COURSES

Content

This course structure is designed to emphasize both theoretical understanding and practical application of AI tools in academia. The following topics will be covered:

• Introduction to AI in Academia
• Ethical Considerations
• Writing Enhancement Tools
• AI in Literature Review
• Research and Data Management
• Collaboration and Communication
• Computational Tools for Analysis
• Practical Application and Case Studies

Learning outcomes

After successful completion, participants will be able to:

• explain what AI is, what technical requirements must be met, and
• what it can be used for;
• select a suitable AI for a specific application;
• evaluate the quality and accuracy of AI-generated results;
• use AI tools and revise their use in a goal-oriented manner;
• assess the scope of the given framework for a selected AI, such as data protection, finances, resources, training data, ethics, and other aspects;
• examine the copyright relevance of AI inputs and outputs; and
• assess their suitability for “good scientific practice”

Programme

Key aspects of using AI tools in academia are to enhance productivity, improve writing quality, efficiency and accuracy, better and clear organization of data, improve learning aid and foster a better understanding of academic content.

Teaching method(s)

Series of online lectures

Extra information on the teaching methods:

• one 90-minute (synchronous) seminar session per week
• synchronous group work activities (self-regulating groups)
• self-study activities

Assessment method(s)

Form of assessment:

• Written (AI assisted) term paper and documentation of AI use

Timing for assessment:

• Seminar Paper submission 28th January 2027 and oral examination 11th February 2027

Further requirements for assessment:

• Regular attendance and active involvement, preparation of term paper using AI tools, documentation of use of AI tools

Participants demonstrate their acquired skills by completing a seminar paper, which uses AI tools throughout the entire process, from topic selection to completion. The use of the tools is documented and reflected upon. The documentation and oral exam serve as the basis for assessment.

Lecturers

Aisha Aamir (University of Göttingen)

Course dates

One 90-minute synchronous online session per week: Thursdays, 10:15 to 11:45 hrs (CEST/CET), 29 October 2026 to 11 February 2027. Teaching and learning material available on Moodle.

Entry requirements: Good command of English. Some experience in writing term papers.

Students from all ENLIGHT partner universities are eligible to participate. Students who meet the requirements mentioned above apply directly to the host university through Application link. Before applying, students should check with their home faculty or programme whether the course can be included in their curriculum and whether the credits will be recognised. Students from Ghent University must obtain faculty approval by completing this form and having it signed by the Faculty Student Administration.

The host university will select the permitted number of students, inform the students as soon as possible following the application deadline (30^th September 2026). Selection of course participants will be based on entry requirements and available course capacities. Selection will refer to a “first come first serve” principle across partner universities, i. e. the first applications from each university will be selected to increase diversity in the course. Unsuccessful students will be placed on a waiting list and may get a place in case of drop outs at a later stage.

Transcript of Records will be available to students by the end of February 2027.

If you have questions about the course (content, structure, requirements, etc.), please contact:

Aisha Aamir, This email address is being protected from spambots. You need JavaScript enabled to view it.