Generative AI and Educational Innovation
Program Overview
This program is for educators, instructional designers, and educational technologists who want to explore the different ways in which generative AI can live in various educational contexts. This program addresses the growing need for professionals who can navigate the intersection of artificial intelligence and education, focusing on human-centered design principles, ethical considerations, and pedagogical practices.
Program Details
Upon completion of the program, graduates:
- Will be prepared to lead innovation in educational institutions, EdTech companies, and other learning-focused organizations.
- Will possess the skills to design, implement, and evaluate generative AI-enhanced educational solutions while maintaining a critical perspective on these technologies' ethical and societal implications.
- Will aim to produce professionals who can bridge the gap between technological advancements and educational needs, fostering more personalized, engaging, and effective learning experiences.
Experiential learning is learning by doing that bridges knowledge and experience through critical reflection. This program offers the following kinds of experiential learning opportunities:
- Case-based exploration and frameworks
- Building an understanding and utilizing tools from the field
- Engaging in critical dialogue and reflection along the continuum of theory to practice
This program is for educators, instructional designers, and educational technologists who want to explore the different ways in which generative AI lives in various educational contexts. Given that this program addresses the growing need for professionals who can navigate the intersection of artificial intelligence and education, those interested in human-centered design principles, ethical considerations, and pedagogical practices would find this program a good fit.
A registration package will be sent to new students after they have been admitted. Registration for the summer term will be available in late winter. Fall and Winter registration opens in the spring. Your Graduate Program Administrator will send more information about registration to you.
Fee details are available through the University Calendar. An explanation of fees is available on the Faculty of Graduate Studies' website.
The University of Calgary offers multiple ways to meet the cost of your education. Please refer to the Awards, Scholarships and Bursaries page to learn more about options available to students. For additional information, please contact Student Financial Support.
Please refer to Admission Requirements for Master's Programs.
Program Schedule & Course Descriptions
- Program begins each July (summer term 1)
- Outlines are normally available 1-2 weeks prior to the start of term in D2L
- 3 units per course
Term 1 - Summer
Foundations of Generative AI in Educational Contexts
This course introduces the fundamental concepts of generative AI and its applications in education. Students will explore the underlying technologies, current capabilities, and potential future developments of AI in learning environments. Key ideas:
- Basic principles of generative AI
- Overview of AI applications in education
- Introduction to prompt engineering and AI interaction
- Case studies of generative AI in various educational settings
Term 2 - Fall
Human-Centered Design Principles for AI-Enhanced Learning
This course focuses on applying human-centered design principles to create effective AI-enhanced learning experiences. Students will learn to prioritize learner needs and pedagogical goals when integrating generative AI into educational contexts. Key ideas:
- Human-centered design methodology
- User experience (UX) in educational technology
- Designing AI-enhanced learning activities and assessments
- Accessibility and inclusivity in AI-driven education
Term 3 - Winter
Ethical Considerations for AI in Education
This course examines the ethical implications of integrating generative AI in education with a focus on academic integrity. Students will explore issues such as privacy, bias, transparency, and the impact on human creativity and critical thinking. Key ideas:
- AI ethics frameworks for education
- Bias detection and mitigation in AI systems
- Data privacy and security in educational contexts
- Balancing AI assistance and human agency in learning
Term 4 - Spring
Technological Pedagogical Knowledge for Generative AI Integration
This course focuses on developing the technological pedagogical knowledge required to effectively implement generative AI in various educational settings. Students will learn to align AI tools with pedagogical approaches and learning objectives. Key ideas:
- TPACK (Technological Pedagogical Content Knowledge) framework
- Integrating AI tools with existing learning tools
- Developing AI-enhanced curriculum and lesson plans
- Evaluating the effectiveness of AI-driven educational interventions