The presentation was delivered to the Bagwell College of Education faculty and students. The outline: 1. Using generative #AI to develop a research question and topic, build a conceptual framework 2. AI-based search engines and the use of generative AI technology for searching 3. Analysis and synthesis of the literature 4. Pros and cons of using generative AI to review literature

1. AI is here to support the
literature review!
http://bit.ly/AI4LR

2. Positionality

3. Literature Review phases
Research Question and Topic
Development
Searching for Evidence Analysis & Synthesis

4. Research Question
Developing research
questions using ChatGPT
prompts
Using Elicit to generate a
research question
Hippo from Sage RQ generator

5. Topic and Concepts Development
Concept
Paper
Conceptual Learning
Topic
Literature or
Knowledge Mapping
Research Question
Research Planning
https://libguides.kennesaw.ed
u/Research_Plan/checklist

6. Concept & Literature Mapping
• Concept Mapping -
VOSViewer, Open
Knowledge Map, Elicit
• Citation Mapping - co-
citation, citation chaining,
reference analysis: LitMAp,
Research Rabbit, Inciteful

7. Research Rabbit

9. Semantic
Search
Engines
• AI algorithms use
vector
comparisons and
NLP.

10. Extract data and
Concepts
Citation Analysis
Search (NLP)
Elicit
Summary

11. Review
Steps
Summarization
•
Smmry
• Paper-Digest
• Scholarcy
• Explainpaper
• RobotReviewer
DataSeer (data extraction)
Meta-synthesis
• Nvivo and Atlas.ti
• RapidMiner
Meta-analysis
• DataRobot
• ASReview
• Network analysis/
• Visualization
• Citation analysis
Analysis Review
•Elicit: The AI Research
Assistant
•Iris.ai
•Laser.ai
•Lateral
•Paper Wizard .
•Snowball
•PaperDigest
•Scite Research Assistant
(Beta)

12. Pro/Cons
Pros Cons
Time efficiency: AI-generated
summaries save researchers time,
allowing them to focus on analysis
and interpretation.
Comprehensive coverage: AI can
review vast literature quickly, ensuring
researchers stay informed of the
latest developments.
Improved accessibility: AI-
generated summaries can make
complex research more digestible,
promoting knowledge sharing and
interdisciplinary understanding.
Accuracy: AI-generated content not
always accurately represent the
original research (hallucinations or
false citations)
Transparency: Sources are not clear
or checked. AI-generated content and
sources for training large learning
models are hidden.
Coverage is limited to open-access
sources.
Synthesis and interpretation:
technical flows – technology is not
available yet

13. Citing generative
AI
• APA Style: How to Cite ChatGPTInformation about
how to quote AI-generated text, create references to AI
models and software, and related issues.
• Chicago Style Online: Citing Content Developed or
Generated by AIThis site features questions and
answers about how to cite AI in text and how to create
formal citations for footnotes or endnotes.
• MLA Style Center: How Do I Cite Generative AI in
MLA Style?This site provides information about using
the MLA template, paraphrasing and quoting text, citing
creative visual works, and more.
• Citing AI-Generated Images Guidance from the U. of
Victoria Libraries on citing images from some of the most
popular AI image generators.