effectively to measure biology student motivation and its related
metrics. These data also suggest that it may be possible to compare
other existing IMI and MSLQ data. However, caution should be
taken when comparing results between different IMI and MSLQ
studies, as each has its own unique student cohort and each instrument has its own history, uses, and theoretical underpinnings
(Pintrich et al., 1991; Ryan, 1994; Duncan & McKeachie, 2005).
Previous studies have shown that many of the motivation subscales
measured here can be predictive of student performance. For example, other MSLQ studies on biology student motivation have found
that intrinsic goal orientation (Pintrich et al., 1993; Lin et al., 2001),
task value (Pintrich et al., 1993; Johnson, 2013), and test anxiety
(Pintrich et al., 1993; Partin et al., 2011; Johnson, 2013) were predictive of final course grades. By contrast, a meta-analysis on MSLQ studies found that MSLQ subscales only had a weak to moderate
relationship to academic performance (Crede & Phillips, 2011). In
the present study, the OLS analysis indicated that student pre-survey scores on value/usefulness (IMI), pressure/tension (IMI),
and test anxiety (MSLQ) subscales were the most predictive of student course performance. These findings contrast with those of
Pintrich et al.’s (1993) MSLQ study, which showed that intrinsic
goal orientation and task value were correlated with students’ final
grades. However, these findings agree with MSLQ studies indicating that task value (Pintrich et al., 1993; Johnson, 2013) and test
anxiety are predictive of student performance (Partin et al., 2011).
One of the more curious results of the present study was the
finding that the more a student’s value (IMI) score declined, the better they did in class. This is counterintuitive because one might
expect students’ value scores to be correlated with their performance. One explanation is that some students might enter the class
with unrealistically high value scores; if students start with unrealistically high scores, they may experience a large score decline while
still leaving the class with a high value score. An alternative explanation is that some students may perform well, or poorly, regardless of
how much they value a given topic. For example, some pre-med students might realize that they do not value basic biology, but they still
strive to perform well in order to be accepted into medical school.
Limitations & Future Directions
While this study yields new insights about biology student motiva-
tion, it is not without its limitations. One limitation is that individual
survey items were altered slightly from the originals to focus students
on the molecular and cell biology portion of the course, and to allow
these instruments to be easily administered in a pre/post-survey for-
mat. Although researchers are allowed and sometimes encouraged to
make minor alterations to IMI and MSLQ subscales (Ryan, 1994;
Duncan & McKeachie, 2005; Muis et al., 2007; Choi et al., 2010),
it is possible that these changes altered the validity of the subscales
used in the present study. Additionally, while the pre/post-survey
format allowed student motivation to be measured at the beginning
and end of the semester, it remains unknown how student motiva-
tion fluctuated during the semester. It is also unclear which aspects
of the course were most closely associated with changes in student
motivation. For example, it may be enlightening to measure motiva-
tion before and after project deadlines or exams. This could be
addressed in future studies by examining motivation several times
during the semester. While my results show that biology student
motivation decreased overall during the semester, it is unknown
whether students experienced similar motivation declines in their
other courses. Was the observed motivation decline course-
specific or more general? The former could suggest shortcomings
within the given course, while the latter could suggest problems
with course sequencing, credit load, or end-of-semester stress.
Future studies could determine how students’ motivation in one
class is related to their motivation in other courses they are taking.
A final limitation is that the anonymous nature of this study made
it impossible to track individual students after the study period
ended. Consequently, it is unknown whether the observed moti-
vation declines influenced student retention or persistence within
the college or major.
My results indicate that biology student motivation changed during
the semester. Biology instructors or researchers wishing to measure
biology student motivation should do so at least twice per semester
to show how a given course affects students’ baseline motivation.
Adding additional timepoints could also be useful for determining
which aspects of a given course have the greatest positive or negative impacts on student motivation.
The fact that value/usefulness (IMI), pressure/tension (IMI), and
text anxiety (MSLQ) pre-survey scores were predictive of student
performance is exciting because it suggests that targeted interventions could be designed on the basis of pre-survey data to improve
motivation in different student cohorts. Some simple interventions
have already been developed and used successfully in a variety of
disciplines (Yeager & Walton, 2011). Similar interventions could
enable biology instructors to build on initial student enthusiasm to
reduce or even reverse its observed decline over the course of the
Overall, my results indicate that the IMI and MSLQ subscales
provide similar, though not equivalent, measures of student motivation and related metrics. These early results are encouraging as they
suggest that valuable comparisons could potentially be made
between the rich data sets found in the IMI and MSLQ literature.
However, additional studies are needed using different classes,
cohorts, and institutions to determine typical results for different
classes, disciplines, and student populations, and to determine
which IMI and MSLQ subscales exhibit the most overlap. Such comparisons are important for answering the ultimate question about
which motivation instruments and theories do the best job of capturing and explaining motivation when given a particular set of students, research questions, and circumstances.
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