The Rethinking Assessment module guides participants through the design, implementation and evaluation of assessments that are authentic, accessible, innovative and learner-centred. The module also broaches the holistic course context in which assessment takes place and the topic of ungrading.
Participants have the option of using the module as an interactive and exportable workbook to support the planning and creation of a new assessment.
You may find it easier to go through the module with certain course materials at the ready. We encourage you to take a moment to locate:
We recognize you may also be coming to the module without an assessment in mind or even a specific course that you are teaching. If it would be helpful, we encourage you to use the module activities as an opportunity to create an assessment for a teaching portfolio or to reflect on the conventions and practices within your scholarly discipline.
Generative AI (e.g. ChatGPT, Gemini, Copilot, etc.) was not knowingly used in the creation of this module aside from drafting rubric criteria for the example rubrics, which is detailed in that section of the module.
This module links to various external resources, drawing on the kindly shared work of other educators. Although we periodically check for broken links, you may encounter some in the module. We encourage you to use a web search to find any links of interest on your own, and, if possible, to let us know which link needs to be repaired at mi@mcmaster.ca.
You are welcome to engage with the module in the manner most helpful to you. There are several activities that encourage you to reflect on your assessment beliefs and practices, and to record your thoughts. The activities are optional. We have structured the module like a workbook to guide the assessment design process, but if you wish to use the module for informational purposes only and forego the activities, that is entirely up to you!
By the end of this module, you should be able to:
Brilleslyper, M., M. Ghrist, T. Holcomb, B. Schaubroeck, B. Warner, and S. Williams. (2012). “What’s the Point? The Benefits of Grading without Points.” PRIMUS, 22(5): 411–427. doi:10.1080/10511970.2011.571346.
Currant, N., et. al. (2024).”Rethinking assessment? Research into the affective impact of higher education grading.” Compass: Journal of Learning and Teaching, 17(1): 82-100. https://doi.org/10.21100/compass.v17i1.1496.
Kohn, A. (2013). “The Case against Grades.” Educational Leadership, 69(3): 28–33. https://www.jstor.org/stable/42982088.
What if, as educators, we take as much interest and care in designing assessments as we do with preparing for classroom teaching? Can we aim to create assessments that are equally valuable opportunities for students to learn?
Assessments that students are intrinsically motivated to complete are less susceptible to academic dishonesty of any kind (Krou et al., 2021). Creating an assessment that is purposefully designed to engage students in a meaningful learning experience – rather than a competition between students or a tedious task – can similarly encourage students to undertake it with integrity.
Take a moment to reflect on what an assessment-as-learning-experience might look like in your discipline: how might students develop their knowledge, skills and/or attitudes through completing the assessment? Or, consider what students learn from the assessment you would like to redesign: if they are only recalling what they already know (which is also important, of course!), can your redesigned assessment incorporate elements that allow them to learn something new?
The ubiquitous presence of generative AI has amplified structural tensions in postsecondary education (i.e. problems with grading and the transactional views of assessment it engenders) and compelled many of us to reckon with our assessment practices. It has also complicated the implementation of various well-designed assessments.
Note: susceptibility to AI misuse is not an indicator of a poorly designed assessment! But the ample availability of AI applications is a reality we must acknowledge in our assessment design practice.
Most current approaches to preventing inappropriate AI use in assessment involve direct supervision of some kind: in-class activities observed by the teaching team, oral assessments or invigilated exams. But many instructors acknowledge the limitations of such forms of assessment, like the difficulties in scaling to large classes, or the constraints on creativity in assessment design, or the barriers to accessibility. Ultimately, assessment design alone is unlikely to wholly address the misuse of AI; clear syllabus statements, conversations with students, documentation tools and other supports also play a role in guiding students towards responsible AI use.
At the same time, completely prohibiting the use of AI may not adequately prepare students to make ethical and well-considered decisions about their use of the technology in the present and future. Course activities or assessments that acknowledge the nuances of navigating the realities of generative AI can help guide students in determining how AI may support a task or hinder their learning, and how to properly document their use.
If you would like some inspiration for assessment designs that either interrogate or incorporate AI thoughtfully, refer to the assignments collected by Harvard’s AI Pedagogy Project (integrating AI use) and the University of Toronto (examples of both integrating and preventing AI use).
