Course Overview

This intensive training introduces researchers to the responsible, efficient, and publication-ready use of Artificial Intelligence (AI) tools across the research workflow—from refining research questions and conducting literature reviews to structuring manuscripts and improving scientific writing. The course emphasizes human-led research supported by AI, with strong focus on ethics, academic integrity, and journal compliance.

Participants will learn what AI can assist with, where it must not be used, and how to integrate it safely into everyday research practice without risking plagiarism, data fabrication, or policy violations.

350+

15

Nature Guide Trainings

Participants

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Module 1: Foundations of AI in Academic Research

Understanding AI capabilities and limitations

• What AI is (and is not) in research contexts

• Types of AI tools used in academia (writing, literature, synthesis)

• Risks of hallucination, bias, and over-reliance

• Positioning AI as an assistant, not an author

Module 2: AI for Research Planning & Literature Review

Early-stage research acceleration

• Refining research questions using AI prompts

• Building conceptual frameworks and hypotheses

• Literature discovery using AI-assisted platforms

• Thematic clustering and gap identification

• Verifying AI outputs with scholarly databases

• Role of AI in drafting vs editing

• Section-wise writing strategies:

• Avoiding fabricated citations and generic phrasing

• Journal scope matching using AI

Module 3: Manuscript Writing Using IMRAD Framework

Structuring publishable scientific papers

Course Structure & Modules

Module 5: Ethics, Disclosure & Future-Ready Research Practice

Compliance with academic standards

• Writing with clarity, precision, and reviewer empathy

• Common reasons proposals fail—and how to avoid them

• Internal review, peer feedback, and revision strategies

• Checklists for final proposal readiness

• Using reviewer comments to improve future submissions

Module 4: Editing, Proofreading & Plagiarism-Safe AI Use

Language improvement without ethical risk

• Scientific tone vs grammatical correction

• Paraphrasing vs rewriting: where to draw the line

• Using AI for clarity while preserving author voice

• Understanding plagiarism detection and AI detection tools

• Safe workflows for thesis and manuscript polishing

Outcomes

1. Integrate AI tools appropriately at different stages of research

2. Improve literature review efficiency without compromising rigor

3. Structure manuscripts clearly using the IMRAD framework

4. Edit and refine academic writing safely using AI assistance

5. Avoid plagiarism, fabricated references, and policy violations

6. Make informed decisions about ethical AI disclosure in publications

FAQs

Is prior experience with AI tools required?

No. The course starts with fundamentals and gradually moves to advanced applications.

Will this course teach automated data analysis?

No. The focus is on research design, literature synthesis, and manuscript preparation, not statistical or modeling automation.

Is using AI in research allowed by journals?

Yes, with limitations. The course explains what is permitted, what must be disclosed, and what is prohibited.

Yes. The workflows taught are suitable for theses, dissertations, and journal manuscripts.

Can this be used for thesis writing?

Will participants receive materials after the session?

Yes. Participants receive prompt templates, workflow checklists, and recommended AI tools.

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