Journal of Research in Innovative Teaching - National University

them in such a way that the likelihood that they are causing the changes is significantly reduced
(e.g., hold them constant, remove them statistically).
Matching versus Random Assignment
In some instances, the research design attempts to deal with group differences by matching the
participants in the groups. In other words, the researcher attempts to reduce initial differences
between participants in the accelerated and nonaccelerated classes or programs by matching
them on one or more critical variables (e.g., age, ethnicity, intelligence). For example, Preziosi
(1995) matched the students in nonaccelerated instruction with students in accelerated instruction
on the bases of a knowledge pre-test (a test administered prior to the start of classes). The study
found that students in the accelerated classes performed better than the nonaccelerated students.
While this is a step in the right direction, there are many other group differences that could
account for Preziosi’s findings. In general, matching is not a substitute for using random
assignment to equate groups. The most effective way of ensuring that the groups are comparable
prior to the study is to randomly assign participants to the groups. Randomization, however, is
not always a realistic option in these kinds of real-world studies (Daniel, 2000). Although
matching is desirable, it should not be seen as accomplishing the same ends as random
assignment.
Time Series and Retrospective Designs
Some research examines a single group of learners before and after they have been exposed to an
accelerated treatment. Collins (2005) used this design to research changes is cognitive
development in two types of accelerated programs by comparing pre-test and post-test scores on
the Learning Environment Preference (LEP) instrument. One advantage to this “time series”
approach is that it eliminates the issue of group differences. Because there is only one group, the
researcher does not have to worry about equating a group that experiences the accelerated class
or program with another group that does not experience the accelerated condition. In a sense, the
time series design uses the single group as both the treatment group and the comparison group
(what is sometimes referred to as using the “subjects as their own control”). Although this does
control for potential group differences (because the treatment and comparison groups are exactly
the same), it does raise other design problems. We cannot know for sure whether any differences
in the before-treatment measures and the after-treatment measures were in fact due to the
treatment itself. As Campbell and Stanley (1963) point out, any number of other factors could be
operating. For example, there may be some historical artifact (i.e., a specific event that occurred
between the first and second measurement), a maturational change (i.e., some process within the
respondents that changes with time such as age or fatigue), or some kind of testing effect (e.g.,
the students are better at taking tests because of exposure to prior tests).
A variation on the time series approach is the “retrospective” study in which students are
asked to compare their current experiences with past experiences. For example, Messina (1996)
asked students to compare how much they learned after taking weekend courses with how much
they had learned when taking more traditional courses. As with the time-series design, the
retrospective study eliminates some group-based differences because subjects serve as their own
control. Unfortunately, the retrospective design has many of the same methodological problems
as the time-series design, and introduces some other methodological limitations such as memory
biases.
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