€¦ · web viewyour task is to report on your analysis and findings of a research question that...

EDAD 982: Advanced Quantitative Methods for Educational Administration Research

Deryl K. Hatch-Tocaimaza, PhD

Paper Draft 2 Directions

Scope and Nature of the Assignment

This is the 2nd in a series of assignments in which you write a manuscript reporting on a research project, leading up to and including the final assignment for this course. The process of writing out initial findings, followed by additional writing and re-writing following feedback and further analyses, mirrors the real life process of writing manuscripts that report quantitative analyses.

Note that much of these instructions are carried over from Paper 1. Substantive changes are highlighted in yellow. But all text is subject to change. You are expected to read and implement all of these instructions thoroughly.

Your task is to report on your analysis and findings of a research question that is assigned to you, according to norms of scholarly journal articles. Ultimately, you will be expected to develop the following selected portions of a research report:

Methods (including data source, variables, analytical approach/design, limitations, etc.) Results (narrative summary of the analytical findings, supported by selected statistical figures in

table format [NOT software output]) Discussion (interpretation of the meaning of the results) Implications (narrative commentary in plain language about the significance of the results in terms

that address the research problem and question at hand)

The research problem, question, and conceptual framing of the paper will be provided to you. As you build on the foundation of your first paper, the manuscript is expected to be more polished and nuanced. Expectations increase with each additional draft.

Future paper versions will require additional analyses or reformulated analytical approaches as appropriate, but will continue to develop the general line of inquiry that started previously by your adding greater nuance to your quantitative analysis of the questions at hand.

Statistical accuracy is necessary, but not sufficient to receive high marks on this paper. Your focus in this exercise should be demonstrating a clear understanding of the “purpose” of each portion of the paper in developing a coherent chain of argumentation backed up by evidence. Indeed, because the bulk of grading criteria are based on your following formatting directions and norms of argumentation, any shortcomings in the technical norms of reporting numbers (such as the amount of detail provided, and the formatting of tables) in writing are of secondary concern. Papers are graded according to the rubric provided for the course.

Consultation and Individual Work

You are encouraged to continue using the course discussion forums to help each other with guidance on the conceptual and practical steps of conducting the analyses if you get stuck and can’t figure out a way forward, but not with the interpretation or writing about the findings. This openness is afforded by the instructor with the understanding that ALL related communication must be done in full view of all classmates (via the course discussion forum exclusively). If you have doubts, feel free to ask the instructor about whether a question or comment is allowable. The instructor will also reserve the right to redact or delete comments that are deemed not allowable for sharing.

Instructions

1. Your paper must be between 1700-2200 words in length, formatted to current APA standards, including in particular: 1-inch margins, 12-pt Times New Roman font, double-spaced.

a. (Note that you are already provided ~500 words, plus information below about the data source and variables that you need to incorporate into your paper.)

b. This word count EXCLUDES front material, references, tables, and all appendices. c. (Tables should be inserted in-line with the text, not inserted after the text.)

2. Include the following front material:a. Title page that includes the following affirmation:

i. The writing of this paper is exclusively my own. I completed it alone and/or by consulting published resources, whether in print or online. The totality of any synchronous or asynchronous consultation I had with individuals regarding conceptual and practical steps needed to accomplish the analysis was conducted only with classmates enrolled in this class and shared exclusively through the course discussion forums. I personally manipulated the data and utilized statistical software to perform the analyses reported in this paper. Likewise, I personally wrote the interpretation and presentation of the findings alone without the aid of consultation of any kind.

ii. Electronic Signature: ____________________________________________________

iii. Date: ________________________________b. DO NOT include other front material.

3. You may add additional references to the reference page if you wish. But this is not required.4. ONLY include selected statistical results in the narrative of your paper, or tables that you craft

yourself. 5. Include ONLY tables of data (descriptive statistics, regression tables, etc.) that are necessary for

advancing your argument. A multiple regression paper without tabular results of some kind is inadequate for scholarly writing.

a. Give your tables numbers and titles per APA requirements.b. Important: Do not necessarily talk about all the statistical data points that in your tables; be

selective. But conversely, do not include any tables of information that you don’t talk about or reference at some point in your narrative.

