Projects & Research Questions

1. The teacher pipeline in Washington State: Examining the transition from student teaching to the classroom and implications for workforce diversity and student achievement

1.1) What is the current state of educator and student diversity in Washington?

1.2) What aspects of preservice teacher education are predictive of workforce entry for prospective teachers (particularly non-white and/or endorsed in difficult-to-staff areas), and what are the implications for the workforce diversity?

1.3) What is the process that determines where preservice teachers do their student teaching and to what extent does this process appear to vary across teacher education programs in Washington State?

1.4) What pre-service and student teaching experiences are predictive of prospective teachers’ workforce entry, effectiveness, and attrition?

1.5) Where do prospective teachers who leave or never enter the public teaching workforce end up employed?

1.6) To what extent are there differences in the effectiveness of teachers given the nature of the partnerships between TEPs and school districts?

 
 

2. The special education teacher pipeline in Washington State: A comprehensive analysis of preservice predictors of special education teacher career paths and effectiveness

2.1) What malleable factors (e.g., student teaching experiences, teacher education coursework, and measures of the match between a candidate’s teacher education experiences, student teaching experiences, and early-career teaching experiences) are predictive of the timing and probability of workforce entry for special education teacher candidates?

2.2) What malleable factors are predictive of the test performance of students with disabilities in the classrooms of special education teacher candidates who enter the state’s public teaching workforce?

2.3) What malleable factors are predictive of the probability that special education teachers stay in the state’s public teaching workforce?

 

3. The STEM teacher pipeline in Washington State: A comprehensive analysis of preservice predictors of STEM teacher career paths and effectiveness

3.1) What aspects of preservice teacher education are predictive of the probability and timing of public teaching workforce entry for prospective STEM teachers?

3.2) Where do prospective STEM teachers who never enter the public teaching workforce end up employed, and what are their starting salaries in these positions relative to starting teaching salaries in the state’s single salary schedule?

3.3) What preservice experiences and characteristics (including measures of content-area preparation, pedagogical knowledge, clinical experiences, and the alignment or “match” between a candidate’s teacher education experiences, student teaching experiences, and early-career teaching experiences) are predictive of future STEM teacher effectiveness?

 

4. What is the value of apprenticeship for teachers? Linking preservice mentor quality to inservice teacher and student outcomes

4.1) What characteristics of cooperating teachers (observable qualifications and characteristics, value added, and candidate perceptions) are predictive of teacher candidate performance on the edTPA portfolio-based assessment?

4.2) What characteristics of cooperating teachers are predictive of the future effectiveness of teacher candidates who enter the state’s public teaching workforce as measured by the test performance of students in their classrooms?

4.3) What characteristics of cooperating teachers are predictive of the retention of teacher candidates who enter the state’s public teaching workforce?

5. Applicant information, selection, and STEM teacher retention and effectiveness

5.1) To what extent is prospective teacher candidate information predictive of STEM teacher retention and effectiveness?

5.2) What attributes of university or TEP applicants are valued by COE STEM and A&S STEM faculty, and how much variation is there in what is valued?

5.3) To what extent do the admissions data collected and institutional selection processes reflect the values expressed?

5.4) Are valued attributes predictive of who enrolls in STEM TEPs?
5.5) Are those attributes that are valued predictive of STEM teacher retention and effectiveness?

Applicant information, selection, and ST
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