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  佛光大學
Fo Guang University
教學計畫表 Syllabus
 
 
課程中文名稱
Course Name in Chinese
AI與多模態傳播專題
課號
Course Code
TECH5C3000
課程英文名稱
Course Name in English
Topics on AI and Multimodal Communication
學年/學期
Academic Yeas/Semester
115 /1
開課單位/學門別
Department/Academic Discipline
應用科技與設計學院碩士班
學制別
Degree
碩士班
學分數
Credits
 3    
每週授課時數
Weekly Hours of Instruction
 3   
修別
Type
選修 Elective
課/學程別
Program
院基礎Foundation
課程分流
學術型
課程內容
Curriculum attribute
■跨領域 ■一般課程 ■SDG 9 工業化、創新及基礎建設:建立具有韌性的基礎建設,促進包容且永續的工業,並加速創新
■自學力 ■SDG 1 終結貧窮:消除各地一切形式的貧窮 ■SDG 10 減少不平等:減少國內及國家間的不平等
■實作 ■SDG 8 合適的工作及經濟成長:促進包容且永續的經濟成長,讓每個人都有一份好工作
AI暨智慧永續發展
AI暨智慧課程:AI融入課程    永續發展課程: 智慧永續入門課程
16+2課程
教學方法
Instructional Strategies
■講授 ■場域教學 ■數位融入課程(包含遠距教學、數位學習平台、zuvio、ppt、數位講桌的設備與功能、其他數位教學輔助軟體等)
■分組討論
授課教師
Instructor
郭龍
聯絡方式
lkuo@mail.fgu.edu.tw
03-9871000 #
上課時間/地點
Time of Class/Location of Class
四.2,3,4(321-1)
先修課程
Prerequisites
課程描述(若為實務型課程需含搭配產業界或非營利組織需求之說明)
Course Description
 
(中文版課程描述)
生成式 AI 的崛起,不只是一場技術革命,更是一次對傳播本質的根本性叩問:當機器能夠同時生成文字、圖像、聲音與影片,「意義」是如何被建構的?「真實」的邊界又在哪裡?
本課程以「多模態傳播」為核心概念,帶領學生從符號學、語用學與社會符號學的理論視角,深入理解生成式 AI 如何重塑當代傳播實踐。課程分為四個階段:首先建立理解 AI 多模態的概念語言,接著觀察其對新聞、廣告、公關等媒體生態的具體衝擊,再進入批判性反思——審視演算法偏見、數位殖民主義與創作勞動的倫理爭議——最終回到實踐,探索 AI 作為傳播工具與創作夥伴的可能性與侷限。
本課程特別強調台灣在地視角,討論正體中文在全球 AI 模型中的邊緣處境、台灣媒體面對深偽技術的脆弱性,以及本地 AI 治理政策的現況與不足。課程開放跨院系修習,歡迎傳播、設計、社會科學及資訊相關背景的學生共同參與,多元的學科視角將成為課堂討論的重要資產。
修課學生將透過案例分析作業、期中研究提案與期末成果展演,逐步建立「以理論看現象、以現象驗理論」的研究能力。期末成果採分組制,學術研究與創作實踐並行,讓不同志向的學生都能找到深化自身能力的路徑。
修完本課程的學生,將不只是 AI 工具的使用者,而是能夠批判性地閱讀技術、參與公共辯論、並以傳播學視角介入 AI 時代的思考者。
(英文版課程描述)
The rise of generative AI is not merely a technological revolution — it is a fundamental challenge to the very nature of communication. When machines can simultaneously generate text, images, audio, and video, how is meaning constructed? And where does the boundary of the "real" begin to dissolve?
This course takes "multimodal communication" as its central concept, guiding students through the theoretical lenses of semiotics, pragmatics, and social semiotics to examine how generative AI is reshaping contemporary communicative practices. The curriculum unfolds in four stages: first establishing a conceptual vocabulary for understanding AI multimodality; then observing its concrete impact on media ecosystems including journalism, advertising, and public relations; moving into critical inquiry — scrutinizing algorithmic bias, digital colonialism, and the ethics of creative labor; and finally returning to practice, exploring both the possibilities and limitations of AI as a communicative tool and creative collaborator.
The course places particular emphasis on a Taiwanese perspective, addressing the marginalization of Traditional Chinese in global AI models, the vulnerability of Taiwanese media to deepfake technology, and the current state and shortcomings of local AI governance policy. The course is open to students across departments and welcomes participants from communication, design, social sciences, and information-related fields. Diverse disciplinary backgrounds are regarded as a valuable asset to classroom discussion.
Through case analysis assignments, a midterm research proposal, and a final presentation, students will develop the capacity to move fluidly between theory and phenomenon — using each to illuminate the other. Final outcomes follow a track system, with academic research and creative practice running in parallel, allowing students of different orientations to deepen their own capabilities.
 
