Thesis advisor: Joseph J. Pedulla / There is considerable evidence that new teachers are ill prepared for classroom practice, including self-reported evidence collected from teachers (e.g., Levine, 2006), and statistical evidence for differences in the achievement of students with new versus more experienced teachers (Rivkin, Hanushek, and Kain, 2005). In light of the challenges encountered by new teachers (e.g., Levine, 2006), this study examined the value of different forms of teacher knowledge for teachers with different levels of experience. In particular, this study investigated the interactive relationship between teaching experience and teacher content knowledge, and student achievement in mathematics and science. In New York City, Boyd et al. (2009) linked practice-focused teacher preparation to student mathematics achievement in the first year of teaching and teacher content preparation to achievement in the second. However, other studies demonstrated interactions between teaching experience and content knowledge with different interpretations (e.g., Kukla-Acevedo, 2009; Monk, 1994). At the same time, this study examined the interactive relationship between teaching experience and teachers' pedagogical content knowledge, and student achievement. Extant models of teacher career development (Huberman, 1989; National Research Council, 2010) and how teacher education affects student achievement (e.g., Desimone, 2009) offered theoretical grounding for the study. With nationally representative samples of fourth and eighth grade U.S. students--participants in the 2011 Trends in International Mathematics and Science Study--this study employed hierarchical linear modeling to address its research questions among an array of student achievement outcomes in the domains of mathematics and science. This study attempted to account for salient student, teacher, and contextual factors, and the probabilities of teachers' receipt of various teacher education "treatments" (i.e., propensity score analysis) to reduce the plausibility of selection threats to internal validity. The study found no evidence for relationships between teacher content knowledge or pedagogical content knowledge and student mathematics and science achievement in fourth and eighth grade. Furthermore, the results indicated no interactive relationships between forms of teacher knowledge and teaching experience, and student achievement in these grades/subjects. The limitations of cross-sectional, observational studies using large-scale data and directions for further research are discussed. / Thesis (PhD) — Boston College, 2013. / Submitted to: Boston College. Lynch School of Education. / Discipline: Educational Research, Measurement, and Evaluation.

Using the multilevel framework, this multi-institutional study took different approaches to study undergraduate students’ retention in engineering programs. The study was conducted in two phases. In the first phase, using Multiple-Institution Database for Investigating Engineering Longitudinal Development, the aim was to control for macro-level factors which may create a selection bias in student admission into engineering programs. The outcome fed the second phase, which aimed to analyze student’s retention for different populations.

The purpose of this study was to examine the potential for using propensity score-based matching methods to estimate teacher contributions to student learning. Value-added models are increasingly used in teacher accountability systems in the United States in spite of ongoing qualms about the validity of teacher quality estimates resulting from those models. Using a large national dataset, teacher effects were estimated for 435 teachers using both value-added and propensity score-based approaches. The two approaches resulted in teacher effect estimates that were moderately correlated, with propensity score-based estimates more highly correlating with the value-added estimates as the matching ratio was increased. For many teachers' students, finding a set of matched control students was impossible unless the set of matching variables was reduced. Results suggest that many teachers have classroom compositions that are unusual, making evaluation of the teachers' impacts on student outcomes problematic. It was also found that, while value-added estimates were relatively insensitive to covariate inclusion choices or method of effect estimation, propensity score-based estimates were somewhat sensitive. Propensity score-based teacher effect estimates offer promise both for better accounting for classroom composition and student background variables and for indicating when a teacher's context is unique with respect to those variables, making the teacher's impact challenging to evaluate.

The purpose of this study was to explore the relationship of honors education to student success by comparing honors-eligible community college students who met requirements to academically matched peers who opted out of honors participation. Honors program participation was defined as completing 12 or more credit hours of honors-level course work. The population for this study included 452 honors-eligible participants with 95 honors participants (HPs) and 357 non-participants (NPs) from a community college in Tennessee. The sampling frame was generated using a five-year participation window from 2008 through 2013. Propensity score matching alleviated the threat to validity for self-selection bias by controlling for confounding variables such as high school GPA, dual-enrollment participation, ACT score, declared major, community college GPA upon first term of eligibility, parental income, parental education, gender, and age. Major findings of the study were: honors program participants (a) earned a significantly higher numerical final course grade in Composition II, a first-year writing course; (b) earned significantly higher cumulative GPAs the second semester after honors eligibility; (c) earned significantly higher cumulative GPAs upon completion; (d) were significantly more likely to graduate. Conclusions generated from the data analyses indicate that honors education benefits community college students and provide empirical support for increased investment in community college honors education, especially for high-achieving students experiencing poverty. Low-income students were defined as those students receiving the maximum federal Pell Grant award provided to undergraduate students with financial need. Within the study sample, it was determined that 50% of NPs met the low-income threshold whereas 47% of HPs were identified as low-income. These participation rates suggest that more low-income high-achieving students who could substantially benefit from participating in honors are participating less. Further empirical research studies and policy levers should identify ways to increase honors participation for low-income, high-achieving students.

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There is a growing demand for studies applying quantitative methods to large-scale data sets for the purpose of evaluating the effects of educational reforms (UVK, 2010). In this thesis the statistical method, Propensity Score Analysis (PSA), is presented and explored in the evaluating context of an extensive educational initiative within science and technology education; the Science and Technology for All-program (NTA). The research question put forward reads; under what conditions are PSA-analyses a useful method when measuring the effects from a school improvement initiative in S &amp; T? The study considers the use of PSA when looking for long-term effects that could be measured, what to take into consideration to be able to measure this, and how this could be done. The baseline references (outcome variables) used in order to measure/evaluate the long-term effects from the studied program is students’ achievements in the national test (score and grades) and their grades in year 9. Some findings revealed regarding the object of study (long-term effects from using NTA) are also presented. The PSA method is found to be a useful tool that makes it possible to create artificial control groups when experimental studies are impossible or inappropriate; which is often the case in school education research. The method opens up for making use of the rich source of registry data gathered by authorities. PSA proves reliable and relatively insensitive to the effects of covariates and heterogeneous effecter if the number of samples is large enough. The use of PSA (or other statistical methods) also makes it possible to measure outcomes several years after treatment. There are issues of concern when using PSA. One is the obvious demand for organized collection of measurement data. Another issue of concern is the choice of outcome variables. In this study the chosen outcome variables (pupils’ score and grading in national tests and grades in year 9) open up for discussions regarding aspects that might not be reflected/measured in national tests and/or teachers’ grading. Findings regarding the long-term effects from using NTA) show significantly positive effects in physics on test scores (average increase 16.5%) and test grades, but not in biology and chemistry. In this study no significant effects are found for course grades. PSA approach has proved to be a reliable method. There is however a limitation in terms of the method's ability to capture more subtle aspects of learning. A combination of quantitative and qualitative approach when studying long-term effects from educational intervention is therefore suggested. / <p>QC 20131120</p>

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