Corbin et al. (2025) propose another reframing of assessment in the era of generative AI, as a wicked problem:
Unlike their counterpart ‘tame’ problems, which have clear definitions and measurable solutions, wicked problems lack definitive formulations, and their solutions are not true or false but rather better or worse, requiring judgment, compromise, and adaptation. This distinction is key because it disrupts the assumption that there is a ‘correct’ policy, assessment method, or institutional response waiting to be discovered. Instead, every approach carries trade-offs, is shaped by context, and must be continually reassessed in response to evolving conditions (737-738).
They also note the significant personal toll on instructors pressured to find the “right” solution, who bear the full consequences of their choices (738, 742). As we engage in our assessment design or re-design process, thinking of assessment after generative AI as a “wicked problem” may remind us that there is no ideal solution eluding our grasp but rather, trade-offs we must make in our given context.
Many of the educators we work with at the MacPherson Institute tell us how grades and grading have come to dominate students’ thinking about the practice of assessment, and their experience of university learning more generally. Grades are also a major source of tension between educators and students, often putting educators in the position of negotiating an incremental change or justifying a particular mark. Furthermore, the overemphasis on grades is likely to be a driving factor in students’ misuse of generative AI, if getting a good mark is prioritized above learning and growth.
While the “Rethinking Assessment” module is intended to support the design or redesign of a specific assessment, we also recognize that no assessment exists in a vacuum. As you think through the particulars of your assessment, you may also wish to consider how it fits into the bigger picture of your course.
The term “ungrading” is a bit misleading: the ungrading movement in higher education encompasses a range of alternative grading strategies, and not necessarily foregoing grades altogether. For many educators, doing away with grades may seem impossible given constraints like class size, student expectations and accreditation requirements.
One of the key proponents of ungrading, progressive educator Jesse Stommel, clarifies:
“Ungrading’ means [questioning] grades as a systemic practice, distinct from simply not grading…. Too many of our approaches to grades treat students like they’re interchangeable and fail to recognize their complexity. Can we imagine flexible approaches to assessment, pedagogies which center intrinsic more than extrinsic motivation, encouraging and supporting learning, rather than policing behavior?” (Stommel, n.d.)
The ungrading movement, then, seeks to take practical steps towards better and more equitable grading strategies, but also towards an eventual future where grades have a minimal role – if any – in the student learning experience.
Stommel has a growing list of ideas to introduce a culture of ungrading into the classroom:
Are any of the ungrading strategies listed above consistent with your teaching values and beliefs? If you have a specific assessment design or need in mind, could aspects of the ungrading strategies discussed above be built in?
* By structured activity, we mean a carefully thought-out and clearly communicated process, which frames self-reflection or peer feedback as a meaningful and respectful practice.
** We acknowledge that not every educator has the privilege of taking risks in their teaching, which can be contingent on factors like employment precarity, race, gender, perceived language abilities, and more.
These ungrading strategies can be used in combination, and not every strategy will be realistic for every teaching context. If you would like to learn more about a particular ungrading approach, the best way to get started is to talk with colleagues who have tried these approaches in their own teaching. Though every offering of every course will have unique opportunities and challenges, your fellow educators can share the lessons they have learned to help you navigate your own ungrading journey.
Corbin, T., Bearman, M., Boud, D., & Dawson, P. (2026). The wicked problem of AI and assessment. Assessment & Evaluation in Higher Education, 51(4), 736–752. https://doi.org/10.1080/02602938.2025.2553340.
Krou, M. R., Fong, C. J., & Hoff, M. A. (2021). “Achievement Motivation and Academic Dishonesty: A Meta-Analytic Investigation.” Educational Psychology Review, 33(2), 427–458. https://doi.org/10.1007/s10648-020-09557-7.
Stommel, J. (n.d.). Ungrading and Alternative Assessment, http://bit.ly/ungrading.
We will now turn to designing an assessment that is authentic, accessible, learner-centred and realistic for you to implement in the context of your course.
