Running Head: ACADEMIC YOUTH DEVELOPMENT 1 Intelligence, Persistence, Sense of Belonging, and Problem-Solving Strategies:
Assessing Change in Student Beliefs in
the Academic Youth Development Program
Angela M. Bush-Richards, Cynthia L. Schneider, Lesley F. Leach, Kristin Harvey,
Carlton J. Fong, and Theodore Chao
The University of Texas at Austin
Author Note
This research was supported by grants from the Noyce Foundation and the Bill and
Melinda Gates Foundation.
Correspondence should be addressed to: Angela Bush-Richards, Charles A. Dana Center,
The University of Texas at Austin, 1616 Guadalupe Street, Suite 3.206, Austin, TX 78701,
abrichards@austin.utexas.edu.
2 ACADEMIC YOUTH DEVELOPMENT
Abstract
The Academic Youth Development (AYD) program was designed to facilitate students’
transitions from middle school to high school mathematics using a unique curricular integration
of mathematics content, youth development concepts, and research-based lessons on the nature
of learning itself. At the heart of the program is the idea of effective effort—that a person’s
intelligence can grow if she or he tries harder. We hypothesize that explicit instruction on a
malleable view of intelligence, persistence, sense of belonging, and problem-solving strategies
may shift AYD students’ beliefs about learning, their willingness to try different strategies to
solve a problem, and their ability to persist through difficult tasks. This study looked at Year 1
(2008) and Year 2 (2009) of the AYD program’s implementation during the summer and
examined the effect of participation in AYD on these student attitudes and beliefs: (a) theories of
intelligence, (b) persistence, (c) sense of belonging, and (d) problem-solving strategies. Results
from repeated measure analyses of variance revealed statistically significant shifts in student
beliefs from the beginning to the end of each year’s summer program implementation.
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3 Intelligence, Persistence, Sense of Belonging, and Problem-Solving Strategies: Assessing
Change in Student Beliefs in the Academic Youth Development Program
Research has shown that when today’s eighth-grade students make the transition into
high school, they confront a number of issues that can affect their academic performance (Neild,
Stoner-Eby, & Furstenberg, 2008). In addition to external factors, students’ internal theories
about the nature of intelligence—linked to their academic confidence, motivation, and
willingness to pursue various problem-solving strategies—can have a positive or negative effect
on high school success (Blackwell, Trzesniewski, & Dweck, 2007; Roderick, 2003; Schullo &
Alperson, 1998). The Academic Youth Development (AYD) program was designed to help
address two issues: the anxiety related to entering a new school environment and the thought
processes linked to academic achievement.
Academic Youth Development Program
AYD is a yearlong program with a 14-day summer experience for students transitioning
to high school and ninth-grade Algebra I. It was developed through a collaborative effort
between the Charles A. Dana Center and Agile Mind. The program began its pilot year in the
summer of 2007. Students attend a 14-day summer program prior to beginning their freshman
year. Each school’s summer AYD class—4 hours per day—is typically co-taught by two high
school Algebra I teachers with whom the AYD students periodically meet as a group throughout
the subsequent school year.
Students are selected based on several key factors: They should be on or near grade level,
have regular school attendance, and show potential to be a leader and role model for others in
their ninth-grade Algebra I class. Because one of the goals of the AYD summer program is to
develop a sense of community among teachers and students, the teachers for the AYD summer
program are the AYD students’ Algebra I teachers during the school year, enabling them to
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ACADEMIC YOUTH DEVELOPMENT
4 continue the relationships formed over the summer. Teachers who participate in AYD (either
self-selected or assigned at the suggestion of their administrators) attend a two-day professional
development experience in which they are taught the motivational concepts on which the
program is built, are given access to all the materials in order to become familiar with the AYD
curriculum, and observe strategies for enacting the curriculum.
The AYD program teaches mathematics content using interactive, applied problems that
enable students to experience mathematics concepts in action and to try on the psychological
knowledge and strategies in the learning of mathematics. The Algebra I course was chosen for
implementation of the AYD program because completion of the course has been considered a
gatekeeper for later academic achievement, often predicting whether students will go on to an
institution of higher education after high school (Moses & Cobb, 2001). Algebra I is required in
all states for high school graduation (Achieve, 2006).
