Articles

Clear writing for curious minds

Practical explainers and essays from Coding Central on computer science, AI, and emerging tech.

Java8 min read

Arrays and ArrayLists in Java

A beginner-friendly walkthrough of Java arrays and ArrayLists, written for students who found arrays confusing at first.

By Jaimee Grubb

Computer Science6 min read

Comp Sci and Space

How computer science supports space exploration, from Apollo-era programming to modern simulations, robotics, and data.

By Jaimee Grubb

Fundamentals7 min read

Looking at Coding Concepts

An introduction to message passing and variables, using Scratch and Java examples to show the complicated side of simple actions.

By Henry Pham

Artificial Intelligence9 min read

Role of AI in the Entertainment Industry

How AI is reshaping games, content creation, and social platforms, and the ethical, privacy, and creative concerns that come with it.

By Henry Pham

Java10 min read

Understanding Loops in Java

Why loops keep games and apps running smoothly, how for, while, and do-while loops work, and a mini number-guessing project.

By Bisrat Ayalew

Algorithms6 min read

How Recommendation Algorithms Work

A clear look at how platforms sort endless options into relevant recommendations using machine learning and user interaction.

By Bisrat Ayalew

Algorithms7 min read

Gnome Sort / "Stupid" Sort

A look at the deceptively simple Gnome Sort: how it works, why it is slow, and why it is still worth studying.

By Thai Nguyen

Python12 min read

Teaching Technology to the Next Generation: Tic-Tac-Toe

Build a complete Tic-Tac-Toe game in Python while learning initialization, loops, state management, and error handling.

By Quang Duong

JavaScript10 min read

Teaching Tech to the Next Generation: Basic Video Game Design

A beginner walkthrough of brainstorming, sprites, the draw loop, controls, and collisions in Code.org Game Lab with JavaScript.

By Danny Le

Artificial Intelligence5 min read

Deep Learning vs. Machine Learning

A clear comparison of machine learning and deep learning, how they differ in data needs, feature work, training, and performance.

By Sarah George