Demystifying Neural Networks: A Stage-Based Learning Approach for Novice Students

The Challenge for Novices

Artificial Neural Networks (ANNs) are fundamental to modern Artificial Intelligence (AI), impacting fields such as healthcare, finance, and autonomous systems. Despite these wide-ranging applications, these concepts can be difficult to master, especially for beginners who often struggle with abstract maths and theory. Traditional teaching methods usually take an instructive approach rather than explorative, making it challenging for beginners to develop hands-on experience and insight on how AI concepts interact.

A key challenge is the lack of interactive environments where students can experiment with parameters like activation functions and learning rates in real time. Without practical engagement, learners struggle to connect theory with real-world applications. While several existing tools enable users to build ANNs without programming experience, they generally do not emphasize the educational aspects or provide structured pedagogical support.

Our Innovative Solution

This poster introduces an interactive dynamic learning playground designed to help students visualize and experiment with ANNs. The tool allows users to adjust key parameters and observe their effects instantly, supported by pre- and post-assessments to measure learning outcomes. Designed to be used independently or alongside traditional teaching, the platform offers staged learning with case studies and practical examples that link abstract mathematical concepts to everyday decision-making, aiming to make ANNs more accessible and enhance AI education.