6. Attach an appendix or supplementary file with your SPSS output in Word, Excel, PDF, or HTM format.

Procedure

Complete the following tasks:

1. TASK 1: Revise and expand your papera. Re-work and revise your first paper in light of feedback and grading received. Also: re-work the

paper to integrate the new variables and analyses specified in these instructions. It is expected that you make substantive improvements to the basic structure and style of your first paper while also adding to it the additional aspects specified below.

b. This includes revisiting the headers you use. For example:i. Purpose and Research Questions

ii. Method1. Data Source2. Variables

a. You may want separate dependent and independent variables sections.

3. Analytical Methoda. You might consider using headers to organize the analytical process

used for each research question in turn.

iii. Results1. You might consider using headers to organize the results that answer each of

the research question in turn.iv. Discussionv. Implications

c. Note the following:i. The purpose and research questions will be provided to you. You can use this text

verbatim. ii. You have flexibility in your use of headings. (But you are expected to use headings per

APA style.)

2. TASK 2: Identify and describe variablesa. HERE’S THE BACKGROUND TO THE RESEARCH : (Remember that APA calls for using NO

header for the introduction. Use the following text verbatim. Or feel free to re-phrase or edit it slightly. In later drafts, you may decide to add your own nuance to the provided topic as the question becomes more involved.)

The impact of college campus climate on the lived experience and educational outcomes of individuals has long been studied, with plentiful evidence that a hostile campus climate has deleterious effects on the wellbeing and educational attainment of individuals from groups who are marginalized or historically underrepresented in higher education (Jayakumar & Museus, 2010). Campus climate is not always readily apparent though, and so neither are its effects. Individuals from different backgrounds can perceive the campus culture in very different ways (Rankin & Reason, 2005). What one individual perceives as generally positive and welcoming may to another be unfriendly and discriminatory. To be sure, such negative climates for marginalized individuals may not be due to intentional attitudes, behaviors, or practices. For instance, it is abundantly clear that structural racism can exist even without individual racists (Bonilla-Silva, 2010). Hurtado and colleagues (e.g., Hurtado, Alvarez, Guillermo-Wann, Cuellar, & Arellano, 2012; Hurtado, Griffin, Arellano, & Cuellar, 2008) have shown that campus climate has many dimensions, including the historical, organizational, and compositional nature of institutions, along with individual-level behavioral and psychological aspects. These latter dimensions are often confounded together as ways to understand the educational environment, yet they are distinct dimensions of the educational environment (Hurtado et al., 2012). For example, instances of constructive inter-group interaction or alternately unintentional microagressions can lead to differing reactions of individuals to those episodes.

It has been proposed that one of the ways that minoritized students may respond to oppressive environments is to develop—or alternately, mobilize within themselves and community—what has been called “resistant cultural capital” (Solórzano and Villalpando, 1998). Resistant cultural capital refers to critical navigational skills informed by class, race, and gendered identities that allow students to turn otherwise oppressive climates into transformational spaces. Resistant cultural capital “highlights the ingenuity and resourcefulness of students of color who must tap into resources not considered by traditional forms of [social and academic] capital” (Abrica, 2009, p. 3). One way to operationalize resistant cultural capital, Abrica (2009) proposes, is through a measure of “transformational impetus” which she defines as the manifest desire of college students to change the world around them in the interests of social justice.

The purpose of this study is to explore whether differences in students’ perception of campus climate are associated with differences in their transformational impetus. Furthermore, prior research shows that faculty interaction and informal interactions with peers from different backgrounds—more so than formal curricular or cocurricular interventions such as diversity coursework—have a strong impact on cognitive and civic outcomes and appear to ameliorate the perception or impact of prejudice (Cole 2007; Cress 2008). Therefore, the study will also test whether these types of personal interactions have an effect above and beyond the effect of campus climate.

b. HERE ARE THE RESEARCH QUESTIONs :

1. What is the relationship between students’ perception of different dimensions of campus climate and the degree of their transformation impetus for social change?

