Exploring the Theoretical Social Capital ''Deficit'' of ...

International Journal of Engineering Education Vol. 30, No. 4, pp. 822–836, 2014 Printed in Great Britain

0949-149X/91 $3.00+0.00 # 2014 TEMPUS Publications.

Exploring the Theoretical Social Capital ‘‘Deficit’’ of First Generation College Students: Implications for Engineering Education* JULIE P. MARTIN Department of Engineering and Science Education, M-15A Holtzendorff Hall, Clemson University, Clemson, SC 29634, USA. E-mail: [email protected]

MATTHEW K. MILLER Department of Engineering and Science Education, M-01 Holtzendorff Hall, Clemson University, Clemson, SC 29634, USA. E-mail: [email protected]

DENISE R. SIMMONS Myers-Lawson School of Construction (MC 0188), 310A Bishop-Favrao Hall, Virginia Tech, 1345 Perry Street Blacksburg, VA 24060. USA. E-mail: [email protected]

This paper investigates social capital, that is, resources accrued through relationships, of engineering students based on their generational status in college. We administered a ‘‘Name and Resource Generator’’ instrument adapted from the field of sociology to a sample of 1,410 engineering undergraduates from five U.S. universities. Quantitative analysis of results revealed many statistically significant differences in the social capital characteristics and accessed resources for First Generation College students (FGC) compared to Continuing Generation College (CGC) students. While some of these results were theoretically anticipated, we also present unique findings regarding (1) the prevalence of available and accessed resources for FGC students, and (2) the type of individual (known as an ‘‘alter’’) providing the engineering-related resources. The retrospective nature of the study allowed us to draw conclusions about the nature of these resources and alter types both during and before undergraduate engineering studies. These results represent a significant theoretical contribution that engineering education stakeholders can use to enhance outreach, recruitment and retention efforts to help grow and diversify the field. Keywords: social capital; first generation college students; resources; alters; engineering

1. Introduction Access to information, resources and opportunities about engineering are critical to students’ decisions to enter undergraduate studies in the field. Our research focuses on understanding the ways in which first generation college students (defined as those whose parents do not have a four year degree) [1] develop and maintain social capital needed for entry and persistence in undergraduate engineering studies. It is well established that first generation college (FGC) students possess limited social capital—that is, resources accrued through social networks— compared to their continuing generation college (CGC) counterparts, and that this ‘‘deficit’’ constitutes a significant barrier to accessing the necessary information and opportunities for successfully pursuing higher education [2, 3]. FGC students, however, represent a growing population in the United States [4, 5]; approximately 60% of all undergraduates are FGC students. As engineering has been referred to as privileged and even as a ‘‘closed club’’ [6], another significant barrier to engineering for 822

FGC students is not having a parent/guardian knowledgeable about college and engineering to help them with this major life transition. Considering these points, the fact that FGC students are an understudied demographic in the engineering education literature [7] is troubling. If engineering educators are to assist first generation college students, then a new paradigm needs to be developed. Understanding the implications that social capital can have for these students who have long been known to be at risk for pursuing and persisting in college can be very important for stakeholders in engineering outreach, recruitment, and retention who aim to lead efforts for inclusivity and diversity. While directing engineering recruitment and retention programs as well as teaching at an institution with a large percentage of FGC students, the first author witnessed the daily impact of these social capital inequities on this often over-looked demographic. These experiences led her to conduct extensive qualitative research in an effort to gain a deeper understanding of how engineering students develop and use social capital in making decisions to * Accepted 23 February 2014.

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enter and persist in undergraduate studies. By identifying what has succeeded in supporting FGC students’ decisions to enter and persist in engineering studies, we are able to contribute to the cycle of connecting educational research, theory and practice. Our prior research has elucidated various differences in the quality and quantity of social capital of engineering students based on parental education attainment [7–10] and in the strength of ties to a group [11]. By studying students who persist in undergraduate engineering studies, we have begun to learn how and why these students develop and use social capital to enter and persist in engineering. For example, we have demonstrated that FGC students:

2.

