Black and Hispanic Black and Hispanic Males in the Males in the Online STEM Online STEM Environment Environment By:Katherine ConwayAlyse C. HacheyClaire Wladis

Diversity in Higher EducationAmerican colleges and universities

serve an increasingly diverse college-going population (Baum & Ma, 2007).

Enrollments between 1976-2008 among◦ Asian/Pacific Islander students grew 561%◦ Hispanic student enrollments grew 495%◦ American Indian/Alaskan Native student

enrollments grew 151%◦ Black student enrollments grew 140%◦ White student enrollments grew 34%

(NCES, 2010).

Minority Students In Community CollegesAmong Hispanic and Native American students more than half are enrolled in community colleges along with 44-45% of Black and Asian students (Fast Facts, 2011)

Public two-year colleges are a particularly important: enrolling 55% of students in all MSIs and from 48-64% of students in the enrollment designated MSIs (the non HBCUs and TCUs) (Li, 2007).

The STEM CrisisDuring the decade ending in

2018, occupations in the computer, mathematical science, life, physical, and social sciences are projected to grow more than twice as fast as the average for all occupations in the economy.

The United States will need more than two million new scientists, engineers, mathematicians and technicians (Occupational Outlook, 2010-11).

STEM and Minority StudentsIn science and engineering

underrepresented minorities receive fewer than 18% of baccalaureate degrees, fewer than 15% of masters’ degrees and fewer than 5% of doctoral degrees (NAS, 2007).

Besides Asians in the aggregate, the gains in STEM by other minority groups have been less than impressive (NSF), 2009).

STEM & Community Colleges

The National Academies of Science stated that “the community college with its diverse student population is an integral player in advancing minority participation in STEM” (p. 34, Expanding Underrepresented Minority, 2011).

STEM & Community CollegesUp to 40% of bachelor’s and

master’s degree recipients in science, engineering and health initiate their studies at a community college (Mooney & Foley, 2011).

Slightly more than 12% of STEM jobs in 2018 will be filled by associate degree holders and many more jobs will be held by students with advanced degrees who at some point studied at a community college (Carnevale, Smith, & Strohl, 2010).

STEM & Community CollegesA fifth of all engineering students

earned at least 10 credits at a community college and 40 percent of bachelor's or master's degree graduates in engineering in 1999 and 2000 had attended a community college

In CA almost half of the graduates with science or engineering degrees from the state system got their start at community colleges (Enhancing the Community College Pathway, 2005).

Getting more Community College Students into STEM

Underrepresented minorities in two-year institutions are less likely to major in STEM or complete their degree in STEM (Expanding Underrepresented Minority, 2011).

By 2019 the combined minority population will equal the white population (College Board, 2011).

Lack of PreparationNationally, 42% of students at public two year colleges report taking a remedial course during their first year of college (NCES, 2011).

One study showed that 85% of minority students were directed away from advanced math and science courses by the start of high school (Campbell, 1996).

Lack of PreparationHispanic students are less likely to attend high schools offering trigonometry, much less, calculus.

Students in the lowest SES quintile attend high schools that are less likely to offer any mathematics above Algebra II (Adelman, 2006).

Lack of InformationCommunity college students are often from low income homes and the first generation to attend college; attributes which often contribute to the students lack of familiarity with STEM careers (Fast Facts, 2011; Hill, Petus &

Hedin, 1990; Mestre & Robinson, 1983).

Lack of SupportA quarter of all students who transfer out of STEM majors cite inadequate advising, counseling, and tutoring (Seymour & Hewitt, 1997).

Estimates of student: counselor ratios near 1000:1 (Grubb, 2001).

H.S. Math = NO STEM DEGREE12th graders

scoring at above proficiency in Math

0

5

10

15

20

25

30

35

40

Math Proficiency

AsianWhiteLatinoAf.Amer.Native A.

Black & Hispanic Male Students

19.8% of Hispanic males30.3% of African-American males ages 25-24 had achieved an associates

degree or higher compared to 49% for white males and 70% for Asian males nationally

Across all ethnicities young women are outperforming young men in educational attainment

(College Board, 2011)

Hispanic Males In/Out of High School

Latino males have consistently been more likely to drop out of high school than males of other ethnic groups (Soza 2007;Fry 2009).

