Cultural influence on educational value between female and male graduates

Culture and Education

The cultural ideals that an individual develops during childhood remain as he/she grows into an adult, influencing basic functions, like communication, relational styles, and thinking processes, as well as conflict resolution. Therefore, these may have different impacts with regard to education for female and male graduates.

The influence of culture on education in graduate females and males is found through multivariate statistical analysis. Study participants come from twelve online graduate-level courses where females (n = 162) outnumbered male students (n = 31).

Culture and Education

The key cultural proficiency concept is to get a grasp of how far the culture pervades our lives. The cultural ideals that an individual develops during childhood remain as he/she grows into an adult, influencing basic functions, like communication, relational styles, and thinking processes, as well as conflict resolution. However, this awareness will not guarantee application of this knowledge by educators. Mindful practice is required before cultural proficiency principles can be applied. Hence, professional development which endeavors to aid educators in becoming culturally proficient should take place with time; also, it must be closely connected with educators' practical work (Guerra & Nelson, 2011).

0. Purpose of the study

It has been proved that culture influences education; this influence may vary with gender. Thus, this study attempts to determine cultural influence on graduate-level students and difference of its impact on females and males (Guerra & Nelson, 2011; Frazzetto, 2011).

0. Research question

What effect does culture have on educational value between female and male graduates?

1.3. Hypothesis

H1: A statistically significant disparity exists on education value between female and male graduates.

H0: No statistically significant disparity exists on education value between female and male graduates.

2.1. Theoretical framework

This study will be guided by the I-E-O (Input--Environment -- Outcome) college impact model of Astin (1991). This model postulates causal relations between three kinds of variables, namely, inputs (students' background and demographic characteristics brought to college by them), environments (college environments and experiences encountered during college-times by students), and outcomes (at the end of college) (Frazzetto, 2011).

3. Methodology

3.1. Research design

In this study, asynchronous courses were presented in classwork. Such a system comprises a consolidated collection of application instruments that students can access through the Internet. The duration of each course was 16 weeks or one semester, and delivered wholly through the Internet. Faculty responsible for delivering these courses -- a combination of female and male professors -- had prior online teaching experience. Some of the course titles were "Technology Integration in Curriculum and Instruction" and "Foundations of Teaching and Learning." (Nuzhat et al., 2013)

3.2. Sample

281 students in total who had joined up any of 12 online graduation courses delivered by a Virginia State accredited university were invited to take part in the research. Out of these, 193 agreed, resulting in a 68.7% volunteer rate. Females comprised 83.9% study subjects while the rest (16.1%) were males. Majority female enrolment in graduate courses is in line with the reasonably large amount of K-12 educators who are female. In terms of ethnicity, study participants were: 62.7% Caucasians, 30.1% African-Americans, 2.1% Asians, and 5.2% of other ethnic backgrounds. Mean participant age was 39.01 (187 subjects were willing to share this information) (Standard Deviation = 9.87) (Rovai & Baker, 2005).

3.3. Instruments

Study data was collected via a web-based survey, which comprised: (a) the CCS or Classroom Community Scale, (b) self-report of perceived cognitive skills, and (c) several demographic questions pertaining to age, sex, and ethnicity. CCS gauges classroom community and comprises a score of self-report questions examining classroom community. Every question is accompanied by a Likert scale with 5 potential responses ranging from strongly disagree to strongly agree (Rovai & Baker, 2005).

3.4. Data collection

Data collection will be done in the course's last two weeks, as well as for two weeks after semester completion for all courses included in the study, for students to have extensive course exposure. Students had to answer the question on perceived learning and demographic questions on age, sex, and ethnicity on an online form (Frazzetto, 2011; Guerra & Nelson, 2011).

3.5. Data analysis

Data analysis will be conducted through MANOVA or multivariate analysis of variance, and subsequently, discrete ANOVAs for all dependent variables as well as discriminant analysis for ascertaining how precisely gender of students can be identified on the basis of a linear arrangement of the measures. Eta squared statistic was employed for effect size calculation, while Cohen's thresholds were the basis for interpretation (.14- large effect; .06- moderate effect; and .01-small effect) (Rovai & Baker, 2005).

3.6. Threats to validity and reliability

Societal conditions/situations - situational framework impacts nature and kind of information gathered from study participants. Low inference descriptors -- sufficient data evidence may not be supporting inferred categories; also, non-supporting information might be excluded. Maturation and history -- events or changes influence data and changes that take place with time. Setting influences -- different researchers have different impacts on research settings; groups that experience extensive research are differently impacted from non-researched groups (Nuzhat et al., 2013; Ostrosky-Sol's & Lozano, 2006).

3.7. Strengths and weaknesses of the design

There are some limitations to this research. Since only one institute was involved, study participants are not representative of the entire student population throughout the board. This design has the following strengths; Generalization of its findings to research population is possible; organizational, community, and individual samples can be chosen for ensuring that outcomes represent study population; and structural elements which establish how disparities (e.g., gender disparities) are created can be evaluated (Rovai & Baker, 2005; Ostrosky-Sol's & Lozano, 2006).

Culture and Education 5