Upon completion of this course, participants will be able to:

• Understand how AI tools can support and accelerate the research process
• Use AI for literature review, data analysis, and academic writing
• Evaluate the limitations, biases, and risks of AI-assisted research
• Apply responsible and ethical standards when using AI in scholarly work
• Explore future directions of AI innovation in research environments

1. Module 1: Introduction to AI in Academic Research

   Duration: 2 hours
   Learning Outcomes:

   • Define AI, machine learning, and large language models (LLMs) in a research context
   • Identify current tools and applications across disciplines
   • Recognize the potential and limitations of AI in scholarly inquiry

   Assessments:

   • Quiz: AI concepts for researchers
   • Reflection: "How could AI impact my research discipline?"

   Resources:

   • Intro video: AI for researchers
   • Reading: "The Role of AI in 21st Century Scholarship"

   Module 2: Using AI for Literature Review and Data Discovery

   Duration: 2 hours
   Learning Outcomes:

   • Use AI to summarize, extract, and synthesize scholarly content
   • Explore AI-assisted research databases and semantic search engines
   • Distinguish between credible sources and AI hallucinations

   Activities:

   • AI literature mapping exercise
   • Compare AI-generated summaries vs. abstract reviews

   Assessments:

   • Submit a mini literature review using AI tools with annotations

   Module 3: AI in Writing, Analysis, and Research Design

   Duration: 2 hours
   Learning Outcomes:

   • Use AI to refine research questions, generate outlines, and support argumentation
   • Leverage AI for data analysis (qualitative and quantitative)
   • Maintain authorship and intellectual integrity when using AI-generated content

   Case Study: Mixed-methods research using AI-assisted transcription and code generation

   Assessments:

   • Submit an annotated research plan using AI for at least one stage of development

   Module 4: Research Integrity, Ethics, and AI Regulation

   Duration: 2 hours
   Learning Outcomes:

   • Identify ethical dilemmas related to bias, transparency, and authorship
   • Understand journal, institutional, and funding body guidelines for AI use
   • Develop a personal code of conduct for AI in research

   Interactive Elements:

   • Ethics scenarios and discussion boards
   • Policy lab: Draft AI usage disclosures for a hypothetical research paper

   Assessments:

   • AI ethics quiz
   • Submission of AI use policy statement

   Module 5: Future Frontiers – Innovation and Critical Reflection

   Duration: 2 hours
   Learning Outcomes:

   • Explore trends like autonomous labs, digital research assistants, and real-time collaboration
   • Assess long-term implications of AI on scholarly publishing and peer review
   • Propose innovative uses of AI in your academic discipline

   Capstone Project:

   • Present a research innovation proposal using AI ethically and effectively

   Assessments:

   • Capstone submission and peer feedback session

• Completion of module activities and quizzes (40%)
• Research plan and ethics submission (30%)
• Capstone innovation project (30%)

Participants will earn a certificate in "AI-Enhanced Academic Research," suitable for inclusion in CVs, research portfolios, or PhD progress documentation.

Endorsement: This curriculum was approved by the Academic Development Committee of the university.