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ResearchProposal
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Example Research Proposal
Download Example Research Proposal. Note that all instructor feedback from your previous activities should be applied in preparing your proposal.
Your Research Proposal is a six- to seven-page plan for a new study on your research topic. Incorporate at least four scholarly/peer-reviewed journal articles in addition to the course text to support your proposed study.
Include the following sections and content in your paper:
· Introduction– Introduce the research topic, explain why it is important, and present your research question and/or hypothesis.
· Literature Review– Summarize the current state of knowledge on your topic by citing the methods and findings of at least two previous research studies. State whether your proposed study is a replication of a previous study or a new approach using methods that have not been used before.
· Methods
· Design– Indicate whether your proposed study is qualitative or quantitative in approach. Select one of the research designs you have studied in the course, and indicate whether it is experimental or non-experimental. Evaluate why this design is appropriate for your research topic. Cite the textbook and one other source on research methodology to support your choice.
· Participants– Identify the sampling strategy you would use to recruit participants for your study. Estimate the number of participants you would need and explain why your sampling method is appropriate for your research approach.
· Procedure/Measures– Apply the scientific method by describing the steps you would use in carrying out your study. Indicate whether you will use any kind of test, questionnaire, or measurement instrument. Cite the source of any instruments to be used.
· Data Analysis– Describe the statistical techniques (if quantitative) or the analysis procedure (if qualitative) you plan to use to analyze the data. Cite at least one source on the chosen analysis technique.
· Ethical Issues– Analyze the impact of ethical concerns on your proposed study, such as confidentiality, deception, informed consent, potential harm to participants, conflict of interest, IRB approval, etc. Explain how you would address these concerns.
· Conclusion– Briefly summarize the major points of your research plan and reiterate why your proposed study is needed.
The Research Proposal
· Must be six- to seven- double-spaced pages in length (not including title and references pages) and formatted according to APA style as outlined in the
Writing Center(Links to an external site.)
’s
APA Style(Links to an external site.)
resource.
· Must include a separate title page with the following:
· Title of proposal
· Student’s name
· Course name and number
· Instructor’s name
· Date submitted
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Example Research Proposal
Pamela Murphy
PSY 326 Research Methods
Instructor’s Name
Date Submitted

NOTE: The details in this example research proposal are based on a published study which I co-
authored with Charles B. Hodges and my doctoral dissertation, both in 2009. Portions of the text
are excerpted from the published article (Hodges & Murphy, 2009) and the dissertation (Murphy,
2009).
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Example Research Proposal

Introduction
The concept of self-efficacy was introduced nearly 40 years ago. “Perceived self-efficacy
refers to beliefs in one’s capabilities to organize and execute the courses of action required to
produce given attainments” (Bandura, 1977, p. 3). Self-efficacy has been identified as an
important construct for academic achievement in traditional learning environments for at least
two decades. Zimmerman and Schunk (2003) go so far as to say that “the predictive power of
self-efficacy beliefs on students’ academic functioning has been extensively verified” (p. 446).
Its importance has been noted consistently through all levels of the educational process, with
various student populations, and in varied domains of learning.
While learner self-efficacy has a well-established literature base in the context of
traditional learning environments, self-efficacy research related to learners in online and other
non-traditional learning environments is relatively new. Hodges (2008a) has called for
researchers to explore self-efficacy in online learning environments. Additionally, in terms of
students’ self-efficacy beliefs toward academic achievement, “there have been few efforts to
investigate the sources underlying these self-beliefs” (Usher, 2009, p. 275). The purpose of the
proposed study is to investigate the relative strength of the four traditionally proposed sources of
self-efficacy beliefs of students enrolled in a technology-intensive asynchronous college math
college.