There are at least two ways to engage with the module:
If you choose the route of recording your responses, we have created an exportable workbook to guide your design of an authentic assessment, including a series of questions to guide your assessment design. The written content from the workbook is repeated below if you would prefer to simply read and reflect without answering the questions.
Some questions may be more useful at the beginning of your assessment design process, while others may be easier to answer with at least a preliminary concept in mind. If you would like to sample some non-traditional assessment ideas before you get started, you may want to jump ahead to the Ideating section of the module first and return to the workbook once you have an assessment idea to work with.
The content in this “Designing Authentic Assessments” tab is based on an open educational resource (OER) developed at the MacPherson Institute, Generative Artificial Intelligence in Teaching and Learning at McMaster. The section about designing assessments in the age of generative AI was co-authored by Joanne Kehoe and Devon Mordell.
Before exploring some of the principles of assessment design, you may wish to begin by documenting a few details about the overall context of your course assessments that might impact their design.
Learning outcomes state what learners are expected to be able to know, do, or value at the end of a class, unit, course or program. For example, “by the end of the workbook, learners will be able to evaluate the (constructive) alignment of their assessments with their course learning outcomes.”
You have likely been asked to write course-level learning outcomes when preparing a syllabus. You may also be aware of the program-level learning outcomes in your department… perhaps you even contributed to their design!
The central feature of a learning outcome is a specific and measurable action verb that implies how to assess the learning outcome, such as “solve,” “compose” and “justify”; verbs like “understand,” “learn” and “know” are typically avoided in learning outcomes as they are imprecise and difficult to observe. In the earlier example of an outcome about learners being able to evaluate the alignment between assessments and outcomes, we might present the learner with a small set of learning outcome / assessment pairs and ask them to discuss whether they are aligned.
Because of the connection between learning outcomes and assessments, some verbs are more prevalent in certain disciplines compared to others – like “calculate” or “critique.” Which action verbs describe competencies within your own discipline?
Consider:
Which course learning outcome(s) could or should the assessment measure? Put another way, if a student successfully completes the assessment, what learning outcomes will they have demonstrated? Will students understand why they are doing what they are doing?
Are there any program-level learning outcomes that students can show they have met in completing the assessment?
Certain factors or teaching conditions may limit the possibilities for assessment design, so it is helpful to identify them early on.
What design constraints must be accounted for in your assessment?
Some disciplines may be required to align assessments with accreditation guidelines; move on to the next question if this is not true of your discipline.
Does the assessment need to conform to any accreditation requirements? If so, what are they?
You may already have an assessment that you have found effective, but you need to adjust it due to a change in assessment circumstances – like the availability of generative AI, or a larger class size.
If not, read on: “Defining Authentic Assessment.”
What are the strengths of the existing assessment? What positive feedback about it have you received from students?
What course or unit learning outcome does it demonstrate that students have achieved? What knowledge, skills or attitudes does it develop in learners?
What are your reasons for wanting to redesign the assessment? Have students made specific comments about it in your course evaluations?
How might the assessment be vulnerable to academic integrity issues, whether related to developments such as generative artificial intelligence or not? Are there a significant number of accommodation requests that suggest a redesign might benefit you and your students alike?
This “Rethinking Assessment” module centres on the idea of authentic assessments, which are meant to “foster disciplinary behaviours and ways of thinking and problem solving used by professionals in the field” (Queen’s University Centre for Teaching & Learning, n.d., para 3). The definition of authentic assessment is not widely agreed upon, however, leading it to become a catch-all term for good assessment practices in general. Because of its openness to interpretation, we will state our understanding of the term – based on the work of Grant Wiggins (1998, via Indiana University Bloomington) – below.
“An authentic assessment:
(Indiana University Bloomington, n.d., para. 2)
Authentic assessments typically draw on complex real-world situations and constraints in their design.
Who are the practitioners in your field? What do they know and do as part of their work or research?
What might the future of your discipline look like, in response to developments such as generative AI or other challenges specific to your area of study?
In what ways does or could the assessment offer opportunities to “do” their field of study?
What tasks are customary in your disciplinary area?
Are there ways you can simulate the context of a workplace, civic or personal life in certain respects? What real-world constraints could an assessment involve?
Authentic assessments are multifaceted and complex. They demand that students use a range of skills and knowledge in coordination, and there is usually more than one right answer.
