A year-long longitudinal study was conducted to quantify different types of teaching in the beginning of the year, and the effect of those choices on end of year instructional practices and student outcomes. Teacher practices were organized around the fidelity of implementation to the Responsive Classroom (RC) program (Northeast Foundation for Children, 2009). Most notably, a central RC tenant entitled “the first six weeks” was examined. RC is a universal prevention program that previously has been categorized as a Tier I social-behavioral program for students when considered within an RTI model (Elliott, 1999). Twenty-seven teachers from the New England region and 179 students participated. The Academic Competence Evaluation Scales (ACES), teacher-form (DiPerna & Elliott, 2000) was used to measure student outcomes. The Classroom Practice Measure (CPM; Rimm-Kaufman et al., 2007) was used to measure level of RC implementation. Finally, to quantify teaching behavior, a momentary time-sampling observation, called the Teaching Observation Tool (TOT; Marcotte, Klein, & Solomon, 2010), was implemented. Results from a series of multilevel models utilizing students nested within teachers indicated that both a constant, high level of instructional time and investment in environmental management time in the fall results in higher levels of student reading (significant) and math achievement (non-significant) in the spring, and lower levels of time spent correcting behavior. Teachers with large discrepancies in instructional time from fall to spring and teachers who failed to release environmental control to students over time had students with lower levels of reading and math growth. Relationships between the CPM, ACES, and the TOT indicate that RC is significantly correlated with increases in student reading achievement and motivation beyond what would be expected of a teacher that does not implement RC. However, in contrast to past research, RC in this study was not correlated with teacher reported improvements in social skills. Implications for practice and directions for future research are discussed.

No description available.

No description available.

No description available.

No description available.

Research to date has demonstrated significant relationships between the presence of outdoor drug markets and violent crime. Scholars have neglected however, to consider the role of travel distance on the drugs/violence nexus. The current study examines whether features of the distributions of travel distance to markets of drug buyers, drug sellers, or the interaction between the two distributions predicts drug market violence levels net of surrounding community demographic structure. Reuter and MacCoun's (1992) as yet untested model about the connections between drugs and violent crime, predicts that the interaction of drug seller and buyer distance distributions from varying distances more powerfully drug market violence levels than buyer and average distance averages. This suggests that how the travel patterns of the two major participants in drug markets intersect is key to understanding differences. That model is tested here. In addition, for comparison purposes, impacts of buyer and seller travel median distances are modeled separately. This work uses 5 years (2006-2010) of incident and arrest data from the Philadelphia Police Department. Reuter and MacCoun's model will be tested using the following analytical techniques. First, a methodology for locating and bounding drug markets using a nearest neighbor, hierarchical clustering technique is introduced. Using this methodology 34 drug markets are identified. Second, hierarchical linear models examining buyers and sellers separately predict travel distances to drug markets. Arrestees are nested within markets. This technique separates influences on distance arising from arrestees from drug market distance differences. Third, how market level median travel distance affects within drug market violence is considered. Specifically, the main effects of median buyer travel distance and median seller travel distance on drug market violence are captured using separate Poisson hierarchical linear models. Finally, impacts of the interaction between buyer and seller distance, Reuter and MacCoun's (1992) focus, are explored in another series of generalized hierarchical linear models. The main findings from the dissertation are as follows: 1. Results provide partial support for Reuter and MacCoun's drug market-violence model using multiple operationalizations. Public markets--those in which buyers and sellers travel from outside their own neighborhoods--are expected to be the most violent. 2. Separate raw distance measures for buyers and sellers correlate with within-drug market violence, after controlling for community demographics. 3. A negative effect of socioeconomic status and violence holds even when modeled with drug market variables. 4. As the proportion of crack cocaine sales within drug markets increases so too does within-market violence. Conceptual implications highlight the need to investigate social ties as an intervening variable in the travel distance »» drug market violence relationship. It is not clear from this research whether the travel distances of drug offenders in some way explains the amount or strength of social ties in a drug market, which in turn serves to suppress or elevate within-drug market violence. Policy implications suggest that Reuter and MacCoun's drug market types may connect with specific policing responses. Policing efforts may not receive much support from community residents because dense social networks may discourage reporting illicit activity. Markets drawing dealers and customers from farther away, and located around commercial and recreational centers may be amenable to place-based policing initiatives and coordinated intervention strategies with multiple city agencies. / Criminal Justice