2. Do students’ personal interactions with faculty and social interactions with those of another racial/ethnic group have an effect above and beyond campus climate?

3. If so, do the effects of those personal interactions on transformational impetus depend on the racial/ethnic background of students?

c. Include these references in your paper:

Abrica, E. (2009). The development of transformational impetus: Exploring the differential impact of an oppressive campus environment. Unpublished manuscript.

Bonilla-Silva, E. (2010). Racism without racists: Color-blind racism and the persistence of racial inequality in the United States (3rd ed). Lanham: Rowman & Littlefield Publishers.

Cole, D. (2007). Do interracial interactions mater? An examination of student-faculty contact and intellectual self-concept. The Journal of Higher Education, 78(3), 249–281.

Cress, C. M. (2008). Creating inclusive learning communities: The role of student—faculty relationships in mitigating negative campus climate. Learning Inquiry, 2, 95–111.

Hurtado, S., Alvarez, C. L., Guillermo-Wann, C., Cuellar, M., & Arellano, L. (2012). A model for diverse learning environments. In J. C. Smart & M. B. Paulsen (Eds.), Higher education: Handbook of theory and research (pp. 41–122). Dordrecht, Netherlands: Springer. Retrieved from http://link.springer.com/chapter/10.1007/978-94-007-2950-6_2

Hurtado, S., Griffin, K. A., Arellano, L., & Cuellar, M. (2008). Assessing the value of climate assessments: Progress and future directions. Journal of Diversity in Higher Education, 1(4), 204–221. https://doi.org/10.1037/a0014009

Jayakumar, U. M., & Museus, S. D. (2012). Mapping the intersection of campus cultures and equitable outcomes among racially diverse student populations. In S.D. Museus & U.M. Jayakumar (Eds.) Creating campus cultures: Fostering success among racially diverse student populations, (pp.1-27). New York, NY: Routledge

Rankin, S. R., & Reason, R. D. (2005). Differing perceptions: How students of color and white students perceive campus climate for underrepresented groups. Journal of College Student Development, 46(1), 43–61. https://doi.org/10.1353/csd.2005.0008

Solórzano, D., & Villalpando, O. (1998). Critical Race Theory: Marginality and the Experiences of Students of Color in Higher Education. In D. Solórzano, & A. C. Torres, Sociology of Education: Emerging perspectives (pp. 211-224). Albany, NY: State University of New York Press.

3. TASK 3: Recode the variables as needed and run descriptive analyses of all relevant variables and calculate correlation matrices

a. As part of your descriptive analysis, you and your readers need a clear understanding of where the data came from and how they were gathered. Therefore, include in your paper a description of the DATA SOURCE(S).

i. For instance, make sure you include an explanation that the data come from all students who (1) took the 2006 Senior Survey (CSS), (2) identify as something other than white (racial/ethnic minorities in the sample), and (3) for whom there were matching Freshman Survey (TFS) records. Make your description robust yet succinct.

ii. IMPORTANT: In contrast to Paper 1, for Paper 2 you will use a larger data set that contains records from individuals of all racial/ethnic minorities.

b. Subsequent to your description of the data source, you and your reader need an overview of the nature of VARIABLES, how they are coded, and any notable trends in the descriptive measures such as means, frequencies, or correlations worth pointing out. Draw on verbiage and description below to write this portion.

c. Include a table with all variables used and descriptive information. But only talk about descriptive statistics regarding the variables that are important to your argument.

d. Tell your readers the steps you took to review and verify that the data are appropriate for regression analysis (for example, any issues with high correlations).

e. Consider how to communicate the variable names and labels in meaningful ways to your readers. If reporting actual variable names, consider crafting new names for them. You might create duplicate or recoded variables to keep track of this in your own data analysis.

f. HERE ARE THE VARIABLES WE'LL USE: i. Dependent Variable:

1. TransImpetCSS: This is a student’s Transformational Impetus score from the CIRP Senior Survey (CSS). It is a scale variable, comprised of 7 student objectives: the goals of influencing the political structure, influencing social values, helping others who are in difficulty, becoming involved in programs to clean up the environment, participating in a community action program, helping to promote racial understanding, and becoming a community leader. It is measured on a scale of 7 to 28.

