Foundations of Generative AI in Education

We’re Manitoba’s largest institute of applied learning and research, and take pride in preparing our students to become leaders in their fields.

In this foundational micro-credential, students will navigate the evolving landscape of Generative Artificial Intelligence (GenAI) in their unique educational context. Students will explore ethical considerations, practical tools, and pedagogical approaches associated with GenAI in education. Students will develop an understanding of the ethical and technical dimensions of GenAI, enabling them to make informed decisions and design inclusive, engaging, and effective learning experiences for their students. This micro-credential ensures educators are well-prepared to address the challenges and opportunities presented by generative AI in their professional practice.

Total course hours and credit hours: 15 hours

Knowledge and Skills Demonstrated

Learning Outcomes are the statements that describe what the student will know and be able to do at the completion of this micro-credential. They are written from a learning perspective to communicate clear, consistent and transparent expectations. Please use RRC’s guidelines for writing Learning Outcomes and Elements of Performance.

This badge certifies that the student can demonstrate the following knowledge and skills:

1. Describe the basic technical considerations underlying generative AI systems to make informed decisions regarding generative AI adoption.
2. Describe the foundational technical aspects of generative AI systems to make informed decisions regarding generative AI adoption.
3. Write effective prompts using large language model generative AI tools.
4. Assess the suitability of various generative AI tools for specific educational contexts.
5. Evaluate generative AI tools in terms of alignment with learning outcomes, ease of use, and their potential impact on student engagement in specific educational settings.
6. Design generative AI-enhanced teaching activities, assessments, and materials.
7. Develop generative AI-enhanced teaching strategies, assessments, and materials that consider diverse student learning needs, promote active engagement, critical thinking, collaboration among students, and uphold principles of equity, diversity, and inclusion.

Evidence/Criteria for Success

The learner shall achieve a minimum combined average of 60% on the following outcome-aligned assessments: