Quantitative Research Methods by Cheryl Vierheilig

Quantitative Research Methods Matrix
Quantitative Research Methods (Experimental, Quasi-Experimental, Ex Post Facto, Descriptive
By: Cheryl Vierheilig
Primary Characteristics Current Peer-Reviewed Study
Experimental
Identifies cause and effect relationships; Researcher
attempts to control all influential factors except those
whose possible effects are the focus of investigation;
Clearly identifiable independent and dependent variable;
Internal validity is essential (Leedy, 2013). Researcher
manipulates the independent variable and examines its
effect on another, dependent variable. People or other
units of study are randomly assigned to groups. (Leedy,
2013). Tests the impact of a treatment or an intervention
on an outcome, controlling for all other factors that
might influence the outcome (Creswell, 2014).
Researchers randomly assign individuals to groups to
control. When one group receives a treatment and the
other does not, the experimenter can isolate whether it is
the treatment and not the other factors that influence the
outcome (Creswell, 2014).
The problem investigated:
The problem of the current study was to investigate the
relationship between a pre-workout warm-up and psychological
processes.
How the sample was selected:
The study surveyed seventy-six (n=76) participants from a small,
Midwestern college aged 18-25. Study primarily focused on the
participant's reported levels of enjoyment and motivation for those
who used warm-up prior to exercise versus those who did not.
Additionally, the researcher was interested in reported short and
long-term adherence rates of warm-up users, versus non-users.
(Thirty-three (n=33) male, forty-three (n=43) female). Participants
were members of introductory psychology and fitness management
classes on the researcher's campus and were between the ages of
18 and 25 (M= 19.21, SD=.93). The researcher's Institutional
Review Board approved the study.
How variables were defined and measured:
The researcher obtained permission from the class instructors and
scheduled class visits. Following the instructor dismissing
themselves from the class, the researcher informed the class of the
nature of the study and solicited participation. Additionally, the
researcher informed the participants that participation was
voluntary and would have no bearing on their grade in the class.
The results would also be confidential; the questionnaires recorded
no identifiable information. The researcher asked participants to
place completed surveys in a manila envelope located at the front
of the classroom. Finally, the researcher thanked the participants

for their participation prior to leaving the classroom.
How data was collected and analyzed:
The researcher collected data using a ten item pen-or-pencil
questionnaire. The first two questions asked for information
pertaining to how often the participant exercised (one day per
week) to (more than five days per week) and how long the
participant had been exercising at this rate (less than three months)
to (over one year). Following these items, the questionnaire asked
participants to report whether or not they used a pre-workout
routine (Yes) or (No). If answering yes to this question, the next
item asked participants to specify the type of pre-workout routine
(Warm-up) or (Stretch). The researcher formulated the option
"stretch" to mask the fact that researcher was interested in solely
warm-up use. The researcher omitted results from participants who
reported using only stretch or a combination of warm-up and
stretch. A debate exists in the literature over the use of five or
seven point ordinal Likert-type scales in the measurement of
exercise-related motivation and other affective ratings. As this
debate is currently not settled, the researcher opted to use five
point Likert-type scales to measure exercise-related motivation and
enjoyment. The questionnaire measured participant's average level
of motivation for exercise with options ranging from 1 (Not
motivated at all) to 5 (Very motivated); enjoyableness of an
average workout with a scale from 1 (Very Unenjoyable) to 5
(Very Enjoyable); how often participants completely finish
planned workouts with a (0%) to (100%) scale in 10% increments.
Participants rated their long-term adherence rates to their exercise
programs from 1 (Less than a week) to 5 (Six months or more).
Additionally, participants reported two final items regarding age
and gender. The researcher did not ask participants to report ethnic
differences in the study.
The key findings:
The study hypothesized that exercisers who reported using a
warm-up prior to exercise would report significantly higher levels

