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1. High School Teachers’ Instructional Use of WASL Data: Exploring the Role of School Culture and Motivation Jack B. Monpas-Huber, Ph.D.
Director of Assessment and Program Evaluation
Spokane Public Schools
2. 2 Who I Am
3. 3 Acknowledgments
4. 4 Background of the Project Work experience:
Assessment department of large school district
Providing data to schools to support DBDM
Dealing with school cultures, politics, leadership
Research interests:
Sociology of education / school organization
Motivation
Measurement, statistics & research design
Validating large-scale accountability systems
5. 5 Organization of this Presentation Framing the Problem
Teachers’ Use of State Assessment Data
Research Methods
Results of the Study
Discussion
6. 6 Framing the Problem Rise of state accountability programs
High stakes attached to student performance
Data fed back to schools for “data-based decisionmaking”
“Theory of Action” research (Fuhrman, 2004)
Two functions:
Accountability
Instructional/feedback
How do the two forces shape teachers’ instructional use of data?
7. 7 Research Questions Considering how much data the state provides to educators, how much are high school teachers using state assessment data as a resource to improve instruction? How useful do they find it?
Considering the mounting policy pressures to improve performance on the state assessment, what motivates teachers to use state assessment data? What is the influence of policy pressure specifically, and aspects of school context in general?
8. 8 Limits in Focus State Assessment data
Instructional decisions
Certificated teachers
High schools
9. 9 Organization of this Presentation Framing the Problem
Teachers’ Use of State Assessment Data
Research Methods
Results of the Study
Discussion
10. 10 Teachers’ Use of State Assessment DataRelevant Literatures Accountability Systems
Data-based Decision-making
Teacher Motivation
Accountability and High Schools
11. 11 Teachers’ Use of State Assessment DataCapacity for Teacher Data Use Technical Skills
Technical skills for working with data
Databases, software
Analysis and interpretation of systematically collected data
Capacity building efforts in Washington
Hypothesis:
Exposure to training in assessment or in WASL item development should be a strong predictor of use of WASL data
12. 12 Teachers’ Use of State Assessment DataCapacity for Teacher Data Use Access to Data
Advances in computer technology
Assessment personnel
Teachers may vary in their perception of access to data
Hypothesis:
Teachers who perceive more access to data should be more likely to use such data than teachers who perceive less access to data
Access as necessary but not sufficient condition
13. 13 Teachers’ Use of State Assessment DataTeacher Motivation and Data Use The Policy Perspective
Some instructional changes are difficult
Teachers need consequences
Behavioral perspective on motivation
Research on high stakes testing
Research issue: perceived pressure as both outcome and predictor
Hypothesis:
Teachers who perceive higher levels of pressure will be more likely to use assessment data than teachers who perceive lower levels of pressure
14. 14 Teachers’ Use of State Assessment DataTeacher Motivation and Data Use Alternative Perspectives
Cognitive perspectives on motivation
Motivation stems from mind/thought/interpretation
Social context and cognition
15. 15 Teachers’ Use of State Assessment DataTeacher Motivation and Data Use Expectancy
“Teacher’s perceived probability that the teacher’s effort will result in the attainment of the goals” (Kelley, Heneman, & Milanowski, 2002, p. 378)
“Will do” of motivation; efforts will result in positive outcomes
Kentucky and North Carolina research
Hypothesis:
Teachers who report higher levels of expectancy (that working with assessment data will actually help them improve instruction for their students) will be more likely to use assessment data than those who expect less to result from it
16. 16 Teachers’ Use of State Assessment DataTeacher Motivation and Data Use Efficacy
“Teacher beliefs about their span of influence and performance capacity” (Kelley & Finnigan, 2003, p. 604)
“Can do” of motivation
The role of performance feedback in motivation research
Hypothesis:
Teachers who feel more efficacious working with assessment data will be more likely to use assessment data than teachers who feel less efficacious
17. 17 Teachers’ Use of State Assessment DataTeacher Motivation and Data Use Goals
Motivation as product of intentions or goals people have for engaging in a behavior
People pursue variety of goals
Goals may conflict with each other
Teachers and “perceived policy intentions” of accountability policies (Leithwood, Steinbach, & Jantzi, 2002)
Ingram, Louis, & Schroeder (2004) study
Hypothesis:
Teachers will be more likely to use state assessment data if they perceive its underlying purpose as consistent with their own goal of helping students learn
18. 18 Teachers’ Use of State Assessment DataSummary of Motivation Research Pressure, expectancy, efficacy, goals
Filtered through school context
Some aspects of context (collaboration, feedback data) influence motivations
These motivations vary:
Among teachers within one school
Possibly by groups of teachers between schools
Research issues
Motivations as predictors of data use
Motivational effects may be different in different schools
19. 19 Teachers’ Use of State Assessment DataBuilding a Model of Teacher Data Use Quantity of Teacher Data Use =
ß0 (mean)
+ ß1(state assessment training)
+ ß2(perceived access to data)
+ ß3(perceived pressure)
+ ß4(expectancy)
+ ß5(efficacy)
+ ß6(goal alignment)
+ e (unmodeled variation)
20. 20 Teachers’ Use of State Assessment DataContextual Influences on Teacher Motivation and Data Use To the extent that motivations are shared by teachers in one school, what influences these motivations?
Are some schools more “motivating” than others, in this case, in regard to using and learning from state assessment data?
