The relationship between selected standardized test scores and performance in advanced placement math and science exams: Analyzing the differential effectiveness of scores for course identification and placement

There is a national need to increase the STEM-related workforce. Among factors leading towards STEM careers include the number of advanced high school mathematics and science courses students complete. Florida's enrollment patterns in STEM-related Advanced Placement (AP) courses, however, reveal that only a small percentage of students enroll into these classes. Therefore, screening tools are needed to find more students for these courses, who are academically ready, yet have not been identified. The purpose of this study was to investigate the extent to which scores from a national standardized test, Preliminary Scholastic Assessment Test/ National Merit Qualifying Test (PSAT/NMSQT), in conjunction with and compared to a state-mandated standardized test, Florida Comprehensive Assessment Test (FCAT), are related to selected AP exam performance in Seminole County Public Schools. An ex post facto correlational study was conducted using 6,189 student records from the 2010 - 2012 academic years. Multiple regression analyses using simultaneous Full Model testing showed differential moderate to strong relationships between scores in eight of the nine AP courses (i.e., Biology, Environmental Science, Chemistry, Physics B, Physics C Electrical, Physics C Mechanical, Statistics, Calculus AB and BC) examined. For example, the significant unique contribution to overall variance in AP scores was a linear combination of PSAT Math (M), Critical Reading (CR) and FCAT Reading (R) for Biology and Environmental Science. Moderate relationships for Chemistry included a linear combination of PSAT M, W (Writing) and FCAT M; a combination of FCAT M and PSAT M was most significantly associated with Calculus AB performance. These findings have implications for both research and practice. FCAT scores, in conjunction with PSAT scores, can potentially be used for specific STEM-related AP courses, as part of a systematic approach towards AP course identification and placement. For courses with moderate to strong relationships, validation studies and development of expectancy tables, which estimate the probability of successful performance on these AP exams, are recommended. Also, findings established a need to examine other related research issues including, but not limited to, extensive longitudinal studies and analyses of other available or prospective standardized test scores.

The Effectiveness of an Intervention Package on Math Computation

Abstract: Four second-grade students participated in a B-A-B withdrawal single-subject design experiment. The intervention package implemented consisted of three components: self-monitoring, performance feedback, and reinforcers. Participants completed math probes across phases. Accuracy and productivity was recorded and calculated. Results demonstrated the intervention package improved accuracy and productivity for all participants.

Can a Broader Education Narrow the Gap? Evidence on Non-Academic Features of Schooling

Empirical studies of education programs and systems, by nature, rely upon use of student outcomes that are measurable. Often, these come in the form of test scores. However, in light of growing evidence about the long-run importance of other student skills and behaviors, the time has come for a broader approach to evaluating education. This dissertation undertakes experimental, quasi-experimental, and descriptive analyses to examine social, behavioral, and health-related mechanisms of the educational process. My overarching research question is simply, which inside- and outside-the-classroom features of schools and educational interventions are most beneficial to students in the long term? Furthermore, how can we apply this evidence toward informing policy that could effectively reduce stark social, educational, and economic inequalities?

The first study of three assesses mechanisms by which the Fast Track project, a randomized intervention in the early 1990s for high-risk children in four communities (Durham, NC; Nashville, TN; rural PA; and Seattle, WA), reduced delinquency, arrests, and health and mental health service utilization in adolescence through young adulthood (ages 12-20). A decomposition of treatment effects indicates that about a third of Fast Track’s impact on later crime outcomes can be accounted for by improvements in social and self-regulation skills during childhood (ages 6-11), such as prosocial behavior, emotion regulation and problem solving. These skills proved less valuable for the prevention of mental and physical health problems.

The second study contributes new evidence on how non-instructional investments – such as increased spending on school social workers, guidance counselors, and health services – affect multiple aspects of student performance and well-being. Merging several administrative data sources spanning the 1996-2013 school years in North Carolina, I use an instrumental variables approach to estimate the extent to which local expenditure shifts affect students’ academic and behavioral outcomes. My findings indicate that exogenous increases in spending on non-instructional services not only reduce student absenteeism and disciplinary problems (important predictors of long-term outcomes) but also significantly raise student achievement, in similar magnitude to corresponding increases in instructional spending. Furthermore, subgroup analyses suggest that investments in student support personnel such as social workers, health services, and guidance counselors, in schools with concentrated low-income student populations could go a long way toward closing socioeconomic achievement gaps.