of exercise-related motivation, enjoyment, and greater short and
long-term adherence rates to exercise programs.
The results demonstrated significantly higher ratings for
motivation and enjoyment for those participants who reported
using a warm prior to exercise. Results for short and long-term
exercise adherence were higher for those using a pre-workout
warm-up, though not statistically significant.
Of the 76 participants, 51 responded "yes" to using a warm-up and
25 responded "no" to this item. Independent samples t-tests were
used to compare the mean scores of those who reported engaging
in a warm-up relative to those who did not. There was a
significantly greater difference for participants who indicated use
of a warm-up (M=4.3, SD=.74) and those who did not utilize a
warm-up (M=3.60, SD=.957); t(74) =2.315, p < .05, in rating their
average level of enjoyment for exercise. Additionally, there was a
significantly greater difference for those participants who indicated
use of a warm-up (M=4.6, SD=1.24) and those who did not utilize
a warm-up (M=3.92, SD=1.48); t(74) =3.593, p < .05, in rating
their level of motivation for completing their workout.
Results were not significant for those who indicated warm-up use
(M=8.52, SD=1.40) and those who did not (M = 7.67, SD=2.51);
t(30.07) =1.551, p>.05, for what percentage of the time
participants completed their workout. The results were not
significant for those who indicated use of a warm-up (M=3.73,
SD=1.23) and those who did not (M=3.16, SD= 1.31); t(74) =
1.838, p>.05, for how long participants adhere to workout routines.
The researcher excluded twelve (n=12) participants for reporting
only stretch use and additionally, five (n=5) participants who
selected both warm-up and stretch options.
The generalizability of the findings:

A larger scale replication is necessary to more powerfully
generalize these findings to the population, and to study the
possible effects of other types of pre-workout routines, such as
stretching. If follow-up research demonstrates a significant effect
for motivation, enjoyment, and adherence reports, this may
warrant experimental research examining the underlying
mechanisms affecting these results. Follow-up studies should
utilize a larger, more diverse sample of young adults to more
readily generalize these findings. Because a large percentage of
respondents were fitness management students, this group may
already have been more active than the other respondents, which
could have affected overall scores. Additionally, one of the
limitations of this study was that the research did not target
whether one type of pre-workout routine-warm-up, stretch, or a
combination of the two-produced significantly higher scores
relating to motivation, enjoyment, and adherence. Future studies
should examine these possible differences. Another limitation of
the current study was that the design only yielded correlations
between the variables and not a cause-and-effect relationship. If
larger scale follow-up research demonstrates a significant effect for
reported motivation, enjoyment, and adherence scores, this may
warrant experimental research examining the underlying
mechanisms affecting these results. After analyzing the data, there
is clear support for one of the major hypotheses. Participants
responding "yes" to warm-up use reported significantly higher
overall mean scores for both exercise-related motivation and
enjoyment than those who did not report using a warm-up.
However, participants reporting warm-up use did not have
significantly greater scores for whether or not participants finished
their workouts more often or for how long participants adhered to a
workout program.
References:
Ladwig, M. A. (2013). The psychological effects of a pre-workout
warm-up: An exploratory study. Journal of Multidisciplinary
Research, 5(3), 79-88. Retrieved from

http://search.proquest.com/docview/1492260371?accountid=35812
Quasi-experimental
Researcher does not control confounding variables so
cannot rule out alternative explanations for the results
obtained (Leedy 2013). Researchers must take whatever
variables and explanations they have not controlled into
consideration when they interpret their data (Leedy,
2013). These designs provide an alternate means for
examining causality in situations which are not
conducive to experimental control. The designs should
control as many threats to validity as possible in
situations where at least one of the three elements of true
experimental research is lacking (manipulation,
randomization, control group) (Simon, 2013).
Quasi-Experimental Design
The problem investigated consists of students’ anxiety over the
courses that are being taught in quantitative research methods
which play a central role in many undergraduate
programs in sociology. Many students perceive the subject as
inherently uninteresting and difficult. This study describes an
experiment designed to introduce aspects of quantitative reasoning
into a large substantively focused class in the social sciences. The
experiment assessed whether students can
learn quantitative reasoning skills in the context of a large
"nonmethods" class in sociology. The experiment measured
students' mastery of these skills by comparing their competence
at quantitative reasoning at the beginning and end of the class term.
The results revealed that students' abilities to interpret and
manipulate empirical data increased significantly. Further, the
increase occurred independent of students ' basic reasoning skills
as measured by baseline SAT verbal and math scores. The
implications of these findings for
teaching quantitative methods in sociology undergraduate curricula
are discussed. The central purpose of the experiment was to assess
whether it is possible for students, at the earliest stages of their
college careers, to learn basic quantitative and analytic skills in the
context of a "nonmethods" class in sociology.
Quantitative reasoning materials were developed in four steps.
First, baseline levels of competence for "average" undergraduate
students in entry-level sociology courses were established.
Students for basic math and analytic skills were tested. Second,

