Concurrent Session One | Centre for Innovation in Teaching and Learning

1 - 1:50 p.m. (12:30 - 1:20 p.m. ADT)

AI and Online Assessment and Evaluations and Best Practices

A working group of professors teaching at an online campus created a Community of Practice to address the impact of evaluating and assessing student work given the rise in the number of students using GenAI to complete assignments. The significance of this work was to develop a list of best practices to address this issue that could be easily implemented into current evaluation and assessment practices and look to future practices as they evolve in the reform of undergraduate STEM education.

The approach involved discussing what were the key elements in trying to evaluate and assess student work that would result in students having to perform and complete assessments with a reduced reliance on GenAI.

The evidence of this work resulted in creating assessments that directed students to complete assignments directly without copying and pasting GenAI created content into the university’s Learning Management System.

This session will focus on some best practices in assessing and evaluating student work in the age of generative artificial intelligence in the online environment. Participants will review several software tools and other strategies that require students to directly engage in course materials, reducing their ability to leverage generative artificial intelligence in providing answers during assessments and evaluations including discussions. Not only will participants see some direct examples of these tools and strategies, but it will also allow them to think about alternate ways to assess and evaluate students in the context of their own digital classrooms.

The expected learning outcomes for the audience are:

Analyze ways to best evaluate and assess student work in the age of AI.
Identify assessment activities that reduce AI usage.
Construct online discussions that reduce AI usage.

Presenter(s): Dr. Trevor Adams, Department of Geography and Environmental Studies

Affiliation: Saint Mary's University

Stream: Authentic Pedagogy and Assessment

Session Format: Presentation

Human Inquiry, Artificial Intelligence & Asking “Why?”: Rediscovering Our Purpose in Teaching and Learning

Abstract: As AI reshapes the edges of teaching and learning, this session returns to a foundational question: Why? Drawing on two decades of practice, we frame AI not as a threat but as a clarifying force that helps educators protect human judgment, creativity, belonging, and ethical reasoning. Participants will explore a practical Three Horizons model—AI as assistant, thinking partner, and co‑creator—alongside strategies for redesigning assignments, strengthening provenance, and assessing process over product. The focus is on aligning purpose, practice, and AI use so learning becomes more meaningful, transferable, and human‑centered.

Summary: As artificial intelligence increasingly handles surface‑level academic tasks, higher education is confronted with a fundamental question: What is learning for? This session aligns with the conference theme Teaching for Tomorrow: Building Transferable Skills and Lifelong Learners by arguing that purpose—not technology—must anchor course and assignment design. Rather than framing AI as a threat, we position it as a clarifying force that pushes educators to foreground enduring, transferable human capacities: judgment under uncertainty, creativity, collaboration, belonging, and ethical reasoning. Drawing on evidence from learning theory and higher‑education research, the session introduces the Three Horizons model (Sharpe et al., 2016) as a practical framework for ethical AI integration: AI as assistant for routine tasks, thinking partner to augment inquiry, and co‑creator when students retain agency and responsibility. This staged approach helps instructors prevent students from bypassing learning while still leveraging AI to support deeper engagement. Research indicates that AI’s impact on learning is mediated by teaching methods rather than tools alone, reinforcing the need for intentional pedagogical design (Dong et al., 2026).

The session appeals across disciplines by focusing on universal academic practices rather than field‑specific content. Every discipline requires students to reason with incomplete information, apply methods responsibly, collaborate ethically, and use feedback productively. Participants will explore a process‑centered assessment approach—including role rotations, co‑creation, public audiences, evidence trails, and reflective memos—that aligns with authentic assessment, formative feedback, collaborative learning, and metacognitive reflection (Anderson & Krathwohl, 2001).

A key contribution is a language shift from “cheating” to “bypassing learning.” This reframing reduces shame, restores student agency, and clarifies what is lost educationally when AI substitutes for thinking. The framing supports clearer policies, healthier classroom climates, and consistent expectations across institutions.

By the end of the session, participants will be able to:

Identify the human capacities their courses should prioritize for long‑term transfer.
Apply the Three Horizons model to make ethical, intentional AI design choices.
Redesign an assignment to assess process, reasoning, and provenance, not just output.

Participants will engage through brief reflective prompts, small‑group assignment redesign (“assignment surgery”), and peer feedback. Interactive polling and shared design templates ensure practical takeaways applicable across disciplines and institutional contexts.

Presenter(s):Dr. Stacey MacKinnon, Associate Professor, Psychology

Affiliation: University of Prince Edward Island

Stream: The Learning Experience

Session Format: Presentation

AI literacy where it can do the most good: research productivity and the mechanisms of agency

In this session, a team of librarians from the University of New Brunswick will give an overview of the current AI driven search tools available to students (via the library, or individual subscriptions). This will include a brief demonstration of the tool Consensus AI in a secondary research context and a subsequent group conversation on how this affects instruction and best practices on finding, evaluating and using sources. We will conclude by presenting on how the library can support in navigating these conversations with students.

Presenter(s): Catherine Gracey, Open Scholarship ad Copyright Librarian

Affiliation: University of New Brunswick

Stream: SoTL and AI-Accelerated Research

Session Format: Short Paper (20 Min)

Integrating AI in the Research Journey: Balancing Research Productivity with Ethical Responsibility

Artificial Intelligence (AI) is becoming more ubiquitous than ever and its integration into the field of academic research has been growing. This session will explore how AI can boost research productivity that is balanced with our requirement to comply with ethical considerations advocated by the academy and the field.

Presenter(s): Jim Tuff, Educator Developer, CITL

Affiliation: 91��ý

Stream: SoTL and AI-Accelerated Research

Session Format: Short Paper (20 Min)

Adopt, Adapt, or Build?

This session shares Dalhousie University's ongoing work adapting an AI Literacy Framework for educators. Following a brief overview of the emerging framework, participants will explore, critique, and help shape the competencies educators may need for teaching and learning in the age of Generative AI.

Presenter(s):Shakir Hussain, Associate Director of Education Technology and Digital Innovation

Affiliation: Dalhousie University

Stream: Workshop

Session Format: Workshop