Wide disparity depending on place of birth: U.S. natives 12% drop-out, foreign born Hispanics, 37% drop-out.

African American Males, An Endangered Species“Gloomy educational outcomes for African American males:

high rates of suspension,expulsion and grade retention;low graduation rates; overrepresentation in special

education; anddisengagement.” (College

Board, 2011)

African American Males, An Endangered SpeciesIn 2008, African American men represented 5% of all undergraduates in the United States, the same proportion in 1976 (Harper 2006a).

The progress that has been made by African Americans in accessing higher education has been made by women.

Demand for a Community College Degree

Community colleges enroll over 12 million students

44% of all undergraduates Enrollment growth between 2008-2010 was 15%

Meeting Enrollment DemandMore than two-thirds of institutions surveyed cited:◦student demand for flexible scheduling

◦providing access for students who might not otherwise be able to attend college (e.g. because of geographic, family or work-related issues)

as the primary reasons for offering online courses (Parsad & Lewis, 2008).

Online Education and Online Education and Student RetentionStudent RetentionOnline learning growing substantially

◦21% growth rate for online enrollments far exceeds 2% growth in overall higher education (Allen & Seaman, 2010)

◦30% of all students take at least one online course (Allen & Seaman, 2010)

◦97% of community colleges offer online courses (Parsad & Lewis, 2008)

Online Education and Online Education and Student RetentionStudent RetentionAttrition = principal measure of

the efficacy of an online education program

◦Drop-out rates in online courses from 30 to 40% in the U.S. (Tyler-Smith, 2006)

◦Retention in distance education courses 10-20 percentage points lower than Face-to-face courses (Morris & Finnegan, 2008).

◦Connected to overall academic non-success in higher education (Diaz, 2002)

Online Education Online Education and and STEM CoursesSTEM CoursesCommunity colleges playing

critical role in STEM fields◦up to 40% of bachelor’s and master’s

degrees in science, engineering and health initiate at community colleges (Mooney & Foley, 2011).

Little data available on number of STEM courses offered online◦ fully online program in STEM field =17% in

engineering to 31% and 33% in computer sciences and health professions and related sciences (Allen & Seaman, 2008).

◦ No data on # of online STEM courses in general This study = ¼ online courses in STEM fields

Online Education Online Education and and STEM CoursesSTEM CoursesPositives to STEM online courses

◦ Greater access for students◦ Use of computer-based simulations with

modeling environments and access to authentic research data

Negatives to STEM online courses◦ Difficulty doing Laboratory work◦ Notation and courseware systems not

optimal for specific STEM course needs

Very Little research available◦ Small sample sizes; none looking specifically

at retention

PURPOSE OF STUDYPURPOSE OF STUDYIdentify factors that affect black and Hispanic male student persistence and retention in online STEM courses•To what extent is attrition in STEM courses affected by the online environment?

•To what extent is black and Hispanic male success and enrollment in STEM courses affected by the online environment?

METHODOLOGYMETHODOLOGY

The Community College

◦Located in large urban area Diverse Student body from around world 37% African-American, 33% Hispanic,

14% Asian, and 16% Caucasian 2/3 student population = women

◦Offers approx. 120 online courses Over 2/3 in Liberal Arts Tenders online degree in Liberal Arts

METHODOLOGYMETHODOLOGY

122 course sections, half taught online and the other half taught face-to-face

Reduced =only sections with instructor taught both face-to-face and online in the same semester

Reduced = only courses where there were at least three pairs of online and face-to-face course sections taught by the same instructor in the same semester

From Office of Institutional Research

Dataset Overview

Categories N %

face-to-face 1172 56.7online 895 43.3Asian/PI 350 16.9Black 716 34.6Hispanic 563 27.2White 438 21.2F 1318 63.8M 749 36.2

Table 1. Dataset Overview

RESULTSRESULTS

Do different types of courses have different retention rates?◦retention was higher in face-to-face

courses compared to online courses, and this difference is highly statistically significant (α=0.01)

◦STEM courses had higher overall retention regardless of delivery method, difference was highly statistically significant (α=0.01).

RESULTSRESULTSWhat effect does the online

environment have on retention in STEM courses?