課程目標 (若為實務型課程請具體描述該課程所要培養之實務能力)
Course Objectives
序號目標描述
1建立跨域的概念語言 / Develop a Cross-Disciplinary Conceptual Vocabulary
2分析 AI 對媒體生態的結構性影響 / Analyze the Structural Impact of AI on Media Ecosystems
3培養批判性的技術閱讀能力 / Cultivate Critical Technology Literacy
4深化研究或創作的實踐能力 / Strengthen Research and Creative Practice Competencies
5形成在地化的 AI 傳播視角 / Develop a Locally Grounded Perspective on AI Communication
授課進度表
Weekly Schedule
週次內容備註
1多模態傳播概論與生成式 AI 演進

Introduction to Multimodal Communication and the Evolution of Generative AI
 
2文字與提示詞工程:跨媒介文本生成的邏輯

Textual Logic and Prompt Engineering: Cross-Media Text Generation
 
3多模態影像生成與視覺符號學

Multimodal Image Generation and Visual Semiotics
 
4AI 繪圖進階控制與動態分鏡預覽

Advanced AI Image Control and Storyboard Previsualization
 
5聲音、語音合成與多模態音訊生成技術

Audio Synthesis, Voice Cloning, and Multimodal Audio Generation
 
6AI 驅動的動態影像與影片生成工作流

AI-Driven Motion Graphics and Video Generation Workflows
 
7虛擬數位人、虛擬主播與多模態互動技術

Digital Humans, Virtual Anchors, and Multimodal Interactive Technologies
 
8期中多模態創意企劃與雛形發表Midterm Project: Multimodal Creative Proposal and Prototype Presentation 
9AI 時代的媒體生態、敘事結構與資訊產製

Media Ecology, Narrative Structure, and Content Production in the AI Era
 
10多模態大型語言模型 (MLLM) 應用與提示詞工程

Multimodal Large Language Models (MLLMs) Applications and Prompting Techniques
 
11深度偽造 (Deepfake)、虛假訊息與多模態辨識

Deepfakes, Misinformation, and Multimodal Detection
 
12AI 與著作權法、倫理框架與傳播權利

AI and Copyright Law, Ethical Frameworks, and Communication Rights
 
13人機互動 (HCI) 與多模態感官體驗設計

Human-Computer Interaction (HCI) and Multimodal Sensory Experience Design
 
14生成式 AI 的社會衝擊、演算法偏見與文化省思

Social Impact of Generative AI, Algorithmic Bias, and Cultural Reflections
 
15專案跨媒介整合、成片打磨與媒體生態評估

Cross-Media Project Integration, Polishing, and Media Ecology Evaluation
 
16期末多模態傳播專題成果總審查

Final Project Review: Special Topics in Multimodal Communication Exhibition
 
1716+2
Optional with 16+2
 
1816+2
Optional with 16+2
 
 
學期成績計算及多元評量方式
Grading Policy
項次配分項目/catagory配分比例/Percentage會考測驗/general_test實務操作/accounting_practice專題發表/case_presentation其他/other
1平時成績/Asssignments 20% V  
2期中考成績/Midterm Exam 30%  V 
3期末考成績/Final Exam 30%  V 
4其他/other 20%   V
主要參考書目
References

指定閱讀
Required Readings

教師座談/晤談地點與時間
Course Management SystemInstructor' Office and Office hours

U423
學生請假規則

1. 學生請假悉依本校「學則」及「學生請假辦法」規定辦理。
2. 依本校「學則」第33條,曠課一小時,以缺課二小時論。學生某一科目之缺課總時數達該科全學期授課時數三分之一,經該科教師扣考後,即不准參加該科目之學期各項學習成績考試或評量。
課程平台

http://elearn.fgu.edu.tw