Attempting to improve standardized test results using Study Islands' web-based mastery program

State standardized testing has always been a tool to measure a school’s performance and to help evaluate school curriculum. However, with the school of choice legislation in 1992, the MEAP test became a measuring stick to grade schools by and a major tool in attracting school of choice students. Now, declining enrollment and a state budget struggling to stay out of the red have made school of choice students more important than ever before. MEAP scores have become the deciding factor in some cases. For the past five years, the Hancock Middle School staff has been working hard to improve their students’ MEAP scores in accordance with President Bush's “No Child Left Behind” legislation. In 2005, the school was awarded a grant that enabled staff to work for two years on writing and working towards school goals that were based on the improvement of MEAP scores in writing and math. As part of this effort, the school purchased an internet-based program geared at giving students practice on state content standards. This study examined the results of efforts by Hancock Middle School to help improve student scores in mathematics on the MEAP test through the use of an online program called “Study Island.” In the past, the program was used to remediate students, and as a review with an incentive at the end of the year for students completing a certain number of objectives. It had also been used as a review before upcoming MEAP testing in the fall. All of these methods may have helped a few students perform at an increased level on their standardized test, but the question remained of whether a sustained use of the program in a classroom setting would increase an understanding of concepts and performance on the MEAP for the masses. This study addressed this question. Student MEAP scores and Study Island data from experimental and comparison groups of students were compared to understand how a sustained use of Study Island in the classroom would impact student test scores on the MEAP. In addition, these data were analyzed to determine whether Study Island results provide a good indicator of students’ MEAP performance. The results of the study suggest that there were limited benefits related to sustained use of Study Island and gave some indications about the effectiveness of the mathematics curriculum at Hancock Middle School. These results and implications for instruction are discussed.

DEVELOPMENT OF AN OPTIMIZATION MODEL FOR BIOFUEL FACILITY SIZE AND LOCATION AND A SIMULATION MODEL FOR DESIGN OF A BIOFUEL SUPPLY CHAIN

A range of societal issues have been caused by fossil fuel consumption in the transportation sector in the United States (U.S.), including health related air pollution, climate change, the dependence on imported oil, and other oil related national security concerns. Biofuels production from various lignocellulosic biomass types such as wood, forest residues, and agriculture residues have the potential to replace a substantial portion of the total fossil fuel consumption. This research focuses on locating biofuel facilities and designing the biofuel supply chain to minimize the overall cost. For this purpose an integrated methodology was proposed by combining the GIS technology with simulation and optimization modeling methods. The GIS based methodology was used as a precursor for selecting biofuel facility locations by employing a series of decision factors. The resulted candidate sites for biofuel production served as inputs for simulation and optimization modeling. As a precursor to simulation or optimization modeling, the GIS-based methodology was used to preselect potential biofuel facility locations for biofuel production from forest biomass. Candidate locations were selected based on a set of evaluation criteria, including: county boundaries, a railroad transportation network, a state/federal road transportation network, water body (rivers, lakes, etc.) dispersion, city and village dispersion, a population census, biomass production, and no co-location with co-fired power plants. The simulation and optimization models were built around key supply activities including biomass harvesting/forwarding, transportation and storage. The built onsite storage served for spring breakup period where road restrictions were in place and truck transportation on certain roads was limited. Both models were evaluated using multiple performance indicators, including cost (consisting of the delivered feedstock cost, and inventory holding cost), energy consumption, and GHG emissions. The impact of energy consumption and GHG emissions were expressed in monetary terms to keep consistent with cost. Compared with the optimization model, the simulation model represents a more dynamic look at a 20-year operation by considering the impacts associated with building inventory at the biorefinery to address the limited availability of biomass feedstock during the spring breakup period. The number of trucks required per day was estimated and the inventory level all year around was tracked. Through the exchange of information across different procedures (harvesting, transportation, and biomass feedstock processing procedures), a smooth flow of biomass from harvesting areas to a biofuel facility was implemented. The optimization model was developed to address issues related to locating multiple biofuel facilities simultaneously. The size of the potential biofuel facility is set up with an upper bound of 50 MGY and a lower bound of 30 MGY. The optimization model is a static, Mathematical Programming Language (MPL)-based application which allows for sensitivity analysis by changing inputs to evaluate different scenarios. It was found that annual biofuel demand and biomass availability impacts the optimal results of biofuel facility locations and sizes.