Our 5 practical tips to reduce the time needed to design your courses thanks to AI, while maintaining quality

In terms of corporate training, AI is an essential tool for accelerating the speed of design without sacrificing educational quality. As training teams seek to respond quickly to changing skill needs, AI offers concrete solutions: it automates the processing of raw content, customizes learning paths, and provides recommendations in real time. However, exploiting AI effectively requires specific strategies to maximize its benefits while ensuring a rise in learners' skills. In this article, discover five practical tips for making the most of AI and optimizing your design timelines without compromising on instructional quality.

Define my goal

For AI to produce content that is adapted and aligned with the expectations of your training, the educational objective must be clearly defined from the start. Let's imagine training in project management. If the educational objective — for example, “to acquire the basics of project planning” — is not specified to the AI, it could generate too general content, or even address peripheral aspects such as task management software or advanced budget monitoring techniques, without a direct link to the targeted learning.

On the other hand, if the AI receives a clear educational objective, it knows how to guide the content to comply with it. For our project management training, an objective such as “mastering the stages of planning and assigning resources” will guide the AI to create a path focused on these aspects, by selecting case studies, examples and exercises that align with the expected level. Learners will then be able to Make progress effectively towards a specific objective, guaranteeing a concrete and measurable increase in skills.

Didask integrates this approach by allowing designers to clearly indicate the skills they are looking for right from the start. This crucial step is facilitated by the fact that each module can be specifically configured to align with learning needs. This process makes AI more effective and reduces the iterations needed to arrive at quality final content, saving valuable time.

Provide detailed context

For AI to produce content adapted to your educational expectations, it is crucial to provide it with a detailed background. It is from this precise information that AI will draw on to build a training course that meets the specific needs of your audience.

Let's go back to the example of project management training. By telling the AI that the participants are beginners, it will be able to adjust the level of complexity and opt for simple examples, focused on concrete situations rather than on theoretical models. On the other hand, if your audience is experienced, AI will be able to integrate deeper case studies and complex situations.

By using a LMS like Didask, it is possible to configure accurate information about learners and their needs from the start. This approach ensures that the AI has the context it needs to generate personalized and engaging modules. A good example to go deeper into this point is Didask's article on The differences between good and bad adaptive learning, which explains how to personalize content as closely as possible to learners' expectations.

Give initial content on which the AI can be based

When you provide the AI with basic content, such as a reference document or a presentation, it helps them produce a result that is true to your educational expectations and tailored to your style. This reference content allows the AI to guide the design around your themes and the desired tone.

Let's take the example of a training course on conflict management : by downloading resources such as an internal communication guide or case studies specific to your company, you offer the AI concrete examples on which to base content. This reduces the risk of results that are inaccurate or out of touch with the realities of your sector. AI will thus be able to generate training materials that are close to your real needs, by bringing added value to the learners' experience.

Didask optimizes this process using its educational AI: you can import files (PDFs, slides, etc.) directly into the platform, allowing the AI to better understand the context and use relevant elements to design a complete course. For more details on how Didask turns reference content into a learning journey, you can consult This article on educational AI.

Structuring content to effectively guide AI

For AI to offer a coherent educational path, it is essential to structure your content in clear steps. The idea is to guide the AI by dividing the subject into distinct sequences, each corresponding to a specific learning objective. This logic helps AI organize information in a gradual manner, ensuring a smooth experience for learners.

Take, for example, training in time management. Instead of presenting the topic in bulk, it is more appropriate to divide it into sections such as “defining priorities”, “discovering organizational techniques” and “using monitoring tools”. Each segment provides a clear benchmark for AI, allowing a step-by-step journey to be built, where each part builds on the previous one to facilitate skills development.
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Review, adjust, and personalize generated content

While AI can produce relevant content quickly, proofreading, adjusting, and customizing are essential to ensure training that is truly tailored to learners. These steps make it possible to transform standard content into a unique and engaging experience for your audience.

Why reread?

Proofreading is crucial to ensure that the content meets the educational goals and values of your business. AI can sometimes be inaccurate or produce generic formulations. For example, in a module on the communication in business, AI could present examples of situations that do not always reflect the specific realities of your teams. By proofreading, you ensure that each word, each example, speaks directly to the learners and responds to specific needs of your organization.

How to adjust?

Adjusting content means refining messages and examples so that they are in line with the context of your learners. For example, you could add concrete work situations or stories that resonate with their daily professional lives. If AI offers a generic use case for resolving conflicts, you can customize it to include dynamics specific to your teams, such as a conflict between technical and commercial services. These adjustments make the course more concrete and reinforce learners' engagement.

Why personalize?

Personalization is a key step in making training a really effective skills development tool. It makes it possible to adapt the tone, the examples and even the levels of difficulty according to the audience. For example, for an audience of junior managers, a more accessible tone and examples from common management situations are often more effective. The LMS Didask integrates personalized feedback options that allow recommendations to be refined as you learn. This continuous feedback enriches the experience and allows each module to be adjusted according to learning outcomes. To learn more about the importance of content personalization, explore this Didask article on AI and adaptive learning, which explains how AI can adapt to the pace and needs of learners to maximize the effectiveness of training.

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AI offers a unique potential to accelerate the design of training courses while maintaining a high level of quality. By clearly defining goals, providing detailed context, structuring content, adding specific examples, and customizing the end result, every designer can maximize the effectiveness of AI to meet the needs of their audience.

Adopting AI does not mean doing without the role of the designer, but rather giving them new tools to design more relevant and flexible learning paths. The LMS Didask makes it possible to implement these best practices, based on an educational AI that combines the advances of technology and the recommendations of cognitive research.
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