quantitative reasoning materials, in the form of exercises and
assignments in interpreting and analyzing empirical information,
based upon knowledge of these baseline competence levels and
upon the teaching skills of TAs who were scheduled to introduce
them were selected. Third, pretested and revised assignments in an
ongoing course prior to their introduction in the large enrollment
sociology class were completed.
Establishing Baseline Competence Levels
The first step in developing the experimental materials was
measuring average baseline levels of competence in
quantitative reasoning skills of entry-level undergraduates. This
required development and administration of a quantitative skills
test to a "typical" entry level sociology class. This test was adopted
from materials developed for mathematics classes, asking students
to answer questions about two-by-two and more complex tables
showing bivariate and multivariate statistical relationships.
Development of Materials
Once baseline competence levels were established, learning
modules were developed with three objectives in mind. First, they
should serve to assist in introducing the substantive material for
the class. Thus, each module was framed in terms of a single
question to be addressed in the class and included introductory
material describing the question and relevant theoretical material
about the question. Second, each exercise was developed with a
specific quantitative problem or set of problems related directly to
the central substantive question. Third, each module included
classroom illustrations and a specific homework assignment for the
students. The homework required the students to manipulate data
(e.g., computing percentages) and to interpret the data in a written
assignment of two to three pages in length.

As noted earlier, the structure of the class (Sociology of Deviance)
included lectures and quiz sections. Lectures met three times a
week and were delivered by the instructor. Quiz sections, where
students met twice a week in groups of 25, were taught by graduate
student TAs. The content of the course was divided into five
segments corresponding to major sociological perspectives on
deviant behavior and social control. Each part of the class was
comprised of a series of lectures delivered by the instructor, a
series of lessons delivered by the graduate student
TAs in discussion sections, and a series of readings from scholarly
articles and books. The course emphasized, as learning objectives,
the development of critical reasoning skills, the mastery of
knowledge about social phenomena and their explanation from the
perspective of sociological theories, and the effective application
of knowledge to solving problems of public policy.
Material on quantitative reasoning was introduced in a series of
stages in lectures and quiz sections. During the first week of the
term, the lecturer delivered presentations on quantitative reasoning
skills (e.g., table reading, computation of percentages,
interpretation of findings) and the logic of causal analysis in the
context of a sequence of examples of juvenile delinquency and its
correlates. Following this presentation, three subsequent
presentations or modules were delivered by TAs in quiz sections
over the course of the academic term. These modules were
deliberately spaced two to three weeks apart and were of
increasing difficulty. Each presentation was divided into three
components: short lectures by the TAs, classroom discussions of
the ideas and the materials, and written homework assignments.
Class discussions followed these lectures. The discussions centered
around in-class assignments in which students individually and
collectively worked to answer questions about a tabular
presentation of data on the classroom subject. Finally, students
were assigned short essays of two to three

pages in length, in which they were asked to interpret additional
data and apply their interpretations to the theoretical issues
addressed in quiz sections. These essays were graded and included
as part of the course grade.
An illustration of one of the modules, as integrated into the class
materials, may prove useful here. One of the major
objectives in the class was for students to learn how to apply
sociological theories of deviance and social control to explain
contemporary social problems. One segment of the class examined
macrolevel theories of conflict and social control. In addition to
several lectures, students examined writing and research on
Marxist or conflict theories of deviance to explain race and gender
differences in rates of imprisonment across regions of the country.
As part of the preparation for the assignment, students read the
published research of one of the present study's authors and
contrasted it with other work on the same general subject.
Then, in their quiz sections, students participated in an in-class
activity, applying the ideas they learned from lectures and class
readings to tabular data on patterns of imprisonment presented by
the TAs. Students discussed the analysis and interpreted the
data in terms of the substantive questions raised by the theories. At
the end of the discussion section, the students received a writing
assignment in which they analyzed and interpreted another set of
tabular data, similar to the data analyzed in class. The assignment
was due at the beginning of the next quiz section, usually two days
later. After turning the assignment in, students participated in a
second activity and discussion involving the completed writing
assignment.
How data were collected and analyzed:
Data on student learning of the material and skills
on quantitative reasoning were collected using a one-group
pretest/posttest experimental design. Only students who completed
both the pre- and posttests were included in the analyses. The tests
were administered as follows. On the first day of the academic