What skills do students develop in the course? How might the assessment require students to apply those skills in ways that relate to other skills and knowledge they gain through your course?
Will assessment products or performances allow for a variety of responses or approaches that are equally valid, if appropriate?
Authentic assessments require more than just correct answers: they require judgment, innovation and justification on the students’ part.
How might your assessment ask students to exercise their judgment – evaluate, critique or otherwise apply what they know in novel scenarios? Will the assessment allow for creativity on the student’s part?
If so, how? If not, what kinds of authentic activities or tasks could be incorporated into the assessment?
Rather than being a “one-shot” task, authentic assessments involve students getting feedback they can use to refine assessment products and performances, and apply particular knowledge or skills in different ways or contexts.
Can formative feedback be built-in to the assessment? Will students have the ability to revise and refine their submissions?
Will students know or be able to predict assessment tasks and standards for judgment in advance? Can assessment tasks be iterative, giving students the chance to improve and grow their understanding of the knowledge and skills they are developing?
Students from outside your discipline may also be enrolled in your course – if it is helpful to your assessment design process, consider what interested or motivated them to take the course.
For what reasons might non-program students be taking your course as an elective? What course competencies can they use or translate to their everyday lives?
In the module, you will find references to “typical” or “traditional” assessments – by this, we mean assessments that have traditionally been used in Canadian universities and elsewhere, which many of us may have experienced in our own education: exams (often with multiple choice questions) and essays.
Grant Wiggins, in “The Case for Authentic Assessment,” suggests an assessment is “authentic” when an instructor can “directly examine student performance on worthy intellectual tasks” rather than “rely[ing] on indirect, proxy ‘items’” of traditional assessment (1). The Center for Innovative Teaching and Learning at the Indiana University Bloomington has illustrated Wiggins’ contrast between authentic assessments from, more precisely, “typical tests” in the table below:
Original source: https://citl.indiana.edu/teaching-resources/assessing-student-learning/authentic-assessment/index.html
“Alternative assessments” is a broader term, simply meaning assessment formats that have not traditionally been used in higher education. The term is typically used to denote assessments that involve creativity (e.g. zines), or digital skill development (e.g. podcasts or video essays), or even assessments that have been used for decades in certain disciplines, like case studies.
To be clear: there is nothing inherently bad about traditional assessments! They may be the most suitable type of assessment for your learning outcomes, or the most viable option given the constraints of your context (e.g. large classes with limited resources for teaching assistants). Certainly, in the Arts, Humanities and Social Sciences, persuasive arguments have been made about the importance of writing as a scholarly practice and bringing back essays as assessments.
Our intention is not to position traditional assessments as inferior to authentic or alternative assessments, but to encourage you to reflect on your thinking around assessment design and the influences that have shaped it.
We appreciate reservations about framing university education as workplace training while also recognizing students’ expectations about employability following their degree. Wiggins’ definition finds common ground between the two concerns: Wiggins sees the “‘ill-structured’ challenges and roles” of authentic tasks as a rehearsal for the complexities of “adult and professional life” (1).
While authentic assessment is a helpful concept to frame our thinking, it does not fully capture the needs our assessment design process. For example, it is also important that we design our assessments with accessibility in mind and ensure that they are aligned with what we want our students to learn. Some other considerations are listed below, and you may have additional ones that are tailored to your teaching context.
From Biggs and Tang, the principle of constructive alignment combines the idea that “learners use their own activity to construct their knowledge as interpreted through their own existing schemata” and “assessment tasks should be aligned to what it is intended to be learned” (2011, p. 97).
The principle of constructive alignment is operationalized through the practice of backwards course design, where you start with the end in mind (i.e. the learning outcome, what you want students to be able to do by the end of the course) and work backwards to determine how to support students in reaching that end through the design of assessments, activities and course content.
Referring back to the learning outcomes you identified in the “Taking Stock of Assessment Constraints” section of the module, what kinds of activities does the verb in your learning outcome(s) suggest? For example, what kinds of assessments would allow you to measure whether students are able to hypothesize, analyze or critique?
When you have determined that your assessment demonstrates students have met course or program-level learning outcomes, ask yourself: what course activities and content will help students to complete the assessment?
