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Field of study

Educational technology, mathematics education, and artificial intelligence.



Open to

Bachelor’s, Master’s, PhD


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)

    • Definition and core concepts of AI
    • Overview of AI’s impact across various sectors, particularly education

AI Applications in Daily Life

    • Practical examples of AI technologies in everyday contexts (e.g., voice assistants, recommendation systems)
    • Future implications and potential developments in AI

AI in Primary School Mathematics Education

    • Case studies demonstrating AI-enhanced learning experiences in mathematics
    • Analysis of benefits and challenges of integrating AI into the classroom

Hands-On Experience with AI Tools

    • Exploration and practical use of AI-powered educational platforms and software
    • Development of skills to effectively navigate and utilize AI tools for teaching mathematics

Assessment and Collaborative Learning

    • Continuous assessment through quizzes and assignments
    • Collaborative projects fostering partnerships among educators to share insights and best practices

Ethical and Practical Considerations

    • Addressing ethical concerns, data privacy, and ensuring equitable access to AI resources
    • Strategies for overcoming challenges in implementing AI in education

Educator’s Role in AI Integration

    • 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:

  1. 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.

  1. Identify AI Applications in Daily Life
    • Recognize practical examples of AI technologies in everyday contexts.
    • Discuss the potential future implications and developments of AI.

  1. 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.

  1. 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.

  1. 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.

  1. 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.

  1. 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 :

  1. 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.

  1. 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.

  1. 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.

  1. Collaborative Participation
    • Group Activities: Willingness to engage in group discussions and collaborative projects.
    • Communication: Active participation in discussion forums and collaborative exercises.

  1. 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.

  1. 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.
  • Vasilina MPISMPIKI (National & Kapodistrian University of Athens, Greece)

  • Christina MISAILIDOU (National & Kapodistrian University of Athens, Greece)

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Categories: Blended courses


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