Scientific Writing & AI Literacy

This three-day workshop is intended for young researchers seeking to master the core principles of scientific writing as a firm foundation that will later empower them when employing Generative AI (GenAI) tools as writing assistants.

Days 1 and 2 of the workshop (held in-house) will prioritise the essential writing principles needed for participants to communicate their research clearly and effectively in a research article for publication at the highest level. Building on these core principles, Day 3 of the workshop consists of an online module on AI-literacy that will complement and apply the theory presented in the first two days. This module will exclusively focus on practical exercises that promote responsible and ethical use of GenAI tools. Critical thinking skills in AI use will be emphasised. The module will advocate best practice as well as the upholding of the highest standards of research integrity.

Distinguishing features of this workshop are:

• Participants are encouraged to achieve AI-literacy so that their published science is clearly differentiated from, and elevated above, the output of competitors who are merely AI-competent or AI-dependent.
• The workshop aims to communicate the findings of recent peer reviewed research on use of GenAI tools to take a practical, evidence-based and humancentred approach that builds participant confidence in their autonomy as authors.
• The interactive nature of the workshop allows the pooling of expertise in use of GenAI tools among participants. Hands on practical exercises focus on general principles that are transferable among GenAI tools rather than focusing on individual tools.
• Accumulating evidence shows that GenAI tools disproportionately benefit authors who already know what does, and what does not, work in academic writing. Therefore, the workshop will first establish a firm foundation in the theory of Scientific Writing thus ensuring that participants can maximise the advantages of GenAI tools to increase writing productivity while minimising these tools’ limitations.

Essential Writing Principles (Days 1 & 2)
Day 1 of the workshop introduces five key principles of scientific writing and shows participants how to apply these in the context of Choosing Words, Structuring Sentences
and Building Paragraphs.
Day 2 of the workshop provides participants with an overview of the essential considerations when writing each section of a typical IMRAD research article i.e.
Introduction, Materials & Methods, Results and Discussion in addition to the Abstract and Title. Participants are provided with an efficient recipe for writing their next research
article.

In addition, through numerous writing examples and relevant exercises as well as class discussions, participants learn how to:

• Target their publication to a specific audience by “framing” their research story for increased impact.
• Construct a memorable “take-home message” by connecting all parts of the paper in a flowing narrative.
• Use the writing process to guide & understand their own research.
• Overcome writer’s block by combatting perfectionism and procrastination.
• For each writing principle, the trainer will provide pointers to issues relevant to the use of GenAI tools and associated pitfalls. The practical implications of these issues will be explored further during hands-on exercises in the AI-literacy module on Day 3.

AI-literacy Module (Day 3)
The AI-literacy module will address the following major topics:

• Careful and critical generation of literature summaries that are free of “hallucinations” while maximizing the power of LLMs in mining the scholarly literature.
• Safeguarding your authorial voice when using AI tools to assist with your writing. Prompt-engineering techniques to train your LLM-of-choice while ensuring your primacy as author and asserting your intellectual autonomy.
• Protecting your academic reputation by avoiding “rookie errors” and common pitfalls typical of novice users of LLMs (e.g. generalization bias, genre misalignment, “AI ghostwriter” effects) that risk undermining not only reader confidence but also public trust.
• Using LLM tools as a conversational agent in a dialogue that stimulates (rather than supplants) thinking. Using LLMs to brainstorm, identify knowledge gaps in the literature and generate hypotheses while maintaining human-centred critical thinking skills through iterative and active interrogation of LLM outputs.
• Ethics and equity issues as well as privacy and intellectual property concerns related to LLM use. Data protection and copyright issues will be addressed.
• Enhancing your academic integrity through best practice in transparently declaring use of AI-tools to leading journals.

N.B. The module will highlight general principles that are transferable among LLMs rather than focusing on or recommending individual tools. 

Participant Preparation

Before the workshop, participants are asked to choose a published research article of interest from their own research field. They also provide a short sample of their own (i.e. self-authored) writing comprising an Abstract and Title (max. 250 words) either from a manuscript currently in preparation or describing their research so far. Earlystage PhD students may choose to submit an outline of their proposed project. The online AI-literacy module will consist of practically-focused live sessions supplemented with video content on theoretical aspects. These sessions will also make efficient use of participants’ self-authored texts.