In the summer of 2009 and spring of 2010, we observed AYD summer sessions and
conducted AYD student interviews to get a sense of how the program was progressing. Twentyone students in Summer 2009 and 33 students in Spring 2010 were interviewed using questions
that focused on AYD students’ experiences. During an interview, one student commented:
I’m so glad I did [AYD]—it helped me figure out stuff by myself, [and gave me new]
problem-solving skills. [AYD] changed my outlook on math a lot; it gives you lots of
confidence; it gives you different strategies you wouldn’t think of if you hadn’t gone.
Other students discussed how they have persisted and used problem-solving strategies. One
student said, “[Due to AYD], I don’t give up whenever I can’t find out the answers … I try
another way to do it.” Another student said, “I try harder if I’m confused about a problem and
spend more time trying to solve a problem.” Students said they felt more academically prepared
Charles A. Dana Center at the University of Texas at Austin, March 2011
ACADEMIC YOUTH DEVELOPMENT
5 for mathematics work. One student remarked: “[In AYD, I learned] new skills to figure out
different ways to solve problems.”
The AYD program also features explicit instruction on psychological and other learning
sciences concepts, including information about how the adolescent brain responds to different
learning strategies. The “youth development” curriculum includes activities, games, computer
animations, and interactive lessons intended to teach students about the effect of effort,
metacognition, productive attributions, and motivation. This curriculum explicitly addresses the
psychology and neuroscience behind the malleability of intelligence. For example, several
animations illustrate how the brain grows new connections as a product of learning. The program
seeks to facilitate a shift in student beliefs from a fixed view of intelligence—the idea that people
are inherently smart or not—toward a malleable view of intelligence (Dweck, 1999), through
which students understand that their capabilities change as they learn: they can get smarter with
effort. It is thought that this view of intelligence fosters academic motivation and persistence,
particularly in solving challenging mathematics problems.
Transition Into High School and Youth Development
Evidence for how transitions in educational settings affect students has been
documented. Wigfield, Eccles, Mac Iver, Reuman, and Midgley (1991) found that students
transitioning into junior high (seventh grade) had decreased perceptions of their ability in
mathematics over the transition period. These authors partially attributed changes in student
beliefs to new school and classroom environments. Neild, Stoner-Eby, and Furstenberg (2008)
showed that an effective intervention aiming to decrease dropout rates in one district worked best
when introduced during key educational transitions (e.g., ninth grade). The transition to high
school and Algebra I is an especially crucial bridge for many adolescents.
Charles A. Dana Center at the University of Texas at Austin, March 2011
ACADEMIC YOUTH DEVELOPMENT
6 The AYD program attempts to ease this transition to high school by providing peer and
teacher support and bolstering students’ beliefs about their intelligence and capabilities at a time
when their perceptions of themselves traditionally decline. In addition to theories of intelligence,
the curriculum explicitly addresses ideas central to academic achievement, including persistence,
sense of belonging, and problem–solving skills. In the face of challenging mathematics
problems, some students give up rather than exerting extra effort. Equipping students with the
appropriate strategies to persist through difficult tasks and providing a strong support system of
peers and teachers can be critical for those adolescent learners.
Malleability of Intelligence
Educating students about the malleable nature of intelligence is key to the AYD curriculum.
Negative student self-beliefs about their inherent intelligence and abilities can hinder
mathematics learning (National Research Council, 2001; Dweck & Leggett, 1988). To explain
this relationship, Dweck (1999) proposed a framework for theories of intelligence, in which she
described students’ views of intelligence as either fixed (i.e., entity theory) — something that is
unchangeable and characteristic — or malleable (i.e., incremental theory) — something that can
be changed. According to Dweck, those with a fixed view typically think expending effort to
learn indicates low intelligence. When students with a fixed view of intelligence encounter a
concept that they do not immediately and effortlessly understand, they typically believe that they
are incapable of mastering it and expend less effort to learn it. Conversely, those who believe
intelligence is malleable typically understand the importance of effort, and typically persist
longer through academic setbacks or challenges.
