This 3-day intensive masterclass provides participants with a comprehensive understanding of how artificial intelligence (AI) is reshaping learning and development in both educational and corporate settings. Through hands-on practice, case studies, and expert insights, participants will explore the application of AI-driven tools such as adaptive learning systems, chatbots, and learning management systems (LMS), and how they can be implemented to create personalized and efficient learning experiences.
Who is this course for?
- Learning and Development (L&D) professionals
- Corporate trainers and HR managers
- Educators and e-learning developers
- Instructional designers
- EdTech entrepreneurs
- AI enthusiasts interested in education
Lessons in this course
Day 1 – Introduction to AI and Learning Technologies
Session 1: What is AI?
Duration: 1.5 hours
Objectives:
- Understand the basic concepts of AI, including machine learning, deep learning, neural networks, and natural language processing (NLP).
- Learn how AI has evolved and its applications in various industries, with a focus on education and corporate training.
- Explore different types of AI technologies (e.g., supervised learning, unsupervised learning, reinforcement learning) and how they contribute to the development of learning technologies.
Content
- Introduction to AI: Definitions and key terminologies
- Overview of AI technologies relevant to learning (machine learning, NLP, etc.)
- Case studies: AI applications in EdTech and corporate learning environments
Interactive Activity
- Group discussion on current AI applications in participants &; organizations or industries
Session 2: AI in Education and Corporate Training
Duration: 2 hours
Objectives
- Explore how AI is used to personalize and enhance learning experiences in both education and corporate settings.
- Understand how AI-powered systems improve learner engagement, knowledge retention, and performance through personalization and real-time feedback.
Content
- AI-driven personalized learning: How adaptive learning systems work (e.g., Squirrel AI, DreamBox)
- AI in corporate training: Automating assessments, analyzing learner progress, and providing feedback
- Tools and platforms: Duolingo, Coursera, and IBM Watson for Education
Hands-On Activity
- Participants will explore and compare different adaptive learning platforms (e.g., Smart Sparrow, Knewton) and create a simple adaptive learning module using a platform of their choice.
Day 2 – Designing AI-Driven Learning Experiences
Session 3: Chatbots and Virtual Assistants in Learning
Duration: 2 hours
Objectives
- Learn how AI chatbots and virtual assistants enhance the learning experience by providing real-time support, answering questions, and offering personalized feedback.
- Understand the process of designing conversational agents tailored to learners & needs.
Content
- Introduction to AI-powered chatbots in learning environments (e.g., Google Dialogflow, IBM Watson Assistant)
- Key components of chatbot design: Natural language processing (NLP) and intent recognition
- Examples of chatbot applications in corporate training and education (e.g., Drift, Intercom)
Hands-On Activity
- Participants will design a simple learning-focused chatbot using platforms like ManyChat or Dialogflow, customized to provide support for a specific learning module or course content.
Session 4: Personalized and Adaptive Learning Systems
Duration: 2 hours
Objectives
- Gain an in-depth understanding of how personalized learning paths are created using AI, analyzing learner data to offer tailored content and recommendations.
- Learn how AI systems dynamically adjust the learning experience based on real-time learner performance and behavior.
Content
- AI algorithms in adaptive learning: How data is collected and analyzed
- Personalization techniques: Learning style preferences, performance tracking, and predictive analytics
- Building personalized learning experiences at scale
Hands-On Activity
- Participants will develop a basic adaptive learning experience using an adaptive learning platform (e.g., Edmodo, Squirrel AI). They will configure personalized learning paths and explore how AI algorithms adjust content based on user input and performance.
Day 3 – Implementing AI and Learning Technologies
Session 5: AI in Learning Management Systems (LMS)
Duration: 1.5 hours
Objectives
- Understand how AI is integrated into Learning Management Systems (LMS) to improve user experience, automate tasks, and provide personalized learning experiences.
- Learn about AI-enhanced LMS features, such as automated grading, predictive analytics, and personalized content recommendations.
Content
- Overview of AI-powered LMS platforms (Moodle, Canvas, Blackboard) and how they incorporate AI tools
- AI-enhanced features: Adaptive assessments, content recommendations, learner progress analysis
- Case studies: Organizations using AI-powered LMS for employee training
Hands-On Activity
- Participants will explore an AI-powered LMS and practice setting up automated assessments, content recommendations, and personalized learner progress dashboards.
Session 6: Ethics and Challenges of AI in Learning
Duration: 1.5 hours
Objectives
- Address the ethical considerations in the use of AI for learning, including issues related to data privacy, bias, transparency, and accountability.
- Discuss challenges in implementing AI-based learning solutions, such as resistance to change, technical barriers, and scalability.
Content
- Ethical concerns: Data privacy, surveillance, and AI bias in learning technologies
- Strategies for mitigating bias and ensuring fairness in AI-driven learning platforms
- Regulatory frameworks for AI in education and training (e.g., GDPR compliance)
- Case studies of ethical issues in AI implementation within learning environments
Interactive Activity:
- Participants will engage in a group debate on ethical dilemmas in AI-enhanced learning technologies and propose solutions to ensure ethical AI practices in their own organizations.
Session 7: AI Trends in Learning and the Future
Duration: 2 hours
Objectives
- Explore the latest trends and emerging technologies in AI and learning, such as gamification, immersive learning (AR/VR), and hybrid AI-teacher models.
- Gain insights into the future of AI-driven learning technologies and their impact on the workplace and education systems.
Content
- AI and gamification: How AI drives engagement through game mechanics
- AI in immersive learning: Augmented Reality (AR) and Virtual Reality (VR) applications
- The future of AI-teacher collaboration: Hybrid learning models combining human and AI instructors
- Emerging trends: Blockchain for learning credentials, peer learning supported by AI
Final Project Presentation
- Participants will present their final project, where they design and propose an AI-driven learning solution tailored to their industry or organizational needs. The project could involve:
– Developing a chatbot-based learner support tool
– Creating an adaptive learning module
– Integrating AI into an existing LMS
– Peer and instructor feedback will be provided.