1. 課程設計方向：
本課程屬於「系所專業 × 資訊科技 ➞ 社會實踐」類型，以AI科技輔助學生分析畜產議題的社會脈絡，並將結果轉化為面向公眾的科學傳播內容。學生將學習如何以人工智慧協助文獻整合、輿情分析、資料可視化與內容生成，進而設計具社會影響力的傳播專案。
2. 課程執行方式：
(1) 以畜產產業實際案例出發，學生針對動物福利、畜牧碳排放、氣味污染、永續農業等主題，運用AI工具分析資料與生成文本，理解科技在社會議題詮釋中的潛能與限制。
(2) 邀請科學傳播、公民科學、農業媒體及AI應用領域之專家共8位，講授AI與資訊科技在農業傳播與政策討論中的實務應用。
(3) 設置「AI實作工作坊」，指導學生以生成式AI輔助專題製作，並反思AI使用的倫理、透明性與真實性等議題，呼應UNESCO「以人為中心」的AI應用原則。
(4) 學生分組設計「畜產公共議題傳播專案」，結合AI文本生成與多媒體製作（影音、Podcast或圖像資料視覺化），針對在地社區或校園進行展示與溝通，落實社會實踐。
(5) 課堂評量採專題導向學習（Project-based learning）與Rubric分析評量，重視學生之跨域應用能力、社會關懷意識與AI倫理反思。

1. Course design direction:
This course belongs to the type of "Department Major × Information Technology ➞ Social Practice". AI technology is used to assist students in analyzing the social context of livestock issues and transform the results into scientific communication content for the public. Students will learn how to use artificial intelligence to assist document integration, public opinion analysis, data visualization and content generation, and then design communication projects with social impact.
2. Course execution method:
(1) Starting from actual cases of the livestock industry, students use AI tools to analyze data and generate texts on topics such as animal welfare, livestock carbon emissions, odor pollution, and sustainable agriculture, and understand the potential and limitations of technology in interpreting social issues.
(2) Invite a total of 8 experts in the fields of scientific communication, citizen science, agricultural media and AI application to teach the practical application of AI and information technology in agricultural communication and policy discussions.
(3) Set up an "AI Implementation Workshop" to guide students to use generative AI to assist topic production, and to reflect on issues such as ethics, transparency and authenticity in the use of AI, echoing UNESCO's "human-centered" AI application principles.
(4) Students work in groups to design a "livestock public issue communication project", combining AI text generation and multimedia production (audio, video, podcast or image data visualization), to display and communicate for local communities or campuses, and implement social practice.
(5) Classroom assessment adopts Project-based learning and rubric analysis and assessment, focusing on students’ cross-domain application abilities, social care awareness and AI ethical reflection.

van Dam F, de Bakker L, Dijkstra AM, Jensen EA. Science Communication: World Scientific; 2019. 276 p. DOI: doi:10.1142/11541

van Dam F, de Bakker L, Dijkstra AM, Jensen EA. Science Communication: World Scientific; 2019. 276 p. DOI: doi:10.1142/11541