term, students' quantitative reasoning skills were measured with
the pretest. At the very end of the term,
students’ quantitative reasoning skills were measured with a
posttest. The posttest was identical to the pretest. Four students
were given approximately 15 minutes to complete each test.
The test consisted of 10 questions designed to measure
students' quantitative reasoning and table-reading skills. The
questions were developed in a manner that would reveal
changes in students' performance that would be attributable to
changes in quantitative reasoning ability rather than to substantive
knowledge contained in the course or in sociology in general.
Questions were divided into three sections addressing three
progressively difficult concepts. The first section measured
students' ability to identify the relationship between two variables.
The second section introduced the concept of theory. This section
included a short vignette describing a theory and four tables
reporting findings. Students were asked to determine which of the
four tables offered evidence supporting the theory and which of the
four tables offered evidence disproving the theory. The final
section addressed the issue of linearity in statistical
relationships. In this section, students were asked to determine the
relative fit of several relationships-that is, whether the relationships
were linear or nonlinear.
Students were given a graded test score ranging from 0 to 10,
depending upon the number of questions they answered correctly.
Partial credit was not given. Neither the pre- nor posttests counted
as a grade or as extra credit for the students. However, material
from the learning modules introduced in the lectures and the
discussion sections did factor into students' grades, as noted above,
because the students were graded on the quantitative writing
assignments and on quantitative exam questions administered
throughout the quarter.
Finally, TAs proctored the pretest and posttest measurements,
collecting observational data on the students as they completed the

tests. Although not systematic, two types of observational
information were collected. First, TAs monitored the time required
to complete the tests. Second, they observed whether students were
actively engaged in completing the tests-that is, whether the
classroom was quiet and students concentrated heavily on the tests.
The key findings:
The difference of means for the latter group is significant,
revealing a substantial increase in correct scores over
the experimental period. For reasons exhibited and discussed
below, we are inclined to attribute this increase to learning and the
acquisition of quantitative reasoning skills. Quite clearly, students
performed better, on average, on the posttest. Whereas the mean
number of correct answers for the pretest was 5.71, the posttest
mean was 6.73. This represents a 20 percent increase in correct
responses between test administrations.
It is possible that students' basic reasoning and analytical skills
may contribute to these differences. Students with strong basic
reasoning skills-as reflected in mathematical or even verbal
reasoning performance-may be more likely to grasp the
concepts in lectures and in quiz sections such that posttest scores
would be higher than for those students with weak basic skills. The
concern here is that some students may enter the class with either
much stronger reasoning skills than others or an accumulated
academic advantage such that their learning will be significantly
shaped by their skills or their past academic success. According to
this reasoning, the pretest/posttest differences may be influenced as
much by an individual's quantitative reasoning ability and/or test-
taking skills prior to the experiment as they are to
the experimental introduction of quantitative reasoning
materials in the class. In order to examine whether
the experimental results were related to quantitative reasoning
skills prior to the course and the experiment, we collected
additional data on students' SAT verbal and math scores.
Of the 455 students who completed the pretest, 414 had also

submitted SAT scores at the time they were admitted to the
university. Of the 261 students who completed both the pretest and
the posttest, 260 had submitted SAT scores at admission. the
correlations between the verbal portion of the SAT and the pretest
and posttest scores were equivalent in strength to the correlations
between the math portion and the pretest and posttest scores. Thus,
our quantitative reasoning results measure analytical abilities that
are different from math or verbal skills that are reflected in SAT
performance.
Equally important is that the correlations between the SAT scores
and the pretest/ posttest difference scores are near zero (r = .04, .
02, .03). Students' improvements in quantitative reasoning skills,
as reflected in the difference scores, are not associated with their
analytical skills as measured by the SAT upon entering the
university. Thus, students with low verbal or math scores were just
as likely to achieve improved quantitative reasoning skills as
students who entered with high math or verbal scores. We also
performed a repeated measures analysis of covariance with SAT
total score as the covariate and pre- and posttest as the repeated
measure. This test examined the hypothesis of no difference
between pre- and posttest scores on the quantitative reasoning test,
once differences in ability as reflected in SAT scores were
removed. However, the differences between the pre- and posttest
scores remained sizable and statistically significant in this analysis
(F = 63.59; df = 1, 259; p< .001), indicating as above that the
change from pretest to posttest was substantial and statistically
independent from SAT scores.
One possible interpretation of the results is that the difference
between the pretest and posttest scores reflects
improvements in testing skills rather than improvements in actual
reasoning skills-that is, improvements in guessing the answers
correctly rather than deriving answers from correct manipulations
of data. While it is impossible to test this hypothesis definitively,
TAs' observations about the test-taking performance of
students in the sessions shed some light on this issue. TAs

