Course Artificial intelligence for scientific writing

The course N/T 626/01 Artificial intelligence for scientific writing is offered by the Graduate School of Natural Sciences/GSNS and Graduate School of Technical Sciences/GSTS, Aarhus University, Fall 2025.

Name of course:

Artificial Intelligence for Scientific Writing

ECTS credits:

1.3 ECTS

Course parameters:

Language: English

Level of course: PhD course

Time of year: Fall 2025

No. of contact hours/hours in total, incl. preparation, assignment(s) or the like: Contact hours: 8. Hours in total: 38 (encompasses revision and comments on students' assignments and reflections, and preparation).

Capacity limits: 20 participants

Objectives of the course:
This course aims to impart knowledge about and give participants an introduction to and practical experience using artificial intelligence (AI) tools to enhance their scientific writing processes.

Learning outcomes and competences:

• Knowledge about AI tools for enhancing academic writing in English
• Knowledge about common pitfalls in using AI for text generation and optimisation purposes
• Knowledge about ethical considerations and legal issues when using AI
• Ability to use a selection of AI tools for academic text production in conformity with current conventions, principles and practices in academic genres and particular scientific text types
• Ability to use AI tools to tailor the linguistic form to the text’s purpose at all textual levels
• Ability to use AI tools to restructure sentences, optimise word choice, improve cohesion and coherence, and ensure grammatical correctness and fluency
• Ability to use AI tools for plagiarism detection.

Compulsory programme: Please see below:

Course contents:
In this practical 8-hour course, participants will work with artificial intelligence (AI) based on their knowledge of academic text production in English and current conventions of written academic English for science. Participants will be introduced to a selection of AI tools underpinning scientific and academic writing processes. The course will equip participants with the skills and knowledge necessary to navigate AI pitfalls while using AI to improve their writing efficiency, accuracy, and quality through AI-powered solutions. Participants will be introduced to ethical issues relevant to AI use for writing and learn how to detect and prevent plagiarism.

1. Streamlining language: This module will train participants’ general ability to use AI tools for disciplinary-specific writing and editing in conformity with contextual/situational, discoursal and genre- and text-type conventions and requirements of written academic English in health and life sciences. Participants will discover how AI-powered tools, pending proper prompting, may help writers tailor the linguistic form to the text’s purpose at all textual levels and how they may be used to restructure sentences, optimise word choice, improve cohesion and coherence, and ensure grammatical correctness and fluency.
2. Avoiding AI pitfalls: Participants will learn to navigate the common pitfalls of using AI tools in their research and writing processes. Through practical exercises and guidance, participants will develop the skills to leverage AI effectively while maintaining academic integrity and quality standards.
3. Ethical considerations: The course will introduce participants to the ethical considerations and legal implications of using AI in academic and scientific writing. Participants will be introduced to plagiarism detection tools, copyright issues, and best practices for maintaining academic integrity when utilising AI technology.

Prerequisites:
University degree in the broad field of science or master’s degree in other fields and/or postgraduate research fellows (PhD students and research-year students). Prior participation in the Basic or Advanced Course in Written English is recommended. Access to a computer and permission to download and install programs are prerequisites.

Name of lecturers:
Morten Pilegaard and Peter Steffensen

Type of course/teaching methods:
The course is taught online as live, interactive Zoom sessions. Training sessions consist of a mix of short presentations, individual and/or small-group exercises and discussions. The course comprises AI-assisted scientific writing assignments that typically take 5-10 hours to complete. Students receive feedback on the assignments they submit for proofreading/feedback.

Course homepage:
Brightspace

Course assessment:
Attendance threshold (80%). Students not reaching the attendance threshold who do complete at least one 4-hour training module will be invited to complete an AI-assisted writing assessment to compensate for any absence.

Provider:
VidKom (Morten Pilegaard and Peter Steffensen)

Time:
Two 4-hour modules, e.g. imparted from 13.30 to 17.30. The modules are separated by at least five working days to allow students to complete home assignments and reflections.

Place:
Online (Zoom sessions)

No-show fee/late-cancellation fee:

Course participants on our transferable skills courses, who do not show up at the course or cancel their course participation after the course cancellation deadline, will be required to pay a no-show fee/late-cancellation fee. Exceptions may apply in certain cases, such as reported illness to the course administrator/course team. In case of late cancellation due to illness, we may require a doctor’s note from you.

The no-show fee/late-cancellation fee is DKK 1,200 (the price of one ECTS). The fee has been introduced due to many late cancellations, thus preventing people from the waiting lists to have a seat at the courses.

Registration:

• Participation in the course is without cost for PhD students from Aarhus University

Due to an Agreement between Danish Universities that came into force as of 1 January 2011, participants from other universities than Aarhus University will have to pay DKK 1,200 per ECTS. In principle this also applies to external parties, but exemption can be granted under specific circumstances.

Please be aware that your registration for the course not necessarily equals your admission for the course. You will receive an e-mail after the registration deadline regarding whether you are admitted for the course or if you are registered on the waiting list. Please note that seats are allocated on a first-come-first-served basis.

If you have any questions, please contact the course administrators at: courses.nat.tech.he@au.dk

Course dates:

• 01 December 2025 08:30 - 12:30
• 08 December 2025 08:30 - 12:30