What Every L&D Director Should Know About Translating Elearning Courses

What Every L&D Director Should Know About Translating Elearning Courses

Have you ever worked on an elearning translation project?

I’d expect that the first part of the project has been wondering where all of the source files are, then the question quickly turns to budget. 

How can you deliver training that works for your global audience without compromising on quality or breaking the bank?

The challenge of multilingual elearning often feels huge. 

A lengthy process, high costs, and cultural missteps can easily derail efforts. Who do you get involved with? When do they get involved and how much will it cost? Importantly, how long will the entire process take?

The demand for multilingual elearning has never been greater, especially with the increasing adoption of off-the-shelf courses:

• The global elearning market size is projected to reach $457.8 billion by 2026 (Source: Global Market Insights).
• 85% of global consumers prefer content in their native language (Source: Common Sense Advisory).
• 75% of users are more likely to engage with content in their native language (Source: Common Sense Advisory).

These statistics highlight the immense opportunity—and challenge—of meeting global learners’ needs with culturally relevant, localised training. But what if there was a way to change that? 

What if translating elearning content could be faster, more cost-effective, and culturally relevant?

At Real Projects, we asked ourselves these very questions:

• How can we deliver high-quality localisation at a fraction of the time and cost? As Scott Hewitt reflects, “The most significant challenge elearning directors face when translating elearning courses is understanding the process. It’s not just about using AI to translate and publish content. To deliver a product that works, you need to have a clear grasp of the entire process.”
• Can we meet the demand for diverse languages without sacrificing quality? “To ensure cultural relevance and accuracy,” says Scott Hewitt, “you need to use humans in your process. AI can play a key role in translation, but native speakers and human oversight remain vital.”
• Could AI not only speed up localisation but also reinvent the process entirely?

 

Innovations in Translation Processes

We approached this as more than a translation project—it was a comprehensive innovation initiative. 

Every step of our workflow was reimagined to incorporate AI tools while ensuring human oversight to maintain quality and authenticity. 

We’d spent years working on translation projects, delivering elearning courses for clients around the world. 

Budgets have always been a challenge for clients and delivering projects in a timely manner is always something to consider. 

Customers are now ready to look at how AI can be used in translation projects, but just pressing translate isn’t the solution. You are likely to run into problems at some point in the future.

Challenges in Multilingual Elearning

To address these challenges, we set out to overhaul how elearning localisation is done, recognising the importance of off-the-shelf courses in meeting diverse needs. 

Here’s how we did it:

1. Script Localisation We developed custom AI models to handle complex terms and idiomatic expressions, avoiding errors like mistranslated metaphors. To ensure accuracy, we introduced a two-stage human review process, combining speed with precision.
2. Video Adaptation AI-powered tools helped us translate and synchronise scripts, ensuring subtitles stayed within character limits for readability. For voiceovers, native speakers reviewed AI-generated options to guarantee authenticity and engagement.
3. Team Training Our team received targeted training to integrate emerging AI tools into their workflows, allowing them to seamlessly balance traditional and AI-enhanced methods.
4. Automated Validation We built internal AI programs to cross-check outputs against style guides and client requirements, ensuring consistency across hundreds of courses.

Key Innovations in Multilingual Elearning

Custom AI Training and Tools

Our team developed proprietary AI models tailored to industry-specific needs.

These tools were trained to recognise and handle cybersecurity terminology, idiomatic expressions, and cultural nuances.

For example, the word “phishing” in cybersecurity had to be accurately translated without losing its context or being mistaken for literal fishing.

Human-in-the-Loop Systems

While AI provided speed and scalability, we recognised its limitations in capturing subtleties. Native speaker reviewers were brought in to verify translations, ensuring both linguistic accuracy and cultural relevance.

This two-tiered review system provided an additional layer of quality assurance.

Dynamic Video Localisation

Traditional AI-based video tools often compressed translated audio to match the pacing of the original video.

If you don’t check the speed of your voiceover, it leads to a rushed voice that doesn’t have the correct pace.

You’ll need to go through and listen to each voiceover to ensure that the pace and pronunciation is correct. If you don’t you’ll miss rushed or unnatural voiceovers. 

To address this, we developed a system for manual pacing adjustments, ensuring natural and engaging audio in every language.

Voice Optimisation for Cultural Authenticity

AI-generated voices can sound robotic if not carefully selected. We worked with native speakers to choose voices that resonated with each region’s linguistic and cultural expectations.

You need to select the right voice, selecting the right tone and dialect for each language, Latin American Spanish requires meticulous testing to ensure relatability and engagement.

AI-Driven Consistency Checks

We wrote custom programs to validate course categories, competencies, and learning objectives against client standards.

This ensured a consistent and accurate user experience across all courses.

Lessons Learned

Practical Insights

Here are actionable takeaways for L&D Directors:

• Identify key languages for your audience.
• Build a budget with room for quality assurance.
• Prioritise cultural relevance alongside linguistic accuracy.

Our process wasn’t without its challenges.

But each hurdle taught us something invaluable. These learnings not only refined our processes but also strengthened our ability to innovate and collaborate effectively.

1. AI Is a Tool, Not a Replacement AI significantly sped up the localisation process, but it couldn’t replace the nuanced understanding of human reviewers. Early in the project, we discovered that AI often struggled with idiomatic expressions and cultural references.
   
   For example, AI tools occasionally misinterpreted phrases or substituted inappropriate metaphors. This reinforced the importance of a human-in-the-loop system to ensure quality.

2. Adaptability Drives Success Innovation is rarely a linear process. Throughout the project, we had to pivot quickly as new challenges emerged.
   
   For instance, some AI tools initially selected for video translations failed to meet pacing and audio clarity standards.
   
   By testing multiple platforms and iterating on our workflows, we found solutions that worked for our specific needs.

3. Collaboration Shapes Strategic Focus Feedback from OpenSesame played a critical role in guiding our priorities. As Scott Hewitt advises, “Collaboration is absolutely key, whether it’s working with your translation team or engaging with your customers. You need to understand how the final product will be used and what’s acceptable for the audience.”
   
   By understanding their customer needs—such as shorter courses, flexible audio options, and high production quality—we were able to align our innovations with market demands.
   
   This collaboration underscored the importance of open communication in driving mutually beneficial outcomes.

4. People Make Technology Work Technology alone couldn’t deliver the desired outcomes. As Scott Hewitt suggests, “My advice to elearning directors starting their first translation project is: don’t dismiss human translators. While their role may have evolved, they are still an integral part of creating high-quality translations.”
   
   Training our team to work with new AI tools and processes was essential. Not all team members were initially comfortable with the shift to AI, but through workshops and hands-on experience, we built a team ready to embrace the future of localisation.

Key Outcomes: Raising the Bar for Multilingual Elearning

Our efforts have paid off in transformative ways:

• 500 Localised Courses in Six Languages: Delivered in under six months, setting new industry benchmarks.
• Enhanced Learning Objectives: Clearer, measurable objectives improved engagement and satisfaction.
• Scalable Framework: The model is flexible enough to expand into additional languages and content areas.
• Global Reach: Courses now connect with learners across Latin America, Europe, and beyond.

Final Reflections

Translating elearning isn’t just about language—it’s about connection. By combining AI’s capabilities with human insight, we’ve created a scalable model that delivers culturally relevant, high-quality training.

As elearning directors, the question isn’t whether you should embrace multilingual content. The real question is: how will you adapt to meet the needs of a global audience? With the right tools, collaboration, and mindset, the possibilities are limitless.