5.00
(2 Ratings)

AI-Enabled Systematic Literature Reviews

By Dr. IQ Categories: RESEARCH
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About Course

Course Aims:

This master class endeavors to furnish participants with advanced expertise and proficiency in executing systematic literature reviews (SLRs) by harnessing state-of-the-art AI tools and methodologies. The course aims to empower participants to adeptly craft research inquiries, refine research precision, employ AI-driven strategies for literature searches, efficiently extract and evaluate data, synthesize extensive literature comprehensively, and produce structured, perceptive review reports enriched by AI-driven insights.

Teaching Methodology:

The course will employ a diverse instructional approach, amalgamating live sessions, video tutorials, interactive engagements, and comprehensive feedback loops for learner submissions. Spanning four weeks, the live sessions will unfold weekly via Zoom, offering a platform for learners to engage with both the course instructor and fellow participants. These sessions will facilitate discussions, queries, and personalized feedback on learner progress.

Video tutorials will comprehensively cover various facets of conducting literature reviews utilizing AI tools, granting learners the flexibility to access and assimilate this content at their preferred pace. Interactive sessions are meticulously designed to enable learners to apply acquired knowledge and skills to their individual research projects. Moreover, these sessions will facilitate peer-to-peer review and constructive feedback mechanisms to enhance learning outcomes and project quality.

Certification Offered:

Upon successful completion of the course, participants will receive certification from The Association of Professional Researchers and Academicians UK, recognizing their expertise in AI-enabled systematic literature reviews. The certification will validate the participant’s mastery of AI-powered methodologies for conducting comprehensive and insightful literature reviews.

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What Will You Learn?

  • Module 1: Prompt Engineering for Systematic Literature Reviews using AI
  • Learning Objectives:
  • • Understanding the foundational role of tailored prompts in guiding AI-driven systematic literature reviews.
  • • Crafting precise and focused prompts essential for optimizing literature search and data extraction.
  • • Techniques for engineering effective prompts to enhance the efficiency and comprehensiveness of review processes.
  • • Practical Application: Participants will create and refine tailored prompts for AI-driven literature searches.
  • Module 2: Developing Research Questions using AI
  • Learning Objectives:
  • • Recognizing the significance of well-crafted research questions in the context of systematic literature reviews.
  • • Identifying the essential components and characteristics of effective research questions.
  • • Employing techniques to formulate clear, targeted, and relevant research inquiries optimized for AI-enabled literature review processes.
  • • Practical Exercise: Participants will create their own research questions and refine them through guided feedback.
  • Module 3: Data Curation and Filtration using AI Tools
  • Learning Objectives:
  • • Introduction to AI-powered tools specifically designed for data collection and curation within literature reviews.
  • • Hands-on experience with diverse AI-based tools, optimizing data collection and filtration processes.
  • • Understanding the impact of filtering criteria on research outcomes and the significance of efficient curation.
  • • Practical Application: Participants will utilize AI tools to curate and filter relevant literature effectively.
  • Module 4: Literature Synthesis and Theory Development using AI Tools
  • Learning Objectives:
  • • Exploring advanced AI-driven methodologies for synthesizing extensive literature and fostering theory development.
  • • Application of AI tools to extract meaningful insights, patterns, and correlations within a diverse range of literature sources.
  • • Strategies for seamlessly integrating AI-generated insights into the synthesis and theory development process.
  • • Workshop Engagement: Participants will actively synthesize literature and develop theories using AI tools, enhancing their understanding of AI-driven synthesis methodologies.

Course Content

Module 1: Prompt Engineering for Systematic Literature Reviews using AI
Learning Objectives: • Understanding the foundational role of tailored prompts in guiding AI-driven systematic literature reviews. • Crafting precise and focused prompts essential for optimizing literature search and data extraction. • Techniques for engineering effective prompts to enhance the efficiency and comprehensiveness of review processes. • Practical Application: Participants will create and refine tailored prompts for AI-driven literature searches.

  • Fundamentals of Systematic Literature Reviews
    11:46
  • Introduction to Systematic Literature Review research article template
    12:02
  • ChatGPT Custom Instructions
    10:54
  • Prompt Engineering for Systematic Literature Reviews
    13:41
  • Live session 1 recording
    01:24:01

Module 2: Developing Research Questions using AI
Learning Objectives: • Recognizing the significance of well-crafted research questions in the context of systematic literature reviews. • Identifying the essential components and characteristics of effective research questions. • Employing techniques to formulate clear, targeted, and relevant research inquiries optimized for AI-enabled literature review processes. • Practical Exercise: Participants will create their own research questions and refine them through guided feedback.

Module 3: Data Curation and Filtration using AI Tools
Learning Objectives: • Introduction to AI-powered tools specifically designed for data collection and curation within literature reviews. • Hands-on experience with diverse AI-based tools, optimizing data collection and filtration processes. • Understanding the impact of filtering criteria on research outcomes and the significance of efficient curation. • Practical Application: Participants will utilize AI tools to curate and filter relevant literature effectively.

Module 4: Literature Synthesis and Theory Development using AI Tools
Learning Objectives: • Exploring advanced AI-driven methodologies for synthesizing extensive literature and fostering theory development. • Application of AI tools to extract meaningful insights, patterns, and correlations within a diverse range of literature sources. • Strategies for seamlessly integrating AI-generated insights into the synthesis and theory development process. • Workshop Engagement: Participants will actively synthesize literature and develop theories using AI tools, enhancing their understanding of AI-driven synthesis methodologies.

Thematic Development using Bibliomatrix

How to write a high quality Abstract

Student Ratings & Reviews

5.0
Total 2 Ratings
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Thank you Prof for the wonderful workshop
KV
4 months ago
One of the best courses I have ever visited. A lot of helpful practical examples, many tutorials and a great techer...thank you so much