Step 3. Contribution on FreeCodeCamp: My Second Translation Task.

After successfully submitting my first translation, the Chinese translation community manager recognised my accuracy in handling technical terminology and maintaining readability(Fig 1). This process deepened my understanding of FreeCodeCamp’s structured workflow and improved my ability to translate complex programming concepts clearly.

During our discussion, my manager explained that FreeCodeCamp offers two different contribution modes:

1. Full Translation Article – Translating an entire article from English to Chinese.
2. Proofread on AI- auto translation Articles – Proof-reading and refining AI-generated translations to ensure clarity and accuracy.

The manager also pointed out that newer articles often received priority for translation, leaving previously AI-translated articles without proper revisions and proofreading. This made it difficult for Chinese learners to access earlier study materials, as many remained available only in English (Fig 2). Realising this gap, I decided to take on a previously untranslated article that aligned with my expertise. With my manager’s suggestions, I selected “How to Write Clean Code – Tips for Developers with Examples”, which was updated slightly earlier in November 2024 (Fig 2a) and is closely related to my background in front-end JavaScript programming. Confident in my ability to ensure precise terminology and readability, I officially began my second contribution.

Having completed my first experience with a translation task, I was already familiar with the process of claiming a new translation project. I quickly navigated the issue tracker and followed the steps in the Contribution guidelines. By commenting on the /postedit in the issue tab, I’ve been assigned this task by the GitHub action bot (Fig 3).

After gaining experience from my first translation task, I decided to run my project modifications on Gitpod this time. Using Gitpod enabled me to edit and preview my translations in a cloud-based development environment (Fig 4), which made the process more efficient. This setup streamlined my workflow, allowing me to make real-time adjustments and verify formatting before committing changes.

After setting up my workspace, I began my task (Fig 5). Initially, I assumed that working with an AI-translated article would simplify the proofreading and translation process. However, I quickly realised that the AI-generated text often lacked sentence fluency and proper technical terminology, making it difficult to grasp the intended meaning. In some instances, the phrasing was so rigid that it was more challenging to understand than translating from scratch. Consequently, I had to frequently refer back to the original English version of the article (Fig 6). By comparing both versions, I found that the readability of the original text helped streamline my translation process, enabling me to produce a more natural and accurate translation. 

During the translation process, I noticed that if no changes were made to the document for a period of time, the Gitpod workspace would automatically close, requiring me to restart the environment and reload my previous translation progress. To mitigate this risk, I kept a real-time backup of my translation work in a local Word document (Fig 7). This step ensured that my progress was always saved, regardless of any unexpected interruptions in the cloud-based environment. Additionally, maintaining a separate backup allowed me to proofread my translations for readability and consistency. Based on my first PR submission, I accidentally forgot to delete the original English sentences. To avoid repeating words or including unnecessary text, I used my Word document to double-check my translation sentences. This process helped me ensure that my final translation was both accurate and natural, eliminating potential readability issues before submitting the PR.

Finally, after completing the proofreading and revisions of the AI-translated file, I submitted my second contribution. Drawing on my experience with the first PR, I promptly followed the Git workflow—creating a new branch, committing my changes to my repository, and pushing them to the main repository. I then prepared the checklist, ensured all necessary details were included, and closed the corresponding issue (Fig 8).

To move my task to the “Work in Progress – In Review” panel, I commented “/proofread”, signalling to the manager that my submission was ready for review (Fig 9).

After the team managers reviewed my translation document, it was merged into the FreeCodeCamp main repository (Fig 10).

My second Pull Request Link

https://github.com/freeCodeCamp/news-translation-tasks/pull/618

Reflection on My Second Contribution:

During my second translation task, I became more acquainted with FreeCodeCamp’s structured workflow, while also reinforcing my technical and theoretical knowledge through the translation process. Unlike my first task, which involved translating an entire article from scratch, this task required proofreading and revising AI-generated translations.

Initially, I presumed that AI-assisted translation would streamline the process, but I soon faced real-world challenges. The AI-generated text frequently lacked fluency and precision in technical terminology, which could result in misinterpretations for learners. Through human proofreading, I recognised how essential it is to ensure clarity and accuracy before these materials are officially published, as misleading translations could adversely affect learners’ comprehension. This process underscored the significance of accuracy and accessibility in educational content.

From the very start, my aim was to assist more learners in accessing programming education, even if English was not their first language. By providing technical resources in Chinese, I aspired to bridge the knowledge divide and create equal learning opportunities. This experience reinforced my choice of FreeCodeCamp as my open-source contribution project—to enhance accessibility and empower more learners worldwide.

Furthermore, I realised the significance of our course contributions beyond just coding, recognising that non-code contributions can be equally impactful. While coding is vital for developing and maintaining software, translating documentation is essential for making technical education genuinely inclusive and accessible. Without proper localisation, language barriers can hinder many learners from fully comprehending and applying technical concepts, limiting their ability to engage with open-source resources.

Through this experience, I gained a deeper appreciation for the collaborative nature of open-source communities, where contributors with different skills—whether in coding, documentation, translation, or community support—work together to make knowledge more widely available. By improving accessibility, translation efforts ensure that more people, regardless of their linguistic background, can benefit from open-source learning materials and enhance their technical skills.