Students from Warren Easton Charter High School – currently the top ranked open admission high school (public or Charter) in the city of New Orleans – are taking advantage of a unique collaboration with the LADC-GEMM research group at the University of New Orleans, to analyze underwater acoustical data collected during the LADC-GEMM 2015 field season. Warren Easton physics teacher, Kendal Leftwich, is also perusing a PhD in physics at the University of New Orleans: as graduate research assistant in the LADC-GEMM project, he is the bridge for this distinctive partnership.
Five students are in the Warren Easton Research group that is working with the LADC-GEMM team from UNO: 4 high schoolers in AP Physics 1, and an 8th grade student. Easton has out-performed almost all other schools in the district and has improved its SPS score for five consecutive years. The school’s mission slogan is “We believe in success.” It has a student population that is 96.6% Black or African American and 2.59% Hispanic or Latino and over 80% of the students qualify for free and reduced lunch due to the socioeconomic status of their families. The school’s reputation of academic excellence, high attendance, low drop-out rate and high graduation rate were all factors that earned the school National Blue Ribbon designation by the United States Department of Education.
The aim of the Warren Easton research group is for students to learn to work independently using scholarly works to analyze and interpret data, as well as to communicate and collaborate in a professional environment.
In order to accomplish these goals, the students will be analyzing data for sperm whale, beaked whale and dolphins sounds, using a graphical user interface created by Kirk Bienvenu, another UNO PhD graduate student research assistant on the LADC-GEMM research team.
Each student will be required to create and submit a weekly PowerPoint of the data he or she analyzed. The PowerPoint will include the signals found, especially the times and locations. The students will compare signals in the data to sounds described in scientific publications, in order to determine the source or species of the signals in the data.
In addition to having the opportunity to work with data from their own ‘backyard’, the students will earn community service hours as well as receive credit for the job shadowing requirement to graduate.