Resnick (2010) echoed Dweck’s focus on the importance of beliefs about the nature of
intelligence and noted that leading up to the 21st century, there have been important shifts in
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ACADEMIC YOUTH DEVELOPMENT
7 how aptitude and intelligence are viewed. While intelligence was once thought of as a fixed
"entity,” intelligence is now seen as learnable through "social processes that include participation
in certain forms of high-demand learning" (p. 186). Resnick identifies this type of instruction as
Thinking Curriculum—teaching the appropriate cognitive skills by embedding them in specific
subject matter. She argues that thinking abilities have to develop by reasoning about specific
information, and that teaching cognitive skills in the absence of specific content is rarely
effective. In light of this movement, the AYD program, which embeds cognitive skills training
and motivation in mathematical content, is a relevant intervention that explicitly addresses
students’ views of intelligence and self-beliefs together with algebraic problem solving.
Effect on achievement
Links have been established between students’ theories of intelligence and their
achievement. For example, in an experimental study by Aronson, Fried, and Good (2002),
students who were given information about the incremental (i.e., malleable) theory of
intelligence earned higher grades than those who did not receive the instruction. A second study
by Good, Aronson, and Inzlicht (2003) found similar results: Student scores on achievement tests
improved after exposure to an incremental theory intervention.
In a study of mathematics achievement, Blackwell et al. (2007) found that after an
intervention to change student beliefs about intelligence, participants endorsed a more
incremental theory of intelligence and maintained a more positive achievement trajectory
through junior high school mathematics. In contrast, the achievement trajectories of those who
did not receive the intervention and more strongly endorsed a fixed theory of intelligence
continued to decline over the course of their junior high career. Furthermore, Schullo & Alperson
(1998) found that interventions targeting student beliefs during the transition to Algebra I were
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8 successful in moving students toward understanding intelligence as malleable rather than fixed.
Research has shown that students who possess a more malleable view of intelligence often
demonstrate greater enjoyment of academics and stronger learning goals (Aronson, Fried, &
Good, 2002; Blackwell et al., 2007).
Persistence
Our definition of persistence is the willingness to continue to put forth effort when
challenged. even on small tasks. We believe persistence can be a driving force to help students
achieve their academic and personal goals. The idea of persistence through adversity is often
described as an outcome of high motivation, and students with a high level of confidence have
been found to persist longer through academic tasks (Bandura, 1997, Pajares, 1996b). Constructs
related to long-term persistence include grit (Duckworth, Peterson, Matthews, & Kelly, 2007)
and resilience (Masten, 2001). We are not looking at persistence over an extended period of time,
but rather over short time periods, such as a class period, when students are working on tasks or
problems they might otherwise give up on.
Sixty-two percent of Algebra I teachers rated working with unmotivated students as the
single most challenging aspect of their jobs (Hoffer, Venkataraman, Hedberg, & Shagle, 2007).
Stipek, Salmon, Givvin, Kazemi, Saxe, and MacGyvers (1998) connected Dweck’s theories of
intelligence to mathematical understanding by showing that higher levels of motivation in fourth
through sixth graders were associated with a heightened focus on learning, an increase in
positive feelings about mathematics, more mathematical self-confidence, and a greater level of
persistence when solving problems.
The AYD curriculum compares exerting effort toward academics with playing a sport
like basketball, which involves repeated practice and honing of specific skills and muscles. The
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9 lesson reminds students that very few people are successful when they play basketball for the
first time. The athletic ability gained through practice is shown to be analogous to the strategy
and skill development gained by the brain through persistent mental effort.
Problem-Solving Strategies
Problem solving, as defined by the AYD program, involves the ability to enact a strategy
and, if that strategy is not working, to pursue a more effective strategy. AYD seeks to impact this
ability by changing student views about the malleability of intelligence in conjunction with
explicitly teaching a variety of methods for solving mathematics problems. As students are
taught that there are multiple ways to reach correct solutions, they broaden their considerations
of potential strategies. As Zimmerman (2002) describes in his phases of self-regulation, when
students enter the forethought phase of learning, they make strategic plans about how to attempt
the task at hand. Students who recognize their ability to utilize different methods are more likely
to explore more options and thus be more successful in their attempts to work out a problem. If
students are unable to recognize the variety of available methods for working out a solution, they
may give up when their initial attempts to solve a problem fail.
