教學大綱 Syllabus

科目名稱：進階創新科技技術

Course Name: Advanced Innovative Information Technology
  • 學年學期：114-1 Fall Semester, 2025
  • 科目代碼：356015001 Course No.356015001

修別：必

Type of Credit: Required

3.0

學分數

Credit(s)

5

預收人數

Number of Students

課程資料Course Details
  • 開課單位：資博學一、資博學二 Course Department:Management Information Systems/D/1&2
  • 授課老師：莊豐源 Instructor: CHUANG FENG-YUAN
  • 先修科目：無Prerequisite(N/A)
  • 上課時間：二D56 Session: tue13-16

課程簡介Course Description

This course explores the economic, technological, and environmental dimensions of Web3 innovations. Students will gain both theoretical knowledge and practical skills in blockchain technologies, smart contract development, and decentralized applications (dApps). Through lectures, discussions, and projects, students will critically examine Web3 applications across industries, with a particular focus on decentralized finance (DeFi), tokenized real-world assets (RWAs), self-sovereign identity (SSI), and sustainable development.

核心能力分析圖 Core Competence Analysis Chart

能力項目說明

    課程目標與學習成效Course Objectives & Learning Outcomes

    By the end of the course, students will be able to:

    • Critically analyze the economic and technological landscape of Web3.
    • Apply blockchain technologies by developing smart contracts and dApps.
    • Evaluate and propose Web3 solutions for business, government, and sustainability challenges.
    • Conduct independent research in selected Web3 fields.

    每周課程進度與作業要求 Course Schedule & Requirements

    Week

    Topic

    Content

    Activity

    1

    Introduction to Web3 (Web3 概論)
    • Economic aspect
    • Technological aspect
    • Environmental aspect
    • Political aspect

    Lecture
    2 Cryptography (密碼學)
    • Information and network security concepts
    • Hashing
    • Symmetric ciphers
    • Asymmetric ciphers (public-key cryptography)
    • The RSA cryptosystem
    • Digital signatures
    • Public-key infrastructure (PKI)
    		 Lecture + Practice

    3

    Bitcoin (比特幣)
    • Token economics of Bitcoin
    • Keys and wallets
    • Transactions
    • Blocks
    • Mining

    Lecture

    4

    Ethereum (以太坊)
    • Token economics of Ethereum
    • Keys and wallets
    • Transactions
    • Blocks
    • Staking and validation
    • Gas fees

    Lecture

    5

    Smart Contracts (智能合約) 1
    • Fundamentals of Solidity programming

    Lecture + Practice

    6

    Smart Contracts (智能合約) 2
    • Smart contract development, testing, and deployment

    Lecture + Practice
    7 Smart Contracts (智能合約) 3
    • Interaction between smart contracts, crypto wallets, and JavaScript
    • Fungible tokens
    • Non-fungible tokens
    		 Lecture + Practice

    8

    Token Economics and Decentralized Finance (代幣經濟學與去中心化金融)
    • Token supply adjustment
    • Automated market makers
    • Collateralized loans
    • Decentralized autonomous organizations (DAOs)
    • Token sales

    Lecture
    9 Self-Sovereign Identity (自我主權身分)
    • Decentralized digital identity
    • Decentralized identifiers
    • Verifiable credentials
    • Zero-knowledge proof
    		 Lecture

    10

    Web3, AI, and Sustainable Development (Web3、人工智慧與永續發展)
    • Blockchain for sustainable development
    • Blockchain data analytics and visualization

    Lecture

    11

    Mid-Term Exam

    Special Issue: Sustainable Development, Supply Chain Management, and Health Care

    Readings

    Student Presentation

    12

    		 Special Issue: Blockchain Data and Machine Learning I

    Readings

    Student Presentation

    13

    Special Issue: Blockchain Data and Machine Learning II

    Readings

    Student Presentation

    14

    		 Special Issue: Decentralized Finance

    Readings

    Student Presentation

    15

    Special Issue: Self-Sovereign Identity

    Readings

    		 Student Presentation

    16

    Group Project Presentation

     

    Student Presentation

    授課方式Teaching Approach

    50%

    講述 Lecture

    30%

    討論 Discussion

    20%

    小組活動 Group activity

    0%

    數位學習 E-learning

    0%

    其他： Others:

    評量工具與策略、評分標準成效Evaluation Criteria

    Course evaluation:

    • Individual assignments: 30% (Late submissions can be accepted only within one week.)
    • Mid-term exam: 10%
    • Class participation: 10%
    • Research paper presentation: 20%
    • Team project presentation: 30%
      • Instructor's evaluation: 10%
      • Intra-group peer evaluation: 10%
      • Inter-group peer evaluation: 10%

    Team composition:

    • Group size: 2–3 members.
    • Diversity: Teams are encouraged to mix technical, managerial, and policy-oriented backgrounds.
    • Team task: Develop and pitch a business, policy, or academic idea related to blockchain and/or token economics.

    Essential elements for a successful pitch:

    • Problem definition: clearly define the problem and scope.
    • Target audience: specify the audience (business, government, civil society, or academia).
    • Importance of the problem: use data, reports, or case studies to justify significance.
    • Blockchain solution justification: explain why blockchain is suitable (immutability, trust, decentralization, efficiency, etc.).
    • Technical details and proof of concept: demonstrate technical feasibility (prototype, system diagram, token model).
    • Potential impact: discuss business, social, and sustainability implications.

    Evaluation criteria for the team project presentation:

    • Novelty (25%): originality of idea, creative use of blockchain, differentiation from existing solutions.
    • Technical depth (25%): understanding of blockchain architecture, token design, or consensus/security trade-offs.
    • Business and social impact (25%): connection to Sustainable Development Goals (SDGs) and measurable value creation.
    • Presentation and communication (25%): clarity, persuasiveness, professional delivery, and effective use of visuals.

    指定/參考書目Textbook & References

    Suggested Readings

    Provided in Moodle.

    已申請之圖書館指定參考書目 圖書館指定參考書查詢 |相關處理要點

    維護智慧財產權，務必使用正版書籍。 Respect Copyright.

    本課程可否使用生成式AI工具Course Policies on the Use of Generative AI Tools

    有條件開放使用:可使用，但不得抄襲。 Conditional Permitted to Use

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