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Effects of the My Teaching Partner Intervention in Secondary School Classrooms

Effects of the My Teaching Partner Intervention in Secondary School Classrooms. Joseph P. Allen Robert C. Pianta University of Virginia. Co-Collaborators: Amori Mikami Anne Gregory. Project Team: Chris Hafen Sharon Deal Judith Wasserman Rachel Boren Janetta Lun. Context.

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Effects of the My Teaching Partner Intervention in Secondary School Classrooms

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  1. Effects of the My Teaching Partner Intervention in Secondary School Classrooms Joseph P. Allen Robert C. Pianta University of Virginia Co-Collaborators: AmoriMikami Anne Gregory Project Team: Chris Hafen Sharon Deal Judith Wasserman Rachel Boren JanettaLun

  2. Context Number of Secondary School Students in U.S.: 24 million Number of Secondary School Classes being taught each week 6 million % of 9th graders who won’t finish High school by the end of 12th grade 25% Number of programs in ‘What Works’ Clearinghouse with demonstrated efficacy improving teaching quality enough to improve student achievement in these classrooms 0

  3. Key Questions • Can we identify teacher-student interaction qualities that predict student engagement and achievement? • Can we change these qualities? • Will changes lead to sustainable student achievement gains? • What are the mechanisms of change?

  4. Key Questions • Can we identify teacher-student interaction qualities that predict student engagement and achievement? • Can we change these qualities? • Will changes lead to sustainable student achievement gains? • What are the mechanisms of change?

  5. Classroom Learning Assessment & Scoring System- Secondary (CLASS-S) Instructional Support Instructional Learning Format Content Understanding Analysis & Problem Solving Quality of Feedback Classroom Organization Behavior Management Productivity Emotional Support Positive Climate Teacher Sensitivity Regard for Adolescent Perspectives Negative Climate Student Outcomes Student Engagement

  6. Evaluation Design • 43 teachers within 8 schools (640 students) (The control condition in an RCT). • 1 focal classroom selected per teacher • Predicting Future Achievement after Covarying Baseline Achievement Test Scores • Teacher Demographics: • 64% female • 83% White, 8% African-American; 6% Mixed-Ethnicity; 3% Other • 54 middle school, 34 high school • 35% BA degree; 65% at least a year of course work beyond BA • Average 8 years of teaching experience

  7. Classroom Characteristics • School type:39% High school; 61% Middle School • Subject:52% Language/Social Studies; 48% Math/Science • Average class size:23 students • Gender: 47% girls 53% boys • Ethnicity:23% African American 2% Asian 4% Hispanic 70% European-American

  8. Observational Assessment of Classroom Environment • Videotaped observations of a classroom • spread throughout course of year • Two 20-minute segments per class session/tape • Each tape rated by 2 raters • Coded Using CLASS-S System • High inter-rater reliabilities; ICC’s range from • .73 - .82 for overarching domains • .50 -.78 for specific dimensions (all but one dimension > .64)

  9. Student Academic Success • Score on State “Standards of Learning” End of Year Subject Test • Themeasure by which schools/students are judged for accreditation/graduation. • Extensive seven-year validation/standardization process.

  10. Analytic Approach • Multi-level modelling • All models covary: • Student factors: • Grade level • Gender • Family poverty status • Classroom factors: • Classroom size • Teacher Factors • Teacher experience • Teacher education • Teacher gender and race • Moderating effects of covariates were also examined.

  11. Predicting Student Achievement

  12. Key Questions ✔Can we identify teacher-student interaction qualities that predict student engagement and achievement? • Can we change these qualities? • Will changes lead to sustainable student achievement gains? • Why?

  13. MyTeachingPartnerOverview • Consultant and teacher work together using the CLASS-Sin cultivating: • Observation • Reflection • Development of knowledge and expertise Reflection Knowledge Expertise Support Teaching Practice Classroom Observation

  14. The Steps of the Consultancy

  15. MTPS Website www.mtpsecondary.net

  16. Detailed Video Examples www.mtpsecondary.net

  17. Key Questions ✔Can we identify teacher-student interaction qualities that predict student engagement and achievement? • Can we change these qualities? • Will changes lead to sustainable student achievement gains? • What are the mechanisms of change?

