Instructor : Dr. Karima Tekaya. IT Trainer, Professor at University of Tunis, NLP coach.
Learning Objectives
By the end of this workshop, participants will be able to:
- Discover cutting-edge AI technologies transforming the field of education.
- Learn to design Next-Generation learning scenarios by integrating:
- The latest AI innovations in education
- The 4MAT model lifecycle enhanced by AI for adaptive learning
- Neuroeducation principles powered by AI to optimize engagement and retention.
Workshop Modalities
- Duration: 7h
- Number of participants: 20 to 30 people
- Location: Tunis, Alecso.
- Accessibility: In-person
- Language: French
Program
Introduction
- Overview of objectives and key challenges of AI in education.
- Exploration of traditional and modern pedagogical models and AI’s impact on them.
- Traditional models: Behaviorism, Constructivism, Socio-constructivism.
- Modern models: UDL, SAMR, 70-20-10, Connectivism.
- AI’s impact on learning: Personalization, automation, adaptive learning.
Pedagogical Models and AI
- The 4MAT Model applied to AI:
- Why? (Engagement): How AI captures learners' attention and enhances motivation.
- What? (Concepts): AI as a tool for discovering and structuring educational content.
- How? (Application): AI as a facilitator of active learning, practice, simulations, and real-time feedback.
- What if? (Reflection): AI’s role in exploring complex scenarios and projects that would be impossible without technology.
- Neuroeducation and AI: Leveraging AI to optimize cognitive processes such as memory and attention.
Interactive Workshop
- Analysis and testing of an AI educational tool.
- Discussion on its integration within a 4MAT-based scenario.
Instructional Design with AI
- Designing learning scenarios using the 4MAT model:
- How AI transforms each phase of the learning process within 4MAT.
- Practical example: Creating a personalized AI-powered learning scenario with adaptive learning.
- Group exercise: Designing a mini AI-driven instructional scenario incorporating the 4MAT model.
AI Tools and Evaluation Criteria
- Quick exploration of three AI tools for education and their impact on learning:
- Educational chatbots: Personalized responses, engagement.
- Adaptive Learning: AI-driven learning pathways.
- Learning Analytics: Data-driven insights for improved learning outcomes.
- Evaluation criteria: Pedagogical relevance, accessibility, biases, and impact on results.
AI-Powered Instructional Design Workshop
Objective: Apply the 4MAT model to design an AI-integrated learning scenario.
- Approach:
- Phase 1 (Why?): Using AI to foster initial engagement and capture learners' attention (e.g., chatbots, interactive videos).
- Phase 2 (What?): Personalizing learning content based on students' needs and preferences (adaptive learning).
- Phase 3 (How?): Designing hands-on AI-assisted activities such as interactive quizzes, simulations, and serious games.
- Phase 4 (What if?): Exploring complex and reflective scenarios through AI (e.g., case studies or immersive simulations).
- Participants will develop a mini-instructional scenario on a given topic, integrating appropriate AI tools.
Ethical Challenges and AI Limitations in Education
- Algorithmic biases and their impact on equity in learning
- Discussion on bias in AI systems and strategies to mitigate it.
- Student data protection
- Understanding regulations (e.g., GDPR) and best practices for ensuring data security and confidentiality.
- AI and learner autonomy
- How AI can support autonomy without replacing it.
- Reflection on the role of human agency in AI-assisted learning and the importance of maintaining critical and reflective autonomy in the learning process.
Teaching Resources
Digital materials for participants (slides, documentation, source code)
- Laptops with Internet access
- A projector, a whiteboard, or an interactive screen