12 ways Skillsoft Percipio Uses AI to Enhance Learning

March 8, 2023 | What's Hot | 7 min read

We often get the question: how does Skillsoft’s Percipio platform use AI to improve the user experience?

At Skillsoft, we have incorporated AI into our Percipio platform in meaningful ways. We continually experiment and test so that we can innovate, learn, and share those insights with our community. We’re proud to be at the forefront of providing AI-driven, transformative learning experiences – efforts of which were recognized by Business Intelligence Group’s 2023 Artificial Intelligence Excellence Awards.

We use AI to do four things that benefit users of the platform and users that access Skillsoft content through learning management system (LMS) integrations:

  • Personalize learning for each user, helping them to progress from Point A to Point B quickly and efficiently;
  • Improve search and discovery, making it easier for learners to find what they need;
  • Link skills, roles, and learning together to guide career paths; and
  • Generate new content and curation, enabling users to assess their skills as they build confidence and understanding and to curate learning paths for trending topics automatically.

Let’s go over the 12 ways we are using AI today. And for those that like to look under the hood, we’ll share the AI model we used and any lessons learned from the experiments.

Personalize Learning

AI is used to personalize learning for each user based on their profile, search behavior, learning activity, skill assessments, and role. In addition to personalized learning paths generated from Skill Benchmark Assessments and interests, Percipio uses AI to:

Recommend content based on recent activity (in production) – Percipio learns a user’s behavior, finds other similar users, and recommends content based on “most similar” users' behaviors. This is modeled after how Amazon recommends products (you might have noticed the “people also bought” section). These recommendations personalize the homepage and the automated re-engagement notifications.

AI model used: collaborative filtering, feedforward

Lesson learned: These recommendations are used most often and users who access them spend 59% more time learning indicating value and relevance.

Recommend content in specific patterns and sequences (in QA testing) – Our AI specialists have spent the last quarter testing and training a new collaborative filtering model that recommends content based on common sequences inherent in the way learners have consumed content.

AI model used: collaborative filtering, feedforward, trained on consumption sequences

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Generate New Content and Curation

AI models are being used to generate content and images and to curate content to meet specific customer needs.

Customer-specific curation of content (in production) – Customers often have specific curation needs that may include aligning content to their own taxonomy or identifying content for inclusion or exclusion from their programs so they can customize the experience to their learners and culture. . An AI model scans and ranks content based on customers’ needs. The customer reviews the content before deploying.

AI model used: GPT-3, fine-tuned

Generate assessment questions (experiment) – Percipio currently assesses skills and knowledge using many different methods including Skill Benchmarks, course assessments, final exams for Aspire Journeys, and mobile flash cards for learning reinforcement. These require a very deep pool of assessment questions to enable each user to assess and reassess without seeing the same questions. Skillsoft is using AI to generate assessment questions to be used for these different platform features.

AI model used: GPT-3 fine-tuned and GPT-3.5 zero-shot

Lessons learned: The GPT-3 quality was mediocre: 50% were usable, 40% needed edits and 10% had to be discarded. The GPT-3.5 zero-shot performed worse, yielding only ~21% acceptable questions. We are exploring ChatGPT and post generation reflection (PGR) techniques which are showing promise in improving yield.

Curation of learning paths (experiment) – Curation of learning paths is typically done by expert curators in each domain and based on sound instructional design. We've collected a tremendous amount of data about how users actually learn and all of this data will be used to automatically curate learning paths for skills and roles.

AI model used: Collaborative-Filtering, GPT

Chatbot for learners (in production) – Percipio has a chatbot currently deployed to select customers that provides Level 1 customer support to learners answering the most common questions. This will be available to all customers in 2023.

AI model: Salesforce Einstein Chatbot

Lesson Learned: For participating customers, 45% of the level 1 common questions were answered by the chatbot.

Create unique images for blog posts and course thumbnails (experiment) – We used DALL-E 2 to create the image for this blog post and plan to experiment with creating eye-catching thumbnail images that will engage and energize the learner. These will appear in Percipio and through LMS integrations.

AI model: DALL·E 2

ChatGPT early use

Skillsoft’s AI team is already using ChatGPT internally to improve our productivity and accelerate our own AI efforts. The AI team has been utilizing GPT-3 and ChatGPT to generate code to implement Percipio features. These features include enhancements to the AI collaborative filtering model and improved search features (auto-suggest and type-ahead). It has been found to be quite effective. The team is exercising great care to ensure we are not violating copyrighted code.

Using these models, the possibilities are endless.

AI model: ChatGPT and GPT-3

Skillsoft courses are intended to guide and incorporate best practices that derive maximized value from the use of artificial intelligence. They are not intended to endorse or advocate for the methodologies, tools, or outcomes of the artificial intelligence tools referred to or utilized.