generally reported that the testing situations for the pre- and
posttests were quite similar. Students completed the tests in about
the same amount of time for both sessions-there were no more
"late" or "early" finishers in the pretest than the posttest. Further,
students exhibited the same level of seriousness and commitment
to the task in both sessions. Very few students in either session
failed to answer all of the problems. Further, there were no more
inquiries from students about the test questions (e.g., "I don't
understand what this question means. Could you explain it to
me?") during the pretest session than during the posttest session.
Thus, there is no observational evidence from students' behavior
during testing sessions that suggests the students were more adept
at taking the posttest than the pretest, having worked with similar
material a few times over the course of the term.
A related issue is whether students' uncertainty or anxiety over the
course changed with the introduction of the quantitative reasoning
modules. We did not incorporate any anxiety measures into the
study design. However, we compared students' evaluations of
the experimental course before and after the experiment was
conducted in order to examine how students' perceptions may have
changed. Three aspects of the evaluations were examined. The first
was a measure of students' satisfaction with the assignments and
grading practices. The second measured students' perception of the
reasonableness of assigned work. The third measure assessed
students' beliefs about the clarity of the instructor's expectations of
them. No qualitative data or written comments by students
regarding the assignments were available for the analyses.
Our analyses of these measures found that students' evaluations of
the course were higher on each of the measures for
the experimental period than in previous courses. Prior to the
inclusion of the quantitative reasoning modules, students
consistently rated the clarity, level of organization, and structure of
assigned work in the class as relatively low. Following inclusion of
the modules, a higher proportion of students felt that the
assignments were clear, that expectations were certain, and that the

organizational level of the class was high. One interpretation of
this pattern is that the structured nature of the quantitative work,
unlike previous writing assignments used in the course, actually
increased the clarity of tasks and students' perceptions of what was
expected from them. By increasing the organization and
predictability in assignments, the inclusion
of quantitative reasoning modules may have actually improved
students' assessments of the course overall and material
included in the course. While this reveals little about whether
teaching quantitative methods in this manner reduces student
uncertainty and anxiety relative to traditional teaching approaches,
it does suggest that adding carefully structured quantitative
material to a substantively oriented class does not increase
students' uncertainty, confusion, or frustration with the class.
The experimental results suggest that students' ability to interpret
and manipulate empirical data increased over the course of a single
term in which instructors introduced quantitative reasoning
modules as part of the course material. Further, the increase
occurred above and beyond the effects of students' basic reasoning
skills as measured by baseline SAT verbal and math scores. Thus,
the improvements in learning are not necessarily attributable to
certain types of students or student experiences prior to
participating in the experiment or the class.
Although these analyses suggest that instructors may achieve
significant improvements in students' learning of statistics and
methods skills in "nonmethods" classes, the results do not inform
debate over many important concerns in teaching sociological
methods. First, our experimental results do not address whether
instruction in the manipulation and interpretation of
data in substantive classes is more effective pedagogically than
instruction in "stand-alone" statistics classes. The analysis
performed in the present study involved no comparisons between
learning in a substantive sociology class with learning in a class

devoted entirely to social statistics or research methods. Indeed, it
is quite possible that greater improvements in
quantitative reasoning, as measured in the present study, might be
achieved in a statistics or methods class. An important
consideration in comparing the two types of instruction would be
to separate differences between substantive and methods
courses in teaching and delivering material to students. Any such
comparison would need to separate "instructor effects" on learning
from the effects of actual exposure to material
about quantitative methods and analyses. An obvious approach to
the comparison would be to conduct the experiment by having the
same instructor teach the same material in two different types of
classes one a substantive class and the other a statistics or methods
class-and then compare student learning between the two types of
classes, adjusting for other important factors like class composition
and baseline reasoning skills.
References from: Bridges, G. S., Gillmore, G. M., Pershing, J. L.,
& Bates, K. A. (2012).

