This module explores the evolving landscape of assessment in the era of GenAI. It provides educators with frameworks and assessment strategies that can foster authentic and meaningful learning, enhance student engagement, and maintain academic integrity.

The ease of finding information on the internet changed how students perceived the benefit of many kinds of learning, and teachers were forced to rethink assessments in the context of different motivations and goals. The ease with which AI can think for us changes the equation again. We need to clarify further what we want students to learn, why is it valuable, and especially why the effort and discomfort required are necessary. (Bowen & Watson, 2024, p. 184)

First key questions:

• What is assessment? Why is it important in your teaching practice?
• How does assessment look in your current practice? (e.g., essays, quizzes, oral performance, etc.)
• How might your current assessment methods be affected by students’ access to GenAI?
• Can students use GenAI in those tasks and how does that impact the integrity and authenticity of learning?

Rethinking Assessment from a Holistic Perspective

It’s important to view assessment as a continuum in the learning process and not a final stage or final product. It should integrate three forms of assessment: assessment as learning, assessment of learning, and assessment for learning.

Key concepts

Assessment as learning: a process where students actively engage in their own learning and reflection. This helps students with metacognitive skills as well as self-regulation by using feedback to further develop their learning strategies and goal setting abilities.

Assessment of learning (summative assessment): a process that evaluates students’ achievement at the end of a learning cycle (e.g., unit, course, program, etc.) against some predetermined learning outcomes. These assessments often result in grades or scores.

Assessment for learning (formative assessment): a process that provides ongoing feedback to guide teaching and learning. This process helps educators identify learning gaps and adjust teaching strategies accordingly.

For further reading related to approaching assessment from a holistic perspective, please check out:

MacMath, S., Wallace, J. & Chi, X. (2009). Curriculum integration: Opportunities to maximize assessment as, of, and for learning. McGill Journal of Education / Revue des sciences de l’éducation de McGill, 44(3), 451–465. https://doi.org/10.7202/039949a

Addressing GenAI in Assessment Design: Considerations and Strategies

• It is essential to design assessment tasks with the assumption at (a) students might use GenAI, and (b) students want to learn, not cheat (Furze, 2024).
• Consider the following motivational factors when creating meaningful assessment activities: (Bowen & Watson, 2024, p. 185)
  1. Purpose (“I care”): ensure assignments are relevant and meaningful to students.
  2. Task clarity (“I can”): provide clear instructions and build students’ self-efficacy.
  3. Criteria for success (“I matter”): provide autonomy and choice so that students feel their work has value and impact.
• Consider this assignment template that combines motivation, task clarity, and criteria for success (Bowen & Watson, 2024, p. 187).
  

  Intrinsic motivator	Components	Questions addressed
  Purpose “I care”	Why	What skills or knowledge will I gain? How will I be able to use it? Are the examples relevant?
  Task “I can”	What	Is there clarity about what to do? What needs to be submitted? (Biography? Hardcopy? AI transcript?)
  	How	Is there a recommended process? Is the process intentionally unclear? What roadblocks or mistakes can I avoid?
  	When	When is it due? Spacing? Can I do this in one sitting?
  	Where and resources	Where can I do this work? Do I need the internet or library? Where do I submit this work? (LMS? Dropbox?)
  	With whom	Do I need to work alone?
  Criteria “I matter”	Checklist	What are the parts? How do I know I am on the right track?
  	Rubric or examples	How will I know what’s expected? What matters most? How will I know I’m doing good work? What’s good or bad in these examples?

• Consider GenAI-resistant assessment strategies. What is appropriate will depend on your individual context and factors such as class size, subject matter, ect.
  1. Modify assessment activities to be more personalized, specific, and context-dependent. This can include designs that directly relate to class discussion, current events, and unique scenarios that are less likely to be successfully addressed by AI.
  2. Encourage in-class assignments either in-person or via educator-monitored online platforms.
  3. Encourage peer review and collaborative and community work, which encourages deeper engagement with the material and fosters collaboration and critical thinking.
  4. Incorporate more oral assessments and low-stakes assessments such as (group) presentations or oral exit exams. (Though this is not encouraged with large classes).
  5. Encourage reflective writing that allows students to share and reflect on their personal experience and personal learning.
• Consider supporting processes when designing assessment activities that allow students to approach those tools.
  1. Shift the focus of learning and assessment from the final product to the process of learning. This can include requiring students to document their learning journey and submit different drafts, outlines, or annotated bibliographies along with their final submission (Hodges & Kirschneer, 2023).
  2. Use this AI assessment scale to guide your design and communicate with students regarding AI use, as well as student responsibility (Perkins, Furze, Roe, & MacVaugh, 2024).

Example: Process assignment template (Bowen & Watson, 2024, p. 192-193)

• Ask an AI to write an essay/write code/draw an image/create a script/design an experiment/draft a press release/propose a new business/analyze data.
• Evaluate the results. Make a list of errors or how this result could have been better.
• Adjust your prompt to improve the output.
• Which result is best and why?
• What was your strategy to improve the prompt? What worked best?
• Take the best output and make it even better with human editing.
• Describe for an employer what value you added to this process.
• Explain why human work improved the AI work.

Further Reading

• Assessment reform for the age of artificial intelligence, commissioned by the Tertiary Education Quality and Standards Agency (TEQSA), explores the transformative impact of generative AI on assessment practices within higher education. The document serves as a guiding framework for educational institutions, offering principles and propositions to adapt assessment strategies in response to AI’s capabilities.
• Dr. Phillipa Hardman’s Post-AI assessment: some initial observations + a ChatGPT prompt to get your started provides compelling ways to think about assignment redesign in the direction of authentic assessment. It also provides a super-prompt that allows you to harness the power of ChatGPT for your own curriculum.
• Explore strategies for redesigning writing assignments in the face of AI (Prochaska, 2023)
• Rethinking Assessment for Generative Artificial Intelligence by Leon Furze (2024) discusses strategies and examples of how to make assessments more authentic and relevant, and promote higher-order thinking skills.

Summary

This module explored the challenges and opportunities presented by GenAI in educational assessment. By reimagining assessment practices, educators can create more engaging, authentic, and effective learning experiences that prepare students for a world where AI is increasingly prevalent. The key is to focus on developing higher-order thinking skills, emphasizing the learning process, and leveraging AI as a tool for enhancing creativity and critical thinking.

Final Reflective Question

What specific change(s) would you implement in your next assessment task?