Estimate read time: 6 minutes

Introduction

At Georgian College, program areas and/or courses can have their own course policies/guidelines around artificial intelligence (AI) usage.  All policies/guidelines must align with Academic Regulation #8: Academic Integrity [new tab]. This article provides suggestions of how faculty may communicate their AI approaches for each learning outcome and assessment.

What?

GenAI tools seem like they are everywhere and integrating into our lives faster than we can keep track of.  Your course may have an AI (artificial intelligence) policy, or you may have a plan around how you want/don't want your students to use AI for your assessments. By clearly understanding how AI may supplement student learning and clearly communicating with students how AI may be used when completing assessments will help ensure all parties have the same understanding of AI in the course.

So What?

Many educators are familiar with Bloom's Taxonomy [new tab] which was developed by Bloom et al in 1956.  Called the Taxonomy of Educational Objectives, this tool outlined a hierarchical level of thinking in the cognitive, affective and psychomotor domains.  Educational institutions have used Bloom's taxonomy (or it's updated version 2001) and related verbs [new tab] to create learning outcomes ever since.

Recently, Oregon State University [new tab] has released “Bloom's Taxonomy Revisited” which aligns distinctive human skills and how GenAI can supplement learning with Bloom's taxonomy.

View Bloom's Taxonomy Revisited below or visit Bloom's Taxonomy Revisited – Artificial Intelligence Tools – Faculty Support | Oregon State Ecampus | OSU Degrees Online.  An accessible version is available at Accessible version of Bloom's Taxonomy Revisited [new tab].

Reflection Opportunity: Identify what changes may be needed to ensure meaningful learning going forward and possible opportunities for thoughtful integration of student use of GenAI. (Oregon State University, 2025)

Regardless if you use artificial intelligence or not or if you would allow your students to use artificial intelligence (AI) or not, the key message is clear communication about your assessment expectations. For course related AI statements, please see Syllabus Statements: Artificial Intelligence - Georgian College CTL [new tab].

According to Flower Darby, author of Small Teaching Online, students want to know for each and every assessment: “what” do you want me to do, “why” do you want me to do it, and “how” do you want me to do it.  These thoughts include usage of artificial intelligence.  Leon Furze shares his AI Assessment Scale [new tab] and included below.

Each level on this scale specifically explains how the students can (or cannot) use GenAI for their assessment work. 

Reflection Opportunity: Consider sharing this scale within your syllabus and then referring to the scale in the instructions for each assessment. Explore and share examples of AI use with your students.

To read more about the research behind the development of the AI Assessment Scale, view The Artificial Intelligence Assessment Scale (AIAS): A Framework for Ethical Integration of Generative AI in Educational Assessment | Journal of University Teaching and Learning Practice [new tab].

To dive in deep to the AI Assessment Scale, consider accessing the free e-book from Leon Furze that offers detailed reasons why you might choose each level of the scale, ideas for assessments that match that level in a variety of subject areas, and selected lesson plans to introduce AI use. To access the e-book, signing up for their mailing list is required.

Now what?

Consider where and when you can support the use of AI in your courses. It's okay to have different usages for each assessment based on the required learning outcomes and the nature of the assessment.  When our students graduate, there will be a workplace expectation to have an understanding of how AI works and how it can be used in daily work duties. As we move forward into the world of AI, clear communication will be key in all aspects of teaching and assessing. 

If we are to prepare students for a world where collaboration with AI is required rather than prevented, then helping student leverage AI to produce better work should become a signature pedagogy of higher education. (Bowen & Watson, 2024, p. 233). 

References

Bowen, J. A., & Watson, C. E. (2024). Teaching with AI: a practical guide to a new era of human learning (First edition.). Johns Hopkins University Press.

Furze, L. (2024, August 28). Updating the AI assessment scale. Leon Furze. 

Oregon State University. (2025). Bloom’s taxonomy revisited – artificial intelligence tools – faculty support. Bloom’s Taxonomy Revisited – Artificial Intelligence Tools – Faculty Support | Oregon State Ecampus | OSU Degrees Online. 

University of Arkansas. (2014, September 18). Bloom’s taxonomy verb chart. Teaching Innovation and Pedagogical Support. 

University of Waterloo: Centre for Teaching Excellence. (2024, May 21). Bloom’s taxonomy. Centre for Teaching Excellence | University of Waterloo.