Problem-solving skills are often developed through the process of monitoring and
evaluating one’s thinking processes while learning. This level of metacognition is referred to as
“higher-order cognition about cognition” (Veenman, Hout-Wolters, & Afflerbach, 2006). When
students consciously consider their own thought processes, they reflect on their problem-solving
strategies and plan out how best to apply them. Self-regulated learning, a related domain to
metacognition, requires learners to monitor and evaluate their mental processes while working
(Zimmerman, 1990). When students are self-aware, they can better motivate themselves and
apply the proper behavioral skills in order to maximize the potential for a positive outcome. As
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10 students shift from an entity to an incremental belief about intelligence, they begin to believe that,
with reasonable effort, they can accomplish a task. This belief in the efficacy of effort leads
students to more metacognitive appraisals about the benefit of planning and organizing their
cognitive efforts (Ames, 1992). Thus a positive iterative cycle is learned to support problem
solving.
Sense of Belonging
Solomon, Watson, Battistich, Schaps, and Deluchi, (1996) and Solomon, Battistich, Kim,
and Watson (1997) define classroom community as “a social organization whose members know,
care about and support one another, have common goals, and a sense of shared purpose”
(Solomon, et al., 1996, pg. 720). Rather than simply describing general aspects of the classroom
atmosphere, the concept of classroom community emphasizes the meaningful and warm
interactions among students and their instructor as key to feeling part of something greater than
oneself (Bush, 2007; Bush, Woodruff, Svinicki, Achacoso, Tomberlin, & Kim, 2004).
The AYD program aims to support students and enhance their sense of belonging through
close peer and teacher interaction as they move from ninth grade to high school because this
transition has been shown to be a predictor of whether students will excel in high school (Neild,
Stoner-Eby, & Furstenberg, 2008; Roderick, 2003). In our interviews, several students
mentioned that AYD heightened their feelings of being supported by and connected to peers and
teachers. One student enthusiastically noted, “ [AYD] helps people, opens them up, shows
they’re not alone on anything they do, especially for high school.” Many students commented
that AYD strengthened their relationship with teachers:
It’s a lot of fun; you meet your teacher, be comfortable around school … not nervous
about asking teachers something … I know I can go to teachers for information and
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11 advice. Here it’s kind of like a real life thing—people actually solve these things [math
problems] and have to figure it out.
The classroom environment and culture are often overlooked when examining students’
motivational processes related to learning. Ryan and Deci (2000) argued that one of three
fundamental needs of a self-determined, motivated learner is a sense of relatedness, or authentic
connection with others. Due to external factors and internal perceptions, the social learning
environment can feel potentially threatening for some students (Inzlicht & Good, 2006).
Within Dweck’s framework of malleability of intelligence, when feelings of hostility or
lack of safety are coupled with a fixed nature of intelligence, students can feel that they do not
belong. They perceive themselves as outsiders and believe that their contributions do not matter.
These threatening environments undermine a student’s feeling of being a valued member in an
academic community (Inzlicht & Good, 2006).
On the other hand, environments that foster beliefs of competence through effort can
create a secure sense of belonging; one’s interest, commitment, and progress matter more than
one’s perceived ability (Inzlicht & Good, 2006). Thus, creating a safe community in which peers
and teachers are viewed as allies is essential for greater engagement and positive self-belief. The
AYD curriculum intentionally attempts to foster a sense of belonging in the AYD classroom
community, which then transfers to their Algebra I classroom via their AYD teacher and summer
classmates who are also in their Algebra I class.
Purpose
The purpose of the current study was to examine the effect of the AYD program on
students’ changing beliefs concerning malleability of intelligence and attitudes toward
persistence, problem-solving strategies, and sense of belonging. It is our hypothesis that students
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12 ACADEMIC YOUTH DEVELOPMENT
will have more positive attitudes and beliefs as a result of participating in the AYD summer
program.
Method
Participants
All students who participated in the AYD program in 2008 or 2009 were recruited to
participate in the research as well. A total of 554 students consented to participate in the research
in Year 1 (2008) and 284 in Year 2 (2009). The subject pool was geographically diverse, hailing
from 33 urban, suburban, and rural school districts across the United States. The subject pools
were ethnically diverse as well. The Year 1 participant group comprised 35% White, 24%
Hispanic/Latino/Chicano/Mexican American, 23% Black/African-American, 13% Asian/Pacific
Islander, 1% Native American/Alaskan Native, and 4% multi-ethnic students. The Year 2 group
comprised 20% White, 32% Hispanic/Latino/Chicano/Mexican American, 32% Black/AfricanAmerican, 7% Asian/Pacific Islander, and 9% multi-ethnic students. These ethnic and gender
categorizations were self-selected by participating students. Approximately 60% of the Year 1
participants, and 53% of the Year 2 participants were female.