 Lack access to the same social supports for college career plans as continuing generation college students [8];  Perceive themselves as autonomous in seeking information about engineering, often turning to books or internet sources rather than through social interactions [7];  Are greatly influenced by high levels of emotional support from kin [10, 12] in entering and persisting in engineering studies, although some perceive their families as active inhibitors of their engineering studies [12];  Use the social capital in pre-college and postsecondary school personnel and programs to a greater extent than their continuing generation counterparts [8, 9];  Are less likely to utilize or have more difficulty in recognizing university support resources because they have little practice in doing so [9].

Research investigating questions about social capital in engineering education is limited. In addition to findings from our own prior work highlighted in the previous section, we do know that social capital is linked to many benefits for engineering students, such as increased retention, academic achievement, academic performance, and engineering identity [13]. Others have shown positive influences of social capital beyond the undergraduate experience, such as helping engineering graduates integrate into the professional workplace [14]. The focus of the present study is to gain a deeper understanding of how social capital influences students to decide to pursue engineering, thus we utilize Lin’s Network Theory of Social Capital [15] and focus on the social networks of individual students. Lin describes social capital from a perspective that emphasizes the social network of an individual, or ‘‘ego,’’ and their network of contacts, or ‘‘alters’’ [16–18]. Though resources can be exchanged between egos and alters in the network, it is usually alters of a higher social position or status who actually provide ego with a unique resource, as alters from equal or lower positions/statuses typically provide resources to which ego already has access. In thinking of social position as a pyramid, fewer individuals are located relatively ‘‘high’’ on the pyramidal structure (e.g., Ego 1 in Fig. 1); these individuals enjoy greater access to and control of resources compared to the larger number of people in relatively lower structural positions (e.g., Ego 2 in Fig. 1) [15]. In the context of the present study, ego is an undergraduate engineering student and his/her network of alters are people who influence his/her decisions to pursue and persist in engineering (e.g., parents, peers, teachers). Where ego is initially located in the social structure is largely dependent on either inheriting their parents’ position (termed ‘‘ascribed position’’) or one that ego has achieved for him/herself (termed ‘‘attained position’’) [15]. According to Lin, ego

Until now, we have been unable to quantitatively describe these differences in terms of specific social capital characteristics, network characteristics, or accessed resources. Here, we will expand on our prior findings by identifying differences in the social capital constructs of strength of ties, homophilious vs. heterophilious relationships, and embedded resources related to engineering. In this paper, we significantly contribute to understanding the social capital development of first generation college students by empirically investigating the differences in the social capital characteristics, access to resources and types of resources between FGC and CGC engineering students at two time points: 1) when making the decision to major in engineering and 2) while enrolled in a four-year engineering program. We investigate the following research questions in this paper: 1.

What social capital characteristics differentiate the networks of FGC and CGC students?

3.

What differences, if any, are there in access to engineering-related resources for FGC and CGC students? Do FGC and CGC students use different types of people (social capital ‘‘alters’’) when pursuing engineering studies?

The answers to these questions will provide stakeholders in engineering education with additional valuable information that can be used to better target engineering outreach, recruitment and retention efforts.

2. Theoretical framework: Network theory of social capital

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able to reach higher quality engineering social capital, as indicated by dashed lines in Fig. 2.

3. Methods 3.1 Survey instrument

Fig. 1. ‘‘Pyramid’’ of Social Capital (adapted from [15]).

starting at a higher position is more likely to have access to better and more highly valued social capital resources. This better position of origin basically gives ego a ‘‘head start’’ at gaining more social capital and moving to a position of higher status, which Lin refers to as a ‘‘structural advantage’’ [15]. Applying these terms to Fig. 1, we would say that Ego 1 has a higher ascribed position related to engineering and thus has a structural advantage over Ego 2. The Network Theory of Social Capital also states that inequalities in social capital occur with differential access to social resources, a disadvantaged position in a network, differential activation, or homogenous network characteristics. All these factors are influenced by ascribed traits (such as race, gender, socioeconomic status) that also limit the quantity or quality of resources available [7, 17, 19]. Educational background is specifically considered a demographic factor that can explain inequalities in social capital [19]. According to social capital theory, CGC students are more likely to have a structural advantage over FGC students. Based on Lin’s theory (and our own prior work), a lower social position related to engineering indicates that FGC students are less likely to have alters with either engineering-related resources or influence to help them in pursuing their engineering interests, goals and studies. Additionally, FGC students are theoretically more likely to have more homophilious connections (i.e. alters that are like themselves), thus FGC students would less often be

