Blended Learning

Tuesday, 8 July 2025

Artificial Intelligence (AI) Tools for Research: Reviews, Analysis



1.  Artificial Intelligence (AI) Tools for Research: Reviews, Analysis (ppt)

2. Innovating Education with Artificial Intelligence

2.1. Unclocking the Potential of Artificial Intelligence for Educational Excellence

3. Applications of AI in Teaching, Learning, and Research 

4. Responsible AI Principles (Elsevier)

5. Scopus AI (pdf)

6. Scopus Lib Guide: Scopus AI

7. How do I Search in Scopus

8. 14 Review Types

9. Tools of Research

10. Educational Research: Innovatie Ways of Researching

Hands-on-activities

1. Student Diversity and Inclusive Education

2. Elsaspeack (How to improve English)

3. Parameters to select a vehicle (four-wheeler)

4. AI-Personalized Learning

5. AI Tools for Research



7 comments:

I Bio Specimen said...

Interesting read. With the growing demand for biospecimens, Internet-based biobanks play a crucial role in global data integration, enhancing research reproducibility and speed.Internet-Based Biobank

morphacademy said...

Top Artificial Intelligence Course in Chandigarh - Morph Academy provides industry-recognized AI Certification Programs designed for aspiring AI professionals. Learn to develop AI-powered applications, predictive analytics, and automation systems.

AI Libry said...

I read your blog. It is very useful for me.
Visit Our: AI Video Tools

Atishay Jain said...

Great insights shared in this post! If you're interested in modern web development and UI/UX design, feel free to check out the portfolio of Atishay Jain — showcasing creative and performance-driven projects.

ahujabooks said...

Really insightful post! We are committed to offer medical books at low prices, so that college student can buy books on a tight budget as well ranging from new & used textbooks.

topseo1011 said...

This post does a great job of explaining the gap between powerful AI models and real-world usability. The emphasis on context really stood out to me, especially how missing context can lead to poor or misleading outcomes even with advanced systems.

I recently read a related piece that goes deeper into this topic and explains why context is often the missing layer in modern AI systems:
https://contextualaisystems.blogspot.com/2026/01/why-context-is-missing-layer-in-modern.html

Thanks for sharing such a thoughtful and practical perspective.

topseo1011 said...

Really appreciated this article, especially the practical angle on analytics rather than just focusing on new tools or trends. Excel’s flexibility and transparency still make it extremely relevant for everyday analysis.

I came across a useful breakdown on why Excel still matters in analytics, particularly for teams that value clarity and control over black-box solutions:
https://contextualaisystems.blogspot.com/2026/01/why-excel-still-matters-in-analytics.html

Great insights overall—looking forward to reading more content like this.