Research and digitalization: application for rural development
(Bio-)ingenieurswetenschappen
(Bio-)ingenieurswetenschappen
This e-course aims to provide participants with comprehensive knowledge and practical skills on how digital tools are used in agricultural research to enhance rural development and how research is conducted on digital tools in rural areas.
As we all have become users and consumers of digital tools, it is of interest to create a platform to share ideas and experiences.
This course is available from December 1, 2025. You can register at any time.
A closing session in Teams will be organised at the end of April 2026.
More info: https://www.ugain.ugent.be/DigiRural2025.htm
Introduction to the course - Overview of the content
What is Generative AI and how it works - Applications of Generative AI- Text-based and image Generative AI - Detecting fake images – Engage by reading, watching, writing and sharing.
Introduction to large language tools such as ChatGPT, Bing, etc. – Tips and tricks for literature search and writing - Limitations of large language tools- Engage by reading, watching, searching and sharing.
Advantages and disadvantages of digital tools for on-site data collection - Comparison of off- and online surveying – Tutorials - Engage by reading, watching, trying and sharing.
Tutorial on creating prompts to analyse survey data - Engage by reading, watching, calculating and sharing.
Introduction to the basics of using drones for data collection - Applications in rural development – Engage by reading, watching, calculating and sharing.
Introduction to spatial data in rural development studies - Mapping, spatial econometrics, and network mapping - Generating local data - Aggregating spatial data with survey data – Engage by reading, watching, trying and sharing.
Overview of digitalization uptake studies - Examples of adoption of digital tools by rural households/farmers - Benefits and limitations of the different frameworks – Engage by reading, watching, writing and sharing.
Explanation of living labs in rural areas - Socio-economic impacts of digital transformation - Findings and experiences from the DESIRA project – Engage by reading, watching, discussing and sharing.
Qualitative and quantitative methodologies for impact studies - Outcomes of impact studies – Engage by reading, watching, trying and sharing.
AI Ethics and Bias in AI Systems - Fairness and accountability in AI -Privacy concerns - AI and human rights - Autonomous AI and responsibility - Transparency and explainability - Examples of moral machines – Engage by reading, watching, trying and sharing
Sharing questions, experiences, comments, and suggestions. In this closing session we will also give a general feedback on the exercises made during the course.
The units are organised in four blocks and participants are able to move to a next block upon completion of the previous block.