Drawing upon tools developed in the field of sociology [17, 20, 21] we created a ‘‘Name and Resource Generator’’ (NRG) instrument tailored to specifically identify engineering-related social capital (people and resources) that current engineering students possess in their networks at two time points: 1) before deciding to major in engineering, and 2) at the time of survey participation as an engineering undergraduate student. These time points will be referred to as 1) ‘‘before engineering’’ or ‘‘TP1’’ and 2) ‘‘during engineering studies’’ or ‘‘TP2’’. Other papers provide more details about the development [22] and validation [23] of this NRG instrument. The NRG instrument consists of a ‘‘Name Generator’’ section and a ‘‘Resource Generator’’ section. The Name Generator is inherently biased toward stronger ties because participants are asked to create a list of names that first come to mind that represent these ties [17], whereas the Resource Generator compliments the Name Generator section by eliciting additional information about the specific resources accessed by participants and the alters who provided them (including weaker ties that participants may not have initially thought of when asked to provide a list of names) [17]. The resources may or may not have been provided by someone named in the Name Generator section, so the inclusion of these items provides us with a more complete picture of the participants’ availability and access to engineering-related resources including those from relationships they may not have originally thought of when completing the Name Generator. 3.2 Measured social capital characteristics The NRG consists of multiple social capital measures related to the goal specificity (in this case engineering academic and career decisions) as emphasized by Van der Gaag and Snijders [24].

Fig. 2. Strong vs. Weak Ties to Alters (adapted from [15]).

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Table 1. Social Capital Constructs and Operationalization in NRG Instrument

Name Generator

Resource Generator

Social Capital Construct

Operationalization

Sources adopted or adapted from

Network Size

Number of specific people listed (up to 8)

[15–17, 20, 25, 26]

Heterophily

Contacts of a different race/ethnicity (cross-racial) [16, 18, 20, 25] Contacts of a different gender (cross-gender) [16, 18, 25] Contacts of a different age (cross-age) [16, 25, 27]

Strength of Ties

Frequency of communication Length of relationship Kin vs. non-kin

Embedded Resources

Range, variety, composition of resources related to [17, 21, 26, 31] (resources engineering studies and careers modified to reflect those relevant to engineering pursuits)

Consistent with this notion, four primary constructs were adopted from social capital literature and used to measure and describe social capital characteristics of undergraduate engineering students: network size, strength of ties, heterophily and embedded resources. The constructs and operationalization for each portion of the survey are shown in Table 1. Network size represents how many people (alters) the engineering student participants listed by name as being influential to their engineering academic and career decisions. According to the Network Theory of Social Capital [19], a larger network size generally provides access to a wider variety of information, influence, and resources. The concept of heterophily describes how alters differ from ego. Though a large network is advantageous, possessing many alters similar to ego may provide but a marginal benefit if the alters have access to the same people, resources, and/or information as ego. The more diverse or heterophilious ego’s network is, the higher the likelihood of access to new, different, and/or better social capital. The concept of strength of ties represents how close or strong ego’s relationship is to his or her alters. Family relationships (kin), frequent communication and long-term relationships indicate ‘‘strong’’ ties. A close ego-alter relationship may be characterized as that in which there is a large amount of trust, and as a consequence, alters may be more likely to go out of their way to assist ego. However, similar to the concept of heterophily, these stronger relationships are more likely to result in a significant overlap in the social networks of both the alter and ego; while the alter may be more willing to do something for ego, the benefit of this action may only be marginal. ‘‘Weak’’ ties are more likely to exist when ego and alter are non-kin, engage in less frequent communication, and have known each other for a short time. Weaker ties theoretically may provide more benefits to ego because there is likely to be less overlap between the people and resources in the networks of alter and ego.

