SIWES Placement Evaluator

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  Introduction

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  Searching for SIWES

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  Display why SIWES matches with user searc

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  Matches gotten from searched SIWES

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  Filter any the user requirements which is transportation

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  If no match is found it display it below

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  Another search with different entries

inspiration

Finding a suitable SIWES placement can be difficult for Nigerian engineering students. A placement may look relevant because of its organization or location, but practical constraints such as distance, transportation, and accommodation can make it unsuitable.

I wanted to build a simple tool that answers a more useful question: “Why is this placement suitable for me?”

What it does

SIWES Placement Evaluator helps engineering students evaluate sample SIWES placements using four practical factors:

• Engineering-field relevance
• Maximum preferred distance
• Transportation availability
• Accommodation availability

Students enter their requirements and receive matching demo placements with a transparent, factor-by-factor explanation of why each result matches.

The project deliberately uses clearly labeled sample/demo records rather than claiming to provide a verified database of employers.

How I built it

The application is a mobile-first web app built with:

• Vanilla HTML
• CSS
• JavaScript
• Local JSON-style demo data
• Client-side matching logic

There is no backend, database, authentication, external API, or framework. The application can run locally with a simple Python HTTP server.

The matching engine checks each requirement explicitly instead of hiding the result behind an opaque score.

What I learned

Building this project helped me practice turning a real-world problem into a focused product scope, defining requirements before implementation, designing transparent matching logic, and testing different combinations of user constraints.

I also learned how to use the Build With AI learning workflow to move from an initial idea through scope, product requirements, technical specification, implementation, testing, and shipping.

Challenges

One challenge was keeping the project small enough to complete while still making the result useful. Instead of attempting to build a nationwide SIWES database, I focused the prototype on the core evaluation experience.

Another challenge was making the matching results understandable. Rather than presenting a single unexplained score, the application shows the individual factors that caused a placement to match or be excluded.

What's next

A future version could include verified employer data, real application links, student accounts, saved placements, reviews, and live location/routing information. Those features are intentionally outside the scope of this prototype.

Built With

• ai
• app
• css
• html
• javascript
• web