Required Courses
The program will run from Summer 2026 to Winter 2027. Courses have both synchronous and asynchronous components, including online (Zoom) class sessions. Any synchronous sessions are in Mountain Time (Edmonton, Alberta, Canada). Dates and times are determined by the course instructor.
These are graduate-level, credit courses, requiring between five and ten hours of coursework per week in the fall and winter terms (13 weeks). Courses offered in the spring and summer terms are condensed (six and three weeks respectively), so the amount of time spent on coursework is increased. This includes time spent on readings, assignments, presentations (group and individual), and writing papers.
Note: you must take a course in the term for which you apply. Course offerings are dependent upon sufficient enrollment.
Summer Term
EDU 570 Technology, AI, and Ethics in Education ★3
The course explores issues arising from the use of digital technologies and artificial intelligence in education, including digital equity and access, digital participation and citizenship, algorithmic bias, privacy, security and surveillance, and their impacts on learning, cognition and agency. Students will examine the integration of digital technology and AI from philosophical, theoretical and social science perspectives, and will consider the ethical and social justice implications for teacher practice and educational policy, including responding to the TRC Calls to Action.
Fall Term
EDU 573 Computational Thinking in Teaching and Learning ★3
This course is grounded in Seymour Papert's philosophy of constructionism, positing that deep learning is an active process of building meaningful public artifacts with others. The course utilizes the Understanding by Design (UbD) framework to focus on the ultimate goal of learning: the ability to transfer knowledge, skills, and understandings across diverse contexts. Aligned with Jeannette Wing’s vision of Computational Thinking (CT) as a universal competence, we challenge students in the course to design project-based learning experiences that move beyond rote memorization to authentic applications that mirror the real world. Artificial intelligence tools are integrated throughout the course to support lesson planning, helping teachers generate ideas, differentiate instruction, and align learning activities with curricular outcomes. This constructionist methodology, where students build and create across a variety of subject areas, serves as the primary vehicle for ensuring that learning is purposeful, flexible, adaptable, and truly transferable.
Winter Term
EDU 595 AI and Computational Thinking in Education: Theory and Practice ★3
This course is designed to help practicing K–12 teachers develop a deeper understanding of the relationship between computational thinking (CT) and artificial intelligence (AI), with a special focus on how machine learning (ML) works. Teachers today face classrooms where students are already encountering AI tools in their daily lives, yet most curriculum resources stop at surface-level explanations. By engaging with this course, teachers will move beyond simply knowing how to use AI and toward developing the ability to explain, model, and design learning experiences that build their students’ AI literacy and guide them toward AI fluency.
Spring Term
EDU 572 Teaching Online - Theory and Practice ★3
This course addresses the theory and practice of teaching and learning in blended and fully online learning environments in both synchronous and asynchronous formats. This course explores topics such as pedagogical frameworks, instructional design, virtual learning communities, technologies to support online teaching, and approaches to online assessment. Where appropriate, Artificial Intelligence is introduced as a tool to enhance teaching and learning in online spaces. Students will investigate how to deal with changing technological environments that mediate the delivery of instruction.