Machine Learning-Driven Avatars in Education

dc.contributor.advisor	Eichelberger, Ariana
dc.contributor.advisor	Hoffman, Daniel
dc.creator	Thompson, Jesse
dc.date.accessioned	2024-05-03T19:26:35Z
dc.date.available	2024-05-03T19:26:35Z
dc.date.copyright	2024
dc.date.issued	2024-05-03
dc.description.abstract	For new and existing educators, using virtual characters as pedagogical agents has been shown to increase learner engagement; however, many perceive this technique as costly and complex. Recent advances in machine learning-based facial action coding recognition have made implementing virtual characters into content more accessible and affordable than ever. Introduction to Virtual Avatars for Instruction is a course designed to bridge this gap and change educators’ attitudes about virtual character-led instruction. The course aimed to provide learners with the key technologies, terms, and examples needed to add virtual characters to instructional content. Results from participants (n = 15) showed an increased understanding of key terms and concepts. Attitudinal changes demonstrated a shift away from concerns regarding the cost and skills required to implement virtual characters.
dc.identifier.uri	https://hdl.handle.net/10125/108071
dc.rights	http://rightsstatements.org/vocab/InC-NC/1.0/
dc.title	Machine Learning-Driven Avatars in Education
dcterms.rights	CC BY-NC 4.0
dcterms.type	Text
dspace.entity.type

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