[28, 29] [28, 29] [20, 30]

The concept of embedded resources represents different types of resources available in ego’s network. The specific resources included in this study represent ways in which participants may learn of information and opportunities that help them either gain an advantage or achieve a goal. The resources in the survey instrument are not intended to provide an exhaustive list of every type of engineeringrelated resource a student may access during his or her life, though the resources at each time point (19 before college, 16 during college and 11 alter types as shown in Table 2) do provide a good snapshot of the different types of resources to which egos have access and from which alters the resources are primarily provided (and/or provided to a greater extent to one group than the other). 3.3 Participants A total of 1,410 participants were recruited from five institutions in the US using stratified sampling to ensure participation among various underrepresented groups in engineering. In total, 44% of our participants identified as female and 56% as male. Twenty nine percent of the participants reported being FGC while the other 71% were CGC. With regard to racial/ethnic backgrounds, 56% of participants identified as White/Caucasian, 23% as Asian or Asian American, 6% as African American, 20% as Hispanic or Latino, 1% as American Indian or Alaskan Native, 1% as Native Hawaiian or Pacific Islander, and 1% as Other. (Note that these percentages add up to more than 100% because participants were given the option to select all racial/ethnic backgrounds with which they identified). 3.4 Statistical analysis Data was analyzed using SPSS version 21 software. Generational status in college was used as the grouping variable to test for significant differences in the assortment of social capital variables previously described. For interval-type variables (e.g., percent Non-Kin contacts), a Mann-Whitney U test was used to compare non-normal data between two

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Table 2. Engineering-related resources and alter types included in the NRG Before Engineering

During Engineering Studies

 Helped you get an internship in high school  Took you to their place of engineering work  Paid for your participation in a science/engineering camp, program, or contest  Helped you study for the SAT or ACT  Took you on a college visit  Bought you engineering-related toys or equipment (e.g., chemistry set, Legos, robot, K’Nex, etc.)  Helped you with a science/engineering fair project  Took you to museums, exhibits related to engineering  Provided you with college admissions information  Provided or helped you with financial aid information  Helped you learn or research about colleges with engineering programs  Gave you information about or helped you research the various engineering disciplines  Worked at some point in their career as an engineer  Told you about their own work as an engineer  Gave you general information about the type of work engineers do  Talked to you about engineering career options  Recommended courses you should take to pursue engineering  Exposed you to science/engineering experiments  Encouraged you to major in engineering

 Helps you with the content in your engineering courses  Helps you with a specific assignment (homework, project, etc)  Advises you or gives you specific information about the engineering curriculum at your school  Recommends courses you should take  Gives you advice about your academic options  Gives you advice about your career options  Talks to you about their own work as an engineer  Gives you information about the type of work that engineers in your field do  Gives specific advice when you face an academic obstacle  Helps you find/get internships, research experiences, jobs, scholarships, etc.  Provides you with financial support  Takes you to their place of engineering work  Introduces you to people in their professional network  Alerts you to job or graduate school opportunities  Writes you letters of recommendation for scholarships, jobs, internships, or awards  Encourages you to stick to your major in engineering

Both Time Points: Alter Choices Available to Participants       

Parent or guardian Other family member Family friend Peer (e.g., friend, classmate, peer mentor) Middle/High school teacher or counselor Community or technical college personnel College/university professor

groups of each independent variable. For categorical-type variables (e.g., specific resource types), Chi Square tests were used and p-values are reported for tests on the overall variables. For Chi-Square tests on variables with more than two levels, pairwise comparisons were conducted to determine significance between FGC vs. CGC differences on each level of the variable (p < 0.05).