The present study explored the effects of the national and cultural contexts on students' mathematics achievement. The study also investigated the nature and magnitude of student-level (level 1), school-level (level 2), and country-level (level 3) factors that are associated with math achievement. The Program for International Student Assessment (PISA) 2018 datasets were used. The main predictors focusing on this study included university admission procedure and the country's culture of mindsets about intelligence at level 3, indicating extra-curricular activities at level 2, growth mindset, and resilience self-efficacy at level 1. Other than main predictors, various predictors including country's characteristics, school characteristics, school climate factors, students' demographic characteristics, and non-cognitive abilities were added in the analysis to examine the main predictors are statistically significant after controlling for other predictors. The findings of HLM analysis showed that mathematics achievement is associated with national and cultural contexts since the study found 31.30% of the total variation was accounted for level 3 in math achievement. Also, the significant findings of the study indicated that university admission procedure was significantly associated with country-mean math achievement while the country's culture of mindsets about intelligence was not at level 3. At level 2, providing extra-curricular activities in school was a significant predictor for math achievement. At level 1, a growth mindset and information and Communication Technology (ICT) usage were positively associated with math achievement. The other significant predictors for math achievement were found in the model. In addition, the study found that the compositional effect of ICT usage explained a significant amount of between schools and countries variance even after controlling for other predictors in the analysis. Moreover, the study found several counterintuitive association phenomena due to shift of meaning. These findings were explained in terms of practical and theoretical implications for policymakers, educators, and researchers to improve students' mathematics achievement. / Doctor of Philosophy / Policymakers and researchers have been concerned about the shortage of students pursuing STEM disciplines in the United States despite the increasing demand for STEM professionals. Since mathematical skills play an important role in a nation's economic development, improving mathematics performance is essential for developing professional STEM workers. Therefore, conducting a cross-national comparative study of mathematics achievement is needed to provide a useful empirical perspective and deeper understanding of mathematics performance. The present study examined the association of diverse predictors at the country-, school-, and student-level with math achievement using multilevel modeling which is also called hierarchical linear modeling (HLM). It was found that university admission procedure was significantly associated with country-mean math achievement at the country-level. Also, providing extra-curricular activities in school was a significant predictor for math achievement at the school-level and a growth mindset and information and Communication Technology (ICT) usage were positively associated with math achievement at the student-level. In addition, the study found the positive compositional effect of ICT usage at school- and country-level which indicates that developing the infrastructure of ICT in school and country should be needed to for high and sustainable students' math achievement. Moreover, the study found several counterintuitive association phenomena due to shift of meaning. These findings were explained in terms of practical and theoretical implications for policymakers, educators, and researchers to improve students' mathematics achievement.

Families play a key role in psychiatric emergency services (PES). Given the cost of PES in terms of dollars and restrictiveness, clients, families, providers, payers, and policymakers involved in these services need more understanding of how families affect these key PES outcomes. Marriage and family therapy theories offer frameworks for understanding family and provider system dynamics in PES. This study explores how family presence and family quality influence restrictiveness and cost of PES dispositions, and how they moderate the effect of suicide risk, homicide risk, and inability to care for self on those outcomes. The sample of 306 clients and 33 clinicians was drawn from the records of a mobile PES unit serving a rural area. A regression-based, quantitative methodology, Hierarchical Linear Modeling (HLM), was employed to explore associations between restrictiveness and client risk and family factors, as well as differences in dispositions between PES clinicians. In order to extend practical implications, the same questions were also examined in monetary terms by translating restrictiveness into cost of dispositions. Results show inability to care for self and suicide risk to be the strongest predictors of increased restrictiveness and cost. Family quality appeared to reduce restrictiveness but not cost and only when not considering interactions with individual risk factors. When interactions were considered, family quality exhibited a statistically significant disordinal interaction with inability to care for self. That is, when clients were unable to care for self, positive family quality worked toward increasing restrictiveness and cost, perhaps due to families seeking help for the client. However, when clients were able to care for self, positive family quality worked in the opposite direction (i.e., toward reducing restrictiveness and cost). Theoretical and practical implications of this interaction were considered. There was found no significant variability in dispositions and associated costs between clinicians, which may be evidence of standardized clinician training and procedures. Non-standardized instrumentation, lack of comparison with other programs or sites, and limited cell sample size are limitations of the study. This study shows the complexity of family systems in PES and provides basis for recommendations for future research and clinical practice. / Ph. D.

This dissertation focuses on the development and testing of a conceptual framework for student motivation in mathematical discussion. Specifically, this document integrates Yackel and Cobb's (1996) framework with aspects of Self-Determination Theory (SDT), as described by Ryan and Deci (2000). Yackel and Cobb articulated the development of students' mathematical dispositions through discussion by facilitating student autonomy, incorporating appropriate social norms and co-constructing sociomathematical norms. SDT mirrors these factors and describes a similar process of self-regulation through fulfillment of the individual needs of autonomy, social relatedness, and competence. Given the conceptual overlap, this dissertation examines the connection of SDT with mathematical discussion with two studies. The first study examined the effect of student frequency of explaining mathematics on their perceived autonomy, competence and relatedness. Results of HLM analyses found that more frequent explanation of mathematics had a positive effect on students' perceived mathematics autonomy, mathematics competence, and relatedness. The second study used a triangulation mixed methods approach to examine high school geometry students' classroom discourse actions in combination with their perceived autonomy, competence, and relatedness. Results of the second study suggest a higher perceived sense of autonomy is indicative of more engagement in mathematical talk, but a measure of competence and relatedness are needed for such engagement to be fully indicative of mathematical discourse. Rather, students who lacked a measure of perceived competence or relatedness would cease participation in mathematical discussion when challenged by peers. While these results need further investigation, the results of the second study provide evidence that indicates the necessity of fulfilling all three SDT needs for engagement in mathematical discussion. Evidence from both the first and second studies presented in this dissertation provides support for the conceptual framework presented. / Ph. D.

Children exposed to trauma experience many negative outcomes including posttraumatic stress disorder (PTSD). Fortunately, cognitive-behavioral therapy (CBT) is an effective treatment for PTSD. Theoretically it may be that not only do children do better in treatment when their parents are involved, but that there is also a reciprocal relationship such that as children improve their parents feel better as well (and vice a versa). Using data from a randomized trial (Scheeringa & Weems, 2014), this thesis used Hierarchical Linear Modeling (HLM) to test if change in child PTSD symptoms mediates change in parent depression symptoms, and vice a versa, across treatment sessions. Results indicated that maternal depression mediates child PTSD symptoms, and that the reciprocal relationship is present. However, this was only true when child PTSD symptoms were measured by parent report. The addition of this reciprocal relationship finding to the literature and future directions are discussed.