Ex-post Facto Researcher can investigate the extent to which specific
independent variables may possibly effect the dependent
variable (Leedy, 2013). Researcher identifies events that
have already occurred or conditions that are already
present and then collects data to investigate a possible
relationship between these factors and subsequent
characteristics and behaviors (Leedy, 2013). After
observing that differing circumstances have prevailed for
two or more different groups—such circumstances
comprise the independent variable—the researcher tries
to determine whether the groups differ on some other
dependent variable (Leedy, 2013). There is no direct
manipulation of the independent variable. The presumed
“cause” has already occurred. Since manipulation is not
possible, the researcher can’t draw firm conclusions
about cause and effect (Leedy, 2013). Experimenter
cannot control for confounding variables that may
provide alternative explanations for any group
differences that are observed (Leedy, 2013). Lacks
control element so can’t draw definite conclusions about
cause and effect (Leedy, 2013).
This study aimed to determine differences between permissive and
authoritarian parenting in play activities motion against the
fundamental movement skills on second grade of elementary
school students.
The research was carried out in 5 villages at Rawamangun
Elementary School in East Jakarta. The population consists of 183
students however 36 students were selected.
Fundamental movement skills were divided into three activities
such as running and jumping, manipulative activities such as
throwing and catching, and stabilizing and balancing activities
such as walking on the bridge. The motion is divided into three
fundamental movement categories, namely locomotor skills, non-
locomotor skills, and manipulative skills. (1) Locomotor skills
refer to movement that uses the body to move from one place to
another or liftthe body up like jumping and hopping. Other
examples include walking, running, skipping, running like leaping,
slidingand galloping, (2) Non-Locomotor skills are defined as a
form of motion without transferring from one place to another.
This category includes movement: bending, stretching, pushing,
and pulling, twisting, turning, and shaking, (3) Manipulative skills

are categorized as a movement in a game when a kid is holding
some kind of object or tool. Most of these capabilities involve the
hands and feet, but other parts of the body can also be used. Most
manipulative things are fundamental for a lot of skills in games
like throwing, catching, and kicking.
Based on the definitions and explanations, it can be concluded that
the fundamental movement skills is a pattern of behavior that is
expressed through three motion activities that have different
characteristics and it is related to (1) moving motion (locomotor):
running, jumping, (2) unmoving motion (non-locomotor): balance,
flexibility, and (3) manipulative motion: throwing, catching,
kicking.
Parenting refers to the ways parents apply reciprocally in dealing
with their children to establish attitudes and behavior as expected
of parents and the community with the aim to become mature in
time. The effect of treatment on the parents during infancy and
early age can affect the development and status of the children
themselves because the involvement of children in this age is
strongly influenced by parental care. Parenting is related to how
the family provides huge impact for the development of a child.
Parenting is not only about caring for or supervising children, but
parenting also includes: education, manners, discipline,
responsibility, knowledge and relationships which are rooted in the
parents' knowledge.
This study used ex-post facto method that collects data through
questionnaires and tests the appearance of motion. In order to
collect data related to parenting types, indicators consisting three
levels of scale using a range of up to three were used to measure
the shape of the patterns of parenting in motion play activities at
home. Test battery consisting of tests run, jump, kick, catch, throw,

balance and, flexibility was used to measure the fundamental
movement skills.
This research used ex-post facto method, by collecting data
through questionnaire and test motion performance. To collect data
related to parenting questionnaire, indicators that measure how the
shape parenting to play in motion activities at home were
prepared/developed. Test battery such as run, jump, kick, catch,
throw, balancing and flexibility was used to test the fundamental
movement skills.
Before determining the selected samples, population was first
established in accordance with the purpose of research. The
selected population characteristics are as follows:
a. The population consists of students of Second grade of
Elementary School located in the village Rawamangun, of which
the physical education teacher's academic background is sports
science in education.
b. A total of 183 Second grade of Elementary School students from
5 (five) elementary schools located in the village Rawamangun
who suit the criteria qualified as the samples.
The sampling measure was conducted as follows: Samples were
collected by using Total Sampling i.e. 183 students. The
questionnaires classified students into two groups namely (1).
Students with permissive parenting, (2). Students with
authoritarian parenting. 36 students were selected for the study.
The key findings:
The analysis found that there were significant differences in
fundamental movement skills of second grade elementary school
students between permissive parenting and authoritarian parenting.
The results show that the fundamental movement skills of