4. Results The results of this study are divided into several subsections according to the research questions. First, we describe the overall participant demographics. 4.1 Participant demographics Table 3 shows statistics for demographic differences between FGC students and CGC students in our study. Groups that include statistically more FGC students also include more students who transferred from a different institution, males, Hispanics, and students from lower-income families (‘‘Lower Medium’’ and ‘‘Low’’ as measured in the NRG). Groups that include statistically more CGC students also include more females, students who knew at least one engineer before going to college, stu-

 College/university personnel (e.g., admissions personnel [TP1], academic advisors [TP2] program directors [both TPs])  Employer or coworker  Camp counselor or club leader  Other  Do not know anyone

dents with at least one parent with an engineering degree, White/Caucasian students, and students from higher-income families (‘‘High’’ and ‘‘Upper Medium’’ as measured in the NRG). No significant differences were found based on the year in school or university class designation. Note that 2.5% of the FGC participants (10 participants) indicated having at least one parent with an engineering degree. We can postulate several explanations for this: 1) the parent may have earned a two-year engineering technology degree, 2) the parent may have an engineering-related job or a job as an engineer without actually earning a fouryear degree, 3) the participant may have been referring to a step-parent, or 4) the participant may have simply filled in their parents’ education incorrectly. Research Question 1: What social capital characteristics differentiate the networks of FGC and CGC students? 4.2 Network size As shown in Table 4a, we do not observe any differences between FGC and CGC students with respect to the size of their networks (measured by number of people listed in the Name Generator

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Table 3. Chi-Square Statistics for FGC vs. CGC Participant Demographics Group Percentages* Demographic Variables

Overall p-value

Variable Categories

CGC n = 1,002

FGC n = 408

Transferred from a different institution

0.006

Yes No

13.8% 86.2%

19.6% 80.4%

Gender

0.001

Female Male

46.9% 53.1%

36.8% 63.2%

Knew engineers before college

< 0.001

Yes No

77.2% 22.8%

51.0% 49.0%

Parent with engineering degree

< 0.001

Yes No

36.8% 63.2%

2.5% 97.5%

Race

< 0.001

Family Income Level

< 0.001

American Indian or Alaskan Native Asian or Asian American Black or African American Hispanic or Latino/a Native Hawaiian or Pacific Islander White or Caucasian Other High Upper Medium Medium Lower Medium Low

1.1% 22.1% 5.8% 14.6% 1.1% 54.4% 1.0% 6.0% 37.4% 37.8% 12.6% 6.2%

0.7% 23.8% 7.1% 31.9% 0.2% 34.1% 2.2% 0.2% 13.0% 32.4% 31.9% 22.5%

* Bold indicates group is significantly higher, p < 0.05.

section of the NRG). This finding applies to both before the students entered engineering and during their engineering studies. 4.3 Strength of ties Data overall demonstrates that before entering engineering studies, FGC students utilize more weak ties in their networks while CGC students have stronger ties. As seen in Table 4b, FGC students had a significantly higher proportion of non-kin contacts in their networks. They also had significantly more contacts with low communication and more contacts that were known for a ‘‘medium’’ amount of time (3–6 years). Conversely, CGC students report significantly less non-kin contacts (i.e., more family members), and significantly more ‘‘lifelong’’ relationships (known 15 years or more) than FGC students. Once the participants became engineering students, however, we did not observe any significant differences between FGC and CGC students on any of the strength-of-ties measures, indicating that once they are in college, both groups arrive at a similar distribution of strong and weak ties, though each group may have developed and/or maintained that distribution differently. 4.4 Heterophily At both time points, FGC students report networks that are more heterophilious in terms of cross-racial ties. Though cross-racial ties is the only statistically significant measure of network heterophily at the first time point, at the second time point we did

observe significantly greater cross-age ties among CGC students than for FGC students. No differences in cross-gender ties were reported at either time point. The data for these findings is shown in Table 4c. Research Question 2: What differences, if any, are there in the access to engineering-related resources for FGC and CGC students? 4.5 Embedded resources—overall access/ availability We investigated embedded resources in several different ways: first by looking at differences in overall availability of resources in students’ networks (Table 4d), and the second by looking at differences in the availability of individual resources students could select from in the Resource Generator section (Table 5 and Table 6). In looking at overall resources (Table 4d), CGC students reported significantly higher overall access to resources in the Resource Generator both before and during undergraduate engineering studies. When looking at the individual resource types in Table 5 and Table 6, we confirm the findings from the overall resource access statistics in Table 4d. Whenever significant, CGC students report significantly higher resource access both before engineering and during engineering studies compared to FGC students. While CGC students reported statistically significant higher access to nearly all of the engineering-related resources, what is remarkable

