Education in the ChatGPT Era: A Sentiment Analysis of Public Discourse on the Role of Language Models in Education - Niel Francis B. Casillano (Journal Evaluation in Education (JEE), 2024)
Purpose of the study: This research explored the public discourse on the role of language models in education, particularly ChatGPT. Methodology: The study employed sentiment analysis, word cloud analysis, and thematic analysis of YouTube video news transcripts. Main Findings: The study identified key themes and public perceptions surrounding AI's role in education. The analysis revealed frequent mentions of AI, education, and learning, highlighting AI's transformative potential in personalizing education and improving administrative efficiency. The study also emphasizes significant concerns about academic integrity, with terms like cheating and plagiarism reflecting ethical apprehensions. The sentiment analysis revealed a compound sentiment of 0.866, a generally positive perception of AI's impact on education. However, some negative sentiments were recorded, particularly around data privacy and potential biases. The thematic analysis identified five key topics: the future of AI and human intelligence, AI in education and learning enhancement, innovative teaching tools and technologies, AI-assisted writing and learning tools, and ethics and academic integrity in AI usage. The findings revealed the importance of developing robust ethical guidelines and policies for integrating AI into educational settings and the need for further research into the long-term impacts of AI on teaching methodologies. Novelty/Originality of this study: The research used YouTube news transcripts to explore public discourse on ChatGPT's role in education, providing real-time insights into societal perceptions. Combining sentiment, word cloud, and thematic analyses offers a balanced examination of the transformative potential and ethical concerns surrounding AI in education.