◦STEM and non-STEM courses had a higher attrition rate online than face-to-face, with STEM courses having a much larger and more highly significant difference in retention rates (α=0.01)

◦Conclusion: Appears gap between face-to-face and online course retention was greater among STEM than non-STEM courses

RESULTSRESULTSTo determine if this interaction was significant, a binary logistic regression was performed

◦Retention rate as the dependent variable and course delivery method and STEM status as the two independent variable

Course delivery type and STEM status were highly statistically significant predictors of course retention (α=0.01)

Interaction between course delivery type and STEM status was a statistically significant predictor of course retention (α=0.05).

•Students in non-STEM courses and in online courses = both much more likely to drop out

•Increased risk of dropping out when moving from a face-to-face to online environment is even greater for students in STEM courses than in non-STEM courses

RESULTSRESULTSA previous study showed that enrollment in online courses varied significantly by ethnicity compared to face-to-face courses.Ethnicity Face-

to-face %

N

Online %

N

z

p

d

White 15.6 207 20.6 206 -1.31 ns -0.13 NonWhite1 84.4 1119 79.4 795 2.81 0.0025** 0.13 ** p < .01 1 Black, Hispanic and Asian Pacific Islander

RESULTSRESULTSTo what extent do enrollments in

online STEM courses vary by ethnicity, compared to face-to-face STEM courses?

◦White students enroll in disproportionately more online STEM courses than other ethnic groups when compared to face-to-face STEM enrollments, and this difference is highly statistically significant (α=0.01).

Ethnicity face-to-face N online N z p d

White 17.20% 208 25.60% 239 -2.15 0.0158 -0.2Asian/Black/Hispanic 82.80% 1000 74.40% 693 4.21 <0.0001 0.21

Table 2: Online Enrollment by Ethnicity

RESULTSRESULTSTo what extent do enrollments in

online STEM courses vary by gender, compared to face-to-face STEM courses?

◦Female students enroll in disproportionately more online STEM courses than other ethnic groups when compared to face-to-face STEM enrollments, and this difference is highly statistically significant (α=0.01).

Ethnicity face-to-face N online N z p d

M 39.80% 482 31.50% 294 2.34 0.0096 0.17F 60.20% 728 68.50% 640 -3.21 0.0007 -0.2

Table 3: Online Enrollment by Gender

RESULTSRESULTSHow do black and Hispanic

male success rates (completed a course with a “C” or better) in online STEM courses compare to face-to-face STEM courses?

◦The gap between black and Hispanic male success rates and those of other ethnic/gender groups narrows online.

face-to-face onlineBlack/Hispanic Males 64.4% 62.5%other 80.2% 70.4%

Table 4: Success Rates by Ethnicity/Gender

RESULTSRESULTSThis phenomenon was tested using a binary logistic regression model:

◦The narrowing of the gap was statistically significant at the α=0.10 level.

Source DF Chi-square (Wald) Pr > Wald Chi-square (LR) Pr > LRcourse delivery type 1 21.038 < 0.0001 21.195 < 0.0001ethnicity/gender 1 28.625 < 0.0001 27.682 < 0.0001course delivery type*ethnicity/gender 1 3.561 0.059 3.579 0.059

Table 5: Type III analysis

•The gap between Black and Hispanic Male success rates and other ethnic/gender groups in STEM courses actually decreased in the online environment in this study.

IMPLICATIONSIMPLICATIONS

This research suggests that increased effort is needed in recruiting men and non-White ethnicities into online courses if we are to achieve completely representative participation in the online environment for all groups.  

Similar analyses should be repeated with larger samples containing a wider range of courses across different college campuses to increase generalizability of findings.

Further investigations could explore why the success gap seems to be smaller in online STEM courses than in face-to-face STEM courses.

For PracticeFor Future Research

LimitationsLimitationsSome of the findings reported in

this study could be institution-specific or course-specific.

Other researchers might classify courses differently based on the quantitative or computational nature of the STEM course.

Final Conclusions from the Final Conclusions from the studystudy Fewer non-White students enroll in online STEM

courses than face-to-face STEM courses.

Fewer men enroll in online STEM courses than face-to-face STEM courses.

The gap between success rates (finishing a course with a “C” or better) for Black and Hispanic men and other groups actually decreased when moving STEM courses from the face-to-face to online environment in this study, suggesting that there may be key features of the online environment that could be implemented more widely to increase Black and Hispanic male success in STEM disciplines. Further research is necessary to see if this result can be replicated in other samples, and to determine why the online environment has such an effect.