Sociological perspectives on school culture and other contextual influence
21. 21 Teachers’ Use of State Assessment DataContextual Influences: Culture Focus on shared attitudes and behavior is focus on culture
Two perspectives on culture (Swidler, 1995):
“Inside out” – internalized attitudes (motivations?) predict behavior
“Outside in” – shared practice, norms, codes regulate behavior irrespective of internal beliefs
22. 22 Teachers’ Use of State Assessment DataCultural Perspectives The Loose Coupling Perspective (Weick, 1976; Firestone, 1985)
Educational organizations are multi-layered
Classrooms disconnected from administration
Because teaching and learning is not precise, schools do not evaluate technical quality of instruction
High schools especially loosely coupled
Challenges bureaucratic models of schools which emphasize centrality of leadership and formal rational procedures
Also helps explain why reform movements have historically failed to change instruction in schools
Loose coupling and assessment data
“Stick them in a drawer”
23. 23 Teachers’ Use of State Assessment DataCultural Perspectives Professional Accountability
Abelmann & Elmore (1999)
Strong and weak internal accountability systems
O’Day (2004)
Professional Collaboration
Student learning data as centerpiece of collaborative work
Recurrent predictor in past research
24. 24 Teachers’ Use of State Assessment DataLeadership Leaders filter and frame accountability policy (Spillane)
Transformational leadership has positive effects on teacher motivation
Trust, collaboration, shared accountability
Principals may vary in how they frame assessment results
School-level variable that influences motivations and assessment data
25. 25 Teachers’ Use of State Assessment DataMethodological Observations Lots of qualitative case studies
No quantitative studies of use as a criterion or dependent variable
Lack basic descriptive data about levels or frequencies of use
26. 26 Teachers’ Use of State Assessment DataA Tentative Model
27. 27 Organization of this Presentation Framing the Problem
Teachers’ Use of State Assessment Data
Research Methods
Results of the Study
Discussion
28. 28 Research MethodsDesign Issues Teacher survey
Study population: certificated teachers in high schools in western Washington school districts that employ a full-time assessment director
Instrument: 4-page questionnaire
Matrix sampling
Three forms
Each contained common and unique items
29. 29 Research MethodsSchool Sample Characteristics
30. 30 Research MethodsSample Characteristics – Teachers
31. 31 Research MethodsScale Development Classical Test Theory
Internal consistency reliability (Cronbach’s coefficient alpha (a))
Item-total correlations
Exploratory factor analyses (EFA)
Item Response Theory
Rating Scale Model (Wright & Masters, 1982)
Item difficulty, fit statistics
32. 32 Research MethodsOutcome Measures Frequency of WASL Data Use
Utility of WASL Data Use
33. 33 Research MethodsPredictor Measures Perceived Access to Data
Training in State Assessment
Training in WASL Item Construction
Pressure to Increase WASL Performance
WASL Goal Alignment
Efficacy with WASL Data
Principal WASL Commitment
Principal Trust
Departmental Professional Collaboration
Professional Accountability
34. 34 Organization of this Presentation Framing the Problem
Teachers’ Use of State Assessment Data
Research Methods
Results of the Study
Discussion
35. 35 ResultsHow much are teachers using data?
36. 36 ResultsHow much are teachers using data?
37. 37 ResultsHow much are teachers using data?
38. 38 ResultsHow much are teachers using data?
39. 39 ResultsHow much are teachers using data?
40. 40 ResultsHow much are teachers using data?
41. 41 ResultsHow much are teachers using WASL data?
42. 42 ResultsHow much do teachers benefit from WASL data?
43. 43 ResultsHow much do teachers benefit from WASL data?
44. 44 ResultsHow much do teachers benefit from WASL data?
45. 45 ResultsHow much do teachers benefit from WASL data?
46. 46 ResultsHow much do teachers benefit from WASL data?
47. 47 ResultsHow much do teachers benefit from WASL data?
48. 48 ResultsHow much do teachers benefit from WASL data?
49. 49 ResultsHow much do teachers benefit from WASL data?
50. 50 ResultsWhat motivates teachers to use WASL data?
51. 51 ResultsVisualizing Hierarchical Linear Modeling, 1/3
52. 52 ResultsVisualizing Hierarchical Linear Modeling, 2/3
53. 53 ResultsVisualizing Hierarchical Linear Modeling, 3/3
54. 54 ResultsFrequency of WASL Data Use – HLM Results
55. 55 ResultsFinal Model of Frequency of Data Use – HLM Results Frequency of WASL Data Use =
ß0 (mean)
+ ß1(utility of WASL data use)
+ ß2(training in WASL item writing)
+ ß3(perceived pressure to increase WASL scores)
+ ß4(principal commitment to WASL improvement)
+ ß5(efficacy with WASL data)
+ r (unmodeled variation)
ß0 = ?00 + ?01(school ethnic composition) + u0
56. 56 ResultsModeling Frequency of WASL Data Use
57. 57 ResultsUtility of WASL Data Use – HLM Results
58. 58 ResultsFinal Model of Utility of Data Use – HLM Results Utility of WASL Data Use =
ß0 (mean)
+ ß1(perceived access to WASL data)
+ ß2(frequency of WASL data use)
+ ß3(departmental professional accountability)
+ ß4(departmenal professional collaboration)
+ ß5(WASL goal alignment)
+ ß6(WASL efficacy)
+ r (unmodeled variation)
59. 59 Organization of this Presentation Framing the Problem
Teachers’ Use of State Assessment Data
Research Methods
Results of the Study
Discussion
60. 60 Conclusions High School Teachers Use of Data
Teachers are using data with moderate frequency and gaining some value from it
This aspect of WASL program is working
Motivation and School Context
Multiple motivations are at work (pressure and efficacy)
Principal leadership provides incentive to use
Sensemaking of data is social / collaborative
Data as feature of more tightly coupled schools
61. 61 Thank you! To contact me:
Jack B. Monpas-Huber, PhD
Director of Assessment and Program Evaluation
Spokane Public Schools
jackm@spokaneschools.org
(509) 354-7396 Office
(206) 947-9926 Cell