This project aims to determine the impact that COVID-19 has had on Alberta teacher retention. Over the last two Phases, a survey was distributed to every public and Catholic school division across Alberta, querying the state of school staff hiring, retention, resignation, and retirement before and after the COVID-19 pandemic. This Phase will conclude the survey collection process, focusing on analyzing the data collected. Many data mining analysis methods will be employed to determine common factors across these teacher retention results, including clustering, decision tree analysis, correlation tables, and more. The R coding language will be used for the analysis, which will be run in the RStudio development environment. Following this analysis, a research paper will be composed, including related works, background information, and an in-depth explanation of the study and the results.

2. Clean and transform the collected data from the survey.

3. Use RStudio to conduct data analysis processes such as clustering and decision trees.

4. Record findings in an academic research paper.

The student will work under the supervision of Dr. Mohamad El-Hajj.