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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

Concept maps: A tool for knowledge management and synthesis in web-based conversational learning.

Ankur Joshi¹, Satendra Singh², Shivani Jaswal³

¹Department of Community Medicine, Gandhi Medical College, Bhopal, Madhya Pradesh, India.

International Journal of Applied & Basic Medical Research

|August 27, 2016

Summary

This summary is machine-generated.

Concept maps can enhance critical thinking in online learning by summarizing vast amounts of collaborative data. This method aids in making connections and extracting collective wisdom from web-based discussions.

Keywords:

Adult learning concept map conversational learning process summary web-based learning

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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

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Published on: June 13, 2025

Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties

Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties

Published on: September 27, 2020

Area of Science:

Educational Technology
Knowledge Management

Background:

Web-based conversational learning facilitates collective knowledge creation.
Online forums generate large, multidimensional data potentially hindering learning.
Constructivist knowledge creation requires complex, often unpredictable information.

Purpose of the Study:

To explore the use of concept maps as a tool for summarizing information in web-based conversational learning.
To investigate how concept maps can improve critical thinking and learning by connecting shared knowledge.
To provide a theoretical framework for understanding the impact of social constructivism on conversational learning.

Main Methods:

An exploratory approach was used, implementing concept maps on the FAIMER-Listserv platform.
Qualitative evidence was gathered through peer feedback.
A theoretical construct linking social constructivism to conversational learning was developed.

Main Results:

Concept maps served as effective "process summary" tools.
The method facilitated making connections between facts and knowledge shared in online discussions.
Peer feedback provided qualitative support for the innovation's utility.

Conclusions:

Concept mapping is a viable strategy for sense-making in complex online learning environments.
This approach supports critical thinking and enhances information extraction from collaborative discussions.
Social constructivism principles underpin the effectiveness of conversational learning enhanced by concept maps.