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Table 4. Mann-Whitney U Test Statistics for Network Size, Strength of Ties, Heterophily, and Embedded Resources (Interval Scale Data) Before Engineering

During Engineering Studies

Group Averages Social Capital Constructs Dependent Variables

p-value*

(a) Network Size

# Names Listed

NS

(b) Strength of Ties

% of Contacts Not Kin % Low Communication % Medium Communication % High Communication % ‘‘New’’ Contacts % ‘‘Medium’’ Contacts % ‘‘Stable’’ Contacts % ‘‘Lifelong’’ Contacts

(c) Heterophily

% Cross-racial % Cross-gender % Cross-age

(d) Embedded Resources

CGC n = 1,002

FGC n = 408

Group Averages p-value*

CGC n = 1,002

FGC n = 408

2.85

2.88

NS

2.57

2.51

< 0.001 0.042 NS NS NS 0.003 NS < 0.001

39.3% 8.9% 18.0% 73.2% 19.0% 12.7% 6.7% 61.5%

48.2% 12.8% 18.9% 68.3% 22.1% 17.8% 9.0% 51.1%

NS NS NS NS NS NS NS NS

40.9% 7.5% 28.0% 64.6% 20.0% 14.7% 6.4% 58.8%

45.3% 7.9% 26.9% 65.1% 19.4% 17.2% 8.9% 54.6%

< 0.001 NS NS

19.3% 41.7% 85.1%

25.6% 38.4% 85.9%

0.014 NS 0.034

20.3% 42.2% 84.1%

24.5% 45.5% 80.4%

% Overall Resource Availability** < 0.001

12.4%

9.9%

< 0.001

13.3%

11.8%

* NS denotes Not Significant, p > 0.05. **Overall resource availability is based on the maximum number of resources a participant could select. For the first time point, this is 19 resources  11 alters = 209; for the second time point this is 16 resources  11 alters = 176. The actual number of resources  alters selected divided by the maximum number gives us the overall resource availability percentage.

about these data is that they show that FGC students still report fairly high access to many resources both before engineering and during engineering studies. Focusing on the resources available to students before they entered undergraduate engineering studies (Table 5), we observe that three of the 19 resources did not differ for FGC and CGC students: alters who helped them get an internship in high school, alters who provided or helped them with financial aid information, and alters who encouraged them to major in engineering. While we might expect high school internships to be more readily accessible to CGC students, this resource has the lowest overall access of any resources, indicating that very few participants overall had access to internships in high school. Conversely, alters who ‘‘encouraged you to major in engineering’’ had the highest overall availability in all student networks, indicating that nearly everyone in our sample had at least one person who encouraged them to pursue a degree in engineering, regardless of parental level of education. Before majoring in engineering, over three quarters of FGC students had access to the resources shown in Table 5a. These resources generally relate to entry-level information about engineering and college, such as: encouragement for studying engineering, help finding college admissions and financial aid information, taking on college visits, and recommending courses to take. More than half of the FGC participants indicated the resources in Table 5b as being available in their networks. Many of these would be available earlier in a student’s life, such as SAT or ACT assistance,