permissive parenting are better than the fundamental movement
skills of authoritarian parenting.
Data of Fundamental Movement Skills of Students with
Permissive Parenting :
The overall data of fundamental movement skills of students with
permissive parenting reveal 18 students with the highest score of
60.45 and the lowest score of 44.22, an average score of 51.97,
standard deviation 4.30, modus 52.8 and median 57.7
Data of Fundamental Movement Skills of Students (with
Authoritarian Parenting)
The overall data of fundamental movement skills of students with
authoritarian parenting show 18 students with the highest score of
56.49 and the lowest score of 39.5, an average score of 48.42,
standard deviation 4.79, modus 45.09 and median 50.19.
The Differences between the Fundamental Movement Skills of
Permissive and Authoritarian Parenting
Results of fundamental movement skills of the students with
permissive parenting showed an average value of 51.97 with a
standard deviation of 4.30, while the fundamental movement skills
of the students with authoritarian parenting showed an average
value of 48.42 with a standard deviation of 4.79.
Results of analysis of variance (ANOVA) related to the differences
in fundamental movement skills of students with permissive
parenting with fundamental movement skills of students with
authoritarian parenting as a whole can be seen in the following
table.
The null hypothesis is rejected. By rejecting the null hypothesis,

this means the alternative hypothesis is accepted. Thus, it means
that there are significant differences between the fundamental
movement skills of students with permissive parenting with
fundamental movement skills of students with authoritarian
parenting. Then the study of alternative hypothesis which states
that the fundamental motor skills of students with permissive
parenting are better than the fundamental movement skills of
students with authoritarian parenting was received.
Based on the data obtained, the hypothesis testing results and
discussion of the results of this study, it can be concluded that
there were significant differences in fundamental movement skills
at second grade elementary school students between permissive
and authoritarian parenting. The calculation results showed that
overall score of fundamental movement skills of students with
permissive parenting better than the score of fundamental
movement skills of students with authoritarian parenting. It also
confirms that there are significant differences between the scores
of fundamental movement skills of students with permissive and
authoritarian parenting suggesting that different parenting type
results in different score.
1) Parents should allow time for the child to perform a variety of
playing activities because the motion activities that children do
have an important thing in stimulating the development of a child's
basic motion.
2) Limited time or opportunity for parents to accompany the child
to play does not make an excuse for parents to restrict children to
play because the restrictions will affect a child's basic motor
development.
3) The scope of this research is still limited and the population of
students with limited sample, thus generalization can only be done
on the population. It is suggested that further research should

examine a bigger sample in a different area to get better result.
4) Other researchers can search for and examine other variables
that can affect the fundamental movement skills of elementary
school students.
Reference:
Sari, E. F. N. (2014). Parenting and fundamental movement
skills. Asian Social Science, 10(5), 22-27. Retrieved from
Descriptive
This analysis should indicate the means, standard
deviations, and range of scores for variables (Leedy,
2013). Involves collecting data in order to test
hypotheses or answer questions regarding the
participants of the study. Data, which are typically
numeric, are collected through surveys, interviews, or
through observation (Simon, 2013). The investigator
reports the numerical results for one or more variables on
the participants or units of analysis of the study (Simon,
2013).
Injuries are one of the main reasons why people stop
participating in health-enhancing physical activities. It is
proposed that musculoskeletal sporting injuries sustained
dining youth can impair mobility later in life and have a
detrimental influence on the aging population. Sport injury
and its prevention are important public health issues and
areas of concern. The prevention of sports injuries relies on
several levels of operation for optimal implementation and
requires active participation from large numbers of
individuals. Future research should study the role and effect
of purposefully prescribed exercises in decreasing the
incidence and severity of musculoskeletal injuries sustained
during recreational alpine skiing and snowboarding. The
aim of this study was to systematically review the
literature for injury prevention recommendations specific to
recreational alpine skiers and snowboarders. The focus was
to discern recommendations that targeted physical fitness,
exercise and/or training in the prevention of
musculoskeletal injuries in these two sports.

