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.

Technology professional development for principals: Impact on the integration of technology in elementary schools

The use of technology in schools is no longer the topic of educational debates, but how to ensure that technology is used effectively continues to be the focal point of discussions. The role of the principal in facilitating the successful integration of technology in the school is well established. To that end, the Florida Department of Education implemented the FloridaLeaders.net: a three-year professional development project in technology for school administrators. The purpose of this study was to investigate the effectiveness of this professional development project on integrating technology in elementary schools. ^ The study compared a group of schools whose principals have participated in the FloridaLeaders.net (FLN) program with schools whose principals have not participated in the program. The National Technology Standards for School Administrators and the National Technology Standards for Teachers were used as the framework to assess technology integration. ^ The sample consisted of three groups of educators: principals (n = 47), media specialists (n = 110), and teachers (n = 167). Three areas of technology utilization were investigated: (a) the use of technology in management and operations, (b) the use of technology in teaching and learning, and (c) the use of technology for assessment and evaluation. Analyses of variances were used to examine the differences in the perceptions and use of technology in each of the three areas, among the three groups of educators. ^ The findings indicated that the difference between FLN and non-FLN schools was not statistically significant in most of the technology indicators. The difference was however significant in two cases: (a) The use of technology for assessment and evaluation, and (b) The level of technology infrastructure in FLN schools. Additionally, all FLN and non-FLN groups reported the need for technology training for teachers to provide them with the necessary "know-how" to effectively integrate technology into the classrooms. ^ These findings would indicate that FloridaLeaders.net was not effective in integrating technology in schools over and above other current efforts. It is therefore concluded that the FLN project had some favorable impact but had not met all of its stated objectives. ^

The Next Generation of Scientists: Examining the Experiences of Graduate Students in Network-Level Social-Ecological Science

By integrating the research and resources of hundreds of scientists from dozens of institutions, network-level science is fast becoming one scientific model of choice to address complex problems. In the pursuit to confront pressing environmental issues such as climate change, many scientists, practitioners, policy makers, and institutions are promoting network-level research that integrates the social and ecological sciences. To understand how this scientific trend is unfolding among rising scientists, we examined how graduate students experienced one such emergent social-ecological research initiative, Integrated Science for Society and Environment, within the large-scale, geographically distributed Long Term Ecological Research (LTER) Network. Through workshops, surveys, and interviews, we found that graduate students faced challenges in how they conceptualized and practiced social-ecological research within the LTER Network. We have presented these conceptual challenges at three scales: the individual/project, the LTER site, and the LTER Network. The level of student engagement with and knowledge of the LTER Network was varied, and students faced different institutional, cultural, and logistic barriers to practicing social-ecological research. These types of challenges are unlikely to be unique to LTER graduate students; thus, our findings are relevant to other scientific networks implementing new social-ecological research initiatives.