An Exploration of Novice Teachers' Core Competencies: Impacts on Student Achievement and Effectiveness of Preparation
Co-Principal Investigator: Kathy Green
Purpose: Licensure policies and accreditation requirements at the national and state levels described expectations for the knowledge, skills, and dispositions that are presumed important to teachers' eventual success in the classroom. These expectations represent "Core Competencies" (CCs). Previous research on CCs is limited in that expectations have been determined by studying high quality teachers only, often selected based on principal recommendations. The purpose of this study is to provide additional information describing the relationship between novice teachers' CCs and student outcomes.
Project Activities: Using surveys, transcriptions, analysis of program documents (including assessments, classroom observations), and statistical modeling, the researchers will answer two questions. First, can teachers' exposure to the CCs as taught in teacher preparation programs be validly and reliably described and quantified? Second, what is the relationship between teachers' exposure to the CCs as taught in teacher preparation programs and students' academic achievement growth in K12 settings? The team will first design survey items and document coding protocols to assess each competency. After administering the survey, the team will evaluate the reliability and validity of the resulting measures. The team then plans to collect data from surveyed teachers, professors and other personnel in preparation programs preparing teachers, and the students of program graduates teaching in K12 settings, to explore whether students' achievement is related to teachers' measured CCs.
Products: Products will include preliminary evidence about whether exposure to the CCs can be validly and reliably quantified, whether these competencies are related to student academic achievement, and peer reviewed publications.
Setting: The research will be conducted in 18 urban, suburban, and rural districts in Colorado, and 20 university and district-based/alternative route preparation programs in Colorado.
Sample: The study sample includes approximately 1500 novice teachers and their students in public schools. These teachers are teaching mathematics and reading/writing in grades 3 to 8, and will have completed one to three years of teaching. Students, whose data are matched to those of the teachers, will represent diverse school settings and socio-economic and racial/ethnic status, including English language learners.
Intervention: Data on teacher Core Competencies (pending data confirmation, original groupings included "Assessment-driven Instruction," "Supporting Literacy and Language Development," "Culturally Responsive / Interactive Practice," and "Classroom Management.") will be collected and coded from surveys and transcripts. Data sources include program documents, surveys of program personnel, and surveys of candidates/novice teachers. Data from the surveys and the program documents will be merged.
Research Design and Methods: The researchers will develop scale scores for each CC at the teacher and program level using a Rasch Model approach to measurement. For each CC, they will conceptualize a construct map as a qualitative, hierarchical representation of the underlying latent variable. Next they will design items capable of eliciting information that would locate programs and teachers on this construct map. These items will then be scored using, for example, the "Depth of Knowledge" approach. Finally, the scored item responses will be calibrated. The reliability of scores from their CC scales will be assessed via inter-rater agreement for coding Depth of Knowledge (for program documents, personnel, and candidates) and Levels of Use (for teaching graduates) and from examining the standard errors of measurement for survey respondents. Validity evidence will come from three sources: content validation of CCs by the expert reviewers, convergence between coding of CC Depth of Knowledge by project staff and personnel/candidate ratings; and regression of student achievement growth on teacher Levels of Use and program-level CC Depth of Knowledge. A multiple cohort-multiple year sampling design will be used. Teachers will complete the CC survey over multiple years. The multiple years of data will allow researchers to examine key questions such as, 1) does the teacher's perspective on the CCs and their impact change as teachers move further from their graduation date?
Control Condition: Due to the nature of this research design, there is no control condition.
Key Measures: Key measures include standardized end of year test scores for a student in mathematics, reading and/or writing, within a grade, within a classroom, within a teacher, within a school, and within a district.
Data Analytic Strategy: Regression models will be applied in two phases. In phase 1, a hierarchical linear model (HLM) will be applied to predict student achievement for students on the basis of their prior grade achievement as a function of minority status, ELL status, and free-or- reduced- price lunch status. The researchers will compute residuals by subtracting a student's predicted performance from his/her observed performance. Every student will have a residual value that is adjusted by his or her demographic subgroup membership. This adjusted residual will become the outcome variable in phase 2 of this analysis, which involves the specification of an HLM. CC measures will be included as a level 2 (teacher level) covariate in the HLM analysis.