Fourteen electronic databases were systematically searched in
October 2011 using relevant MeSH terms, keywords. Booleans
and truncation symbols. The databases searched were: AMED
(1985-), CINAHL® (1981-), Cochrane Central Register of
Controlled Trials (1898-), Cochrane Database of Systematic
Reviews (1995-), Database of Abstracts of Reviews of Effects
(1994-), EMBASE (1947-), MEDLINE® (1948-), PEDro (1929-),
PsycINFO® (1806-), PubMed (1951-), SciVerse Scopus (1823-),
SPORTDiscus(TM) (1985-), Web of Knowledge(TM) (1864-) and
Web of Science® (1898-). The search strategy employed was:
"(skiing OR snowboarding) AND ((wounds and injuries) OR
injur*) AND ((prevention and control) OR (accident prevention)
OR (primary prevention) OR prevent*))". In addition to the
systematic electronic database search, the reference lists of all
articles subsequently included in the review were manually
searched, as were relevant journals and key authors in the field of
injury prevention research.
Study Selection Articles were included if they addressed injury
prevention, recreational alpine skiing or snowboarding and
musculoskeletal injuries. Only original research articles published
in peer-reviewed journals, and in the English-language, were
reviewed. Articles on elite athletes were excluded.
Study Appraisal and Synthesis Methods Two independent
reviewers quality assessed articles meeting inclusion criteria using
a modified version of the Downs and Black Quality Assessment
Checklist. Data on study population, study design, study location
and injury prevention recommendation(s) were extracted from
articles using a standard form and subsequently categorized to
facilitate data synthesis.
A total of 30 articles met the inclusion criteria and were

reviewed, having an average ± standard deviation quality
score of 72 % ± 17 % (range: 23-100 %). Overall, 80
recommendations for the prevention of musculoskeletal
injuries in recreational alpine skiers and snowboarders were
identified and classified into five main groups: equipment
(n = 24), education and knowledge (n = 11), awareness and
behaviour (n = 15), experience (n = 10) and third-party
involvement (n = 20). No recommendations pertained to
physical fitness, exercise and/or training per se, or its role
in preventing injury.
The key findings:
The importance of targeting physical fitness in injury prevention is
accepted in sports medicine and rehabilitation; yet, there was a
paucity of articles included in this review that explicitly
investigated this aspect with regards to recreational alpine skiing
and snowboarding. The most frequent
recommendations for preventing skiing and snowboarding injuries
concerned equipment or the involvement of third parties. The
dominance of equipment related measures in the injury prevention
literature may be rationalized from a sports biomechanics
viewpoint, as these activities involve high velocities and impact
forces. Nonetheless, this also indicates a need for appropriate
levels of strength, endurance and conditioning to meet the
technical demands of these sports.
Future research is encouraged to investigate the role of
physical fitness, exercise and training in decreasing the incidence
and severity of skiing and snowboarding injuries in recreational
athletes.
References:
Hébert-Losier, K., & Holmberg, H. (2013). What are the exercise-
based injury prevention recommendations for recreational alpine

skiing and snowboarding? A systematic review. Sports
Medicine, 43(5), 355-66. Retrieved from
References for Primary Characteristics of Research Designs
Bridges, G. S., Gillmore, G. M., Pershing, J. L., & Bates, K. A. (1998). Teaching quantitative research methods: A quasi-experimental
analysis. Teaching Sociology, 26(1), 14. Retrieved from http://search.proquest.com/docview/223521919?accountid=35812
Creswell, J. W. (2014). Research design. Qualitative, quantitative, and mixed methods approaches. (4th
ed.). Retrieved from The
University of Phoenix eBook Collection database.
Leedy, P. D., & Ormrod, J. E. (2013). Practical research: Planning and design (0th ed.). Boston: Pearson.
Simon, Marilyn (2013). Quantitative Research: The “N” Side in the Paradigm War. Retrieved from University of Phoenix website.

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