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Literature Review
Self-efficacy beliefs have been found to be significant contributors to motivation and
performance in academic achievement (Multon, Brown, & Lent, 1991), group functioning
(Gully, Incalcaterra, Joshi, & Beaubien, 2002; Stajkovic & Luthans, 1998), health (Holden,
1991), and sports performance (Moritz, Feltz, Fahrbach, & Mack, 2000). Research revealing the
connection between self-efficacy and mathematics, the context of the proposed study, includes
many cultures and levels of education (Malpass, O’Neil, & Hocevar, 1999; Pietsch, Walker, &
Chapman, 2003; Randhawa, Beamer, & Lundberg, 1993; Stevens, Olivarez, Lan, & Tallent-
Runnels, 2004) and continues to the present (Usher, 2009).
Sources of Self-Efficacy
Albert Bandura’s (1977) introduction of self-efficacy theory included the proposition that
self-efficacy is derived from four principal sources: mastery experiences, vicarious experience,
social persuasion, and physiological/affective states. These four areas are generally accepted in
the literature as core elements in the development of self-efficacy beliefs, but an ordering of the
importance of each of these sources is unsettled.
Mastery Experiences. Mastery experiences refer to previous, successful experiences a
learner has had performing a task. Successes build positive self-efficacy beliefs and failures
undermine self-efficacy. If failures are experienced before a firm positive belief in one’s self-
efficacy is formed, the creation of positive self-efficacy beliefs is more difficult.
Vicarious Experience. Vicarious experience refers to one’s observation of a role model
performing a task. Knowledge of how others have performed a similar task helps one determine
whether or not a performance should be judged a success or failure. Surpassing the performances
of others increases self-efficacy and falling below others’ performances lowers self-efficacy.
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Note the importance of the selection of individuals for comparison. Self-efficacy beliefs will
vary depending on the abilities of those chosen for comparison, thus, models for comparison
should be selected carefully (Wood, 1989).
Social Persuasion. Social persuasion is commonly used due to the ease with which it can
be dispensed. The believability of the persuader(s) is important in the use of social persuasion.
The receiver must view the persuader as competent to provide meaningful and accurate
feedback. Bandura (1997) cautions that verbal persuasion consists of more than flippant, off-
hand comments of encouragement. Unrealistic comments from the persuader may mislead the
receiver, which may decrease self-efficacy and diminish the belief in the persuader as one
competent to evaluate the performance. “Skilled efficacy builders encourage people to measure
their successes in terms of self-improvement rather than in terms of triumphs over others”
(Bandura, 1997, p. 106).
Physiological/Affective States. Stress, emotion, mood, pain, and fatigue are all
interpreted when making judgments regarding self-efficacy. For example, someone may have
prepared well for an exam, but upon learning of some unfortunate news, stress may reduce
concentration, thus impacting performance on the exam. In general, success is expected when
one is not in a state of aversive arousal (Bandura, 1997).
Usher and Pajares (2006) summarize the inconsistent findings regarding the relative
strength of each self-efficacy source well. They follow with the proposition that “exploring the
predictive value of the sources of students’ academic self-efficacy beliefs and determining
whether this prediction varies as a function of group membership such as gender, academic
ability, and race/ethnicity is a matter of import” (p. 130).

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Methods
Design
The proposed study is quantitative in nature and will use a survey research design
(Newman, 2016). Survey research falls into the non-experimental category of research designs.
The survey questions use mostly ordinal scales and will result in numeric scores summarizing the
extent of use of each source of self-efficacy beliefs as well as a score representing the level of
self-efficacy held by each student in relation to the ability to learn math in an asynchronous
learning environment.
Participants
Approximately 300 students in an asynchronous college algebra course offered at a large,
state supported university in the mid-Atlantic region of the United States will be invited to
participate in a survey. This is a convenience sample, and participation is voluntary, so the final
sample size may be considerably smaller than the number of students invited. The course is
delivered using an emporium format (Twigg, 2003) which is technology intensive. The students
enrolled in the course tend to be engaged in academic majors that are not math-intensive. They
may have a high degree of math anxiety or at least some negative feelings toward their math
abilities. In addition, the emporium model may be an unfamiliar concept for them.
Procedure/Measures
This course is offered through the Math Emporium and has no traditional class meetings.
After a brief, face-to-face, orientation meeting, students complete the course asynchronously.
There are weekly deadlines for quizzes, and proctored tests are administered periodically.
Students prepare for the quizzes and tests by taking advantage of various technology resources
available to them online. Lesson pages serve as an online textbook for the course, short
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streaming video lectures are available on most topics, and an unlimited number of practice
quizzes are available. For students who desire it, face-to-face interactions with assistants in the
computer lab are available several hours each week. No appointment is needed for the face-to-
face assistance.
At the conclusion of the course, data will be collected using a web-based survey tool.
Students who provide informed consent to participate will be given an ID number and survey
access information. They may access the survey either in the Math Emporium or offsite through
the internet. Specific instruments to be used are the Self-Efficacy for Learning Mathematics
Asynchronously (SELMA) survey (Hodges, 2008b), a demographics survey, and the Sources of
Mathematics Self-Efficacy (SMSE) scale (Lent, Lopez, & Bieschke, 1991).
The SELMA survey is a 25-question survey constructed for use in college algebra and
trigonometry courses offered in an emporium model. A validation study showed an internal
consistency Cronbach’s alpha value of 0.87 (Hodges, 2008b) which is greater than the 0.80
minimum level recommended by Gable and Wolf (1993) for instruments in the affective domain.
The SMSE scale consists of four 10-question subscales designed to measure each of the
four sources of self-efficacy: mastery, vicarious experiences, social persuasion, and
affective/physiological state. In a validation study of the SMSE, Lent et al. (1991) reported
internal consistencies of 0.86 for mastery, 0.56 for vicarious, 0.74 for persuasion, and 0.90 for
affective/physiological arousal.
Data Analysis
To investigate the relative strength of the four traditional sources of self-efficacy beliefs
of students in an asynchronous math course, analysis of variance (ANOVA) and multiple
regression will be used. Scores from each of the four subscales of the SMSE will be used as
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predictors of the SELMA score. Bivariate correlations will also be examined. Significant
correlations among the predictor variables may present a problem of multicollinearity. If
necessary, additional statistical tests such as ridge regression (Joe & Mendoza, 1989; Kidwell &
Brown, 1982) will be applied to solve this problem.
Ethical Issues
Participation in the survey will be strictly voluntary, and will not be tied to evaluation of
the student’s performance in the course in any way. As a non-experimental survey study, no
deception will be used. Signed informed consent will be obtained from those who wish to
participate. Those who agree to participate may withdraw from the study at any time without any
type of penalty.
Confidentiality of participants will be protected by the assignment of ID numbers to be
used on the survey documents instead of names or any other type of identifying information. A
single copy of the list matching the ID numbers with participants’ names will be kept in a secure,
locked location for a period of three years after the completion of the study. After three years, the
list will be destroyed in accordance with the instructions of the Institutional Review Board
(IRB).
As a token of appreciation, all participants will be entered into a drawing for an Amazon
gift card. The proposed amount of the gift card, subject to IRB approval, is $25. University
facilities, including the computer lab known as the Math Emporium, its computers and a survey
software program, will be used if this study is approved. This project will not receive any
external funding from commercial or other sources, and no conflicts of interest are reported by
the researchers.
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Conclusion
Self-efficacy and its relationship to academic achievement in asynchronous online
learning environments are only recently beginning to be researched (Hodges, 2008a). Given the
growing prominence of asynchronous online learning, it is essential that we understand what role
constructs such as self-efficacy play in these learning environments. The proposed study will
address this need by using a survey research design. The surveys will provide data on the four
sources of self-efficacy which will serve as predictors of students’ self-efficacy for learning
mathematics in an asynchronous online setting. A multiple regression model using the four
predictors with the SELMA survey score as the dependent variable will indicate how much each
source contributes to self-efficacy.
The results of this study are expected to be important to instructional designers and
educational practitioners who either currently use or are considering using an emporium model,
as they will give indications of which elements of the asynchronous course design should be
emphasized to best promote students’ self-efficacy relating to the subject matter. An expedited
review of this proposal by the IRB is requested for approval to begin this research as soon as
possible.

