Post-AI Assessment Design
A simple, three-step guide on how to design assessments in a post-AI world
Hey folks 👋
As initial fear of AI among educators turns more and more into curiosity, the question I get asked most is: how can I assess learning if ChatGPT can write assignments?
This week, I’ll share a simple, three-step guide to get you started on designing assessments for the post-AI classroom, plus some tips on how to use ChatGPT to help you to rapidly redesign your assessments.
🚀 Let’s go!
Step 1: Write Inquiry-Based Objectives
Inquiry-based objectives focus not just on the acquisition of knowledge but also on the development of skills and behaviours, like critical thinking, problem-solving, collaboration and research skills.
They do this by requiring learners not just to recall or “describe back” concepts that are delivered via text, lecture or video. Instead, inquiry-based objectives require learners to construct their own understanding through the process of investigation, analysis and questioning.
By shifting to inquiry-based objectives, we remove the risk of learners “cheating” (i.e. generating text-based responses using AI tools like ChatGPT) and assess instead their ability to use AI tools like ChatGPT along with books, articles and other resources to explore, analyse and construct meaning from information.
Here’s what it looks like in practice:
🚀 Pro Tip: ask ChatGPT to review your draft or existing learning objectives and turn them into inquiry-based objectives. To optimise the quality of the objectives that ChatGPT generates, include:
a description of what inquiry-based objectives are, what they enable learners to do and why;
an example of a great inquiry-based objective for ChatGPT to use as a template.
Step 2: Design a Project for Each Inquiry-Based Objective
Now you have IBOs, the next task is to design projects that learners will complete to hit the objectives.
To do this, design a project, problem statement or scenario for each objective. Frame the objective as a problem to be solved or a challenge to be addressed.
Choose a real-world scenario, project or or problem statement related to the objective which puts the project into a real world context that will make sense to the learners.
Here’s what it looks like in practice:
🚀 Pro Tip: ask ChatGPT to turn your inquiry-based learning objectives into short projects for learners to complete in order to hit the objectives. To optimise the quality of the projects that ChatGPT generates, include:
a description of who your learners are (e.g. age, level of understanding, level of confidence);
some examples of real-world contexts that will make sense to and engage your learners.
Step 3: Design Performance-Based Assessments for Each Project
Now you have a set of learner projects, the final task is to design assessments & mark schemes for each project.
When gauging learner success in an inquiry-based approach, it's essential to create a comprehensive mark scheme that considers not only knowledge acquisition but also skills development and methods demonstrated during the inquiry process.
This often involves applied, authentic activities and assessments that require learners to demonstrate their competence in a tangible way. Research shows that these assessments provide a more comprehensive and authentic evaluation of a learner's abilities compared to traditional assessments, such as exams and multiple-choice questioning.
Creating performance-based assessment is a three step process which involves reviewing each student project and identifying three things:
Skills assessment: the skills the learners need to demonstrate in the course of their project. In the post-AI classroom, this includes the ability to use ChatGPT to explore & understand the topic.
Knowledge assessment: the conceptual knowledge & understanding that learners need to demonstrate. In the post-AI classroom, this includes identifying any misconceptions generated from ChatGPT "hallucinations".
Process assessment: the methods, processes and/or behaviours that students need to demonstrate in the course of their project. In the post-AI classroom this includes the ability to both prompt and critique, compare & validate ChatGPT outputs.
Here’s what it looks like in practice:
🚀 Pro Tip: ask ChatGPT to use your projects to generate a performance-based assessment criteria and mark scheme. To optimise the quality of the outputs that ChatGPT generates, include:
a description of what performance-based assessment is, what it assesses, how and why;
a requirement to include the assessment of learners’ ability to engage critically with and verify the outputs of generative AI tools like ChatGPT.
That’s all folks! You can download a full copy of the Post-AI Assessment Design guidebook here.
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Happy designing,
Phil 👋