1. Program Evaluation Luke’s Perspective

2. Ideal Framework Context: What needs to be done? (before) Input: How should it be done? (before) Process: Is it being done? (during) Product: Is it succeeding? (during/after) Real world: We focus on the Product first, and then work backward. Example – NCLB / AYP

3. Case Study: New York City Purpose of the program evaluation: – Identify why schools are failing (NCLB/AYP background) Expected program evaluation outcome: – list of findings and recommendations to remedy the situation – organized by curriculum, assessment, and professional development (arrived at through covisioning)

4. Mixed Method Qualitative – Stakeholders identified as district level, principals, teachers, and aides – Stratified random interviews – Complete stakeholder focus groups – Key document review – Recorded, coded, emergent themes identified, data analyzed, data summarized Quantitative – Teacher/classroom observations (random mts) – Student performance data (tests) – Surveys of Enacted Curriculum (SEC) (next)

5. Review: Two Major Approaches Qualitative Attempts to figure out why things are the way they are, to describe cultures, groups, events Microscopic look at phenomena Quantitative Attempts to figure out the extent to which something is related to something else; to generalize to a larger population Wide-angle look at phenomena In program evaluation we often want both, we want the specific, but also need the big picture

6. New York Exemplar SEC instrument and results (next slides) Sample methodology Sample report Sample data collection Sample data analysis Final report

7. SEC

9. Use links on website for more examples

10. What is Program Evaluation In a program evaluation we are interested in evaluating outcomes - at the program level. We are not as interested in individual student performance as we are interested in how well a program drives student performance. In schools, student outcomes are usually aligned with goals, objectives, and performance standards. There are many paths to evaluating the relative worth of a program, but a nice way to conceptualize these alternative methods is on a continuum from absolutely qualitative to absolutely quantitative.

11. Program Evaluation for You Critical component of Program Evaluation is data triangulation toward some purpose You might choose to get info from… – Classroom curriculum (akin to action research) – Schoolwide program (behavior? Technology?) – District initiatives

12. Brainstorm (this isn’t a commitment, just a start) Take 5 mins and make a list… – What program might you be interested in evaluating? (can be class, school, district) – What are the key variables?

13. Brainstorm (this isn’t a commitment, just a start) Take 5 mins and make a list… – What program might you be interested in evaluating? (can be class, school, district) – What are the key variables? – Share in groups of 2-3

14. Review Program evaluation is what it sounds like – evaluating something at the program level, and often calls for mixed methods No matter what you choose to evaluate, you will likely want different sources of data

15. Example Data Sources Performance Attendance Behavior Fiscal Professional development participation Parent survey data

16. Conceptual Dimensions of Data sources of question making 1.Organization – How does the school function? Where do we put our money? 2.Demographics – Who are we? Who is here? 3.Academics – How do students perform? 4.Conation – What is school climate like? 5.Behavior – How do students misbehave? 6.Time – How does it change over time?

17. Conceptual Model of Data Dimensions Organization Conation Behavior Academics Time Demographics

18. Example of a 4 Dimensional Question Demographics – who are the low SES students? Conation – which students like school? Academics – who scored above average in math? Organization – which students are in AP math? Question: In terms of SES, how do above average math students who report liking school distribute in tracked math classes? AD CO Program: School practice of tracking students

19. Example of a 4 Dimensional Question In terms of SES, how do above average math students who report liking school distribute in tracked math classes? BasicAdvancedAP Low SES 914826 High SES 395845 All of these students are above average math achievers who like school

20. Example of a 4 Dimensional Question BasicAdvancedAP Low SES 55.229.115.8 High SES 27.540.831.7 In terms of SES, how do above average math students who report liking school distribute in tracked math classes? Ultimately, we will want to track this data over time

21. Organization Demographics Academics Conation Behavior Time Example Question: Based on who we have as students and how they are being taught, what are the differences in the reading scores? Organization Demographics Academics Conation Behavior Time Program: Current teaching practice

22. Organization Demographics Academics Conation Behavior Time Common Example Question: Do different groups of students perform the same on standardized tests? Organization Demographics Academics Conation Behavior Time Program: District ‘closing the achievement gap’ initiative

23. Organization Demographics Academics Conation Behavior Time Better Example Question: Over the last five years, have different groups of students performed the same on standardized tests? Organization Demographics Academics Conation Behavior Time Program: District ‘closing the achievement gap’ initiative

25. Review Program evaluation is what it sounds like – evaluating something at the program level, and often calls for mixed methods 6 dimensions of data 6 common data collection methods

26. Collecting Data Six common methods – Surveys (questionnaires) – Interviews (1:1) – Document review (examine an organization’s literature) – Observations (watch something happening at an organization) – Focus groups (group interviews) – Data mining (using data that has already been collected) Break into 6 groups and identify advantages and disadvantages to each method. I’ll present my ideas. Everyone we agree with you get a point – to a maximum of 6.

