This review is on Jennifer Peterson
and Janet Hyde's research study on the expectancy-value theory.
This study investigates self-perceived math
ability, math utility value, and math interests from 5th grade through 10th
grade. They studied how these trends in
math motivation changed over time, across gender, how they are related to one
another, and if they had any correlation to high school math performance in
10th grade (Peterson, 2017, p. 442)
The research took place in Wisconsin
and included 223 participants. All
participants were given 5 minutes to complete 17 math problems in the 5th grade
to provide a base line for math performance.
They were also given three questionnaires to determine the level of
self-perceived math ability, utility value, and math interest across 5th grade,
7th grade, and 9th grade. When the
participants entered 10th grade, they took a state standardized test in math to
assess performance level. (Peterson,
2017, p. 443)
Results:
Gender Differences: The study found that self-perceived math
ability in boys in 5th, 7th, and 9th grades correlated with 10th grade math
performance, whereas self-perceived math ability in girls only correlated in
7th and 9th grade to 10th grade math performance. There was not a significant
difference between boys and girls in overall math performance (Peterson, 2017, p.
445).
Trends in math motivation overtime:
Self-perceived math ability declined over time overall. Participants with high self-perceived math
ability in the 5th grade showed a steeper decrease in self-perceived ability
than those who reported having a low self-perceived ability to begin with
(Peterson, 2017, p. 447). Although Math
utility value declined over the years as well, it did not directly predict 5th
grade math performance nor 10th grade math performance (Peterson, 2017, p 449)
Math interest in 5th grade overall declined, however student's 10th grade math
performance was correlated with math interest levels in 5th grade. When comparing this with performance in 5th
grade however, it was found that students with higher performance also showed
higher interest, and therefore it may be the performance, not the interest that
predicts 10th grade performance (Peterson, 2017, p. 449)
How the trends relate to one
another: All three trends in math motivation were positively associated with
one another, meaning that as one declined, so did the others. The other correlation is that those who had
higher self-perceived math ability, math interest, and utility value scores in
5th grade showed a steeper decline across time. The only trend that correlates with math
performance in 10th grade is self-perceived math ability. For the students who
actually showed an increase in self-perceived ability in 7th and 9th grades
compared to 5th grade demonstrated
greater math performance in 10th grade regardless of initial math performance
in 5th grade (Peterson, 2017, p. 451).
Conclusion: The researchers suggest that although all of
the three trends in math correlate with one another, the most efficient
predictor of future math performance is self-perceived math ability. They argue that further studies are needed
regarding interventions that target math ability could improve math performance
through hard work and dedication (Peterson, 2017, p.
452)
Implications for my study:
This study greatly reflects the
interest of my current research by focusing on math motivation trends across
important developmental years, as I am looking at math performance in middle
school. I did not find it surprising
that there were no significant gender differences, as I have not observed many
in my experience. I understand that
there are stereotypes concerning girls performance in math, and the only
observation I have ever made is that girls who struggle in math tend to resist
interventions more than boys. I believe
that this can definitely reflect the self-perceived math ability, however I
also would argue that the concept of a growth mindset is a more precise term to
focus on.
I did find it surprising that
although a high level in math interest correlated with future math performance,
it cannot be considered a predictor of math performance because the students
already had better performance in math (Peterson, 2017, p. 449). That implies that increasing math interest at
a Tier 2 level of intervention may not produce desired results and that it
should not be the focus of my study.
The fact that the only significant
predictor of future math performance regardless of initial math
performance is an increase in
self-perceived math ability (Peterson , 2017, p. 452), supports my mission to find methods
to improve math performance in Tier 2 level intervention classes in the 7th and
8th grades. This finding gives me a
strategy to base my intervention on. The
students in my classes are labeled as Tier 2 level students because of low
performance in math. Increasing their
self-perceived math ability could lead to improved math performance. Based on the findings in this study, it could
also increase their math interest and utility value indirectly, as there is a
positive correlation between the three trends that are described in this study
(Peterson 2017 p. 451)
I believe the next step for me is
to research how a Growth Mindset approach towards math ability can successfully
be implemented at a middle school level.
References:
Petersen,
J. L., & Hyde, J. S. (2017). Trajectories of self-perceived math ability,
utility value and interest across middle school as predictors of high school
math performance. Educational Psychology, 37(4), 438. doi:10.1080/01443410.2015.1076765
Great organization in your review. I felt that your summaries were factual and accurate, as if I had read parts of the article myself. I think it is really interesting that students were seemingly able to accurately perceive their own math ability, as indicated by their performance. I wonder what other factors reflected their perceptions. I am curious to find out what other information you can uncover about the power of perception. I agree with your assessment of not focusing on meth interest, since it is not a predictor of performance. If changing a student’s interest level in math will not transfer to improve on their ability to perform in math, it should not be your focus. I admire your passion for your subject and your devotion to improving your students' performance in math. I feel that by middle school that students end up on two opposite sides of the spectrum of loving or hating math. Although interest in math is not your focus, it may be interesting to measure it as an indirect factor.
ReplyDeleteI do suggest defining some of the vernacular used, that may not be common knowledge, such as math utility value. You may also want to give a background explanation of the expectancy-value theory at the beginning of your summary. Another suggestion is to have an active voice in some of your personal reflections. You have great ideas that should be mentioned straightforwardly, not in passive voice.