Designing a Research-Informed AI Ethics Course for Educators
K–12 teachers needed practical, policy-grounded guidance on using AI responsibly in their classrooms — at a moment of rapid, anxiety-inducing change.
The Context
In classrooms across the world, teachers were being asked to engage with AI tools before clear policies, frameworks, or professional guidance existed. Many felt anxious, underprepared, and unsure where the boundaries should be — particularly around ethical and responsible use.
This course — Establishing a Classroom AI Policy — was designed as the capstone project for the MicroMasters Certificate in Instructional Design & Technology, and formed part of a broader professional development programme for K–12 teachers navigating AI in education.
The Challenge
Designing for a rapidly evolving, emotionally charged topic requires more than good content structure. The challenge was to create a course that moved teachers from anxiety to agency — building informed confidence rather than just surface-level awareness — while remaining practical for educators with limited time and variable levels of digital confidence.
The course also needed to be genuinely research-grounded, not trend-reactive. With so much noise around AI in education, the design had to offer something more rigorous: a stable ethical framework that would remain relevant even as the technology continued to change.
The Approach
The design process began with a structured review of existing research — on AI in education, teacher decision-making, ethical frameworks (including UNESCO guidance), and best practice in asynchronous online learning. Rather than reacting to the conversation happening online, the course was anchored in what the evidence actually supported.
A constructivist course structure was chosen deliberately: rather than presenting AI as a solved problem with a single right answer, the course invited teachers to explore, reflect, and develop their own policy positions within an evidence-informed framework. The SAM (Successive Approximation Model) was used to iteratively develop and refine the course experience.
The Solution
The final course was a four-week asynchronous programme built in Rise 360, combining short focused content blocks with interactive knowledge checks, structured discussion forums, and reflective journaling activities.
The capstone assessment required teachers to develop a personalised classroom AI integration plan — grounded in ethical policy, specific to their own context.
Outcome & Value
For teachers — a structured, research-grounded path from uncertainty to informed, policy-ready practice — with confidence and agency, not just awareness
For the field — a demonstration that instructional design can handle emerging, sensitive topics rigorously — without oversimplifying or amplifying anxiety
For ElevateIDT — a showcase of research-informed design, authentic assessment, and the capability to develop asynchronous online courses to a high standard
Tools & Methodology
Research-informed instructional design
Constructivist learning design
SAM — Successive Approximation Model
Learning outcomes and alignment mapping
Authentic and reflective assessment design
Rise 360 for online course development
This project showed me that research-informed design isn't just about academic rigour — it's about giving learners something stable to hold onto when the ground is shifting. AI in education will keep evolving, but a well-designed ethical framework gives teachers a foundation that will outlast any particular tool or trend. — Carren Beukes, Founder, ElevateIDT