This blog reflects on the One-Week Free Online Faculty Development Program (FDP) on Research and Writing with AI Assistance organized by the Institute of Public Enterprise (IPE), Hyderabad – India’s Premier Business School.
In this blog, I share my key takeaways and insights from the five-day FDP.
Day-1 Idea Generation and Sourcing Literature
Resource person: Dr. Rama Krishna Yelamanchili
In this session, the resource person provided a hands-on demonstration of various AI tools for research and literature review. He practically showcased how these tools can be used to generate research ideas, build literature maps, and manage references. Additionally, he introduced ChatGPT-based tools like Innovative Research Idea Generator, Paper Wizard, Brain Wave, and EduInnovate, which assist in brainstorming research topics and academic writing.
Essential Elements of a Research Paper
- Novel Topic: Choose a unique and relevant research topic.
- Strong Theoretical Framework: Establish a solid foundation with existing theories.
- Extensive Literature Review: Conduct a thorough review to understand research gaps.
- Meticulous Methodology: Ensure precise and well-structured research methods.
- In-depth Analysis: Provide comprehensive and critical data interpretation.
- Robust Results: Present well-supported and credible findings.
Convincing Conclusion: Summarize key insights effectively.
- How to Pick a Research Topic
- Observe real-world events and trends.
- Draw inspiration from your teaching subjects.
- Engage in discussions with peers.
- Explore research journals in your field.
- Conduct an extensive literature review.
AI Tools for Research and Literature Review
Idea Generation:
- PaperGuide.ai
- Editpad
- AppyPie
Literature Mapping & Connections:
- Citrus Search
- ResearchRabbit
- Inciteful
- Litmaps
- Connected Papers
Reference Management:
- Hypothesis Maker
- Zotero
- Bibliography (Zbib)
This session has significantly enhanced my understanding of AI-assisted research and writing. The practical exposure to these tools will streamline my research process, improve idea generation, and enhance the depth and efficiency of my literature review and academic writing.
Day-2 Literature Review with AI Assistance
Resource person: Dr. Kalyani
Conceptual Base of Literature Review
- A literature review is not just a summary but a critical analysis of existing research.
- It connects past studies with your research objectives, identifying trends and gaps.
- A strong conceptual foundation ensures a well-structured and meaningful review.
How to Write a Literature Review
- Begin with a clear objective and research question.
- Identify relevant sources and critically analyze them.
- Organize the review systematically using a structured approach.
Approaches to Writing a Literature Review
- Chronological Approach – Organizes studies based on publication years.
- Reverse Chronological Approach – Begins with the latest research and moves backward.
- Thematic Approach – Groups studies by themes or topics.
- Methodological Approach – Categorizes research based on methods used.
- Conceptual Framework Approach – Focuses on theoretical concepts and models.
Structure of a Literature Review
- Introduction: Defines the research scope, importance, and key themes.
- Body: Uses various approaches (thematic, chronological, etc.) to analyze research.
- Conclusion: Identifies research gaps and highlights future research directions.
- Use of AI in Literature Review AI tools assist in searching, summarizing, and structuring research papers.
- Despite AI’s help, reading a few key papers thoroughly is crucial for understanding theories.
- Demonstrated various AI tools for literature review (as listed in the session).
- New Tool: Lateral.ai – Helps organize and create an LR table for better structuring.
SMART Framework for Literature Review
S – Search: Identify relevant literature using databases and AI tools.
M – Map: Organize and categorize studies based on themes and approaches.
A – Analyze: Critically evaluate research findings, methodologies, and arguments.
R – Refine: Identify gaps, inconsistencies, and missing links.
T – Transform & Rewrite: Synthesize information to align with your research objectives.
Day-3 Research Design with AI tools
Resource person: Dr. Rama Krishna Yelamanchili
The session covered different types of research designs and methods, emphasizing their role in structuring a study. It introduced Mono-method (using a single approach) and Mixed-method research (combining qualitative and quantitative approaches). The book recommended for Mixed-method research was Research Design: Qualitative, Quantitative, and Mixed Methods Approaches by John W. Creswell.
A key takeaway was that methodology is the heart of research, as it ensures rigor and validity in findings. The session also highlighted the use of AI tools like ChatGPT to generate research paper titles and refine research approaches.
Some AI tools suggested for research support include:
Prompt Diary – For tracking research-related AI prompts.
CPT Explore - Mentor for Research – A guided research assistant.
Design Academic Guide – For structuring research work.
Research Method Advisor – Providing insights into research methodologies.
Research and Methodology Assistant – Offering assistance in refining research techniques.
Day-4 Data Interpretation and Analysis with AI Tools
Resource person: Dr. Rama Krishna Yelamanchili
1. Scales of Measurement
- Understanding data begins with knowing its measurement scale:Nominal: Categorical data without order (e.g., Gender, Colors).
- Ordinal: Ordered categories but without equal differences (e.g., Rankings, Satisfaction Levels).
- Interval: Numeric data with equal differences but no true zero (e.g., Temperature in Celsius).
- Ratio: Numeric data with a true zero, allowing meaningful ratios (e.g., Weight, Height).
2. Using Statskingdom for Descriptive Analysis Upload data to Statskingdom.com to perform descriptive analysis (mean, median, standard deviation, frequency distribution).
Obtain summary statistics to understand central tendencies and variability.
3. GPT for Data Refinement & InterpretationRevise the output from Statskingdom and re-upload structured data to GPT for further analysis and interpretation.
Utilize GPT-Data Analysis and Report AI to generate insights, trends, and reports.
Explore Advanced Data Analysis in GPT for deeper statistical modeling, correlation, and forecasting.
4. Key TakeawaysStatskingdom helps with fundamental descriptive statistics.
GPT tools enhance interpretation and provide a refined, structured data-driven narrative.
Advanced Data Analysis in GPT assists with deeper insights, trend recognition, and comprehensive reporting.
Day- 5 Finalizing the manuscript with AI Assistance
Resource person: Dr. Swati Mathur
Choosing the Right Journal
- Select a target journal based on Q1-Q4 or ABCD ranking.
- Ensure citations come from journals of the same level for credibility.
Discussion & Conclusion Section
AI can assist with idea formation, but direct AI-generated content should not be used.
The session covered structure, content, and best practices for writing a strong discussion.
AI Tools Explored
ChatGPT, Jenni.ai for idea generation.
Writefull.com (Word plugin) for paraphrasing AI-generated text.
Thrix.ai to check references (free once a day).
Manuscript Proofreading & Readability
Sentence-by-sentence proofreading is essential.
Introduction to Flesch–Kincaid readability tests for clarity improvement.
AI-assisted abstract writing based on the discussion and conclusion section.
Writing Style Guidelines
Emphasis on passive voice usage in academic writing.
Prompt directory creation for AI-driven writing support.
Thank you for reading. I hope my reflection was helpful to you as well.