LLM/Storyline
Personalized Learning at Scale: Leveraging AI for Dynamic Feedback in eLearning
Providing personalized feedback in eLearning is crucial for learner engagement and knowledge retention, but it’s often challenging to implement at scale. This project explores the innovative integration of ChatGPT with Articulate Storyline to deliver dynamic, AI-powered feedback tailored to individual learner responses.
The Process
THE CHALLENGE
The Need for Engaging and Personalized Feedback
Static feedback in traditional eLearning can be generic and less engaging, hindering learner motivation and comprehension. Dynamic, personalized feedback that adapts to individual learner performance is essential for creating more effective and impactful learning experiences.
THE SOLUTION
Bridging the Gap: Integrating AI-Powered Feedback into Storyline
- ChatGPT Integration: By engineering precise prompts and structuring JSON for API communication, I successfully integrated ChatGPT into a Storyline module. This allows for real-time, AI-generated feedback based on learner input captured through Storyline variables.
- Prompt Engineering: I focused on crafting prompts that would elicit relevant and contextually appropriate feedback from ChatGPT, addressing both correct and incorrect answers with targeted explanations and resources.
- Storyline Development: This project leveraged Storyline’s robust functionality, including variables, triggers, and JavaScript integration, to seamlessly connect with the ChatGPT API and display the AI-generated feedback.
ADDRESSING BIAS IN CUSTOMER SCENARIOS
Creating Inclusive and Representative Learning Experiences
Future iterations of this project will use US demographic data to generate diverse and representative customer personas for contact center simulations. This approach aims to eliminate unconscious bias in scenario design and create more inclusive and relatable learning experiences.
IMPACT AND FUTURE APPLICATION
Transforming eLearning with AI-Powered Personalization
This integration has the potential to significantly enhance learner engagement, improve knowledge retention, and provide personalized learning at scale. Future applications include expanding to more complex scenarios and integrating with other learning platforms.


Preview the Prototype
00:00 User enters incorrect response
00:10 Fetches GPT response
00:16 User receives feedback
00:24 User clicks try again
00:26 User enters better answer
00:41 Fetches GPT response
00:49 User receives feedback