Today, artificial intelligence and micro-credentials are essential concepts. On the one hand, AI is omnipresent in publications and conferences; on the other, micro-certifications, or “micro-credentials” in English, are increasingly establishing themselves as essential tools in skills management. So, could AI enhance the usefulness of micro-credentials?
The key functions of micro-credentials
Before exploring how AI could contribute to micro-credentials, it is essential to understand their core functionalities. Micro-certification systems (or MCS for “Micro Credential Systems”) are technological platforms specialized in awarding these certifications. They are structured around three main functions:
- Issuance of certificates: To secure certifications, these systems use technologies such as blockchain, digital badge standards (Open Badge), or in France, registration on the Caisse des Dépôts skills passport.
- Promotion of certifications: Micro-certifications are highlighted, both for the individual and for the company that issues them. This distribution is generally done via social networks such as LinkedIn, Facebook or Instagram.
- Skills assessment: Micro-credentialing systems include assessment tools to ensure the quality of certified skills. In short, an MCS evaluates, issues and communicates certifications.
Contribution of AI in the design of certifications
In a certification project, two stages can particularly benefit from AI: the identification of the skills necessary for a specific task and the implementation of the evaluation protocol. AI is revolutionizing these traditionally long and complex processes by automating a large part of these tasks. We’ll see how.
Facilitate the creation of skills repositories
The first step in a skills assessment is to precisely define the skills required. This work, often laborious, consists of auditing managers to identify the key skills of each position, then harmonizing this data in a skills framework enriched with performance indicators. Thanks to AI, this process is accelerated and simplified.
Based on a job or skill description, machine learning algorithms suggest relevant skills by drawing on data available on the web. This approach not only saves time, but also diversifies sources of information beyond the company. The proposals from AI can then be adjusted or enriched with internal data to refine the framework.
When AI is associated with an AGILE approach in the management of micro-certifications, we obtain a modern and effective tool for managing skills.
Simplify assessments with AI
Once the skills framework has been defined, the next step is the skills assessment. Historically, creating and correcting quizzes was a tedious task for evaluators and HR managers. AI now makes this process faster and more accurate.
By automatically generating quizzes adapted to the skill levels of participants, AI makes it possible to offer a fairer and more personalized assessment. For multiple choice questions, correction can be done instantly. For open-ended questions, the AI uses pre-defined keywords to analyze the answers, assign a score and provide feedback. Although this assisted assessment remains under the supervision of the marker, it saves him time and allows him to concentrate on more complex tasks.
Potential for strategic development
AI is transforming skills management by facilitating the creation of benchmarks and automating assessments. Beyond simple technical progress, this advancement allows companies to remain flexible and responsive in a constantly evolving environment.
Adopting these technologies saves time and resources, while ensuring more accurate and fair skills assessment, thereby contributing to the long-term success of organizations. It is for these reasons that companies like Procertif are already integrating AI into their certification solutions.
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