ii. Independent Variables1. Control Variables:

a. TransImpetTFS: Transformational Impetus from the CIRP Freshman Survey (TFS). This is the same as the CSS Transformational Impetus score, used to control for students’ beginning, or baseline, measure.

b. SEX (Recode the variable to reflect a simple binary 0 and 1 according to which gender will be the reference.)

i. Existing coding: ii. 1 = Maleiii. 2 = Female)

c. RACEGROUP (Recode this variable into a simple binary variable 0 vs. 1 of white and minoritized racial/ethnic background according to which gender will be the reference.)

i. Existing coding: ii. 1= American Indianiii. 2= Asianiv. 3= Blackv. 4= Hispanicvi. 5= Whitevii. 6= Otherviii. 7= Two or more race/ethnicity

d. SLFCHG01 (Treat as continuous variable. Compared with when you first started college, how would you now describe your ability to get along with people of different races/cultures?)

i. 1= Much weakerii. 2= Weakeriii. 3= No changeiv. 4= Strongerv. 5= Much stronger

e. SLFCHG18 (Treat as continuous variable. Compared with when you first started college, how would you now describe your interpersonal skills?)

i. 1= Much weakerii. 2= Weaker

iii. 3= No changeiv. 4= Strongerv. 5= Much stronger

f. COLACT02_9406_new (Act in College: Attended racial/cultural awareness workshop?)

i. 0= Not markedii. 1= Marked

g. COLACT13_9406_new (Recode to simple binary. Act in College: Had a roommate of different race/ethnicity?)


h. COLACT17_9406_new (Recode to simple binary. Participated in an ethnic/racial student organization?)


i. HPW15 (Treat as continuous variable. Hours per Week: Socializing with friends)

i. 1= Noneii. 2= Less than 1 houriii. 3= 1 to 2 hoursiv. 4= 3 to 5 hoursv. 5= 6 to 10 hoursvi. 6= 11 to 15 hoursvii. 7= 16 to 20 hoursviii. 8= Over 20 hours

j. HPW26 (Treat as continuous variable. Hours per Week: Working (for pay) off campus)


k. HPW27 (Treat as continuous variable. Hours per Week: Working (for pay) on campus)


2. Climate Variables:a. HostileClimateScale: This is a scale variable, comprised of 4 items

that ascertain students’ perception of a positive (friendly, socially inclusive, improving, caring) or negative campus climate (hostile, socially exclusive, worsening, impersonal). From the CIRP Senior Survey (CSS).

i. It is measured on a scale of 4 to 20, with higher scores indicating more negative climates (to match the hypothesis that students may react to hostile climates with greater transformational impetus).

b. CLIMATE3: This is a measure on a scale of 1 to 5 of the degree to which a student perceives the campus as being tolerant or intolerant of diversity. Higher scores indicate a perception of greater intolerance. From the CIRP Senior Survey (CSS).

3. Interpersonal Interaction Variables:a. FAC_INTERACTION: This is a scale variable that measures the

degree to which students have different interactions with faculty members (for instance, inside/outside of class, regular communication, attending office hours, etc.). Measured on a scale from 27 to 73. From the CIRP Senior Survey (CSS).

b. GENACT30: This is an item that measures, on a scale from 1 to 3 (from not at all to frequently) the frequency in the last year that a student socialized with someone of another racial/ethnic group. From the CIRP Senior Survey (CSS).

4. TASK 4: Run multiple regression analyses.a. In your paper, explain to your reader the kind of ANALYTICAL PROCEDURE(S) that you took

to answer each of the research questions and explain why it is appropriate to address the question.

b. Run a simultaneous and then a sequential multiple regression analysis to address research questions 1 and 2.

i. Enter the variables in 2 blocks. 1. In Block 1: All control variables and special interest campus climate variables. 2. In Block 2: FAC_INTERACTION, GENACT30.

c. To answer research question 3, center the pertinent continuous variables, create a cross product, and conduct the necessary sequential regressions. Specifically: center FAC_INTERACTION and GENACT30, create a cross product with your new binary race variable, and test for TWO interactions by running a regression model with all the control variables so far, then another block with each of the interaction terms.

i. IMPORTANT: NOTE THAT THIS REQUIRES TWO SEPARATE INTERACTION TESTS.

d. Report the RESULTS in as simple terms as possible, but by providing sufficient technical detail for fellow researchers. Don’t discuss all of the statistics in your software output or even in the tables you opt to include. Discuss in the narrative only the parts consequential to your argument.

e. Include a simple table with regression statistics following APA standards. i. TIP: Use journal articles for examples of how to do this. Do a web search for how to

report MR in narrative.ii. TIP: Don’t copy and paste SPSS output. Put selected statistics in a table. Do a web

search (such “APA regression table template”) to find ideas and templates of how to present necessary statistics.

iii. IMPORTANT: Though it is required you craft some kind of a table with regression results that shows effort to meet APA style, accuracy and completeness is not expected at this time.

iv. TIP: You may not need a table to show the interaction tests for research question 3. It may be sufficient to report the relevant statistics and explain the results in narrative form.

5. TASK 5: Interpret your results and explain what it all means.a. Include a DISCUSSION of your results by explaining what the numbers mean.b. Include an interpretation of the IMPLICATIONS of the findings for researchers and/or

practitioners in plain language. Make sure to revisit the original research problem and question to show your reader what the evidence shows (and any limitations of what it does not show).

Resources: Here is a pretty good guide to how to build APA-compliant tables in MS Word:

http://web.cortland.edu/hendrick/APA%20Making%20Tables%20and%20Figures.pdf This document has a template for reporting of multiple regression models, including sequential

regression, etc.:o people.oregonstate.edu/~acock/tables/regression.doc

Here are some additional ideas and template for regression tables:o http://oak.ucc.nau.edu/rh232/courses/EPS624/Handouts/Table%201%20-%20Regression

%20Example.pdf

http://oak.ucc.nau.edu/rh232/courses/EPS624/Handouts/Table%201%20-%20Regression%20Example.pdf

http://oak.ucc.nau.edu/rh232/courses/EPS624/Handouts/Table%201%20-%20Regression%20Example.pdf

http://web.cortland.edu/hendrick/APA%20Making%20Tables%20and%20Figures.pdf

Solution Report:

EDAD 982: Advanced Quantitative Methods for Educational Administration Research

The writing of this paper is exclusively my own. I completed it alone and/or by consulting published resources, whether in print or online. The totality of any synchronous or asynchronous consultation I had with individuals regarding conceptual and practical steps needed to accomplish the analysis was conducted only with classmates enrolled in this class and shared exclusively through the course discussion forums. I personally manipulated the data and utilized statistical software to perform the analyses reported in this paper. Likewise, I personally wrote the interpretation and presentation of the findings alone without the aid of consultation of any kind.

IntroductionThe impact of college campus climate on the lived experience and educational outcomes of individuals has

long been studied, with plentiful evidence that a hostile campus climate has deleterious effects on the

wellbeing and educational attainment of individuals from groups who are marginalized or historically

underrepresented in higher education (Jayakumar & Museus, 2010). Campus climate is not always readily

apparent though, and so neither are its effects. Individuals from different backgrounds can perceive the

campus culture in very different ways (Rankin & Reason, 2005). What one individual perceives as

generally positive and welcoming may to another be unfriendly and discriminatory. To be sure, such

negative climates for marginalized individuals may not be due to intentional attitudes, behaviors, or

practices. For instance, it is abundantly clear that structural racism can exist even without individual racists

(Bonilla-Silva, 2010). Hurtado and colleagues (e.g., Hurtado, Alvarez, Guillermo-Wann, Cuellar, & Arellano,

2012; Hurtado, Griffin, Arellano, & Cuellar, 2008) have shown that campus climate has many dimensions,

including the historical, organizational, and compositional nature of institutions, along with individual-level

behavioral and psychological aspects. These latter dimensions are often confounded together as ways to

understand the educational environment, yet they are distinct dimensions of the educational environment

(Hurtado et al., 2012). For example, instances of constructive inter-group interaction or alternately

unintentional microagressions can lead to differing reactions of individuals to those episodes.

It has been proposed that one of the ways that minoritized students may respond to oppressive

environments is to develop—or alternately, mobilize within themselves and community—what has been

called “resistant cultural capital” (Solórzano and Villalpando, 1998). Resistant cultural capital refers to

critical navigational skills informed by class, race, and gendered identities that allow students to turn

otherwise oppressive climates into transformational spaces. Resistant cultural capital “highlights the

ingenuity and resourcefulness of students of color who must tap into resources not considered by

traditional forms of [social and academic] capital” (Abrica, 2009, p. 3). One way to operationalize resistant

cultural capital, Abrica (2009) proposes, is through a measure of “transformational impetus” which she

defines as the manifest desire of college students to change the world around them in the interests of

social justice.

The purpose of this study is to explore whether differences in students’ perception of campus climate are

associated with differences in their transformational impetus. Furthermore, prior research shows that

faculty interaction and informal interactions with peers from different backgrounds—more so than formal

curricular or cocurricular interventions such as diversity coursework—have a strong impact on cognitive

and civic outcomes and appear to ameliorate the perception or impact of prejudice (Cole 2007; Cress

2008). Therefore, the study will also test whether these types of personal interactions have an effect above

and beyond the effect of campus climate.

Research questions1. What is the relationship between students’ perception of different dimensions of campus climate

and the degree of their transformation impetus for social change?

2. Do students’ personal interactions with faculty and social interactions with those of another

racial/ethnic group have an effect above and beyond campus climate?

3. If so, do the effects of those personal interactions on transformational impetus depend on the

racial/ethnic background of students?

MethodSource of dataThis study focusses on exploring whether difference in the perception of students in a campus climate are

associated with differences in their transformational impetus. The data has therefore been collected from a

campus environment with focus on different variables that can provide reliable insight on the perception of

students to campus climate. The data focusses on different types of students within the campus and

provides information on the different activities that the students engage in in and out of campus.

VariablesThe data entails different variables which provide information on students and their campus activities. To

enable us to be able to know whether perception difference of students in a campus climate are linked to

transformational impetus, data has been collected on different variables and below is a table which shows

the different variables within the dataset.

Variable Definition

Year Represents the CSS year

YEAR_TFS TFS Year

ACERECODE ACE Recode

SUBJID Subject I.D.

TransImpetCSS Transformation impetus for CSS

TransImpetTFS Transformation impetus for TFS

SEX Gender of the participant

RACEGROUP Race or ethnicity of the participant

SLFCHG01 Change: Ability to get along with people of different races/cultures

SLFCHG18 Change: Interpersonal skills

COLACT02_9406_new Act in College: Attended racial/cultural awareness workshop

COLACT13_9406_new Act in College: Had a roommate of different race/ethnicity

COLACT17_9406_new Act in College: Participated in an ethnic/racial student organization

HPW15 Hours per Week: Socializing with friends

HPW26 Hours per Week: Working (for pay) off campus

HPW27 Hours per Week: Working (for pay) on campus

HostileClimateScale Scale for the hostile climate

CLIMATE3 Climate: Intolerant of Diversity/Accepting of Diversity

FAC_INTERACTION CSS Student-Faculty Interaction Score

GENACT30 Act in Part Year: Socialized with someone of another racial/ethnic

group

All the datatypes of the different variables have been well defined within the SPSS software therefore

allowing for reliable manipulation of the data.

ToolsFor the purpose of finding answers to our research questions, the data collected was entered in SPSS

software and analyzed using different statistical techniques so as to be able to gain insights on the different

research questions presented. SPSS software was used since it has quality automated algorithm and

statistical formulas which make it easier to manipulate and analyze the data.

AnalysisResults and discussionThe analysis within the study has been done based on the different research questions. We first start by

studying the relationship between the students’ perception of different dimensions of campus climate and

the degree of their transformation impetus for social change. This shall be done by drawing 2 bar graphs

between climate dimensions and both TransImpetCSS and TransImpetTFS.