purchasing engineering-related toys/equipment, assistance with a science fair project, and visits to science and engineering-related museums and exhibits. Several resources involved providing assistance in seeking out the most appropriate engineering schools and learning about the various engineering disciplines at their schools of choice. Other resources involve a more long-term outlook of engineering careers (of importance because they can provide students with the motivation to begin framing their goals, such as beginning and persevering in engineering study). Such resources include knowing and speaking with engineers about their profession, and providing students with information about the work of engineers and what career options are available in engineering. About a third of FGC students reported knowing an engineer with whom they could visit at their place of employment or someone who paid for their participation in a science/engineering camp, program, or contest, compared to over 50% of CGC students with access to similar resources. Less than one quarter of FGC students reported knowing someone who helped them secure internships in high school (though CGC students reported similarly low levels of access to such people). These resources are categorized as ‘‘hands-on’’ influences related to engineering as they provide more of an immersion experience but are likely harder to access for all students, particularly for FGC students with lower social positions related to engineering. Focusing on the resources available to engineering undergraduates during the second survey time point (during their engineering studies, shown in

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Table 5. Chi Square Statistics for Embedded Resources before Engineering (ordered from most to least accessed by FGC group) % with Access to the Resource Engineering-Related Resources

CGC n =1,002

FGC n = 408

(a) >75% of FGCs accessed these resources

Encouraged you to major in engineering Exposed you to science/engineering experiments Provided you with college admissions information Provided or helped you with financial aid information Took you on a college visit Recommended courses you should take to pursue engineering

98.1% 91.4%*** 88.8%** 82.7% 85.4%*** 84.4%***

98.5% 83.6% 82.8% 82.4% 76.5% 75.0%

(b) >50% of FGCs accessed these resources

Talked to you about engineering career options Gave you general information about the type of work engineers do Helped you with a science/engineering fair project Bought you engineering-related toys or equipment (e.g., chemistry set, Legos, robot, K’Nex, etc.) Worked at some point in their career as an engineer Helped you learn or research about colleges with engineering programs Told you about their own work as an engineer Took you to museums, exhibits related to engineering Gave you information about or helped you research the various engineering disciplines Helped you study for the SAT or ACT

83.6%*** 86.2%*** 80.1%*** 79.6%***

74.8% 74.0% 70.3% 68.1%

81.7%*** 79.4%*** 79.2%*** 72.2%*** 71.2%***

65.7% 64.7% 60.5% 59.3% 56.9%

60.1%*

54.2%

(c) >25% of FGCs accessed these resources (d) 75% of FGCs accessed these resources

(b) >50% of FGCs accessed these resources

(c) >25% of FGCs accessed this resource

Note: * p < 0.05, ** p < 0.01, *** p < 0.001.

studies were well underway. It is clear that the influence of kin decreased during engineering studies, with friends and education professionals (e.g., teachers, academic advisors) providing the balance of the resources accessed. Conversely, before beginning and after undertaking engineering studies, FGC students responded that education personnel provide access to significantly more of their resources. No differences were observed in resources provided to FGC vs. CGC students by friends or from other alter types. We then used this overall view of the primary engineering related resources accessed by FGC and CGC students to expand our findings. Specifically, we sought to determine which of the alters (out of all 11 rather than the combined groups in Table 7) provided both FGC and CGC students all 35 resources listed in the resource generator section of our instrument. Overall, it is clear in Table 8 that

before deciding to major in engineering, CGC students accessed the majority of their engineering-related resources from their parents significantly more often than FGC students for every resource in the survey (p < 0.001). Though FGC students also primarily accessed approximately half of their resources via parents and guardians, education professionals (middle and high school teachers and counselors) and extended family and friends made up the gap in social capital created that existed when parents did not or were not able to provide a resource. Furthermore, Table 8 shows that community or technical college personnel, employers and coworkers had a significantly greater influence on FGC students than their CGC counterparts. Even though these alters were not the primary resource for FGC students, the fact that FGC students used them at significantly higher levels than CGC students

Table 7. Overview of Resources Provided by Various Alter Types Before Engineering

During Engineering Studies

Group Averages

Group Averages

% of Resources Provided By

p-value

CGC n = 1,002

FGC n = 408

p-value

CGC n = 1,002

FGC n = 408

Kin Friends Education Personnel Other

< 0.001 NS < 0.001 NS

51.5% 15.7% 27.6% 4.3%

38.2% 16.7% 37.8% 5.6%