Using LEGO Robots to Support Understanding of Absolute Value in a Mathematics Classroom

This presentation will allow participants to become middle school mathematics students as they apply their understanding of absolute value through the use of LEGO robots. A classroom lesson will be conducted (with the participants playing the role of the student) to show how LEGO robots can be an engaging tool to create collaboration among students as well as support the understanding of concepts. Participants will work in groups of 2-3 to operate a robot along a number line and record data on a task sheet as the robot moves forward or backward in random increments. This presentation will culminate with a discussion regarding participants’ reactions to the activity and its implication for classroom use

Using LEGO robots to support understanding of absolute value in a mathematics classroom

Presentation co-presented by Georgia Southern faculty member Shelli L. Casler-Failing with students Ann Mitchem and Jillian Arnold at Interdisciplinary STEM Teaching and Learning Conference, Savannah, GA. This presentation will allow participants to become middle school mathematics students as they apply their understanding of absolute value through the use of LEGO robots. A classroom lesson will be conducted (with the participants playing the role of the student) to show how LEGO robots can be an engaging tool to create collaboration among students as well as support the understanding of concepts. Participants will work in groups of 2-3 to operate a robot along a number line and record data on a task sheet as the robot moves forward or backward in random increments. This presentation will culminate with a discussion regarding participants’ reactions to the activity and its implication for classroom use

Analysis of Horizontal Axis Wind Turbine Array Optimization

Wind energy is the fastest growing form of renewable energy, with a multitude of possibilities for expansion. This, as well as other forms of renewable energy, will facilitate understanding of the growing concerns regarding global warming by decreasing our dependence on fossil fuels. Wind energy requires wind speeds of at least six miles per hour; therefore, only certain geographical areas are suitable for the use of this technology. The purpose of this experiment was to determine whether the orientation of an array of wind turbines increases or decreases energy production and efficiency. In this study, various arrays consisting of five wind turbines were tested. The total energy output of each array was tested using a wind tunnel from the wind energy lab at Georgia Southern University, INA219 current sensors, custom software written by Matthew Kiernan, and five “Cutting Edge Power” wind turbines. The most efficient array in terms of voltage, power and current was the 2-1-2 array, with average outputs of: voltage at 3.98 V, current at 440.73 mA, and power at 900.92 mW. The efficiency was determined through the power coefficient, which was 32.64%. The next most efficient array was the Left-Right Staggered array, with averages of: voltage at 3.90 V, current at 208.47 mA, and power at 838.08 mW. The efficiency was determined through the power coefficient, which was 32.13%. The Diagonal array was the third most efficient in overall energy output, with averages of: voltage at 3.75 V, current at 200.66 mA, and power at 789.07 mW. The efficiency was determined through the power coefficient, which was 29.54. The least efficient array array for energy output was Single File, with averages of: voltage at 2.79 V, current at 137.69 mA, and power at 451.05 mW. The efficiency was determined through the power coefficient, which was 18.31%. The results demonstrated that the close proximity of turbines negatively affects energy output, as observed through the turbulence that was produced. Possible errors observed were due to turbine models that did not perform as expected as well as the breadboard configuration

Relations between sinkhole density and anthropogenic contaminants in selected carbonate aquifers in the eastern United States

The relation between sinkhole density and water quality was investigated in seven selected carbonate aquifers in the eastern United States. Sinkhole density for these aquifers was grouped into high (\u3e25 sinkholes/100 km2), medium (1–25 sinkholes/100 km2), or low (\u3c1 sinkhole/100 km2) categories using a geographical information system that included four independent databases covering parts of Alabama, Florida, Missouri, Pennsylvania, and Tennessee. Field measurements and concentrations of major ions, nitrate, and selected pesticides in samples from 451 wells and 70 springs were included in the water-quality database. Data were collected as a part of the US Geological Survey (USGS) National Water-Quality Assessment (NAWQA) Program. Areas with high and medium sinkhole density had the greatest well depths and depths to water, the lowest concentrations of total dissolved solids and bicarbonate, the highest concentrations of dissolved oxygen, and the lowest partial pressure of CO2 compared to areas with low sinkhole density. These chemical indicators are consistent conceptually with a conduit-flow-dominated system in areas with a high density of sinkholes and a diffuse-flow-dominated system in areas with a low density of sinkholes. Higher cave density and spring discharge in Pennsylvania also support the concept that the high sinkhole density areas are dominated by conduit-flow systems. Concentrations of nitrate-N were significantly higher (p \u3c 0.05) in areas with high and medium sinkhole density than in low sinkhole-density areas; when accounting for the variations in land use near the sampling sites, the high sinkhole-density area still had higher concentrations of nitrate-N than the low sinkhole-density area. Detection frequencies of atrazine, simazine, metolachlor, prometon, and the atrazine degradate deethylatrazine indicated a pattern similar to nitrate; highest pesticide detections were associated with high sinkhole-density areas. These patterns generally persisted when analyzing the detection frequency by land