| Course Name |
(中) 農業資訊技術(3156) |
| (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-FALL |
| 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 |
Agricultural Data Statistics and Analysis
1. Charts/diagrams creation of agricultural statistics
2. Interpretation and application of agricultural statistical information
*AI Toolkit exercise (tentative): Google NotebookLM、 Google Antigravity |
| Week 6 |
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 7 |
Guest Speaker: AI and database applications in modern agriculture
(Topic/Schedule: tentative; Further detail will be provided in class) |
| Week 8 |
Mid-term review section
1. Synthesis and reviews of Week 1-8 contents
|
| Week 9 |
Mid-term Exam |
| Week 10 |
2026 GEAR-UP FORUM： Advancing Agricultural Science in the Age of Data and AI
*Required to participate the morning section of the Borlaug Lecture Series on 11/10 |
| Week 11 |
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 12 |
Smart Farming and Internet of Things (IoT) in Agriculture
1.Concept of smart farming
2.IoT-enabled farm management (e.g., use of drones, robotics and/or automated irrigation)
3.Role of ICT in agricultural extension services
4.Final Project Instruction
*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 |
01.Participation in professional forums, lectures, and corporate sharing sessions related to industry-government-academia-research exchange activities.
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 |
| Sustainable Development Goals, SDGs(Link URL) |
| include experience courses：N |
|