Faculty Syllabus

After completing this course, you should be able to:

• Apply basic React concepts, such as components, state, props, and JSX, to create advanced web pages and applications.
• Configure and set up a React development environment for web development projects.
• Understand the React component lifecycle and implement lifecycle methods to add interactivity to web pages and applications.
• Use event handlers to add interactivity and manage state to build dynamic web pages and applications.
• Apply styling techniques to React components, including inline styles, CSS classes, and libraries such as Material UI.
• Implement React Router to create different routes and manage complex navigation in web pages and applications.
• Use forms and CRUD to manage input and validation in web pages and applications.
• Understand and apply hooks, including useState and useEffect, to manage state and side effects in React components.
• Make API requests in React and handle API data with state and props to create dynamic web pages and applications.
• Develop and implement unit tests for React components using testing frameworks and libraries.
• Connect web application to a real time database.

How to Pass INEW 2334

In our previous course, everything was competency-based: you had to fully master one area before moving on, and the system unlocked the next section only after you hit the required score. That approach worked like building blocks—each step depended on the one before it.

This 4-week course works differently. Instead of waiting for you to “unlock” the next stage, the course follows a fixed schedule with real deadlines. Everyone moves forward together, and your assignments and assessments must be submitted by the posted due dates. Think of it less like a self-paced ladder and more like a group project on a timeline—you’ll need to stay on track each week to keep up.

About Assessment Attempts

For this course, you have two attempts for each end-of-competency assessment. However, your score will be based on the average of both attempts.

Capstone Competency: Start Planning Early

The Capstone is the exception to the sequence. You’re not required to finish it right away, but you should review it early. It outlines your final project, and understanding what’s expected ahead of time will help you stay focused and organized throughout the course.

Follow the Sequence — It’s There for a Reason

This course is set to a forced sequence, which means you must complete each section in order. Skipping ahead or jumping around will either be blocked by the LMS or result in confusion if you just click "completed". The material has been carefully arranged to build your skills step-by-step and taking shortcuts will only create unnecessary setbacks. Stick to the path and trust the process. You’ll be glad you did.

To "complete" each section, there may be a button or checkbox to click saying you are done with that section.

Pace Yourself — But Stay on Schedule

You’re welcome to move quickly through the course, but please note that Competency deadlines are firm. Once a due date passes for that competency, you will not be able to go back and submit. Be sure to manage your time wisely and stay on top of all requirements.

📅 Due Dates & Deadlines

All due dates are listed in Blackboard Ultra and linked to the calendar tool 🗓️. You're responsible for checking this calendar regularly. Late work policies still apply.

This course is flexible in pace, but that flexibility requires excellent time management skills. You can work ahead — but not behind.

COMPETENCY 1 - ORIENTATION, SDLC, and TDD

Understanding this competency is essential because it combines both project management principles and hands-on technical skills. By identifying key course components, students build a clear foundation for meeting expectations and managing their own learning effectively. Exploring the Software Development Life Cycle (SDLC) ensures students can recognize the value of structured processes and choose the right model for different projects, improving quality and reducing risk. On the technical side, practicing with Jest and Test-Driven Development (TDD) equips students to write reliable, maintainable code. Together, these skills prepare students to approach software projects with both strategic planning and practical testing discipline.

COMPETENCY 2 - REACT: AN INTRODUCTION

Students will learn how JavaScript’s asynchronous model supports responsive applications and why this differs from traditional object-oriented programming. By working with callbacks, Promises, and async/await, students will understand how to control timing and handle delayed results. They will also apply these concepts in React by managing state and props while fetching and displaying data. This module is important because it equips students with the ability to build interactive applications that remain smooth and reliable, even when waiting for external resources. Mastery of these skills prepares students to design real-world web apps that users expect to be fast, dynamic, and seamless.

COMPETENCY 3 - REACT FORMS & VALIDATION

Forms are where users and applications meet, making them one of the most important skills you can master in React. You will see why React takes a different approach from HTML forms and how that shift gives you more control, clarity, and flexibility. You’ll explore the role of controlled and uncontrolled components and understand why choosing the right approach impacts the reliability of your app. You’ll also discover how React Hook Form reduces the headaches of managing complex state and validation, while React’s event system keeps your code consistent across browsers. Finally, you’ll learn how combining React Hook Form with Yup schemas creates a solid foundation for building forms that are both user-friendly and production-ready.

COMPETENCY 4 - DATABASES

Databases exist in nearly every modern application, and their design can impact performance and reliability. Poorly structured databases lead to duplication, inconsistencies, and the loss of information. This module introduces you to normalization, a systematic approach to organizing data that ensures consistency and strengthens integrity. You will explore how different database types handle data, why relational structures are powerful, and where NoSQL solutions offer flexibility. You will also consider the role of security, including the risks of SQL injection, and the importance of backups for recovery. These concepts provide the rationale for why thoughtful database design is essential to building scalable and secure systems.

