MindEdge Learning Blog

Pretesting has been shown to improve students' retention

By Heather Morton
Senior Editor, MindEdge Learning

When I first started working as a senior editor at MindEdge, I was baffled by the company's routine reliance on pretests. Why test students on material they have not yet studied? Their performance on a multiple-choice pretest, I thought, would lead either to discouragement ("I'm obviously not qualified to take this course") or to complacency ("Why bother completing the module?").

taking a pretest

Unsurprisingly, there turns out to be an evidence-based foundation for this pedagogical practice. Research shows that students who have completed a pretest retain 10 percent more information than students in a similarly situated control group who haven't. Furthermore, there is some evidence that forcing students to predict an outcome—essentially what a pretest does—helps them engage more with the material, leading to better discussion-board postings.

Pretesting falls into a larger category of predicting, the act of having students forecast future information: how a novel will end, the effects of an economic factor they have not yet studied, how a formula might be modified to take into account another influence on profit.

Experts have several theories about how and why predicting works:

Pretesting increases students' interest in the material that follows. Imagine you're watching a curling match for the first time. If you've been forced to predict a winner in the match, you will pay closer attention to what follows. You might wonder if the techniques you saw on the ice led to the win or loss of the team you chose. Similarly, when you see information on a topic you were tested on in the pretest, you might look for information that explains why your answer was correct or not.

Pretesting helps students recognize what they should pay attention to. Novices in a field rarely have an intuitive sense of what information is important. In literature classes, for example, students may note that a character went out for a walk after dinner (unimportant) while failing to notice that other characters are addressing him as "sir" (important). A pretest primes students to focus on certain aspects of a topic. A pretest that asks about the social class of a character will direct students' attention to information that reveals class while they are reading the novel—including how the character is addressed by others.

Pretesting primes retrieval, aiding students' ability to connect new knowledge to old. This theory is a bit more technical. One of the most important ways we remember information is through its connection to other information. As a writing teacher, I see this most clearly with words that are only partially known. A student who has heard "benign" will connect it to "tumor" and know that a "benign tumor" is the best kind of tumor to have. She will know that long before she knows what the word "benign" means on its own. Our brains use a network of connections to store and retrieve information. "Tree" will be connected to "leaves," "tall," "plant," "wood," "forest," "deciduous" and a host of other information we have on the topic. It turns out that we learn new information more easily when we have connected it to an already-existing network. A pretest asks us to ransack our minds for information on an unknown topic. This activation of previous knowledge allows us more easily to connect and retrieve the new information we are about to learn.

Experts caution that in the studies showing the effectiveness of prediction, students were provided immediate feedback on their predictions. Our use of prediction, therefore, should follow that model: it's easier to remember the wrong guess you made on the pretest rather than the right answer you learned several days later. To ensure that you are harnessing the full power of prediction for your students, make sure the course provides feedback shortly after the prediction.

A pretest, of course, is not the only opportunity to mobilize the learning power of prediction. Here are some other ways a course can use the power of prediction to improve student retention:

  • In a finance course, a video might pause after a real-world problem is presented and ask students to predict which formula is most appropriate to solve it. Students choose the formula from a multiple-choice list. The video continues and reveals the formula the professor chose.

  • In a writing course, students might read the first draft of a paper and then write into a text box their prediction of the three most important issues the writer should fix in the next draft. What the instructor is looking for in the next draft is revealed and explained immediately after.

  • An art history course introduces the Baroque period by displaying side-by-side works of art depicting the same Biblical story from the Renaissance and Baroque periods. Students are asked to post to a discussion board about how the Baroque piece differently renders the Biblical story.

Because predicting can be incorporated into a variety of technological applications and applied to almost any field, it is another powerful and versatile tool to boost your students' learning in an online environment.


1 Lang, James M. Small Teaching: Everyday Lessons from the Science of Learning. San Francisco: Jossey-Bass, 2016, pp. 46-47.

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