Ensuring that your assessment is accessible to the greatest extent possible for all learners is an important consideration from the outset of assessment design. The universal design for learning (UDL) guidelines offer one approach to improving the accessibility of your assessments for all learners, with recommendations such as building in flexibility, sharing rubrics to clarify expectations and providing mastery-oriented feedback.
Are there any potential barriers for students within the assessment? For example, are there graphs that would need to be described for students who are blind or who have low vision? Are there aspects of the assessment that may disadvantage students who are English-language learners, such as lengthy and complex instructions?
Is it possible for students to be provided with multiple options to demonstrate their abilities and learning? That is, can the assessment exemplify the UDL principle of multiple means of action and expression?
How will you communicate your expectations around the successful completion of the assessment? Will there be opportunities for students to receive feedback on their work before submitting a high-stakes assessment?
Learner-centred instruction is grounded in a constructivist theory of learning, where students are recognized as having an active role in the construction of their own knowledge rather than being passive recipients of content.
In its fullest expression, “[s]tudent-centered learning demands that students set their own objectives for learning and determine the resources and activities that will help them meet those objectives” (Jonassen, paraphrased in Duncan & Buskirk-Cohen, 2011, p. 247). While it may not be possible in most teaching contexts for students to design their own assessments, consider incorporating elements of choice and scaffolding (e.g. breaking a large project into stages or sharing approaches to studying) to build students’ confidence in their ability to learn.
Through an equity lens, learner-centredness also recognizes the diversity and individuality of learners; that is, students are able to see themselves reflected in the assessment.
How might the assessment acknowledge the lived experience of the learner? I.e. Will the assessment allow students to draw on their own background, circumstances, strengths, and interests?
In what ways will the assessment offer tailored opportunities for learners to show what they know and what they can do? Can the assessment support the development of autonomous, self-directed learners?
When appropriate, assessment design can offer an opportunity to develop students’ digital and AI literacy. It is important, however, to consider whether incorporating AI might distract from the learning outcomes that the assessment intends to assess. It should be students who execute the key actions at the heart of the intended learning outcomes, thus demonstrating their competency in those areas (with the technology merely playing a support role).
Definitions of what constitutes AI literacy are in flux, but Long and Magerko (2020) broadly capture the idea as “a set of competencies that enables individuals to critically evaluate AI technologies; communicate and collaborate effectively with AI; and use AI as a tool online, at home, and in the workplace” (p. 2). Commonly cited competencies include writing effective prompts, assessing the correctness of facts referenced, having a general understanding of how AI works and evaluating for bias.
In what ways might the assessment prepare students for an AI-integrated future? If generative AI is integrated into the assessment, does it encourage students to reflect and be critical about their use?
Could any generative AI components overshadow or take away from the original goals of the assessment?
References
Biggs, J. B., Tang, C. S. (Eds.) (2011). Teaching for quality learning at university: What the student does (4th ed.). McGraw-Hill, Society for Research into Higher Education & Open University Press.
Duncan, T., & Buskirk-Cohen, A. A. (2011). Exploring Learner-Centered Assessment: A Cross-Disciplinary Approach. International Journal of Teaching and Learning in Higher Education, 23(2), 246–259.
Long, D., & Magerko, B. (2020). What is AI Literacy? Competencies and Design Considerations. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 598–598. https://doi.org/10.1145/3313831.3376727
Mordell, D., & Kehoe, J. (2023). Part 2: Redesigning Your Assessment. Paul R. MacPherson Institute for Leadership, Innovation and Excellence in Teaching. https://ecampusontario.pressbooks.pub/mcmasterteachgenerativeai/chapter/part-2-redesigning-your-assessment/.
Wiggins, G., (1990) “The Case for Authentic Assessment,” Practical Assessment, Research, & Evaluation, 2(1): 2. https://doi.org/10.7275/ffb1-mm19.
An important step in designing or redesigning an assessment is to explore what might be possible. Below is a list of alternative assessment ideas – as in, alternative to traditional assessments – to seed your imagination.
Even if none of them seem like a good fit for your current assessment design needs, we hope that a few pique your interest enough to keep them in mind for future assessments.
