Perceptions of STEM education and artificial intelligence: a Twitter (X) sentiment analysis
Demetrice Smith-Mutegi, Yoseph Mamo, Jinhee Kim, Helen Crompton, Matthew McConnell
Abstract
Artificial intelligence (AI) is becoming increasingly prevalent in science, technology, engineering, and mathematics (STEM) education, holding promising potential for supporting the design and implementation of quality STEM education. However, there is a lack of data-based research studying the diverse perceptions of AI in STEM education as conveyed on social media, the factors that influence those perceptions, or the change in those perceptions over time among public audiences. The purpose of this study was to examine public perceptions of AI in STEM education by analyzing X posts (Tweets) between 04/28/2020 and 04/27/2023. We used a machine learning-based sentiment analysis to analyze the public’s perception of AI and the factors that influence it. Findings suggest a range of perceptions among X users regarding AI in STEM education, with most sentiments neutral and positive. However, some negative sentiments were also identified, suggesting that some users may be wary of AI’s potential impact on STEM education. This work will contribute to government, policymakers, and educators in making necessary decisions and improving overall public awareness of AI in STEM education. Additionally, the results of this study suggest that further research is needed to better understand public sentiment about AI in STEM education.