Journal of Research in Innovative Teaching - National University

and curricula. Most of the studies in the literature fall within the category of research that
Campbell and Stanley (1963) refer to as “quasi-experimental.” These studies lack the kinds of
controls, random assignment, and measurement precision that characterize true experiments.
Consequently, the validity of the inferences and conclusions drawn from this research is limited.
This is not to say that the research has no value; it just means that we must be very cautious
about what we can say with confidence about the results. Many of the threats to validity noted by
Campbell and Stanley (e.g., repeated testing, selection bias, differential loss of respondents) are
found in the studies review above, and it is beyond the scope of this paper to discuss them all.
However, there are some artifacts that are common to many of the studies and bear special
attention. In addition, certain measurement issues are relevant and will be addressed.
Different Populations
A frequent problem with the studies of accelerated education is that the individuals engaged in
the accelerated courses or programs come from different populations than the comparison group.
For example, Wlodkowski, Mauldin, and Gahn (2001) compared grades in accelerated programs
at Regis University with grades for similar programs at the University of Missouri at Kansas City
run under a semester system. Obviously, the population of students was quite different, and the
superior grades for students in the accelerated classes may have been due to differences in the
type of student rather than the pace of the class.
Selection Bias
Somewhat related to population differences is selection bias. Even within the same population,
different types of students, when given the choice, may gravitate to either accelerated classes or
traditional classes. Wlodkowski, Iturralde-Albert, and Mauldin (2000) compared four
undergraduate courses (economics, history, human relations, and labor relations) taught in their
accelerated program (5 weeks) with the same courses taught in their traditional program (16
weeks). Despite the fact that the courses remained the same, the differences in performance may
be due to differences in the type of student who chooses one type of instruction over another.
Likewise, when Jonas and Weimer (1999) reported that the business students in their accelerated
program scored higher on a standardized test than the business students in their traditional
program, the results could have been due to a selection bias rather than program differences.
Extraneous Variables
The primary goal of much of the research in this area is to allow causal inferences from the
results (e.g., accelerated classes lead directly to improved learning). To make an unambiguous
cause-and-effect connection between two variables (e.g., type of class causes different learning
outcomes), all or most of the other competing variables must be controlled within the study
design. Most of the studies on accelerated education do not adequately deal with these
“extraneous variables.” Some of these variables are an inherent part of the accelerated approach
(e.g., differences in teaching style), but many others are simply nuisance variables that compete
with the primary causal variables in the study (e.g., differences in time of day, instructors,
textbooks, type of testing, class size). Geltner and Logan (2001) is an example of a study that
involved many extraneous variables. These researchers demonstrated several advantages of 6-
week classes over 8-week and 16-week classes, but there were many differences between these
classes besides their length (e.g., time of day, academic discipline, student age, cumulative GPA
of students, faculty status). To eliminate these extraneous variables, researchers need to control
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