In Year 1, 80% of the students reported plans to enter ninth grade in the academic year
following the summer implementation; however, there were instances of seventh (4%), eighth
(15%), and tenth grade (1%) matriculation due to local preference for program implementation.
For Year 1, 75% of the participants reported intent to enroll in Algebra I for the academic year
following summer implementation. The remaining 25% of participants reported plans to enroll in
Pre-Algebra, Geometry, and Integrated Math courses. In Year 2, 61% of the students reported
plans to enter ninth grade during the academic year, 3% in seventh grade, 34% in eighth grade,
and 2% in tenth grade. Of Year 2 participants, 92% reported plans to enroll in Algebra I during
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13 ACADEMIC YOUTH DEVELOPMENT
the academic year. The remaining 8% reported plans to enroll in Pre-Algebra, Geometry, and
Algebra II courses.
Procedure
Data were collected to measure changes in students’ attitudes and beliefs in Years 1 and 2
using the AYD Student Belief Survey (see Appendix). The 30-item instrument asked students to
rate their level of agreement with statements concerning their beliefs on four constructs: (a)
Malleability of Intelligence, (b) Sense of Belonging, (c) Persistence, and (d) Problem-Solving
Strategies. Responses to each of these items were measured on a 4-point Likert-type scale
(1=Disagree, 2=Somewhat disagree, 3=Somewhat agree, 4=Agree). All subscales were created
based on a review of the literature by research staff for the purposes of the study (Paek, 2008;
Paek & Brown, 2009). Reliability estimates for each subscale’s scores are presented in Table 1.
The survey was administered to students on the first day of the AYD summer curriculum
(pre-survey); a post-survey was given directly after students finished the 14-day program. The
survey was administered to students online or via a printed copy.
Results
Quantitative Survey Results
Table 1 presents descriptive statistics for the pre- and post-test scores on the AYD
Student Survey for Years 1 and 2. To determine whether students’ beliefs and attitudes changed
from pre- to post-survey, we conducted separate multivariate repeated measures analyses of
variance (RM MANOVA) for each year, with the pre-post differences for each of the four
subscales serving as the dependent variables in the respective analyses. In Year 1, the overall
student belief change was statistically significant, λ=.82, F (4,550) = 30.87, p<.001,
partialη2=.18. Subsequent univariate analyses of the individual constructs showed statistically
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14 significant growth (p < .001) on each of four subscales (see Table 2). It should be noted that
running multiple statistical significance tests can inflate the family-wise error rate (Hinkle,
Wiersma, & Jurs, 2003). To correct for this potential problem, we used an alpha level of .01 for
each univariate test, thereby limiting our family-wise error rate to .04 (i.e., .01 x 4 tests). We
considered a potential error rate of .04 to be acceptable given the widespread use of .05 alpha
rate in studies within the social sciences.
In Year 2, the overall student belief change was again statistically significant, λ=.83, F
(4,280) = 14.31, p<.001, partial η2=.17, and pre-post differences for all but the Persistence
subscale were statistically significant. That is, student scores on the Malleability of Intelligence,
Sense of Belonging, and Problem-Solving Strategies subscales were statistically significant
different from the beginning to end of AYD summer program in Year 1 and Year 2.
The partial eta-squared effect size provides a descriptive measure of the strength of
association between an independent variable and a dependent variable(s) with the influence of
other variables partialled out. In a within-subjects design with no between-subjects factor, partial
eta-squared isolates the strength of the change over time by removing the influence of the
variation attributable to individual participants. In the present analysis, the multivariate partial
eta-squared (Green and Salkind, 2003) represents the strength of the pre-post change of the
multivariate synthetic combination of the attitudes and beliefs constructs. The eta-squared results
indicate that, taken together, the subscale pre- to post-test changes were able to account for 18%
of the total score variance in Year 1 and 17 % in Year 2.
To determine which of the individual subscales scores were statistically significantly
different from pre- to post-survey, univariate repeated measure analyses of variance were
conducted for each of the individual subscales. Table 2 presents the univariate results. All pre- to
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post-survey subscale differences were statistically significant, p < .01, except for the Persistence
subscale in 2009 (p = .03). The greatest effect was seen on changes in Malleability of
Intelligence (Year 1 partial η2=.14, Year 2 partial η2=.12). Effects on this subscale were at least
twice that of effects for the other three constructs (each were equal to or less than .06).
