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Jinhee Kim; Young Hoan Cho – Asia Pacific Journal of Education, 2025
Educators expect artificial intelligence (AI) to augment student capabilities and rapidly transform teaching and learning practices. However, little is known about students' perceptions of AI and what they expect from AI in student-AI teaming. There is a lack of holistic understanding of the nature, effects, and areas of improvement in teamwork by…
Descriptors: Artificial Intelligence, Technology Uses in Education, Student Attitudes, Expectation
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Jonathan W. Camp; Heather Johnson – Communication Teacher, 2025
This paper introduces generative AI for the graphic design of student presentation aids in a university public-speaking classroom. Students learn to use generative AI as an efficient enhancement to the creative process while preserving the integrity of the content. Students' slide presentations show improvement resulting from the activity, and…
Descriptors: Artificial Intelligence, Technology Uses in Education, Public Speaking, Computer Software
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Jinhee Kim; Yoonhee Ham; Sang-Soog Lee – Australasian Journal of Educational Technology, 2024
Recent advances and applications of artificial intelligence (AI) have increased the opportunities for students to interact with AI in their learning tasks. Although various fields of scholarly research have investigated human-AI collaboration, the underlying processes of how students collaborate with AI in a student-AI teaming scenario have been…
Descriptors: Artificial Intelligence, Computer Graphics, Freehand Drawing, Assignments
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Lee, Sang Yeal – Journal of Advertising Education, 2019
The changes in the advertising industry are rapid and dizzying. The advertising industry is going through structural change and advertising education faces a daunting challenge in keeping up with the real world. Advertising educators must recognize the urgency of revising the curriculum to address this challenge. If not, while the industry…
Descriptors: Advertising, Change, Teaching Methods, Educational Change
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Essa, Alfred; Ayad, Hanan – Research in Learning Technology, 2012
The need to educate a competitive workforce is a global problem. In the US, for example, despite billions of dollars spent to improve the educational system, approximately 35% of students never finish high school. The drop rate among some demographic groups is as high as 50-60%. At the college level in the US only 30% of students graduate from…
Descriptors: Artificial Intelligence, Computer Graphics, Computer Interfaces, Statistical Analysis
Madhyastha, Tara M.; Tanimoto, Steven – International Working Group on Educational Data Mining, 2009
Most of the emphasis on mining online assessment logs has been to identify content-specific errors. However, the pattern of general "consistency" is domain independent, strongly related to performance, and can itself be a target of educational data mining. We demonstrate that simple consistency indicators are related to student outcomes,…
Descriptors: Web Based Instruction, Computer Assisted Testing, Computer Software, Computer Science Education