Assessment
The assessment cycle
How do you design effective assessment of student learning? The assessment cycle can help you with this. The cycle consists of seven stages that each have their own place within the assessment process. In each of the chapters on the right, you will find a brief introduction outlining key concerns, followed by frequently asked questions and answers.
Please keep in mind that your degree programme may have its own policies on assessment, impacting the options available to you. Make sure you are familiar with the rules and guidelines relating to assessment in your faculty or programme. For individual advice, please contact your faculty’s Teaching and Learning Centre.
Contact
Do you need advice about assessment? Would you like to use different assessment methods in your course, or would you like feedback on your assignment guidelines or exam questions? Please contact an assessment specialist through your faculty’s TLC. You can also always ask the central TLC’s assessment specialists for advice (tlc@uva.nl).
Other assessment resources
Click on one of the stages in the assessment cycle to read more:
| 1. Designing
How do I choose a form of assessment that accurately measures my learning outcomes? |
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How do I construct effective questions and assignments? |
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What should I keep in mind while administering an exam? |
| 4. Grading
How can make sure my grading is efficient and reliable? |
| 5. Analyzing How do I evaluate and improve assessment quality after the fact? |
| 6. Reporting
What should I keep in mind when returning grades and feedback? |
| 7. Evaluating
How do I improve my assessment next year? |
Below you can find articles from the TLC network about Assessment. Also view the other didactic themes.
Lane 2: Approaches to AI-integrated assessment
AI can be integrated into assessment in different ways depending on the role AI plays in the learning task.
Lane 2: Transparency and documentation
When AI tools are permitted or integrated into assessment, transparency becomes an important mechanism for maintaining valid, reliable, and fair assessment. Find out how to make the learning process visible with practical formats.
Lane 2: Designing AI-robust assignments
Lane 2 assessments are unsupervised; students may use generative AI at their discretion. Often the outcomes stay the same—what changes are the task design and criteria that govern permitted AI use and still allow students to evidence those outcomes.
Lane 2: Unsupervised assignments
Lane 1: Supervised assessment
Generative AI can support student learning, but in some assessments you must be sure that students can reason, communicate and perform tasks independently of AI. This page explains when AI should be excluded from assessment and where you can get support. A balanced assessment strategy usually combines several formats to assess different learning outcomes, while supporting accessibility and fairness.
GenAI and assessment in higher education
How can we design assessments that maintain integrity and foster learning in the GenAI era? Which learning outcomes must students demonstrate independently, and which involve responsible use of AI tools?
Constructing closed-ended questions to assess higher order thinking
A common criticism of MCQs is that they only measure simple recall, since the correct option is already provided. In this article, we will show that you can also construct MCQs that require higher-order thinking.
Inclusive assessment
Wil je zorgen dat jouw toetsing zo inclusief en toegankelijk mogelijk is? In dit artikel vind je belangrijke aandachtspunten, geordend aan de hand van de vier kwaliteitseisen aan toetsing.
Oral examinations: good practices
Oral exams used to be frequent. In higher education, this assessment method has become less popular because of concerns about efficiency and reliability.
Oral examinations: manual
Oral examinations: good practices
GenAI and Assessment Checklist
The GenAI assessment checklist helps you assess whether your course assessment is vulnerable to misuse of AI. It critically evaluates and (re)designs assessments with AI in mind. The checklist is not intended as an evaluation tool for exam boards, but as an aid for reflecting on and discussing assessment quality.