NCHU Course Outline
Course Name (中) 農業資訊技術(3033)
(Eng.) Introduction to Agricultural Information Technology
Offering Dept International Bachelor Program in Agribusiness
Course Type Elective Credits 3 Teacher Szu-Hung Chen
Department International Bachelor Program in Agribusiness/Undergraduate Language English Semester 2026-SPRING
Course Description 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.
Prerequisites
self-directed learning in the course Y
Relevance of Course Objectives and Core Learning Outcomes(%) Teaching and Assessment Methods for Course Objectives
Course Objectives Competency Indicators Ratio(%) Teaching Methods Assessment Methods
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.
topic Discussion/Production
Exercises
Discussion
Lecturing
Written Presentation
Oral Presentation
Assignment
Quiz
Other
Course Content and Homework/Schedule/Tests Schedule
Week Course Content
Week 1 Introduction and Fundamental Concepts (I)
1. Course introduction
2. Definition and fundamental concepts
Week 2 Introduction and Fundamental Concepts (II)
1. Information Technology vs. Agricultural Information Technology
2. Overview and historical development of IT applications in agriculture.
Week 3 Agricultural Data Collecting, Processing and Management (I)
1.Role of data in modern farming
2.Types of agricultural data (e.g, weather, soil, crop or livestock productivity

*Hand-on exercise: Agricultural data searching and collecting
Week 4 Agricultural Data Collecting, Processing and Management (II)

*Hand-on exercise : Agricultural data processing and synthesis
Week 5 Guest Speaker: AI and database applications in modern agriculture
(Topic/Schedule: tentative; Further detail will be provided in class)

*AI Toolkit exercise (tentative): Google NotebookLM、 Google Antigravity
Week 6 Agricultural Data Statistics and Analysis
1. Charts/diagrams creation of agricultural statistics
2. Interpretation and application of agricultural statistical information
Week 7 Make-up holiday for University Anniversary and Annual Sports Meet
*No on-site class; take-home exercise may be assigned
Week 8 Agricultural Data Management and Databases
1. Basic concepts and operations of database
2. Agricultural database development and management
3. Application of Agricultural Database and Information System
Week 9 Mid-term Exam
Week 10 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-clas discussion: GIS or/and remote sensing in agriculture production (e.g., crop monitoring, site selection or farmland management)
Week 11 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
3.Role of ICT in agricultural extension services
Week 12 Final Project Instruction;
Challenges and Ethical Issues in Agricultural Information Technology (e.g., Data privacy and cybersecurity in farm management,environmental and ethical concerns)

*In-class discussion (Tentative): Final Project Group Arrangement
Week 13 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
Week 14 Future Trends in Agricultural Information Technology
1.Emerging trends: AI, blockchain, cloud computing
2.Future challenges and career opportunities in Agri-IT

*Final Project Development
Week 15 Final Project Development
Week 16 Final Project Presentationn (Group/Individual) and Post-class self-reflection report (Individual)
self-directed
learning
   02.Viewing multimedia materials related to industry and academia.
   03.Preparing presentations or reports related to industry and academia.

Evaluation
(1)Attendance: 10%; (2) Exercise and Assignment (e.g., discussion, hand-on exercise):30 %; (3)Midterm Exam: 30%; (5)Final Project Development : 30% (20% Group Presentation+ 10% self-reflection report)
Textbook & other References
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.
Teaching Aids & Teacher's Website
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.
Office Hours
By Appointment
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Update Date, year/month/day:2026/02/09 20:14:38 Printed Date, year/month/day:2026 / 3 / 10
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