2.4 Spark an Idea 3: Nifty Assessments

2.4.1 Developing Students’ Economics Writing Skills through Scaffolded AI-Assisted Feedback
Nazanin Khazra, Assistant Professor, Teaching Stream, Economics, Faculty of Arts & Science, Victoria Sheldon,Faculty Liaison Coordinator, Generative AI Pedagogies, Centre for Teaching Support & Innovation

This session introduces an innovative assessment method for a Microeconomics theory course (ECO200) that combines economic analysis with reflective writing, supported by critically engaging with AI-assisted feedback. The assessment includes pre-exam preparation, a pre-test assignment with reflection on AI feedback, and an in-person writing exam on real-world economic scenarios. This approach leverages generative AI to provide personalized feedback on students' pre-exam essays, with the aim of supporting their ability to articulate complex economic concepts in writing. In addition, the multi-layered approach to this assessment guides students to become self-directed learners, nurturing their critical thinking, AI literacy, and metacognitive skill development. By encouraging students to confront and learn from their mistakes, this scaffolded, reflective approach supports their growth through the challenges of writing, transforming potential discomfort into an opportunity for learning.

The structure of the assessment aims to address the challenge of balancing quantitative skills (derivatives and equation-solving) with qualitative analysis in economics education. The in-person portion of the writing assessment focuses on real-world economic issues such as food deserts and market competition. By incorporating metacognitive reflection on AI-assisted writing feedback, this formative assessment aims to improve students' economic writing skills, critical thinking, and ability to apply theoretical concepts to practical scenarios.

*** Structured as a dialogue, this session will reflect on the pedagogical impacts of this innovative assessment approach and explore the role of developing inclusive assessments with generative AI in mind, particularly in the context of economics education. ***

2.4.2 Leveraging artificial intelligence: Using ChatGPT to develop clinically relevant case studies for student assessments
EmilyWood, Course Instructor (CUPE 3902, Unit 1), Speech-Language Pathology, Rehabilitation Sciences Institute

Case studies are a dynamic teaching and assessment tool, enabling students to integrate theoretical knowledge, develop critical reasoning skills, and apply their learning to realistic scenarios. However, developing case studies can be time-intensive and challenging. Educators often face obstacles such as privacy risks associated with collecting and sharing personal information and sourcing cases that align with specific learning objectives that reflect the diverse experiences of their students.

This session introduces educators to using Microsoft Copilot as a practical solution for generating customized, contextually rich case studies for student assessment. Attendees will learn how AI chatbots like Copilot can be used to quickly create realistic and relevant cases tailored to assessing specific learning objectives while maintaining ethical considerations and avoiding privacy concerns.

A structured, six-step approach to developing effective prompts for generating case studies will be presented. These steps include (i) characterizing the target audience, (ii) setting case and assessment parameters, (iii) describing particularities of the case, (iv) defining student skills and abilities to be assessed, (v) integrating this information into a concise prompt, and (vi) revising the generated case for relevance, appropriateness and accuracy. A live demonstration will walk attendees through these steps, allowing them to see how to refine prompts and adapt outputs to suit their students’ needs.  We will also briefly discuss critical AI literacy and some potential issues with AI-generated cases and how these can be mitigated.

Following the session, participants will be able to outline and apply these steps to create tailored case studies. They will also develop the ability to analyze how written prompts impact the quality of cases, empowering them to produce diverse, relevant, and robust cases.

2.4.3 Advocacy in Action: A Scaffolded Assessment for Civic Engagement
AshleyWaggoner Denton, Associate Professor, Teaching Stream, Psychology, Faculty of Arts & Science

How can we help students move beyond theoretical learning to take meaningful action on societal issues? This session presents a multi-stage advocacy assessment that empowers students to apply psychological principles to real-world challenges. Through researching a social issue, analyzing existing advocacy efforts, crafting an issue brief, and writing a persuasive letter to a policymaker, students develop essential skills in evidence-based communication, policy analysis, and civic engagement.

Designed for a community psychology course, this assignment fosters critical thinking, professional writing, and real-world impact. Students not only gain a deeper understanding of pressing social issues but also build confidence in their ability to advocate for change. This session will outline the structure and intended outcomes of the assessment, highlight student responses, and discuss how advocacy-based assignments can be integrated into different teaching contexts. Links to resources will be provided. A brief Q&A will allow participants to explore practical applications in their own courses.