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?").
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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