The above graph represents a clustered bar graph which can be used for checking the mean degree of

transformation impetus for social change within different values of campus climate. From the above we can

see that for every dimension of the campus climate the TranImpetTFS is always lesser than the

TransImpetCSS. The means for the both TransImpetCSS and TransImpetTFS are almost the same for all

the climate dimensions and in case there is a difference the difference is quite small. This is to mean that

the degree of transformation impetus is almost the same for all the dimensions of the campus climate.

For the 1st and the 2nd research questions, the statistical procedure to be done is the multiple regression

analysis whereby the TransImpetCSS variable is the dependent variable while the independent variables

are the control variables and special interest campus climate variables for the first research questions and

the FAC_INTERACTION, GENACT30 are the independent variables for the 2nd research question. Using

multiple linear regression would allow us to study the significance of the predictors and have a clue on the

significance of the difference models with regards to predicting the dependent variable which in both cases

is TransImpetCSS.

Based on the multiple regression carried out to answer the first question, the results which were obtained

are as indicated below.

Model Summaryb

Model R R Square Adjusted R Square Std. Error of the

Estimate

Durbin-Watson

1 .343a .118 .116 4.27773 1.836

a. Predictors: (Constant), Climate: Intolerant of Diversity/Accepting of Diversity, Hours per Week: Working (for

pay) off campus, Change: Ability to get along with people of different races/cultures, Hours per Week:

Socializing with friends, Act in College: Attended racial/cultural awareness workshop, Act in College: Had a

roommate of different race/ethnicity, HostileClimateScale, Hours per Week: Working (for pay) on campus, Act

in College: Participated in an ethnic/racial student organization, Change: Interpersonal skills

b. Dependent Variable: TransImpetCSS

From the above results we can see that the adjusted R square for the model is 0.116 which means that the

model only accounts for 11.6% of the variations of the dependent variable. The durbin Watson test for the

model is less than 2 showing that there is evidence for positive serial correlation within the model. The

general significance of the model was also presented using the ANOVA results as shown below.

ANOVAa

Model Sum of Squares df Mean Square F Sig.

1

Regression 9892.470 10 989.247 54.060 .000b

Residual 73964.513 4042 18.299

Total 83856.983 4052

The p-value obtained for the model is less than 0.05 meaning that the model is statistically significant in the

prediction of the dependent variable TransImpetCSS. To be able to study the effects of the different

predictors used, the coefficients of the model predictors had to be looked into. Below is a summary of the

different predictors used and their coefficients. From the p-values we shall also be able to tell whether a

given predictor is statistically significant or not.

Looking at the p-values of the different predictor variables, all the variables are statistically significant

predictors of the dependent variable apart from the HostileClimate Scale which has a p-value that is

greater than 0.05. The different coefficients indicate how the variables change with every unit change in the

dependent variable. Based on the coefficients, the COLACT02_9406_new variable seems to the variable

which undergoes the highest change for every unit change in the predictor variable. It can therefore be

assumed to be the predictor variables which highly affect the dependent variable.

So as to answer the second research question which focusses on whether student’s personal interactions

with others of another racial/ethnic group have an effect above and beyond campus climate. To be able to

study this we also use a multiple linear regression so as to attain the statistical significance of the

independent variables to be used and to study how the independent variables vary with changes in the

dependent variable. The multiple regression model formed had TransImpetCSS as the dependent variable

and the independent variables were GENACT30 and FAC_INTERACTION. Below are some of the results

which were obtained.

From the model summary, the adjusted R square value is 0.296 which tells us that the model only

accounts for 29.6% of the variation experienced by the dependent variable. The Durbin Watson value is

1.921 which is less than 2 thereby indicating presence of positive serial correlation within the model. Other

traits of the model were looked into by studying the ANOVA summary as shown below.

From the above we can see that the regression is statistically significant since it has a p-value of less than

0.05. The coefficients of the independent variables have been given below.

With the p-values obtained in the second model which entails the addition of the GENACT30 and the

FAC_INTERACTION, we can see that the latter is a significant predictor of the dependent variable while

the former is not. GENATCO however seems to change with a much greater value for every unit variation

in the dependent variable.

