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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
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Michelle Pauley Murphy; Woei Hung – TechTrends: Linking Research and Practice to Improve Learning, 2024
Constructing a consensus problem space from extensive qualitative data for an ill-structured real-life problem and expressing the result to a broader audience is challenging. To effectively communicate a complex problem space, visualization of that problem space must elucidate inter-causal relationships among the problem variables. In this…
Descriptors: Information Retrieval, Data Analysis, Pattern Recognition, Artificial Intelligence
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William Cain – TechTrends: Linking Research and Practice to Improve Learning, 2024
This paper explores the transformative potential of Large Language Models Artificial Intelligence (LLM AI) in educational contexts, particularly focusing on the innovative practice of prompt engineering. Prompt engineering, characterized by three essential components of content knowledge, critical thinking, and iterative design, emerges as a key…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Prompting