  18. Evaluation Design 88 classrooms 45 Tx. 43 Control (Classrooms Randomized within school) 2237 Students Assessed Across 2 Years

  19. Evaluation Design Treatment group: Year 1: • Introductory Workshop (late summer) • Ongoing consultancy • ~ 2 days total in-service time Year 2: • Booster Workshop (late summer) only + Web site access • Control group: Usual in-service practice.

  20. Intervention Effect on Change in Classroom Qualities

  21. Intervention Effect on Change in Classroom Qualities

  22. Intervention Effect on Change in Classroom Qualities

  23. Year 1 Change in OverallTeacher-Student Interactions Standardized Effects: Baseline = .45*** Intervention = .19* MTPS participation predicts higher quality teacher-student interactions

  24. Key Questions ✔Can we identify teacher-student interaction qualities that predict student engagement and achievement? ✔Can we change these qualities? • Will changes lead to sustainable student achievement gains? • What are the mechanisms of change?

  25. Year 1Intervention Effects on Achievement • No relation of intervention to either baseline or exit achievement test scores in Year 1 (all p’s > .35). • Why? • No evidence we changed the classroom until the very end of the year when most teaching was past.

  26. Year 2Change in Achievement Standardized Effects: Pre-test = .54*** Intervention = .22* MTPS is predicting increases in End of Course Achievement Tests

  27. Year 2Intervention Effects on Achievement • Real-world effect size = .22 SD increment in Achievement Test scores • Average ‘Bump’ of students in MTP from 50th to 59th percentile in achievement • If effect applies equally at all parts of achievement spectrum (as appears to be the case): a .22 SD boost would reduce failure rates from: 14% without the intervention to 10% with it Reducing the number of failing students each year by 29% *** This occurs in the year AFTER the intervention year (i.e., sustainability), across diverse subject matter/content areas.

  28. Key Questions ✔Can we identify teacher-student interaction qualities that predict student engagement and achievement? ✔Can we change these qualities? ✔Will changes lead to sustainable student achievement gains? • What are the mechanisms of change?

  29. A Preliminary Mediational Analysis Intervention Environmental Outcome Observed Change in Student Achievement “My Teaching Partner” Intervention *

  30. A Preliminary Mediational Analysis Intervention Intervention Target Environmental Outcome ?? Observed Change in Student Achievement “My Teaching Partner” Intervention

  31. Mediational Analyses • Assessed via Multi-level Structural Equation Modelling, followed up via parametric bootstrapping analysis (Preacher et al., 2010) • Focus on target of intervention (Teacher-student interactions assessed via CLASS-S) • Using Centered/Standardized data for ease of interpretation.

  32. MTP-S Effect as Mediated via Observed Interactions Intervention Intervention Target Student Outcome Observed Teacher-Student Interactions .16** .37** .12* Change in Student Achievement “My Teaching Partner” Intervention Initial Model (Simple Direct Effects)

  33. MTP-S Effect as Mediated via Observed Interactions Intervention Intervention Target Student Outcome .06* * Indirect effect Observed Teacher-Student Interactions .16** .37** .12* Change in Student Achievement “My Teaching Partner” Intervention .06 ns Initial Model (Simple Direct Effects) Final Model (Including Mediated Effect)

  34. Limitations • Design only supports causal interpretations for outcomes, not for mediating processes with analyses thus far. • Some Attrition Took Place (though it was unrelated to the intervention in every possible way we could test). • Modest statistical significance with small sample

  35. Conclusions • We CAN identify elements of the classroom environment that predict student achievement. • We CAN change these environmental factors. • If we do, student achievement will change as well, eventually. • Changes can be sustained over time and in new classrooms, post-intervention. • We can identify potential mechanisms of change linked to the intervention. • Which has implications for cost effectiveness…

  36. Potential Significance – Costs vs. Benefits (BOE* Calculation) *BOE = Back of Envelope

  37. MyTeachingPartner Secondary Replication is ongoing with the support of IES Further information available at: www.myteachingpartner.net

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