how to design and conduct comparative experiments and begin to use random assignment. Students … demonstrate correct methods for…comparison of treatments. Students randomly assign treatments to experimental units. … Students should understand that causal claims may be possible if experiments are conducted with random assignment. C.2.2Students understand what constitutes good practice in conducting an experiment. Students identify, discuss, and explain best statistical practice … identification of the statistical question; variables; and the random assignment of treatments to the experimental units. … students design or critique an experimental design. Aspects of statistical design are included in the study … to allow for the possibility of making causal conclusions about differences between groups.

8. Three Levels from GAISE Framework Ideally (Franklin & Mewborn, 2006) –A: Elementary school grades –B: Middle school grades –C: High school Two levels of Assessment: –Beginning and Intermediate (Levels A and B) –Intermediate and Advanced (Levels B and C)

9. Approximate Emphasis on Practice and Process Components of Statistical Problem Solving Process ComponentBeginning/IntermediateIntermediate/Advanced Formulating Questions10-15%15-20% Collecting Data25-30%20-25% Analyzing Data30-35%25-30% Interpreting Data25-30%30-35%

10. Teachers’ Performance Process Component Preservice Teachers (n=268) Inservice Teachers (n=493) Formulating Questions84%88% Collecting Data70%76% Analyzing Data66%69% Interpreting Data64%71% Overall69%74%

11. Teachers’ vs. Students’ Performance Process Component Preservice Teachers (n=268) Inservice Teachers (n=493) AP Statistcs (n=936) Formulating Questions 84%88%78% Collecting Data70%76%67% Analyzing Data66%69%61% Interpreting Data64%71%56% Overall69%74%63%

12. Teachers’ vs. Students’ Performance Process Component Preservice Teachers (n=268) Inservice Teachers (n=493) AP Statistcs (n=936) Grade 6-12 Students* (n=3,430) Formulating Questions 84%88%78%62% Collecting Data 70%76%67%46% Analyzing Data 66%69%61%39% Interpreting Data 64%71%56%52% Overall69%74%63%49%

13. Formulate Questions

14. Collect Data

15. Analyze Data

16. Interpret Data

17. What Should We Do? Teacher performance is encouraging considering there has been limited training LOCUS Measures Statistical Understanding Expected of STUDENTS in grades 6-12

18. ASA’s Statistics Education of Teachers

19. ASA and NCTM K-12 Resources

20. ASA K-12 Resources

21. Some Ongoing Projects NSF-Funded CAREER: Investigating Middle and Secondary Mathematics Teachers” Transformative Learning of Statistics within Professional Development (PI: Sue Peters, University of Louisville) MOOC-Ed Teaching Statistics Through Data Investigations http://mooc-ed.org/tsdi (PI: Hollylynne S. Lee)http://mooc-ed.org/tsdi Project-SET: Statistics Education for Teachers (PI: Anna Bargagliotti)

22. https://locus.statisticseducation.org

23. Register for an Account

24. Next Step for LOCUS Website aimed at professional development of teachers –Commentaries –Sample items –Evidence Model Continue to influence statistics items on high-stakes assessments

25. Thank You for Participating (or Watching) Tim Jacobbe, jacobbe@coe.ufl.edu DRL-1118168