國立中興大學教學大綱
課程名稱 (中) 農業資訊技術(3033)
(Eng.) Introduction to Agricultural Information Technology
開課單位 國農企學程
課程類別 選修 學分 3 授課教師 陳思宏
選課單位 國農企學程 / 學士班 授課使用語言 英文 英文/EMI Y 開課學期 1132
課程簡述 The course-Introduction to Agricultural Information Technology introduces students to the role of information technology in modern agriculture. It covers fundamental concepts of data management, precision agriculture, Geospatial Information Science and Technology, decision support systems, digital extension services, and more. Through case studies and hands-on activities, students will learn how information technology enhances productivity, sustainability, and decision-making in agricultural systems.
先修課程名稱
課程含自主學習 Y
課程與核心能力關聯配比(%) 課程目標之教學方法與評量方法
課程目標 核心能力 配比(%) 教學方法 評量方法
Through the course, students will be able to:
1. Understand the fundamental concepts of agricultural information technology and its impact on modern farming.
2. Learn various types of agricultural data and their applications in decision-making.
3. Accumulate the knowledge of data-driven decision-making in agricultural planning and production.
4. Develop a basic project that applies information and data-driven solutions to agricultural challenges.
專題探討/製作
習作
討論
講授
書面報告
口頭報告
作業
測驗
其他
授課內容(單元名稱與內容、習作/每週授課、考試進度-共18週)
週次 授課內容
第1週 Introduction and Fundamental Concepts (I)
1. Course introduction
2. Definition and fundamental concepts of agricultural informatics.
第2週 Introduction and Fundamental Concepts (II)
1. Information Technology vs. Agricultural Information Technology
2. Overview and historical development of IT applications in agriculture.
第3週 Agricultural Data Collection and Processing
1.Role of data in modern farming
2.Types of agricultural data (e.g, weather, soil, crop or livestock productivity)

*In-class exercise: Agricultural data collection, editing and synthesis
第4週 Agricultural Data Statistics and Analysis
1. Charts/diagrams creation of agricultural statistics
2. Interpretation and application of agricultural statistical information
第5週 Agricultural Data Management and Databases (I)
1. Basic concepts and operations of database
2. Agricultural database development and management
第6週 Guest Speaker: AI and database applications in modern agriculture

(Topic/Schedule: tentative; Further detail will be provided in class)

In-class exercise (tentative): How to use Google NotebookLM
第7週 Agricultural Data Management and Databases (II)
1. Application of Agricultural Database and Information System
2. Other related data informatics (e.g., cloud-based platform)
第8週 Geographic Information Systems (GIS) and Remote Sensing in Agriculture
1.Basics of GIS and mapping in agriculture
2. Role of remote sensing in agriculture

*In-class case study discussion: GIS or/and remote sensing in agriculture production (e.g., crop monitoring, site selection or farmland management)
第9週 Digital Extension and Mobile Applications in Agriculture
1.Role of ICT in agricultural extension services
2.Mobile apps for farmers (e.g., weather forecasting, pest management)
3.E-agriculture and knowledge-sharing platforms
第10週 Mid-term Exam
第11週 Smart Farming and Internet of Things (IoT) in Agriculture
1.Concept of smart farming
2.IoT-enabled farm management; for example:Use of drones, robotics and/or automated irrigation
第12週 Precision Agriculture Technologies
1.Concepts of precision agriculture
2.Use of IoT devices, GPS, and sensors
3.Spatial data and GIS application in precision agriculture
第13週 Challenges and Ethical Issues in Agricultural Information Technology
For example : Data privacy and cybersecurity in farm management,environmental and ethical concerns
*In-class discussion (Tentative)
第14週 Future Trends in Agricultural Information Technology
1.Emerging trends: AI, blockchain, cloud computing
2.Future challenges and career opportunities in Agri-IT
第15週 Final Project Development

*Toolkit: Google NotebookLM
第16週 Final Project Presentation (Group/Individual)
第17週 Self-learning Week: Completing the post-class self-reflection report (Individual) on key learnings

第18週 Self-learning Week: Video Watching
學習評量方式
(1)Attendance: 10%; (2) In-class Activity (e.g., discussion, hand-on exercise):15%; (3) Assignments: 20%; (4)Midterm Exam: 25%; (5)Final Project and Presentation: 30%
教科書&參考書目(書名、作者、書局、代理商、說明)
There is no mandatory textbook. Course handouts will be made available through NCHU iLearning if needed.
However, several selected references as below may be synthesized or cited in class materials. For examples:
[Example Reference #1] Snapp, S. S. and B. Pound.(eds.) 2017. Agricultural Systems: Agroecology and Rural Innovation for Development (2nd Edition). Academic Press, Burlington, MA
[Example Reference #2] Muller, T. and Sassenrath (eds.) 2015. GIS Applications in Agriculture, Volume Four: Conservation Planning. CRC Press, Boca Raton, UK.
課程教材(教師個人網址請列在本校內之網址)
NCHU iLearning may also be used to conduct quiz/exams, to submit course exercises, to broadcast announcements, and so on. It can be accessed via NCHU iLearning Portal (https://lms2020.nchu.edu.tw/ ) or NCHU Single Sign On System.
課程輔導時間
By Appointment
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更新日期 西元年/月/日:2025/02/16 15:33:14 列印日期 西元年/月/日:2025 / 3 / 14
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