Business Intelligence Analyst The University of North Texas Health Science Center Arlington, Texas, United States
Session Abstract: This session examines the role of sentiment analysis and opinion mining in education, emphasizing how these technologies can enhance student outcomes, foster learner engagement, and inform institutional strategies. Participants will explore various sentiment levels, annotation techniques, and the application of AI in educational prediction models. Ethical considerations, including data privacy, bias, and accuracy, will also be addressed, providing attendees with strategies for responsibly implementing sentiment analysis in their institutions. Attendees will learn about methods such as machine learning and natural language processing (NLP) tools like NLTK and spaCy, alongside key educational data sources. By the end of the session, participants will have a solid understanding of sentiment analysis, including insights derived from course evaluations and student feedback, equipping them to effectively interpret sentiments and enhance educational experiences for all stakeholders.
Keywords: sentiment analysis, AI in education, data analytics, education technology
