Professor Li Kun Chung

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Five Steps of Teaching with Generative AI
Abstract
This report aims to elucidate the five steps of teaching with generative AI, assisting teachers in mastering the teaching principle of "use wisely, not prohibit; an assistant, not a ghostwriter." The five steps of teaching with generative AI are "Preparation, Prompt, Verification, Integration, and Optimization."
1.Preparation involves comprehensive readiness, adhering to the premise that "good preparation leads to good questioning, and asking the right questions is more important than providing the right answers." This step encourages students to awaken old experiences or prior knowledge, collect and read new information, and form preliminary ideas.
2.Prompt focuses on precise inquiry. Questions should fit the role scenario, task theme, action level, and output requirements, and provide appropriate guiding examples or advanced inquiries. Teachers must guide students in developing a questioning scaffold.
3.Verification entails critical examination, specifically scrutinizing the information provided by generative AI for accuracy or errors, consistency of content, relevance to related information, comprehensiveness, bias, and potential violations of privacy and intellectual property rights.
4.Integration represents diverse consolidation, integrating the results of multiple uses of generative AI with the knowledge (or skills and attitudes), academic journal articles, and peer discussions taught by teachers. It can consider both horizontal and vertical integration, adopting methods from physical to chemical integration.
5.Optimization/Annotation involves optimizing the integrated results and appropriately annotating and citing them to avoid plagiarism and infringement, striving for innovation and improvement. It emphasizes strengthening the PDCA (Plan-Do-Check-Act) quality assurance cycle and competency-oriented teaching.
These steps guide teachers in effectively leveraging generative AI in education, emphasizing preparation, critical thinking, and integration to enhance teaching and learning outcomes.
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Important Dates
Submission Deadline
Extended to September 15, 2024
Notification of Acceptance
From August 10, 2024
Early Bird Registration Deadline
Extended to September 30, 2024
Registration Deadline
September 30, 2024
Conference Dates
November 21 - 23, 2024
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