1. Data for Student Success Sustaining a Culture of Quality Data May 5-6 Ann Arbor, Michigan “It is about focusing on building a culture of quality data through professional development and web based dynamic inquiries for school improvement.”

2. Beyond Achievement Data Kris Jenkins, MA CTE Director, CISD Tony Warren, MA, Education Consultant, CISD

3. Pre-Test Using Data for Results Trish Hatch Ph.D. Pre-Test President, CEO of Hatching Results, LLC

4. 1. Standardized test data 1.achievement data 2.achievement related data 3.process data 4.perception data 5

5. 2. Completion with a “C” or better of College Prep Course Requirements 1.achievement data 2.achievement related data 3.perception data 4.process data 5

6. 3. Discipline referrals 1.achievement data 2.perception data 3.achievement related data 5

7. 4. Grade point average 1.achievement data 2.process data 3.achievement related data 5

8. 5. Suspension Rate 1.perception data 2.achievement data 3.achievement related data 5

9. 6. Number of students received individual tutorial assistant 1.achievement data 2.process data 3.perception data 4.results data 5.achievement related data 5

10. 7. Attendance rate 1.achievement data 2.process data 3.achievement related data 5

11. 1.Process 2.Perception 3.Results 8. “What others think, know or demonstrate” as a result of instruction is considered what kind of data? 5

12. 9. “What you did for whom” or evidence that the event occurred is considered what kind of data? 1.Process 2.Perception 3.Results 5

13. 1.Process 2.Perception 3.Results 10. What type of data provides proof your program has impacted students’ ability ? 5

14. 11. I am excited about using data to effect change 1.Strongly agree 2.Agree 3.Neutral 4.Disagree 5.Strongly Disagree 5

15. 12. My understanding of achievement related data 1.Extremely high 2.High 3.Neutral 4.Low 5.Extremely low 5

16. The Data Wheel RESULT Data Perception Data Process Data

17. Process Data ( Evidence that an event occurred ) –What did you do and for whom? –Who, what, when, where, and how long information Ex. – All 6 th through 8 th grade students received violence prevention lessons in their fall semester. Ex. – All 9 th grade students took the Explore test. Policies and procedures and systems we have in place that define how we do business

18. Why is Perception Data Important? “ Perception data helps us understand what students, parents, teachers, and others think about the learning environment.” “Perceptions are important since people act based on what they believe. It’s important to know how students, teachers, parents and community think about school, what relations have been like in the past, and what expectations they have for the future.”

19. Importance of Perception Data NCLB’s requirement for broader collection of information on individual student performance includes not only outcomes, but also behaviors and perceptions which correlate with student achievement. Perception data can identify intervening variables which need improvement to positively impact student achievement and will contribute to the reporting requirements outlined in NCLB’s Safe Schools provisions.

20. CTE Survey Example of Perception Data

21. Results Data –Achievement Data State Test data, SAT/ACT, GPA, Drop-out Rates, College acceptance rates etc. We have been focusing on the same data, doing the same thing, getting the same results – now we need to look at other data and do other things to get different results.

22. Before the Autopsy...make a difference in your classroom today! SAT/ ACT & GPA Graduation Rates Course enrollment patternsDiscipline referrals Suspension rates Attendance rates Parent participation Homework completion rates extra-curricular activities

23. What is Achievement Related Data ?

24. Achievement-related data measures those fields that literature has shown to be correlated to academic achievement. These data fields include: Course enrollment patterns Discipline referrals Suspension rates Alcohol, tobacco and other drug violations Attendance rates Parent or guardian participation Homework completion rates Participation in extra-curricular activities Physical, mental, social health

25. Mathematics Course Taking Patterns Total number of students: 900 Total number of 9 th graders: 225 06/0707/08 Percent of student body

26. Achievement Related

27. New routes open when one type of data crosses another” Victoria L. Bernhardt Journal of Staff Development, Winter 2000 (Vol. 21, No. 1) “It is not until we intersect all four measures, at the school level and over time, that we are able to answer questions that will predict if the actions, processes, and programs that we are establishing will meet the needs of all students.”

28. Jigsaw Activity Objective The objective of this activity is to deepen your understanding of different types of data and how analyzing different types of data impact each other.

29. Jigsaw Activity Intersections Article by Victoria Bernhardt

30. Data Analysis Activity Objective The objective of this activity is to look at achievement related data and begin to actually use the data and analyze it. Focus questions in your notebook will assist you in organizing this data.

