Multidisciplinary Engagement of Diverse Students in Computer Science Education through Research Focused on Social Media COVID-19 Misinformation
129th ASEE Annual Conference and Exposition: Excellence Through Diversity, ASEE 2022
; 2022.
Article
in English
| Scopus | ID: covidwho-2045096
ABSTRACT
The ongoing COVID-19 pandemic has disrupted vital elements of personal and public health, society, and education. Increasingly with the viral pandemic, misinformation on health and science issues has been disseminated online. We developed an undergraduate training program focused on producing and presenting research to combat the rampant spread of this misinformation. Online misinformation represents a complex, multidisciplinary problem. Consequently, recruitment of students to the program was not exclusive to those from Computer Science or Science, Technology, Engineering, and Math (STEM) educational backgrounds. Participants were actively recruited from fields such as Linguistics, Social and Political sciences. This data analytics outreach program aimed to train educationally and demographically diverse undergraduate students in computational techniques and presentation skills through guided research regarding the current burst of misinformation. Over ten weeks, participants were instructed in an online curriculum covering five milestones Python programming, data processing, machine learning with natural language processing, visualization, and presentation. Subsequently, participants were engaged in Computer Science research analyzing a real-world data set gathered from Twitter™ 1 between January and June 2020. Participants were organized into teams to investigate subtopics within the broader subject of misinformation 1) detecting social media bot accounts, 2) identifying propaganda with computational methods, and 3) studying the discourse surrounding science preprints (i.e., papers that have been posted to the Internet but have not been peer reviewed). The program culminated in an exposition where each team presented research results to program officers, senior faculty, deans, government officials, and industry experts. Here we present the program curriculum, metrics of educational effectiveness, and feedback collected from participants. © American Society for Engineering Education, 2022.
Computer programming; Curricula; Data Analytics; Data handling; Data visualization; Engineering education; Learning algorithms; Learning systems; Natural language processing systems; Social networking (online); Students; Computational technique; Computer Science Education; Multidisciplinary problems; Outreach programs; Political science; Science technologies; Social media; Training program; Undergraduate students; COVID-19
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Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
129th ASEE Annual Conference and Exposition: Excellence Through Diversity, ASEE 2022
Year:
2022
Document Type:
Article
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