CAPSTONE - BRIGHT FORGE WIDGETS - PHASE 1

Students learn how to bridge the gap between stakeholder needs and technical solutions by analyzing narratives and translating them into clear user stories. They also gain practical skills in designing normalized databases that ensure accuracy and scalability while reducing duplication. Finally, by creating wireframes and applying a consistent branding palette, students connect functionality with user-friendly design, preparing them to deliver applications that are both effective and engaging.

All materials will be supplied in class through BlackBoard as needed.
 

Introduction

In this course, Generative AI (GAI) tools—such as ChatGPT, Copilot, Bard, and similar platforms—can be powerful aids for learning and creativity. I support their responsible, transparent, and ethical use when it enhances understanding and does not replace your own critical thinking or original work. In fact, you will have AI assignments which must be completed before starting other course work.

Used correctly, these tools can help you explore ideas, understand terminology, and see multiple approaches to solving a problem. Used incorrectly, they can hide gaps in understanding and produce work that looks correct but is not. This policy sets clear expectations so you can use these tools in ways that strengthen your skills and protect academic integrity.

Rationale

In the world today, being able to use AI is a must. Even in non-programming roles, the understanding and uses of AI are inescapable and required for all jobs eventually. But to use it correctly, you need to understand what it can do and how it can be used to break things very easily. Imagine GAI as a 6-foot chainsaw that everyone now has. But do you need a 6-foot chainsaw for everything? Use it responsibly.

In technical fields, AI can speed up learning, but it can also amplify mistakes. AI can generate insecure code, misleading explanations, and incorrect citations with high confidence. Learning to verify outputs, recognize limitations, and document your process is part of professional readiness. This course treats AI literacy as a real-world skill that must be practiced with discipline and good judgment.

Definition

For this course, GAI refers to any technology that can generate text, code, images, audio, or other media in response to prompts, including—but not limited to—OpenAI ChatGPT, Google Gemini, GitHub Copilot, DALL·E, and similar AI-driven content creation tools. If you must tell the system what to do, chances are it is AI and falls under this category. Applications like Grammarly and Zotero are great for typos, grammar, and citations BUT they do not always work! Please double check your citation submissions!

This definition includes tools embedded inside editors, browsers, learning platforms, and search engines when they produce generated output rather than simply retrieving sources. If a tool is “suggesting” full sentences, paragraphs, solutions, or code blocks based on prompts or context, it is included. When in doubt, treat the tool as GAI and disclose its use so there is no confusion later.

Resources

• Review the tool’s terms of service and privacy settings.
• Cross-check AI-generated content with authoritative sources.
• Use AI output only as a starting point, not as a final submission, unless noted in assignments and assessments.
• Apply proper citations when AI output informs your work.

For technical topics, “authoritative sources” means official documentation, standards, reputable textbooks, and instructor-provided materials. If AI provides a claim, you should be able to verify it independently. Keep brief notes about what you asked, what you received, what you accepted or rejected, and why. This habit strengthens learning and makes disclosure easy.

Assessment

Unless otherwise noted, all assignments must reflect your own comprehension and skills. AI assistance must be disclosed as a formal APA 7 citation when used. See Resources link for how to use APA 7 properly.

Disclosure is required whether AI helped you generate content, refine wording, produce code, summarize sources, or brainstorm approaches. If AI influenced your final submission in any meaningful way, cite it. Your grade depends on demonstrating your understanding, so you should be prepared to explain and defend your choices, your code, and your reasoning without relying on the tool during grading.

Penalties

Failure to follow this policy—including failure to disclose AI use—will be treated as a violation of the college’s academic integrity policy. Penalties may include a zero for the assignment, additional work, or escalation to the Academic Integrity Committee.

This includes submitting AI-generated work as if it were entirely your own, using AI during restricted activities, or presenting generated output that you do not understand. Penalties may also apply when citations are missing, misleading, or intentionally vague. If you are unsure whether your use requires disclosure, disclose it. Transparency protects you.

Exceptions

Specific assignments may prohibit AI use entirely (e.g., in-class exams) or require it (e.g., AI prompt engineering exercises). Such exceptions will be clearly stated in the assignment instructions.

When AI is prohibited, you must complete the work without AI assistance, including drafting, rewriting, or “checking” your work with a tool. When AI is required, you must follow the stated workflow, including documenting prompts and outputs, and meeting any citation or submission rules. If instructions conflict, the assignment instructions take precedence.

Usage Permissions

Please closely read requirements for all assignments and submissions as they differ from one to the next.

Some tasks will allow AI for brainstorming but not for final wording. Other tasks may allow AI-generated starter code but require you to modify, test, and explain it. In all cases, you are responsible for the final product you submit, including correctness, security, and clarity. If an assignment requires disclosure details, follow that format exactly.