The third study examines individual pathways that lead to high school graduation or dropout. It employs a variety of machine learning techniques, including decision trees, random forests with bagging and boosting, and support vector machines, to predict student dropout using longitudinal administrative data from North Carolina. I consider a large set of predictor measures from grades three through eight including academic achievement, behavioral indicators, and background characteristics. My findings indicate that the most important predictors include eighth grade absences, math scores, and age-for-grade as well as early reading scores. Support vector classification (with a high cost parameter and low gamma parameter) predicts high school dropout with the highest overall validity in the testing dataset at 90.1 percent followed by decision trees with boosting and interaction terms at 89.5 percent.

Utilizing Traditional Cognitive Measures of Academic Preparation to Predict First-Year Science, Technology, Engineering, and Mathematics (STEM) Majors' Success in Math and Science Courses

For the past several years, U.S. colleges and universities have faced increased pressure to improve retention and graduation rates. At the same time, educational institutions have placed a greater emphasis on the importance of enrolling more students in STEM (science, technology, engineering and mathematics) programs and producing more STEM graduates. The resulting problem faced by educators involves finding new ways to support the success of STEM majors, regardless of their pre-college academic preparation. The purpose of my research study involved utilizing first-year STEM majors’ math SAT scores, unweighted high school GPA, math placement test scores, and the highest level of math taken in high school to develop models for predicting those who were likely to pass their first math and science courses. In doing so, the study aimed to provide a strategy to address the challenge of improving the passing rates of those first-year students attempting STEM-related courses. The study sample included 1018 first-year STEM majors who had entered the same large, public, urban, Hispanic-serving, research university in the Southeastern U.S. between 2010 and 2012. The research design involved the use of hierarchical logistic regression to determine the significance of utilizing the four independent variables to develop models for predicting success in math and science. The resulting data indicated that the overall model of predictors (which included all four predictor variables) was statistically significant for predicting those students who passed their first math course and for predicting those students who passed their first science course. Individually, all four predictor variables were found to be statistically significant for predicting those who had passed math, with the unweighted high school GPA and the highest math taken in high school accounting for the largest amount of unique variance. Those two variables also improved the regression model’s percentage of correctly predicting that dependent variable. The only variable that was found to be statistically significant for predicting those who had passed science was the students’ unweighted high school GPA. Overall, the results of my study have been offered as my contribution to the literature on predicting first-year student success, especially within the STEM disciplines.

The background impact in HEI math lectures: an experience in math in the 1st year of Accounting and Management Degree

It is a fact, and far from being a new one, that students have been entering Higher Education courses with many different backgrounds in terms of secondary school programs they attended. The impact of these basic skills is a general and worldwide challenge, fundamentally when facing some specific “constructive” subjects like foreign languages and Mathematics. Working with students with an extensive variety of Math qualifications is an outrageous challenge when they enter an advanced Math course, leading to an almost generalized expectations’ failure - from students enrolled in course and from their teachers, who feel powerless in trying to monitor knowledge construction from completely different “starting points”. If teachers’ "haste" is average, more than half of the students do not “go along” and give up, even before experiencing any kind of evaluation procedure. On the contrary, if the “speed” is too low, others are discouraged (feeling not progressing at all) and the teacher runs the risk of not meeting the minimum objectives (general and specific) of its course, which may have a negative impact on students’ future training development. Failure in Mathematics, despite being a recurrent and global issue, does not have any “magical solution”, however, in general, teachers in this area seem untiring, searching, investigating, trying and implementing new and old “recipes” to tackle and demystify this subject. In this article we describe a project developed in a Math course, with the first year students from an Accounting and Management bachelor degree, and its outcomes since it was brought to practice, revealing its impact in students’ success, from approval to dropout rates, in this course. We will shortly describe students’ differentiated Math backgrounds, their results in a pre-assessment analysis and how we try to deal with these differences and level them up, having in mind the same “finish line”. One should never forget that all these students where officially accepted in higher education institutions, so they are ones’ reality, the reality of institutions whose name one should value and strive to defend.

Prosocial behavior and self-concept of Spanish students of Compulsory Secondary Education

This study analyzed the relationship between prosocial behavior and self-concept dimensions in a sample of 2022 Spanish students (51.1% males) of Compulsory Secondary Education. The prosocial behavior was measured with the Prosocial Behavior scale of the Teenage Inventory of Social Skills (TISS) and the self-concept was measured with the Self-Description Questionnaire-II (SDQ-II). Logistic regression analyses revealed that prosocial behavior is a positive and significant statistically predictor of high scores on the following self-concept dimensions: physical ability, parent relations, same-sex relations, opposite-sex relations, verbal, school, trustworthiness, and self-esteem. Those results were found in males, females and every Compulsory Secondary education year. However, prosocial behavior is not a significant statistically predictor of high scores on physical appearance, math, and emotional stability.