The following section showcases an open educational resource (OER), Beyond the Exam: An Alternative Online Assessment Toolkit. The toolkit was developed collaboratively between Brock University, College Boreal and McMaster University. The team was led by Joanne Kehoe and Samantha Duncan.
In keeping with the conditions of the Creative Commons Non-Commercial, Share-Alike license, we are releasing the resource with the same Creative Commons license.
A mind map is a visual representation of a subject or topic that allows you to creatively represent key information. A mind map is like a diagram with pictures, words, drawings and links or connections between different ideas. Mind maps let you think through the key areas of your theme or topic. Some people use mind mapping to take notes in class, to brainstorm new ideas and plan projects.
Read more on the eCampusOntario ePub.
A board game assignment, as the name implies, asks learners to design a boardgame that engages creatively with their disciplinary topic. It may help to explore an example of student work to envision the assignment.
The scavenger hunt assignment is an activity to promote and facilitate students moving beyond skimming towards more meaningful, engaged deep reading. It can be used for a full text or a series of readings. Students create a series of ten quiz questions and an answer key based on the content of reading material for a particular week. Students are responsible for 2 chapters/readings.
Students design a lesson on a topic related to the course disciplinary topic (either included in the course content or one of their own choosing – it is for the instructor to determine) by curating existing resources from the web. They will decide on a learning goal that they want their (imagined) audience to achieve and then, using a web-based curation tool or practice, create a curated collection from web-based resources that they select to support the goal of their lesson.
The press release assessment was created for a business course at College Boréal and can be used in any course that includes an outcome related to writing a press release for a company as part of marketing / administrative responsibilities and skill-building. The course example used had the following learning outcome: Write a press release using an objective writing style that is respectful of the Associated Press style and the inverted pyramid style of writing.
The minute paper takes – well, just about a minute – and while usually used at the end of class, it can be used at the end of any topic discussion. [It] is a formative strategy and participation in the activity is normally not assessed, but it could be considered as part of a participation grade that is supervised in class. Students write a paper or response for one-minute about what was discussed in class (refer to the expanded description of the minute paper in the “Read more” section below for examples of question prompts).
A multimodal project may also be called a digital media artefact. Multimodal refers to the use of two or more communication modes. In a multimodal project, the modes are typically digital in nature. This could involve the use of images, text, video, audio, webpages, presentation slides, animation, blogs, e-book, etc..
The multimodal project assessment reflects the principles of universal design for learning by giving choice and encouraging diversity around the modes of representation, as well as allowing students to explore the topic through a creative lens.
Creating an infographic – visual representations of information that can include numbers, text, images, or any combination of the three – enables students to develop skills in graphic design and data visualization. Effective infographics tell a story. Students also gain experience in using a different-than-usual mode to convey findings.
When students create infographics, they are using information, visual, and technology literacies.
The alternative group presentation is a combination of individual and collaborative work. Used in a class taught by McMaster University instructor Dr. Joanne Wilson, she integrated a twist on an otherwise conventional group project [in an advanced seminar style course].
Students were required to read one research article per week in preparation for a synchronous seminar style lecture led by a guest speaker. To build individual and class understanding of the research topic contained in the article, a group assignment was integrated, which contained three distinct components:
An annotated bibliography is a list of citations – or short, topic-relevant synopses – of sources (books, articles, websites, films, etc.) used to research a topic that includes a summary and evaluation of each source.
We realize the list above is daunting in length, so we will stop here. But, if you are interested, you can further investigate:
There is no shortage of innovation in teaching and learning, and we hope you might be inspired to add your own example.
If you decided to start your assessment design process by ideating, we encourage you to take a few moments to draft an outline of your new assessment idea and then return to the “Designing” section of the module to help develop your assessment in greater depth.
Otherwise, move on to the final part of the module – Evaluating Authentic Assessments.
Duncan, S., & Kehoe, J. (Eds.). (2022). Beyond the exam: An alternative online assessment toolkit. McMaster University. https://ecampusontario.pressbooks.pub/beyondtheexam/.
