How can I develop homework and quizzes to learn about student thinking?
These are quick tips from the Faculty Teaching Institute for developing homework and quizzes to learn about student thinking. Homework and quizzes are useful tools for students to practice new concepts and skills and get feedback. In-class formative assessments (Classroom Assessment Techniques, or CATs) give on-the-spot feedback to students and teachers. See the Universe of Formative Assessment Techniques for more.
General formative assessment
Design assessments around your student learning outcomes (SLOs) so that you’re assessing what you value, including concepts, problem-solving, higher-order thinking, etc. Make sure that assessments will help you and your students gain insight into your students’ level of understanding in areas you care about.
Use regular formative assessment, such as weekly quizzes, one-minute papers every class and/or other frequent in-class and out-of-class formative assessments to assess students’ learning along the way. This also gives students practice for (possibly high-stakes) summative assessment. Grade these for participation only.
Use a variety of assessment types and questions to assess a variety of outcomes and give opportunities for every student to shine. Assessments don’t have to be tests. See the “universe of formative assessments” and “universe of summative assessments”’ for ideas.
Teach students to self-assess their own work, and give them opportunities to do so, to help them develop their metacognition skills. For example, ask students to reflect on where they got stuck on a problem or exam, and how they might proceed in thinking about the problem this time.
Homework
Make the purpose and goals of homework explicit, possibly with TILT. The TILT framework (https://tilthighered.com/tiltexamplesandresources) helps you be more transparent and explicit.
Include typical test questions on homework sets, and consider labeling them as such.
Have students generate test questions as a homework assignment, and use some on the test. This is a very effective study strategy for students, as well as empowering.
Give actionable feedback. Focus on feedback that tells them what to do (not just whether it is correct). Don’t just tell them to be more strategic in problem-solving; tell them exactly how.
Use semi-automated feedback to reduce your feedback load. One way is with “response categories”; pre-written feedback statements are applied to student work by copy-pasting, selecting from a list in an online system, or using numeric codes to identify the category to students. Many online systems allow the option to add standard sentences to grade statements.
Use a variety of question types and assignments such as problem-solving, conceptual questions, sketching, essays, discussion board posts, reflective journaling, summarizing reading, etc., to get at all your SLOs. PhET and other simulations are also great starting points.
Additional practices:
- Include reasoning in problem-solving sets; ask students to explain their choice of a solution method.
- Give examples of success criteria such as multiple examples of good problem solutions or a discussion of the strengths and weaknesses of work of different quality.
- Have students start a problem on homework that you then finish in the lecture. The challenge they encounter will set them up well for learning from the expert solution method.
- Make students identify their own errors rather than pointing them out for them. For example, “Five of these are wrong; find them and fix them.” “There are 3 mistakes in this solution, find them” and allow them to revise and resubmit. Peer review is another strategy. This helps students learn from mistakes, especially in larger classes where individual feedback may be impractical.
- Reduce hand-grading. See “grading practices” for tips on grading.
This Expert Recommendation is based in part on K. Hogan & V. Sathy, Inclusive Teaching: Strategies for promoting equity in the classroom (West Virginia University Press, 2022) and D. Wiliam, Embedded Formative Assessment (Solution Tree Press, 2018).
This material is based upon work supported by the National Science Foundation under grants DUE-2141678, 2141745, 2141769, 2141795, and 2142045. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
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