Growth on the Sense of Belonging, Persistence, and Problem-Solving Strategies
subscales was less than on the Malleability of Intelligence construct, but growth on almost all
subscales is still worth noting. The Sense of Belonging subscale saw gains from pre- to postsurvey in both Year 1 (partial η2=.06) and Year 2 (partial η2=.05). The Problem-Solving
Strategies subscale saw smaller gains from pre- to post-survey than the Sense of Belonging
subscale (Year 1- partial η2=.04, Year 2 - partial η2=.03). Pre- to post-survey gains on the
Persistence subscale were even smaller (Year 1 - partial η2=.04, Year 2 - partial η2=.02).
Discussion
Research has shown that many students have difficulty not because of their inability to do
the academic work, but because they do not believe they are capable of performing successfully
(Pajares, Schunk, & Aronson, 2002). Designed to address this problem of negative student
beliefs, the AYD program facilitates change in students’ attitudes and beliefs of malleability of
intelligence, persistence, problem-solving strategies, and sense of belonging. The results of the
two-year study indicate that students’ attitudes and beliefs toward the youth development
components significantly increased over the course of the AYD summer bridge class (except for
the Persistence subscale in Year 2). These changes occurred in students’ beliefs about
malleability of intelligence, their attitudes toward belongingness, their beliefs about persistence,
and their beliefs about problem-solving strategies. Interestingly, the greatest pre-post difference
was detected in malleability of intelligence: Student beliefs shifted towards viewing intelligence
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16 as more malleable than fixed. This finding was also supported by interviews with AYD students
that highlighted their understanding of the importance of "working harder to get smarter"—the
idea that effort is needed to increase intelligence.
Limitations of the Study
Limitations of the study include low response rates for student consent forms. Additional
limitations include low construct reliability on our measures. To strengthen measurement of our
AYD constructs, we have changed our measures and included additional research-based
subscales for 2010-2011.
Additionally, from observations and interviews conducted over the AYD program, we
learned fidelity of implementation and data consistency were issues of concern. First, from our
site observations and interviews, we found that not all teachers were conducting the AYD
program in the same way, meaning that many schools probably implemented the program with
some differences. Despite the variation in fidelity of implementation, it appears that the
magnitude of changes in students’ beliefs was large enough to overcome the variability in
program fidelity. Results may have been even stronger had the program been consistently
implemented with greater fidelity.
We have not been able to capture data on the impact of this program on students’
transition to high school. Conducting a third time point survey has proven to be problematic with
respect to response rates, so future plans include creating closer ties to the teachers in the
program as well as more clear commitments from administrators to help in data collection.
As we look towards the next phase of research on AYD, we see areas of growth for our
research design. We are currently working with another research institution to construct a
measuring of fidelity of implementation with a research-based tool to inform our program
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17 ACADEMIC YOUTH DEVELOPMENT
implementation goals. As of this writing, we are working on ways to identify practices at specific
school districts that could inform significant student change, and correlating teacher belief
change with that of their students. So, while the research analysis yielded exciting results about
the belief changes that students made in the summer program, we would like this to eventually
move towards a predictive model of student achievement outcomes. Future research will include
an algebra content assessment to better meet these goals. We will also collect both survey and
assessment data from a matched sample of non-AYD students to look at differences in those who
did and did not attend AYD.
Conclusion
The overall results support the positive impact of the AYD program. Knowing that it is
possible to impact students’ theories of intelligence has strong implications for merging current
research on student beliefs with mathematics instructional practice—drawing a roadmap for
educational initiatives that develop positive beliefs towards mathematics learning. We hope that
this helps the mathematics education research community understand the crucial importance of
building student motivation and sense of belonging in the classroom in conjunction with
algebraic thinking during the transition into high school.
Research on student motivation is central to understanding why some students struggle
and some thrive (e.g., Pintrich, 2003). In particular, student self-beliefs and motivation are a
significant predictor of mathematics achievement (e.g. Pajares, 1996a). The need for large-scale
research on youth development and motivation in mathematics is clear, and the results of this
study provide initial evidence for changing student beliefs about intelligence in a mathematics
context. So, while the research analysis yielded exciting results about the belief changes that
Charles A. Dana Center at the University of Texas at Austin, March 2011
ACADEMIC YOUTH DEVELOPMENT
18 students made through the summer bridge program, we need to move towards a predictive model
of student achievement and youth development outcomes.
