ECTS: 2.5
Course leader: Morten Pilegaard
Language: English
Graduate school: Faculty of Health
Course fee: 3,000.00 DKK
Status: Course is finished
Semester: Fall 2024
Application deadline: 17/09/2024
Cancellation deadline: 01/10/2024
Course type: Online education
Start date: 17/10/2024
Administrator: Anne Fabricius Søndergaard
The course A331/03 Artificial intelligence for scientific and academic writing is being offered by the Graduate School of Health, Aarhus University, 2024.
Criteria for participation:
University degree in medicine, dentistry, nursing, or master’s degree in other fields and/or postgraduate research fellows (PhD students and research-year medical students).
Requirements for participation:
Prior participation in the Basic or Advanced Course in Written English is recommended. Access to a PC and permission to download and install programs are prerequisites. AI tool access: Free trial plans are available; tool upgrading benefits typically include higher word limits, access to advanced features, priority support and no usage limits. One-month subscriptions for premium versions of 4-5 AI tools used total 40 < Euro (DKK 300).
Aim:
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 and academic writing process.
Learning outcomes:
- 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 restructure sentences, optimise word choice, improve cohesion and coherence, and ensure grammatical correctness and fluency
- Ability to use AI tools for plagiarism detection.
Content: In this practical 8-hour course, participants will work with artificial intelligence (AI) based on their knowledge of academic text production in English from the Basic and Advanced course in Written English and current conventions of written academic English for medicine and life sciences. 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 and legal issues relevant to AI use for writing and learn how to detect and prevent plagiarism.
Key topics covered: Efficient, correct and fluent AI-assisted academic and scientific writing, AI-assisted writing tools, AI-assisted plagiarism detection, avoiding AI pitfalls
- 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.
- 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.
- Ethical considerations and legal issues: 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.
Instructors: Morten Pilegaard and Peter Steffensen
Venue: The course is taught online
Participation in the course is without cost for:
- PhD students, Health Research Year students from Aarhus University
- PhD students enrolled at partner universities of the Nordoc collaboration
- PhD students from other institutions in the open market agreement for PhD courses
Course dates:
- 17 October 2024 08:30 - 12:30
- 24 October 2024 08:30 - 12:30