The last research question is the 3rd research question which mainly concerns itself with how the effects of

those personal interactions on transformational impetus depend on the racial/ethnic background of

students. So as to be able to know this, we had to conduct a regression analysis with regards to the

minoritized race i.e. RACEGROUP=1. The GENACT30 and the FAC_INTERACTION are centered

whereby their means are subtracted from original values. Below are the results which are obtained.

ANOVAa,b

Model Sum of Squares df Mean Square F Sig.

1 Regression 10023.214 10 1002.321 68.244 .000c

Residual 25702.961 1750 14.687

Total 35726.175 1760

2

Regression 10587.652 12 882.304 61.351 .000d

Residual 25138.523 1748 14.381

Total 35726.175 1760

Both of the models from the two blocks are significant meaning that the dependent variable for the

minoritized group can be predicted using the models above.

In the above results, p-values greater than zero represent predictors which are not statistically significant

and as a result cannot be used for the prediction of the dependent variable for minoritized group. When

centered values for the interaction terms are added then the only interaction variable which is significant is

the FAC_INTERACTION variable. With regards to model efficiency, the centered variables added to the

second block improve on the model efficiency since the adjusted R square value is increased when the two

variables are added.

ConclusionRegression model has proved to be a very useful technique in the study of how different variables effect

what may be considered as the dependent variable. For the study which has been performed above, it has

been notices that the addition of interaction terms increases model reliability since it increases the

percentage by which the model affects the variations of the dependent variable which in this case is

TransImpetCSS. For all the different predictor variables within this study, we have seen that there are

variables which are significant predictors meaning that any changes in the variable lead to noticeable

changes in the dependent variable and other predictors which are not significant therefore variations in the

variables do not necessarily have a huge impact on the dependent variable.

ReferencesAbrica, E. (2009). The development of transformational impetus: Exploring the differential impact of an

oppressive campus environment. Unpublished manuscript.

Bonilla-Silva, E. (2010). Racism without racists: Color-blind racism and the persistence of racial inequality in the United States (3rd ed). Lanham: Rowman & Littlefield Publishers.

Cole, D. (2007). Do interracial interactions mater? An examination of student-faculty contact and intellectual self-concept. The Journal of Higher Education, 78(3), 249–281.

Cress, C. M. (2008). Creating inclusive learning communities: The role of student—faculty relationships in mitigating negative campus climate. Learning Inquiry, 2, 95–111.

Hurtado, S., Alvarez, C. L., Guillermo-Wann, C., Cuellar, M., & Arellano, L. (2012). A model for diverse learning environments. In J. C. Smart & M. B. Paulsen (Eds.), Higher education: Handbook of theory and research (pp. 41–122). Dordrecht, Netherlands: Springer. Retrieved from http://link.springer.com/chapter/10.1007/978-94-007-2950-6_2

Hurtado, S., Griffin, K. A., Arellano, L., & Cuellar, M. (2008). Assessing the value of climate assessments: Progress and future directions. Journal of Diversity in Higher Education, 1(4), 204–221. https://doi.org/10.1037/a0014009

Jayakumar, U. M., & Museus, S. D. (2012). Mapping the intersection of campus cultures and equitable outcomes among racially diverse student populations. In S.D. Museus & U.M. Jayakumar (Eds.) Creating campus cultures: Fostering success among racially diverse student populations, (pp.1-27). New York, NY: Routledge

Rankin, S. R., & Reason, R. D. (2005). Differing perceptions: How students of color and white students perceive campus climate for underrepresented groups. Journal of College Student Development, 46(1), 43–61. https://doi.org/10.1353/csd.2005.0008

Solórzano, D., & Villalpando, O. (1998). Critical Race Theory: Marginality and the Experiences of Students of Color in Higher Education. In D. Solórzano, & A. C. Torres, Sociology of Education: Emerging perspectives (pp. 211-224). Albany, NY: State University of New York Press.

€¦ · web viewyour task is to report on your analysis and findings of a research question that...

Documents