31. Activity Middle School Data Profile Answer Focus questions? What can you tell about this school, based on Achievement Related Data?

32. Break 15 minute break

33. Achievement Related Data How do you begin to organize achievement related data in your school? Think of achievement related data in your school. Draw a picture, analogy or diagram of how achievement related data is utilized in your school.

34. Mental Models Mental models can be a story, an analogy or a two dimensional picture. Mental models are deeply held internal images of how we see our work. Very often we are not consciously aware of our mental models or the effects they have on our behavior. Mental models are powerful, because they determine what we pay attention to, and therefore what we do.

35. Mental Models Show Example

36. Video of Mental Model Terie Dreussi Smith - mental model of teacher and classroom mov.mpg

37. Mental Model Activity Objective The objective of this activity is to organize the achievement related data in your school. Connect that achievement related data to a mental model about how you use the data in your school. Present your mental model to the group explaining your different achievement related data and giving a short background of your school.

38. Mental Models Work on your mental model of achievement related data in your school.

39. Achievement-related data measures those fields that literature has shown to be correlated to academic achievement. These data fields include: Course enrollment patterns Discipline referrals Suspension rates Alcohol, tobacco and other drug violations Attendance rates Parent or guardian participation Homework completion rates Participation in extra-curricular activities Physical, mental, social health

40. Mental Model Introduce your self and explain your professional role in your district. Share your mental model with your table group

41. Beyond Achievement Data Educational and psychological research has identified several factors that contribute to students’ ability to achieve and that directly impact student achievement data. –See bibliography for resources.

42. Bibliography Course enrollment patters. Students who take more rigorous course work do better on standardized test (e.g., Smith & Niemi, 2001). Discipline referrals. Students who behave better achieve better achieve better (e.g., Van Horn, 2003). Suspension rates. Student who are suspended are less likely to be high academic achievers (e.g., Williams & McGee, 1994). Alcohol, tobacco, and other drug use. Students who use drugs or alcohol perform at a lower rate academically than those who do not(e.g.,Jeynes, 2002). Attendance rates. Students who attend school perform better than those who do not (e.g., easton & engelhard, 1982). Parent involvement Students whose parents are involved in meaningful ways in the school outperform those whose parents are not (e.g., Merchant, Paulson, & Rothlisberg, 2001). Extracurricular activities. Students who feel connected to school participate in extracurricular activities and perform better than those who do not (e.g., Mahoney, Cairns, & Farmer, 2003. Homework completion rates. Students who complete and turn in homework do better in school (e.g., Cooper, Lindsay, Nye, & Greathouse, 1998).

43. Achievement Related Data Action Plan Template Activity Objectives The objective of this activity is to give you a tool to go back to your school with a plan on how you will attack achievement related data. The who, when, where, why of achievement related data will be answered, specific to your school.

44. Achievement related data What is your data source Who is on your data team Analyzing the data Student Input Define Problem What is your intervention What is your timeline How do you know you have achieved results Achievement Related Data Action Plan

45. 1. Standardized test data 1.achievement data 2.achievement related data 3.process data 4.perception data 5

46. 2. Completion with a “C” or better of College Prep Course Requirements 1.achievement data 2.achievement related data 3.perception data 4.process data 5

47. 3. Discipline referrals 1.achievement data 2.perception data 3.achievement related data 5

48. 4. Grade point average 1.achievement data 2.process data 3.achievement related data 5

49. 5. Suspension rate 1.perception data 2.achievement data 3.achievement related data 5

50. 6. Number of students received individual tutorial assistant 1.achievement data 2.process data 3.perception data 4.results data 5.achievement related data 5

51. 7. Attendance rate 1.achievement data 2.process data 3.achievement related data 5

52. 1.Process 2.Perception 3.Results 8. “What others think, know or demonstrate” as a result of instruction is considered what kind of data? 5

53. 9. “What you did for whom” or evidence that the event occurred is considered what kind of data? 1.Process 2.Perception 3.Results 5

54. 1.Process 2.Perception 3.Results 10. What type of data provides proof your program has impacted students’ ability ? 5

55. 11. I am excited about using data to effect change 1.Strongly agree 2.Agree 3.Neutral 4.Disagree 5.Strongly Disagree 5

56. 12. My understanding of achievement related data 1.Extremely high 2.High 3.Neutral 4.Low 5.Extremely low 5

57. Closing Reflection What possibilities have opened up for you today? How will you take what you have learned in this session and share with colleagues to begin the initial stages of creating a culture of assessing achievement related data?

58. What Questions Do You Have ?