Multiple-choice questions: they just might be (with apologies to chemists) the "universal solvent" of assessments for their ubiquitous appearance in tests across a variety of disciplines. Despite their common use, multiple-choice questions (MCQ) are often maligned. Criticisms, for student learning, include that: MCQs test recognition rather than recall (Little, Bjork, Bjork & Angello, 2012), poorly written MCQs can frustrate students’ accurate interpretation of a question (Burton, Sudweeks, Merrill & Wood, 1991) and tests students’ ability to memorize material rather than assessing higher-order thinking (DiBattista, 2008).
There are certain contexts where multiple-choice tests are not suitable for students to demonstrate the achievement of learning outcomes (e.g. outcomes where students need to document their process, organize thoughts, perform a task, or provide examples to demonstrate their learning). However, in other instructional contexts, such as large classes, the MCQ test is often seen as the most pragmatic choice due to the logistical limitations of other test types. The goal, then, is to develop the best multiple choice test possible for these situations. But how can MCQs and, in turn, multiple-choice tests, be constructed in such a way to addresses the often-cited limitations of the assessment?
Writing “better” multiple-choice questions
There certainly are benefits (beyond the simple question of logistics) for selecting MCQs to assess student learning. As DiBattisa (2008, p. 119) describes, for tests of a comparative length, “well-chosen multiple-choice questions can provide a broader coverage of course content than [short-answer or essay-type] questions”. An additional benefit is the (generally) higher statistical reliability of multiple-choice questions when compared to short-answer or essay-type questions. It is worth mentioning that, in this context, higher reliability means that if the same student wrote two tests designed to measure their understanding of the same material, their scores would be more comparable.
So, what guidelines can instructors follow to emphasize the benefits of MCQs for student learning, while addressing the limitations of MCQs?
The scholarly literature on writing MCQs is clear: writing well-written MCQs is a difficult and time-consuming process (Collins, 2006). Some literature suggests limiting yourself to creating no more than three to four questions in one day. One strategy instructors take to ensure they set aside enough time for authoring MCQs is writing one to two questions after each class.
When creating questions, it is also worth making note of the answer’s source. A direct reference to the source material will help save you time, in case you need to revise the question at a later date, or want to address student questions.
Each MCQ should be constructed to test a single course concept or outcome. If you follow the suggestion in guideline #1 of spreading the construction of MCQs over time, consider writing one or two MCQs that are linked directly to a lecture’s or seminar’s learning outcomes for that day.
Here, Anderson & Krathwol’s (2001) expanded taxonomy of learning can help to ensure that MCQs are aligned to the complexity of knowledge expected. This taxonomy, a revised version of Bloom’s taxonomy, includes six levels describing increasinging cognitive complexity, listed below from least-complex to most-complex:
In the case of MCQs, avoid writing a question which tests a student’s recall (Anderson & Krathwol’s remember category) if what you expect is that students in the course should be able to make judgements about the material (Anderson & Krathwol’s evaluate category). The key here is the alignment between the complexity of learning that students are expected to demonstrate, and the MCQ.
One approach to consider is evaluating multiple-choice questions using the Blooming Biology Tool (Crowe, 2008), or a disciplinary-appropriate adaptation of the tool, and ranking MCQs based on the complexity of learning being tested. You would want to see a tight alignment in complexity between the outcomes expected of learners in the course, and the MCQs used to assess that.
As summarized in the video above, the question stem needs to be a complete statement, linked to a single specific concept or problem, written so that only one of the provided alternatives is correct. Avoid repeating words in each of the alternatives; rather, place that language in the stem (Burton et al., 1991). Structure the stem so that you’re asking for a correct answer—negatives and double negatives are more difficult for the student to understand (Collins, 2006), which means you’re testing a students’ reading ability and not their understanding of the concept being tested.
Properly-constructed multiple-choice tests have been shown not only to assess student learning, but act as learning events in and of themselves (Little et al., 2012). A key condition of whether the multiple-choice test improves student performance in future tests is the plausibility of all alternatives—that is, the alternatives should be seen as possible answers.
Distractors are the alternatives that result in an incorrect answer. If your aim is to write MCQs that assess student learning, “implausible, trivial or nonsensical” (Collins, 2006, p. 548) distractors should not be used, even if they may be amusing for test-takers. Collins (2006, p. 548) goes on to note that “The best distractors are (a) statements that are accurate but do not fully meet the requirements of the problem and (b) [are] incorrect statements that seem right to the examinee. Each incorrect option should be plausible but clearly incorrect.” Distractors should all be created or linked to one another, and should fall into the same conceptual category as the answer.
A meta-analysis of assessment research (Rodriguez, 2005) has shown that in well-written MCQs, with equally plausible alternatives, three alternatives are enough to test student understanding: two distractors and one correct answer. Consider that if you construct more questions with just three alternatives, you can likely increase the number of questions in a multiple-choice test, thus improving the coverage of concepts being tested. Writing MCQs with five or more alternatives offers no real benefits to assessing student’s understanding.
Writing multiple choice questions to assess higher-order thinking
MCQs do not have to be limited to only assessing recall. Students’ higher-order thinking, such as application, analysis, and synthesis, can be tested using well-constructed MCQs.
DiBattista (2008) offers two strategies to “ramp up” recall-type questions for higher-order thinking:
- Write question stems that expose students to a situation that incorporates the concept being tested, but in a way that students would not have encountered before.
- Make MCQs interpretive exercises, where students are presented with novel material (e.g. a map, reading or data set) and have to apply the appropriate cognitive skills to a series of MCQs that relate to the material.
Assessment Series - this series for instructors occasionally offers workshops on writing multiple-choice questions to assess higher order thinking, and item analysis for multiple-choice questions.
If you would like to talk in more detail about writing MCQs, please contact one of our educational developers.
Anderson, L.W. & Krathwohl, D.R. (Eds.) (2001). A taxonomy for learning, teaching, and assessing: A revision of Bloom’s taxonomy of educational objectives. New York: Addison Wesley Longman.
Burton, S. J., Sudweeks, R. R., Merrill, P. F., & Wood, B. (1991). How to prepare better multiple-choice test items: Guidelines for university faculty. Provo, UT: Department of Instructional Science, Brigham Young University. Retrieved from https://www2.kumc.edu/comptraining/documents/WrittingbetterMCtestitems1991BrighamYoung.pdf
Collins, J. (2006). Writing multiple-choice questions for continuing medical education activities and self-assessment modules. Radiographics, 26(2), 543–551. doi:10.1148/rg.262055145
Crowe, A., Dirks, C., & Wenderoth, M. P. (2008). Biology in bloom: implementing Bloom's Taxonomy to enhance student learning in Biology. Cell Biology Education, 7(4), 368–381. doi:10.1187/cbe.08-05-0024
DiBattista, D. (2008). Making the most of multiple-choice questions: Getting beyond remembering. Collected Essays on Learning and Teaching, 1, 119–122.
Little, J. L., Bjork, E. L., Bjork, R. A., & Angello, G. (2012). Multiple-choice tests exonerated, at least of some charges. Psychological Science, 23(11), 1337–1344. doi:10.1177/0956797612443370
Rodriguez, M. C. (2005). Three options are optimal for multiple‐choice items: A meta‐analysis of 80 years of research. Educational Measurement: Issues and Practice, 24(2), 3–13. doi:10.1111/j.1745-3992.2005.00006.x