On September 20, 2017, Hurricane Maria struck the island of Puerto Rico. The damage was extensive, and many people found themselves to be natural disaster refugees. As a result, schools in Central Florida saw an influx of new students who had their educations interrupted by the disaster and now were resuming school in a new language of instruction. These students not only faced linguistic challenges but also academic differences due to the high prevalence of poverty and the effects of neocolonialism in their previous schooling. This mixed methods study implemented an intensive intervention in probability to aid students in developing mathematical understanding and forming meaningful connections. Student participants, who had been affected by Hurricane Maria, were now attending a public high school and were paired one-on-one with a bilingual, mathematically high performing student mentor to complete culturally responsive, bilingual probability tasks. Data collection occurred over the course of six weeks in fall 2019. Both mentor and mentee students participated in focus group interviews, and the mentees completed a probability pre-test and post-test. Student participants were found to have statistically significant increases in the understanding of probability concepts when comparing pre-intervention and post-intervention results, with the understanding and usage of the multiplication rule showing the most significant improvement. Both mentors and mentees reported feeling a stronger sense of unity and belonging post-intervention as well as improvement in bilingual academic vocabulary. With the impact of natural disasters on the rise, implications of this study include its adaption to respond to future displaced students as they resume schooling post-interruption in Central Florida and beyond.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-7723 |
| Date | 01 January 2019 |
| Creators | Kurtz, Brianna |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations |
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