Part of the process in designing an alternative assessment is to plan a means of evaluating the assessment. Since authentic assessments resist the idea of one correct answer, we need a way of providing feedback to students about their learning that acknowledges a diversity of perspectives but at the same time does not add significantly to our grading workload.
You may also want to consider the holistic dimensions of the assessment, or how it exists within the larger context of your course. If you are rethinking your assessment design for compassionate or equity-based reasons, it follows that your broader grading scheme or approach might reflect similar concerns.
Flexible grading practices, such as:
can lessen the pressure or anxiety students experience in relation to your course assessments.
That said, flexible grading practices can also result in an increased workload (e.g. regrading) or impact the ability of you or your teaching assistants to give timely feedback (e.g. grace periods). We appreciate that there are numerous factors to weigh when deciding on a grading strategy, and not all practices are realistic for every instructor.
You may have chosen a new-to-you assessment format and are not sure how to approach grading the assessment, if you will be assigning a grade. Rubrics can help to break the daunting prospect of evaluating students’ work into set of manageable criteria.
Rubrics are often rendered as a grid or table, where the rows of the table describe the various criteria, and the columns of the table contain the levels of achievement and/or the points allocated. The cells of the table typically describe the characteristics of the various levels so that it is clear to students and those grading student work (e.g. teaching assistants) where the work falls on the grid.
If you are unfamiliar with rubrics, you may find an example helpful:
Some additional examples can also be found in York University’s “All About Rubrics” guide.
Types of Rubrics
All of the example rubrics are analytic rubrics, the most commonly used type of rubric. But it is not the only option, and you may find another type of rubric more suitable for your assessment design needs.
An analytic rubric has two dimensions: criteria and achievement / performance level. There are usually descriptions for each performance level in each criterion that clearly communicates expectations to students.
Analytic rubrics tend to be the most labour intensive to develop when writing descriptions to fill out the entire table. As such, they may be best suited to larger assessments or a set of repeated assessments that can reuse the same rubric. The labour can be worthwhile, however, when the rubric is used in a learning management system to automate the process of giving detailed feedback on the rubric criteria.
Note: we used generative AI (Claude) to draft realistic rubric criteria for a generic writing example. While there are many good examples of rubrics on the web, finding a suitable one can be a challenge; large language models (LLMs) are better suited to semantic queries than conventional search engines (e.g. “an analytic rubric for a writing assignment that emphasizes qualities of good academic writing which generative AI does not do well”). Further documentation regarding the prompt and response can be found under “References” on this page.
Learn more about how to use rubrics in D2L / Brightspace
A holistic rubric considers all of the criteria at once when assigning a level; it is like an analytic rubric where the criteria have been consolidated into one row of the table. The criteria or level description should clearly communicate the differences between levels.
As a result, a holistic rubric can take less time to develop than an analytic rubric. The trade-off is that students receive more generic feedback, and it can be more challenging to assign a level when student work is inconsistent across the various criteria.
While a holistic rubric “flattens” the number of criteria to one, a single-point rubric reduces the number of levels to two: either achieved or not achieved. It is like pass / fail grading on each criterion.
A single-point rubric can make it easier to decide where a student’s work falls in the rubric, but you may find yourself needing to compensate for the lack of gradation through written comments.
Note: it is possible to include levels of achievement in a single-point rubric; refer to the rubric guide created by Brock University’s Centre for Pedagogical Innovation.
To create a rubric, start by identifying the key competencies you want students to demonstrate through the assessment. Your learning outcomes and ideas about what the assessment is meant to measure will be a guide.
You may find it helpful to look for an existing rubric that you can adapt, or you can ask generative AI for suggestions. You can also refer to the guiding questions below:
Of course, rubric design is also shaped by disciplinary norms and the form of the assessment that you choose.
There is no optimum number of criteria to include but try to find a balance between adequately representing the characteristics that define your expectations for student work and burying the most salient characteristics within a large list. If you have more than 5 criteria, consider organizing them into categories of related criteria.
Note: Not every criterion has to have the same weight. When creating a rubric in a learning management system, you can usually have multiple groups of criteria with different maximum scores.
The rubric levels indicate to students the degrees of achievement. They are generally expressed in both quantitative (as points or scores) and qualitative (as level descriptors) terms.
