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David Rae; Edward Cartwright; Mario Gongora; Chris Hobson; Harsh Shah – Industry and Higher Education, 2024
This paper demonstrates how the innovative application of a Collective Intelligence approach enhanced Local Skills Improvement Planning information for employers, education and skills training organisations and regional economic policy organisations. This took place within a Knowledge Transfer Partnership between a Chamber of Commerce and a…
Descriptors: Cooperative Learning, Intelligence, Knowledge Management, Skill Development
Reem Khojah; Alexandra Werth; Kelly W. Broadhead; Lawrence W. Dobrucki; Chris Geiger; David A. Rubenstein – Biomedical Engineering Education, 2025
The integration of generative artificial intelligence (GenAI) is reshaping biomedical engineering (BME) education. This paper presents insights from "The Fifth Biomedical Engineering Education Summit", which brought together educators from across the U.S. to address challenges and opportunities in integrating GenAI into BME curricula.…
Descriptors: Artificial Intelligence, Technology Uses in Education, Technology Integration, Educational Technology
Sandra Leaton Gray; Mutlu Cukurova – Cogent Education, 2024
Debates surrounding the use of data science in educational AI are frequently rather entrenched, revolving around commercial models and talk of teacher replacement. This article explores the potential for digital textual analysis within humanities and social science education, advocating for a sociologically-driven approach that complements, rather…
Descriptors: Humanities, Social Sciences, Social Science Research, Research Methodology
Preel-Dumas, Camille; Hendra, Richard; Denison, Dakota – MDRC, 2023
This brief explores data science methods that workforce programs can use to predict participant success. With access to vast amounts of data on their programs, workforce training providers can leverage their management information systems (MIS) to understand and improve their programs' outcomes. By predicting which participants are at greater risk…
Descriptors: Labor Force Development, Programs, Prediction, Success

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