NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 4 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Todd Cherner; Teresa S. Foulger; Margaret Donnelly – TechTrends: Linking Research and Practice to Improve Learning, 2025
The ethics surrounding the development and deployment of generative artificial intelligence (genAI) is an important topic as institutions of higher education adopt the technology for educational purposes. Concurrently, stakeholders from various organizations have reviewed the literature about the ethics of genAI and proposed frameworks about it.…
Descriptors: Artificial Intelligence, Natural Language Processing, Decision Making, Models
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Danah Henriksen; Punya Mishra; Lauren Woo; Nicole Oster – Impacting Education: Journal on Transforming Professional Practice, 2025
The emergence of generative artificial intelligence (GenAI) fundamentally shifts how educational knowledge is created, shared, and validated. Through the lens of epistemic technologies--tools that transform knowledge creation and dissemination--we analyze how GenAI challenges traditional notions of practical wisdom in education doctorate (EdD)…
Descriptors: Doctoral Programs, Education Majors, Artificial Intelligence, Natural Language Processing
Peer reviewed Peer reviewed
Direct linkDirect link
Stephanie Moore; Amir Hedayati-Mehdiabadi; Victor Law; Sung Pil Kang – TechTrends: Linking Research and Practice to Improve Learning, 2024
Early hype cycles surrounding new technologies may promote simplistic binary options of either adoption or rejection, but socio-historical analyses of technologies illuminate how they are worked into shape by human actors. Humans enact agency through many choices that result in adaptations and contextual variations. In this piece, we argue that…
Descriptors: Artificial Intelligence, Natural Language Processing, Man Machine Systems, Ethics
Alex Warstadt – ProQuest LLC, 2022
Data-driven learning uncontroversially plays a role in human language acquisition--how large a role is a matter of much debate. The success of artificial neural networks in NLP in recent years calls for a re-evaluation of our understanding of the possibilities for learning grammar from data alone. This dissertation argues the case for using…
Descriptors: Language Acquisition, Artificial Intelligence, Computational Linguistics, Ethics