This project explores the relationship between teaching qualities and student ratings of professors, utilizing a dataset from RateMyProfessor.com. The research focuses on identifying how specific teaching behaviors—such as providing feedback, delivering inspirational lectures, and being a tough grader—impact overall student evaluations. Additionally, it examines whether there are differences in ratings between online and in-person courses. By applying techniques such as sentiment analysis, topic modeling, and statistical testing, the project aims to provide actionable insights for educators and administrators to improve teaching practices and course design, ultimately enhancing student engagement and satisfaction.

This study analyzes public sentiment and emotional trends in Twitter discussions about Common Core State Standards (CCSS) and Next Generation Science Standards (NGSS). Using text mining and sentiment analysis (Bing, AFINN, NRC), it explores how opinions have evolved over time and compares emotional responses. Findings provide insights for educators and policymakers to understand public perceptions and improve communication strategies.

In this independent analysis, I utilized the opd_survey.csv dataset from our case study, which is located in the data folder within the Unit 1 Analysis Project. The analysis focused on exploring the usage and effectiveness of online professional development (PD) resources among educators. Using data manipulation, visualization, and text analysis techniques, I identified key trends in PD resource preferences, engagement levels, and perceived benefits.

This project explores the Usage of Social Media Among Students, focusing on understanding how social media habits influence academic productivity, behaviors, and perceptions. Through a detailed analysis of demographic characteristics, Fear of Missing Out (FOMO), time spent on social media, and its academic versus non-academic purposes, the project aims to uncover meaningful patterns and relationships. The findings are designed to benefit students, educators, and policymakers by providing actionable insights into balancing social media usage for optimal academic engagement and personal well-being. The study combines descriptive statistics, visualizations, and predictive modeling to address critical questions about the role of social media in students' lives.