STUDENTS’ PERCEPTIONS OF TEACHER INSTRUMENTAL SUPPORT AS A PREDICTOR OF MOTIVATION IN READING AND MATH AND ACHIEVEMENT FROM SECOND THROUGH TWELFTH GRADE

In this study, relations among students’ perceptions of instrumental help/support from their teachers and their reading and math ability beliefs, subjective task values, and academic grades, were explored from elementary through high school. These relations were examined in an overall sample of 1,062 students from the Childhood and Beyond (CAB) study dataset, a cohort-sequential study that followed students from elementary to high school and beyond. Multi-group structural equation model (SEM) analyses were used to explore these relations in adjacent grade pairs (e.g., second grade to third grade) in elementary school and from middle school through high school separately for males and females. In addition, multi-group latent growth curve (LGC) analyses were used to explore the associations among change in the variables of interest from middle school through high school separately for males and females. The results showed that students’ perceptions of instrumental help from teachers significantly positively predicted: (a) students’ math ability beliefs and reading and math task values in elementary school within the same grade for both girls and boys, and (b) students’ reading and math ability beliefs, reading and math task values, and GPA in middle and high school within the same grade for both girls and boys. Overall, students’ perceptions of instrumental help from teachers more consistently predicted ability beliefs and task values in the academic domain of math than in the academic domain of reading. Although there were some statistically significant differences in the models for girls and boys, the direction and strength of the relations in the models were generally similar for both girls and boys. The implications for these findings and suggestions for future research are discussed.

e-Math Workshops : a forum for exchanging experiences of mathematics e-learning at university level

We report here about a series of international workshops on e-learning of mathematics at university level, which have been jointly organized by the three publicly funded open universities in the Iberian Peninsula and which have taken place annually since 2009. The history, achievements and prospects for the future of this initiative will be addressed.

Patient education in glaucoma: what do patients know about glaucoma?

PURPOSE: To evaluate the knowledge glaucoma patients have about their disease and its treatment. METHODS: One hundred and eighty-three patients were interviewed at the Glaucoma Service of Wills Eye Hospital (Philadelphia, USA, Group 1) and 100 at the Glaucoma Service of University of Campinas (Campinas, Brazil, Group 2). An informal, relaxed atmosphere was created by the interviewer before asking a list of 18 open-ended questions. RESULTS: In Group 1, 44% of the 183 patients did not have an acceptable idea about what glaucoma is, 30% did not know the purpose of the medications they were taking, 47% were not aware of what was an average intraocular pressure, and 45% did not understand why visual fields were examined. In Group 2, 54% gave unsatisfactory answers to the question What is glaucoma?, 54% did not know the purpose of the medications they were taking, 80% were not aware of what was an average intraocular pressure, and 94% did not understand why visual fields were examined (p<0.001). Linear regression analysis demonstrated that level of education was positively correlated to knowledge about glaucoma in both groups (r=0.65, p=0.001). CONCLUSION: This study showed that patients' knowledge about glaucoma varies greatly, and that in an urban, American setting, around one third of the patients have minimal understanding, whereas in an urban setting in Brazil around two thirds of patients were lacking basic information about glaucoma. Innovative and effective methods are needed to correct this situation.

Educação física e inclusão educacional : entender para atender = Physical education and educational inclusion : understanding to attend

Universidade Estadual de Campinas . Faculdade de Educação Física

Pedagogia do esporte : organização, sistematização, aplicação e avaliação de conteúdos esportivos na educação não formal = Sport pedagogy : organization, systematization and application of sports content in non-formal education

Universidade Estadual de Campinas . Faculdade de Educação Física

Cidadania e educação física : matrizes históricas e políticas, contradições e perspectivas = Citizenship and physical education : historical and political matrices, perspectives and contradictions

Universidade Estadual de Campinas . Faculdade de Educação Física

O esporte paralímpico na formação do profissional em educação física : percepção de professores e acadêmicos = The paralympic sport in physical education professional forming: perceptions of teachers and students

Universidade Estadual de Campinas . Faculdade de Educação Física

Trajetórias de vida : lembranças, caminhos e constituições dos saberes docentes de professores de Educação Física = Paths and trajectories of life : memories, paths and establishment of teaching knowledge of Physical Education Professors

Universidade Estadual de Campinas . Faculdade de Educação Física

Corpos na escola : (des)compassos entre a educação física e a religião = Bodies in school: (un)measures between physical education and religion

Universidade Estadual de Campinas . Faculdade de Educação Física