DESCRIPTION OF CORE ASSESSMENT FOR EC 315:
All Park University courses must include a core assessment that measures the course's Core Learning Outcomes. The purpose of this assessment is to determine if expectations have been met concerning mastery of learning outcomes across all instructional modalities. For this course, the core assessment is a research project that includes a written proposal and final research paper. This project is worth 20 percent of the student's final grade and will assess students' mastery of four Core Learning Outcomes (outcomes 1, 2, 3, and 4 listed on this syllabus). Although guidelines for the research proposal are listed below, the Core Assessment Rubric refers to the grading of the final research paper only.
Research Topic Proposal
As preparation for the final research paper, formulate an original theory about the correlation between four measurable independent variables (causes) and one measurable dependent variable (the effect). The topic proposal should include the following four items which serve as the foundation for the final research paper after instructor feedback is given.
1) Purpose Statement
In one paragraph, state the correlation and identify the primary independent variable.
State the correlation:
“The dependent variable _______ is determined by independent variables ________, _________, ________, and ________.”
Identify and defend the “primary” independent variable, or the variable believed to have the strongest impact on the dependent variable:
“The most important independent variable in this relationship is ________ because _________.”
2) Definition of Variables
For each variable, write a single definition paragraph (five paragraphs total). Paragraphs should be in this order: dependent variable, primary independent variable, and remaining three independent variables.
In addition to defining the independent variables, defend why each determines the dependent variable.
For the primary independent variable, at least two research sources that discuss the variable also must be cited. These sources need not be technical documents but should contain evidence to justify the relationship between the primary independent variable and the dependent variable. List these sources on the Works Cited (reference) page. Citations from encyclopedias, abstracts, or non-governmental websites are not acceptable research sources.
3) Data Description
For each of the five variables, at least 30 observations of cross-sectional data must be obtained. Thus for the final research paper, a data matrix that is at least 30 rows by five columns must be presented.
In one paragraph, identify the data sources and describe the data (i.e., which government agencies supply the data, which methods are used to compile them, when they were collected, etc.). Attach a Xerox copy of the original data tables from which the data will be compiled after the proposal is reviewed and approved by the instructor.
4) Works Cited Page
The final page of the proposal should be a Works Cited page listing the two research sources for the primary independent variable and the data sources, with a separate citation for each table of data, including specific table numbers for each of the five sources. The appropriate format should be employed (see below).
Final Research Paper
Purpose Statement and Model
1) In the introductory paragraph, state why the dependent variable has been chosen for analysis. Then make a general statement about the model:
“The dependent variable _______ is determined by variables ________, ________, ________, and ________.”
2) In the second paragraph, identify the primary independent variable and defend why it is important.
“The most important variable in this analysis is ________ because _________.” In this paragraph, cite and discuss the two research sources that support the thesis, i.e., the model.
3) Write the general form of the model, with the primary independent variable as X_{1}:
The model is:
Y =
Where
Y: brief definition of Y
X_{1}: brief definition of X_{1 }[etc. for each variable]
Definition of Variables
4) Define and defend all variables, including the dependent variable, in a single paragraph for each variable. Also, state the expectations for each independent variable. These paragraphs should be in numerical order, i.e., dependent variable, X_{1}, then X_{2}, etc.
In each paragraph, the following should be addressed:
< How is the variable defined in the data source?
< Which unit of measurement is used?
< For the independent variables: why does the variable determine Y?
< What sign is expected for the independent variable's coefficient, positive or negative? Why?
Data Description
5) In one paragraph, describe the data and identify the data sources.
< From which general sources and from which specific tables are the data taken? (Citing a website is not acceptable.)
< Which year or years were the data collected?
< Are there any data limitations?
Presentation and Interpretation of Results
6) Write the estimated (prediction) equation:
The results are:
=
7) Identify and interpret the adjusted R^{2 }(one paragraph):
< Define “adjusted R^{2}.”
< What does the value of the adjusted R^{2} reveal about the model?
< If the adjusted R^{2} is low, how has the choice of independent variables created this result?
8) Identify and interpret the F test (one paragraph):
< Using the p-value approach, is the null hypothesis for the F test rejected or not rejected? Why or why not?
< Interpret the implications of these findings for the model.
9) Identify and interpret the t tests for each of the coefficients (one separate paragraph for each variable, in numerical order):
< Are the signs of the coefficients as expected? If not, why not?
< For each of the coefficients, interpret the numerical value.
< Using the p-value approach, is the null hypothesis for the t test rejected or not rejected for each coefficient? Why or why not?
< Interpret the implications of these findings for the variable.
< Identify the variable with the greatest significance.
10) Analyze multicollinearity of the independent variables (one paragraph):
< Generate the correlation matrix.
< Define multicollinearity.
< Are any of the independent variables highly correlated with each other? If so, identify the variables and explain why they are correlated.
< State the implications of multicollinearity (if found) for the model.
11) Other (not required):
< If any additional techniques for improving results are employed, discuss these at the end of the paper.
Works Cited Page
12) Use the proper format to list the works cited under two headings:
Research: two sources