EDU 608: Teaching the Digital Generations in a Globalized World (3 credits)
EDU 638: Foundations of AI in Education (3 credits)
EDU 639: Designing AI-Driven Learning: Collaboration, Personalization, and Data-Informed Pedagogies (3 credits)
EDU 640: Ethical Leadership, Research, and Policy in AI-Driven Education (3 credits)
EDU 608: Teaching the Digital Generations in a Globalized World (3 credits)
The evolution of information, communication, and artificial intelligence technologies has fundamentally transformed how people, big businesses, and governments communicate and operate. The modern world is experiencing disruptive innovation on an unprecedented scale, with AI driving advancements in automation, data analytics, and personalized services. However, schools have not experienced the same philosophical and technological shift as the rest of the world. Many pedagogical practices and instructional resources remain rooted in outdated methodologies, leaving learners ill-prepared for a future dominated by AI-driven industries and globalized workforces.
In essence, schools must prepare learners for their futures, not our past. In this course, learners will explore emerging issues related to teaching, learning, and assessment in the 21st century, with a particular focus on the role of AI in reshaping education and society. They will examine the pervasive nature of disruptive innovation, including AI-powered tools and platforms, and identify essential skills such as adaptability, critical thinking, and digital literacy that students need to thrive in the new workforce. By the end of the course, participants will be equipped to design learning experiences that embrace technological advancements and empower the digital generations to succeed in a rapidly evolving world.
EDU 638: Foundations of AI in Education (3 credits)
Artificial intelligence (AI) is transforming education, shaping how students learn, educators teach, and institutions operate. This course provides a comprehensive introduction to the concepts, history, and transformative potential of AI in educational settings. Participants will explore foundational topics, including machine learning, natural language processing, and generative AI, while examining real-world applications such as adaptive learning platforms and personalized instructional systems.
Through case studies and practical examples, learners will analyze the profound implications of AI on teaching, learning, and assessment. Special emphasis will be placed on ethical considerations, such as bias, equity, and data privacy, to ensure responsible and inclusive use of AI in educational contexts. By the end of the course, participants will have the knowledge and tools to critically evaluate AI technologies and design thoughtful strategies for integrating AI into learning environments. Prepare to gain the insights and skills needed to lead the way in leveraging AI to enhance education and empower learners in a rapidly evolving digital age.
EDU 639: Designing AI-Driven Learning: Collaboration, Personalization, and Data-Informed Pedagogies (3 credits)
Artificial intelligence is revolutionizing teaching and learning, enabling educators to create dynamic, personalized, and data-informed experiences for every learner. This course equips educators with the knowledge and skills to design, implement, and collaborate with AI technologies to enhance instructional practices and student outcomes.
Participants will explore AI-powered tools for personalized learning, adaptive assessments, and differentiated instruction, emphasizing their practical application in real-world classrooms. They will also examine the role of educators as partners with AI, balancing human expertise with machine intelligence to foster student growth. The course includes hands-on practice with data analytics tools to identify learning gaps, predict outcomes, and make informed decisions to support diverse learners effectively.
Special attention will be given to ethical and inclusive considerations, ensuring AI is used responsibly to promote equity, accessibility, and student success. By the end of the course, participants will have developed actionable strategies and AI-enhanced learning designs that empower learners and position educators as leaders in a data-driven educational landscape.
EDU 640: Ethical Leadership, Research, and Policy in AI-Driven Education (3 credits)
As artificial intelligence reshapes education, ethical leadership and evidence-based research are essential to ensure its responsible and inclusive integration. This course prepares educators and leaders to navigate complex ethical, equity, and policy challenges posed by AI in education. Participants will explore algorithmic bias, accessibility for diverse learners, data privacy, and security.
Through research-driven inquiry and collaborative projects, learners will critically evaluate AI’s impact on education, using AI-powered analytics and qualitative research methodologies.
Participants will examine policy development processes, funding considerations, and advocacy techniques to champion ethical and equitable AI use in learning institutions. By the end of the course, students will conduct an AI-related research study and develop a policy proposal for AI integration in education.
