Before you design any assessment tool, you need to define your learning outcomes clearly and explicitly. Learning outcomes are statements that describe what students should know, do, or value as a result of your course or program. They should be aligned with the level, content, and purpose of your course or program, and they should be measurable and observable. Learning outcomes provide the foundation for your assessment plan, as they help you determine what and how to assess your students' learning.
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This paragpraph is exactly what comes in my mind when thinking about assessments, knowing that assessment tools are designed to evaluate the knowledge and skills that students gained studying specific module, it cannot be determined before deciding what the learning outcomes are.
Once you have defined your learning outcomes, you need to choose appropriate assessment methods that match your learning outcomes and your instructional methods. Assessment methods are the ways you collect evidence of your students' learning, such as tests, assignments, projects, portfolios, presentations, or peer reviews. You should select assessment methods that are valid, meaning that they measure what they are supposed to measure, and that are reliable, meaning that they produce consistent and accurate results. You should also consider the feasibility, suitability, and diversity of your assessment methods, as well as the feedback and support you will provide to your students.
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The chronological placement of choosing assessment methods AFTER defining learning outcomes in this article is so appropriate, and critically important. However, I would argue that there is a step missing before choosing assessment methods: articulating what evidence of learning we need to see in order to know the student has successfully mastered the learning outcomes. By combining the learning outcomes with the desired evidence of learning, an even more informed decision regarding assessment methodology can be made. This combination becomes even more critical when considering off-the-shelf assessment instruments.
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Methods are also be informed by philosophical assumptions or paradigms of inquiry. Knowing your assumptions prior to deploying methods will ensure the validator of the assessment. If our methods operate with the assumption that there are multiple constructs of reality (constructivism), then we will use assessment methods that can attend to the multiple ways that students learn. From an equity or critical lens we will be sure that our assessments do not perpetuate dominant culture ideas of worth and value.
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In addition to choosing appropriate assessment methods, the contribution of each assessment towards the total module mark should be also appropriately distributed, this should be based on the learning outcomes evluated by each assessment and the nature of the module.
Another important practice for designing valid and reliable assessment tools is to design clear and transparent assessment criteria that communicate your expectations and standards to your students. Assessment criteria are the specific aspects or dimensions that you will use to judge your students' performance, such as knowledge, skills, attitudes, or behaviors. They should be aligned with your learning outcomes and your assessment methods, and they should be expressed in observable and measurable terms. You should also provide your students with rubrics, checklists, or exemplars that illustrate how you will apply your assessment criteria and how you will differentiate between different levels of performance.
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Clear and transparent assessment criteria are essential for designing valid and reliable assessment tools. Clearly defined criteria help students understand what is expected of them and take ownership of their learning. For example, when students receive a detailed rubric that outlines assessment criteria and different performance levels, their engagement and understanding improve. Transparent criteria also promote fairness and consistency of assessments, especially when multiple evaluators are involved. Involving students in the development of assessment criteria can foster shared responsibility and trust.
Finally, you should review and refine your assessment tools regularly to ensure that they are valid and reliable, as well as fair and meaningful. You should collect feedback from your students, colleagues, or external reviewers on the quality and effectiveness of your assessment tools, and use it to identify and address any gaps, errors, or biases. You should also analyze the results of your assessment tools to evaluate their validity and reliability, and to identify any areas for improvement or adjustment. By reviewing and refining your assessment tools, you can enhance your assessment practice and your students' learning experience.
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Student/learner feedback is incredibly helpful for effectively shaping assessment tools. I’ve found one key factor in getting actionable feedback is ensuring you present them with open-ended options and closed-ended questions. I also recommended refining your questions as you can. Asynchronous surveys are helpful for gathering large amounts of feedback, but I’ve found some of the most insightful feedback comes from synchronous conversations. Multiple factors make the latter more resource consuming but I recommend the human touch of conversation, when possible. This is because people usually only respond to surveys if they perceived their experience as incredibly bad or good. If you can, find a way to incentivize learners to give feedback!
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An important concept to understand in assessment is: instruments are not valid, but rather interpretations made based on the scores are valid (or not). First consider the interpretation (the claim) being made, and then ensure the scores support the claim. As an example, consider a scale: regardless of the type of scale, (kitchen, bathroom, etc.), all measure weight. I can theoretically use any scale to weigh anything. However...it is probably not appropriate to use a veterinary scale to weigh sugar needed to make a cake. The veterinary scale is unlikely to give me the correct amount of sugar to make a good cake. When choosing instruments, consider whether the resulting scores can support claims about learners based on those scores.
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