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References
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Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change.
Psychological Review, 84(2), 191-215.
Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W. H. Freeman and
Company.
Gable, R. K., & Wolf, M. B. (1993). Instrument development in the affective domain: Measuring
attitudes and values in corporate and school settings, 2nd ed. Boston: Kluwer Academic
Publishers.
Gully, S. M., Incalcaterra, K A., Joshi, A., & Beaubien, J. M. (2002). A meta-analysis of team-
efficacy, potency, and performance: Interdependence and level of analysis as moderators
of observed relationships. Journal of Applied Psychology, 87, 819-832.
Hodges, C. B. (2008a). Self-efficacy in the context of online learning environments: A review of
the literature and directions for research. Performance Improvement Quarterly, 20(3-4),
7-25.
Hodges, C. B. (2008b). Self-efficacy, motivational email, and achievement in an asynchronous
math course. Journal of Computers in Mathematics and Science Teaching, 27(3), 265-
285.
Hodges, C. B., & Murphy, P. F. (2009). Sources of self-efficacy beliefs of students in a
technology-intensive asynchronous college algebra course. Internet and Higher
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Holden, G. (1991). The relationship of self-efficacy appraisals to subsequent health-related
outcomes: A meta-analysis. Social Work in Health Care, 16, 53-93.
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Howell, D. C. (2002). Statistical methods for psychology, 5th ed. Pacific Grove, CA: Duxbury.
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with multicollinearity. Journal of Marriage and the Family, 44(2), 287-299.
Lent, R. W., Lopez, F. G., & Bieschke, K. J. (1991). Mathematics self-efficacy: Sources and
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Malpass, J. R., O’Neil, H. F., & Hocevar, D. (1999). Self-regulation, goal orientation, self-
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Moritz, S. E., Feltz, D. L., Fahrbach, K. R., & Mack, D. E. (2000). The relation of self-efficacy
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Murphy, P. F. (2009). Relationships of parenting practices, independent learning, achievement,
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Newman, M. (2016). Research methods in psychology, 2nd edition. San Diego, CA: Bridgepoint
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http://scholar.lib.vt.edu/theses/available/etd-04022009-174950/
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Pietsch, J., Walker, R., & Chapman, E. (2003). The relationship among self-concept, self-
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Randhawa, B. S., Beamer, J. E., & Lundberg, I. (1993). Role of mathematics self-efficacy in the
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Twigg, C. A. (2003). Improving learning and reducing costs: New models for online learning.
EDUCAUSE Review (September/October), 28-38.
Usher, E. L. (2009). Sources of middle school students’ self-efficacy in mathematics: A
qualitative investigation. American Educational Research Journal, 46(1), 275-314.
Usher, E. L., & Pajares, F. (2006). Sources of academic and self-regulatory efficacy beliefs of
entering middle school students. Contemporary Educational Psychology, 31(2), 125-141.
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