Field of study
Educational technology, mathematics education, and artificial intelligence.
Format
Online
Open to
Bachelor’s, Master’s, PhD
Keywords
Artificial Intelligence (AI) Mathematics Education Primary Education Personalized Learning Educational Technology
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Objective: Empower primary school teachers with the knowledge and practical skills to integrate AI into mathematics teaching methods.
Week 1: Foundations of AI in Education
- Activities: Introduction to AI concepts and their impact on various sectors, focusing on education.
- Workload: 5 hours (80% individual, 20% group discussions; 30% synchronous, 70% asynchronous).
- Facilitator Role: Provide content overview, guide initial concepts, moderate Q&A.
Week 2: Exploring Everyday Applications of AI
- Activities: Practical examples of AI in daily life and discussions on future implications.
- Workload: 6 hours (70% individual, 30% group discussions; 40% synchronous, 60% asynchronous).
- Facilitator Role: Lead webinars, guide discussions, monitor forums.
Week 3: AI in Primary School Mathematics
- Activities: Case studies highlighting AI-enhanced learning experiences in mathematics.
- Workload: 7 hours (60% individual, 40% collaborative; 50% synchronous, 50% asynchronous).
- Facilitator Role: Introduce case studies, guide discussions, moderate collaborative exploration.
Week 4: Hands-On Exploration of AI Tools
- Activities: Practical experience with AI-powered educational platforms and software for teaching mathematics.
- Workload: 8 hours (50% individual, 50% collaborative; 60% synchronous, 40% asynchronous).
- Facilitator Role: Lead tool demonstrations, guide hands-on exercises, address queries.
Pedagogical Features
- Assessment: Quizzes and assignments after each unit to ensure continuous engagement and understanding.
- Collaboration: Participants collaborate on projects, sharing insights and experiences.
- Delivery Method: Online resources, live webinars, discussion forums, and hands-on activities via the Moodle platform.
Theoretical Background
- Introduction to AI in Education: Understanding AI and its potential to revolutionize teaching.
- AI Applications in Education: Personalized learning and intelligent tutoring systems.
- Benefits of AI Integration: Improved student engagement and personalized learning paths.
- Challenges: Ethical considerations, data privacy, and equitable access.
Main topics addressed
Fundamentals of Artificial Intelligence (AI)
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- Definition and core concepts of AI
- Overview of AI’s impact across various sectors, particularly education
AI Applications in Daily Life
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- Practical examples of AI technologies in everyday contexts (e.g., voice assistants, recommendation systems)
- Future implications and potential developments in AI
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AI in Primary School Mathematics Education
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- Case studies demonstrating AI-enhanced learning experiences in mathematics
- Analysis of benefits and challenges of integrating AI into the classroom
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Hands-On Experience with AI Tools
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- Exploration and practical use of AI-powered educational platforms and software
- Development of skills to effectively navigate and utilize AI tools for teaching mathematics
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Assessment and Collaborative Learning
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- Continuous assessment through quizzes and assignments
- Collaborative projects fostering partnerships among educators to share insights and best practices
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Ethical and Practical Considerations
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- Addressing ethical concerns, data privacy, and ensuring equitable access to AI resources
- Strategies for overcoming challenges in implementing AI in education
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Educator’s Role in AI Integration
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- Importance of teacher training and professional development in AI
- Empowering educators to effectively integrate AI into their teaching methodologies
Learning outcomes
Upon completion of the module “Harnessing Artificial Intelligence in Primary School Mathematics Education,” participants will be able to:
- Understand AI Fundamentals
- Explain the basic concepts and definitions of Artificial Intelligence.
- Describe the broad impact of AI across various sectors, with a specific focus on education.
- Identify AI Applications in Daily Life
- Recognize practical examples of AI technologies in everyday contexts.
- Discuss the potential future implications and developments of AI.
- Analyze AI Integration in Mathematics Education
- Evaluate case studies of AI-enhanced learning experiences in primary school mathematics.
- Assess the benefits and challenges associated with integrating AI into the classroom.
- Utilize AI Tools for Teaching
- Demonstrate proficiency in navigating and utilizing AI-powered educational platforms and software for teaching mathematics.
- Apply practical skills to integrate AI tools effectively into their teaching practices.
- Engage in Continuous Assessment and Collaboration
- Complete quizzes and assignments to show ongoing engagement and understanding of the material.
- Collaborate with peers on projects, sharing insights and experiences to enhance collective learning.
- Address Ethical and Practical Considerations
- Identify ethical concerns and data privacy issues related to AI in education.
- Develop strategies to ensure equitable access to AI resources and address implementation challenges.
- Enhance Professional Development
- Reflect on the importance of ongoing professional development in AI.
Leverage the knowledge and skills acquired to innovate and improve teaching methodologies in primary school mathematics
Language : English
Total workload : 26 hours
Requirements :
- Technical Requirements
- Hardware: Participants need access to a computer or tablet with internet connectivity.
- Software: Access to the Moodle platform for course materials and activities.
- Tools: Necessary software and AI-powered educational platforms will be provided or specified.
- Participant Requirements
- Background Knowledge: Basic understanding of primary school mathematics teaching methods.
- Technical Skills: Fundamental computer skills, including the ability to navigate online platforms and use common software applications.
- Time Commitment
- Weekly Engagement: Approximately 26 hours total over four weeks.
- Week 1: 5 hours
- Week 2: 6 hours
- Week 3: 7 hours
- Week 4: 8 hours
- Synchronous Sessions: Attendance in live webinars and Q&A sessions as scheduled.
- Weekly Engagement: Approximately 26 hours total over four weeks.
- Collaborative Participation
- Group Activities: Willingness to engage in group discussions and collaborative projects.
- Communication: Active participation in discussion forums and collaborative exercises.
- Assessment
- Completion of Quizzes and Assignments: Participants are required to complete quizzes and assignments at the end of each unit to demonstrate understanding and engagement.
- Support and Resources
- Facilitator Guidance: Access to facilitator support for guidance, questions, and feedback.
- Supplementary Materials: Availability of additional readings and resources for further exploration of AI concepts and applications.
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Vasilina MPISMPIKI (National & Kapodistrian University of Athens, Greece)
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Christina MISAILIDOU (National & Kapodistrian University of Athens, Greece)
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