If you are creating a holistic or analytic rubric, aim for 3 to 5 achievement or performance levels (the columns in the grid). The levels do not necessarily have to be evenly distributed – for example, a four-level rubric might distribute the score as 5 points / 4 points / 2.5 points / 1 point.
The level descriptors communicate information about the level of achievement. A few examples of descriptors are given below:
Some educators critique rubrics for giving an illusion of objectivity to a fundamentally subjective act. If you like the structure that rubrics provide but want to introduce another dimension of fairness to assessment, you can incorporate anonymous grading, where the assessor does not know the name of the student who created the work.
Some learning management systems have a feature that allows you to hide student names during assessment when creating an assignment submission folder.
Reflection is a contemplative act of purposefully analyzing experience in a deliberate manner. It is an important dimension of active learning but also acts a record of learning when documented.
Here are some helpful resources for designing and evaluating reflective activities.
Students who are accustomed to traditional assessments like multiple choice exams may need guidance on the types of questions to ask themselves when reflecting. You might provide structured prompts or exemplars to communicate your expectations. For more guidance around incorporating reflective practice into your teaching and sample prompts, please refer to the Reflective Teaching Practices module.
Model: Claude Haiku 4.5 (least intensive model chosen due to simplicity of the task)
Human-authored prompt:
“For a second-year university scholarly essay assignment, please suggest 4-5 criteria to be used in an analytic rubric with four performance levels. Students are not permitted to use generative AI in writing the assignment and the rubric criteria should reward student work done independently of generative AI, and qualities of good writing in general. E.g. critical thinking, specificity of examples, student voice, etc.”
Generative AI response:
“Here are 4-5 rubric criteria designed to assess authentic student scholarship while discouraging reliance on generative AI:
Rewards students for developing their own interpretations rather than restating conventional wisdom.
Rewards careful selection and integration of precise examples—a hallmark of genuine research and close reading.
Rewards authentic expression, consistent perspective, and honest engagement with complexity and uncertainty.
Rewards logical architecture that reflects the student’s conceptual understanding, not formulaic templates.
Rewards demonstrated learning from lectures, seminars, and assigned readings—showing the student has done the actual coursework.
This rubric prioritizes qualities that emerge from genuine engagement with ideas rather than surface features that AI systems excel at mimicking.”
Human in the loop:
I reviewed the output from Claude closely and judged it to be more than adequate, even using the most lightweight Claude model. Because the rubric descriptions were merely for the purposes of illustration – and yet, ideally still helpful to module learners – I only made a few minor edits to increase the tenor or precision of the language and omitted the fifth criterion.
You should now have much of the background information you need to write an outline for your new or redesigned assessment! If you are feeling motivated after finishing the module, you could even start drafting your assessment instructions.
Consider the following when planning your assessment instructions:
Adapted from the Transparent Assignment Instructions Template, Taylor Institute for Teaching and Learning (University of Calgary).
Remember to ask a colleague, teaching assistant or other willing reviewer for feedback on the clarity of your assessment instructions before debuting them with your students!
After you have introduced your new or redesigned assessment to your students, however, it is still a good idea to get feedback from them to help refine your design. If you are new to asking students for feedback or would like some formal guidance, please refer to the Collecting Feedback on your Teaching MacPherson Institute Learning Catalogue module. You may also wish to be transparent with your students about your intentions with the (re)design (e.g. sharing your rationale or motivations, what you hope the design will accomplish, etc.) – acknowledging that such a conversation requires vulnerability, and it can be more difficult to be vulnerable in large classes, or as a precariously employed and/or minoritized instructor.
In completing this module, you should now be able to:
Recall that an authentic assessment (Wiggins 1998):
We also explored a number of alternative assessment ideas to inspire your assessment design.
We hope that this module has been helpful as you work to design or redesigning an assessment.
To complete the module, please write a response to both of the following reflection questions:
Congratulations on completing a module in the MacPherson Institute Learning Catalogue!
We hope you found the experience meaningful and relevant to your teaching and learning practice. As part of our ongoing effort to improve and grow the Learning Catalogue, we invite you to take just a few minutes to complete a short reflection form.
We know your time is valuable, and we deeply appreciate your willingness to share your thoughts.