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19 ACADEMIC YOUTH DEVELOPMENT
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Charles A. Dana Center at the University of Texas at Austin, March 2011
23 24 ACADEMIC YOUTH DEVELOPMENT
Appendix
AYD Student Belief Survey
Theories of Intelligence
Students can learn new things, but that does not change their basic math intelligence.
If a student has to work really hard at math, she or he probably isn’t that good at it.
It is easy to tell how smart a student is in math by how quickly things come to him or her.
Mathematics intelligence is based more on ability than effort.
Persistence
When I get frustrated with a math problem, I give up.
When math is difficult, I usually only study the easy parts.
When I find homework boring, I still finish the assignment.
When I can’t solve a math problem with one strategy, I will try another way to solve the problem.
Problem-Solving Strategies
Knowing different solution strategies makes me better able to solve a variety of math problems.
When I solve a math problem, I ask myself what information is most important.
When I solve a math problem, I look for information that supports my solution.
When I solve a math problem, I eliminate unnecessary information.
Sense of Belonging
I work with other students as part of my regular math class.
I feel that other students in my math class support me learning about math.
I feel that my peers support me doing well in school.
I believe my math teacher wants to help me learn.
Charles A. Dana Center at the University of Texas at Austin, March 2011
25 ACADEMIC YOUTH DEVELOPMENT
Table 1
Descriptive Statistics of the Attitudes and Beliefs Scores on the AYD Student
Survey in Year 1(N = 554) and Year 2 (N = 284)
Pre
Post
Subscale
Year
M
SD
aa
M
SD
a
Malleability of
Intelligence
2008
2.83
.64
.47
3.11
.70
.61
2009
2.85
.64
.46
3.09
.64
.46
Sense of
Belonging
2008
3.23
.62
.70
3.38
.57
.70
2009
3.27
.56
.64
3.40
.52
.64
2008
3.10
.65
.63
3.22
.65
.68
2009
3.28
.61
.61
3.35
.62
.69
2008
3.36
.59
.68
3.48
.59
.77
2009
3.42
.51
.58
3.53
.60
.78
Persistence
ProblemSolving
Strategies
a
Cronbach’s alpha (a) provides an estimate of reliability (i.e., internal
consistency) for scores on each administration of the survey.
Charles A. Dana Center at the University of Texas at Austin, March 2011
26 ACADEMIC YOUTH DEVELOPMENT
Table 2
Univariate Repeated Measure Analysis of Variance Results for the AYD Survey Subscale Scores in Year 1 (N = 554)
and Year 2 (N =284)
Subscale
Malleability of
Intelligence
Year
2008
2009
Sense of Belonging
2008
2009
Persistence
2008
2009
Problem-Solving
Strategies
2008
Source
Individuals
Within-Subjects 2
Error
SS
362.77
21.54
133.58
Individuals
Within-Subjects
Error
df
p
Partial η2
MS
F
553
1
553
21.54
.24
89.17
<.001
.14
167.88
8.38
62.15
281
1
283
8.38
.22
37.89
<.001 .
.12
Individuals
Within-Subjects
Error
302.28
5.92
89.56
553
1
553
5.92
.16
36.55
<.001
.06
Individuals
Within-Subjects
Error
119.65
2.30
45.52
281
1
283
2.30
.16
14.19
<.001
.05
Individuals
Within-Subjects
Error
379.82
3.96
91.01
553
1
553
3.96
.17
24.07
<.001 .
.04
Individuals
Within-Subjects
Error
172.27
.75
41.63
281
1
283
.75
.15
5.03
.026
.02
Individuals
Within-Subjects
Error
294.45
3.99
93.32
553
1
553
3.99
.17
23.65 < <.001
.04
2009
Individuals
120.05
281
Within-Subjects
1.70
1
1.70
9.07
.003
Error
52.80
283
.19
Note. Partial eta- squared (η2) provides a measure of relative effect size for each of the pre- and post-test
differences.
Charles A. Dana Center at the University of Texas at Austin, March 2011
.03