Project # 48
Center name: Dr. Terri Kurz's Research Team
Campus/Location: Fully remote
Faculty lead: Terri Kurz
Project description
Teacher retention is a problem on a national scale. Teachers enter the field but do not persist, eventually leaving the profession. Teacher turnover is a problem in many communities throughout the nation but is particularly widespread in Arizona. Arizona teachers are more likely to say they will leave the profession, and data show they do, in fact, leave at one of the highest rates in the nation. Per year, approximately one out of every four Arizona teachers (24%) quit the profession or switch districts compared to a national rate of 8% (Sutcher et al., 2019). Using 10 years of data (2011-2021), Barrett Fellows will support the organization of data. The focus will be on tracking Maricopa County teachers’ persistence in the profession, specifically examining whether or not preparation plays a role in their persistence. All data are anonymous and provided by the Arizona Department of Education. The data are disorganized, messy and spread across multiple Excel documents. Barrett Fellows participation in this project will focus specifically on the organization of data of all teachers who entered the profession across that 10-year period.
Special skills needed
Any major that focuses on data is welcomed (a major in education is not required); specific skills needed include: 1) data analysis - the ability to analyze the data to understand its structure, patterns, and anomalies is crucial (this includes identifying missing data, outliers, duplicates, and inconsistencies); 2) problem-solving - a problem-solving mindset is essential to devise appropriate strategies to clean and organize the data (this involves breaking down complex data sets into manageable parts and developing logical solutions); 3) attention to detail - being meticulous in spotting errors, discrepancies, and patterns is crucial to effectively organize the data (small details can significantly impact the accuracy and reliability of the final results); 4) familiarity with Excel - proficiency in using data spreadsheets is necessary (these tools enable data sorting, filtering, and transformation, making it easier to organize and clean the data); and 5) finding enjoyment in working independently with data.
Majors
Any undergraduate major that focuses on data collection or analysis would best fit this project. Appropriate majors might include: Statistics, Data Science, Mathematics, Computer Science or Education (with a strong background in mathematics or STEM). Anyone with a strong STEM background who enjoys data might be a good fit for this project.
Years
3rd-year students, 4th-year students
Themes
Cross-listed with the following themes:
Data Analytics and Mathematics, Education