27. Collecting Data Method: surveys, questionnaires, checklists Purpose: when need to quickly and/or easily get lots of information from people in a non threatening way Advantages – anonymous – inexpensive to administer – easy to compare and analyze – administer to many people / can get lots of data – many sample questionnaires already exist Disadvantages – might not get careful feedback – wording can bias client's responses – are impersonal – in surveys, may need sampling expertise – doesn't get full story – only the part you target

28. Collecting Data Method: interviews Purpose: when want to fully understand someone's impressions or experiences, or learn more about their answers to questionnaires Advantages – get full range and depth of information – develops relationship with client – can be flexible with client Disadvantages – can take much time – can be hard to analyze and compare – can be costly – interviewer can bias client's responses

29. Collecting Data Method: document review Purpose: when want impression of how program operates without interrupting the program; review of curriculum, texts, finances, memos, minutes, etc. Advantages – get comprehensive and historical information – doesn't interrupt program or routine in program – information already exists – few biases about information Disadvantages – often takes much time – info may be incomplete – you probably wont find everything – need to be quite clear about what looking for – not flexible means to get data; data restricted to what already exists

30. Collecting Data Method: observation Purpose: to gather accurate information about how a program actually operates Advantages – view operations of a school as they are actually occurring – real and accurate data! – can adapt to events as they occur Disadvantages – can be difficult to interpret seen behaviors – can be complex to categorize observations – Your presence can influence behaviors of program participants – can be expensive / time consuming

31. Collecting Data Method: focus groups Purpose: explore a topic in depth through group discussion, e.g., about reactions to an experience or suggestion, understanding common complaints, etc. Advantages – quickly and reliably get common impressions – can be efficient way to get much range and depth of information in short time – can convey key information about programs Disadvantages – can be hard to analyze responses – need good facilitator for safety and closure – one or two people can monopolize discussion – steer the discussion – difficult to schedule lots of people together

32. Collecting Data Method: data mining Purpose: use extant data to form a picture Advantages – Data does not need collecting – Usually easy to analyze – Tends to be reliable Disadvantages – Human rights – permission issues when you use data for another purpose – Gaining access to data sometimes difficult – Aggregating data / merging data sets sometimes difficult

33. Review Program evaluation is what it sounds like – evaluating something at the program level, and often calls for mixed methods 6 dimensions of data 6 common data collection methods 3 perspectives when answering questions

34. 3 Perspectives (Referents) In measurement the question we often need to ask is, to what will we compare our data? There are three corresponding referents, This organization is not always perfect, but reminds us to address a referent in questioning and analysis Individual Norm Criterion

35. Norm Referenced

36. Criterion Referenced

38. Individually Referenced 5 th grade individual student report - ORF

39. Norm Criterion Individual Example Question: Compared to last year, what are the differences in student reading scores because of attitudes related to whom students have as teachers? Norm Criterion Individual

40. Norm Criterion Individual Check for Understanding Question: How does Luke like the new scheduling system in the middle school? Norm Criterion Individual

41. Check for Understanding Team up, describe a norm, criterion, and individual reference for the following…

42. Review Program evaluation is what it sounds like – evaluating something at the program level, and often calls for mixed methods 6 dimensions of data 6 common data collection methods 3 perspectives when answering questions The purpose leads to questions which become refined over time

43. Program Evalation Questions Program evaluation begins with a broad purpose – What are you going to evaluate and why? Program evaluation then moves to more refined measureable questions – Dictates the research design (the method) – Guides the gathering of data – Usually dictates the kind of analyses – Constrains the kinds of conclusions that can be drawn

44. The Prog Eval has a purpose Purpose What is the state of our curriculum in NYC? How is the curriculum broken? What are the good parts?

45. Questions are raised Purpose What is the state of our curriculum? How is the curriculum broken? What are the good parts? Questions What is curriculum? What is our curriculum? What does a good curriculum look like?

46. Questions are refined Purpose What is the state of our curriculum? How is the curriculum broken? What are the good parts? Questions What is curriculum? What is our curriculum? What does a good curriculum look like? Measureable Questions: (examples) At the elementary level, what is the quality of the taught curriculum measured by the SEC to teachers? At the middle-school level, to what degree is the social studies curriculum aligned with provincial standards?

47. Local Example Purpose Is the Coquitlam Master’s Program (CMP) succeeding? QuestionsMeasureable Questions What questions are relevant? How can we make them measureable?

48. Local Example Purpose Is the Coquitlam Master’s Program (CMP) succeeding? QuestionsMeasureable Questions: Alone or team up, 10 minutes then share a little

49. Team scenarios (optional) Read your scenario Identify the purpose and guiding questions for the program evaluation Identify measureable questions that cross data dimensions Identify where you will find the data, and to what you will compare it (referents). What data collection method will you use? Alone or team up, 20 minutes then share