Coaching in Literacy Collaborative and Its Effects on Teachers and Students

1. Coaching in Literacy Collaborative and Its Effects on Teachers and Students Gina Biancarosa, University of Oregon Anthony S. Bryk, Carnegie Foundation for the Advancement of Teaching Allison Atteberry, Stanford University Heather Hough, Stanford University Annual Meeting of the Society for Research on Educational Effectiveness March 2010

2. Key Features of Literacy Collaborative • Comprehensive school reform program designed to improve elementary children’s reading, writing, and language skills primarily through school-based coaching • Used in over 700 elementary schools in 200 districts across 26 states • Intensive professional development • Coaches trained over one year (Lesley University and the Ohio State University) • Ongoing support from local and national network • Coaches • In-school professional development courses • One-on-one coaching: viewed as the high leverage activity

3. Key Features of Literacy Collaborative • Anatomy of a coaching session • Pre-briefing • Observation • Modeling • Debriefing • Elements of literacy instruction • Interactive read aloud • Shared reading • Guided reading • Interactive writing • Writing workshop • Word study

4. Main Research Questions • Does Literacy Collaborative improve the value-added to student literacy learning? • Can any effects of Literacy Collaborative be indirectly attributed to coaching via teachers’ changing expertise implementing the instructional practices? • Can any effects of Literacy Collaborative be directly attributed to coaching? • Does overall coaching activity in a school predict value-added to student literacy learning? • Does individual teacher participation in coaching predict value-added to student literacy learning?

5. Student Data • Value-added analyses focused on grades exposed to LC professional development (K-2) • Sample: 8576 children, 341 teachers, and 17 coaches in 17 public schools across 8 states in the Eastern U.S. • Children tested in fall and spring for 4 years to measure change over time in students’ literacy learning using: • Dynamic Indicators of Basic Early Literacy Skills (DIBELS) • Terra Nova in spring

6. Accelerated Longitudinal Cohort Design6 cohorts studied over 4 years Grade Training year Year 1 of implementation Year 2 of implementation Year 3 of implementation

7. Our early literacy scale Mean at 2nd grade end Mastery of component skills Reads 90 wpm Answers 2/3 of 1st grade comprehension questions correctly, 1/3 of 2nd grade questions correctly 4 • Equal differences on scale imply equal differences on the trait measured at any level • Reported in logits (which describe the probability of a student with a given ability level getting a particular item right or wrong) • But what do they mean given the particular assessments used? Mean at 1st grade end & 2nd grade entry Accurate (not fast) PA Reads 50-60 wpm Answers 1/3 of 1st grade comprehension questions correctly 3 Mean at K end & 1st grade entry Accurate and fast letter recognition Good initial sound PA Little evidence of decoding 2 Mean at K entry Names about 30 letters in a minute Very low phonemic awareness (PA) 1

8. Additional Measures

9. Prior Findings:Coaching sessions per month (n=249)

10. Prior Findings:Frequency and expertise of implementation (n=249)

11. Value-added Hierarchical Cross-classified Effects Modeling • Four Levels – time : (students x teachers) : school • Repeated measures on students (level 1) • Students (level 2) who cross Teachers (level 3) over time • All nested within Schools (level 4) • The analysis model can be conceptualized as a joining of 2 separate multi-level models • One two-level model for individual growth in achievement over time, and • A second two-level model which represents the value-added that each teacher in a school contributes to student learning in that school in a particular year.

12. Hierarchical Crossed Value-added Effects Model Individual growth parameters overall value- added effects teacher-level school-level value-added effects

13. Value-added effects by year (prior to adding coaching as predictor) Ave. student learning growth is 1.02 per academic year

14. Variability in school value-added, year 1 Average student gain per academic year High value-added schools Low value-added schools Year 1 mean effect (.16) No effect

15. Variability in school value-added, year 2 Average student gain per academic year Year 2 mean effect (.28) Year 1 mean effect (.16) No effect

16. Variability in school value-added, year 3 Average student gain per academic year Year 3 mean effect (.33) Year 2 mean effect (.28) Year 1 mean effect (.16) No effect

17. Variability in teacher value-added within schools, year 1 Average student gain per academic year No effect

18. Variability in teacher value-added within schools, year 2 Average student gain per academic year No effect

19. Variability in teacher value-added within schools, year 3 Average student gain per academic year No effect

20. Explaining variability in value-added effects • Tested models with cumulative number of coaching sessions per year (derived from coach logs) • Per teacher • Averaged across teachers at school-level • Also tested a variety of controls thought to influence teachers’ openness to, participation in, and selection for coaching • Prior use of reform literacy practices • Role conception • School commitment • New to school

21. Hierarchical Crossed Value-added Effects Model Individual growth parameters Predictors added to baseline and LC value-added effects overall value- added effects teacher-level school-level value-added effects

22. Summary of findings • Only one teacher characteristic significant • Teacher expertise of implementation not significant • Coaching at the school level not significant • Coaching at the teacher level significant

23. Teachers’ role conception • High scorers: Teachers who take an active stance in their professional role in terms of initiating contact and offering help to colleagues • Higher value-added to student literacy learning in their schools in baseline and Y2

24. Average Value-added of Coaching by year

25. Average Value-added of Coaching by year

26. Across Seventeen Schools, Over Time 17

27. Value-added by coaching, year 1 0 0 1 5 12 No coaching effect

28. Value-added by coaching, year 2 0 4 8 12 33 No coaching effect

29. Value-added by coaching, year 3 0 8 14 24 43 No coaching effect

30. Summary of findings • Evidence that the mechanism for improved value-added shifts from over time • Year 1: Coaching has no value-added • Year 2: Coaching begins to add to value-added for student learning • Year 3: Coaching becomes the primary mechanism for value-added to student learning • Cumulative coaching explains differences in teacher value-added effects, but not school effects

31. Implications • Coaching explains differences in teachers’ value-added to student learning • Shift in coaching effects from negative in Year 1 to positive in Years 2 and 3 raises interesting hypotheses but offer no answers • A selection effect (on the part of coach or teacher) • A dosage effect • A change in coaching expertise effect • Unexplored school/coach effects • Direct positive effects of coaching on students appear to take time to emerge

32. Limitations • Limited sample, especially at school level, limits ability to explore contextual mechanisms • Coaching was embedded in a school-wide reform model • Professional development for coaches is more intense than in most other models

33. Future Steps • Continued analyses of current data • Length of coaching session • Focus of coaching session • Observation vs. modeling • Development and piloting of the Performance-based Assessment of Literacy Coaching (PALC)

34. Thank you! ginab@uoregon.edu