ArticlePDF Available

Problematizing college internships: Exploring issues with access, program design and developmental outcomes

Authors:

Abstract and Figures

Internships are widely promoted as a "high-impact" practice, yet the literature is limited by insufficient attention to the impacts of program format on student outcomes. In this mixed-methods study survey (n=1,129) and focus group (n=57) data from students in three U.S. colleges were analyzed using inductive thematic analysis, chi-square, and hierarchical linear modeling to document intern characteristics, access-related problems, program structure, and impacts on student outcomes. Results indicate that internship participation varied significantly by race, institution, enrollment status and academic program, and that high degrees of supervisor support, supervisor mentoring, and relationship between internships and academic programs were significant predictors of students' satisfaction with internships and perceived value for their career development. Consequently, colleges and universities should work to ensure equitable access to internships and that additional research be conducted on how individual, institutional, and programmatic factors influence student participation in internships and their subsequent outcomes.
Content may be subject to copyright.
Problematizing college internships: Exploring issues with
access, program design and developmental outcomes
MATTHEW HORA1
ZI CHEN
University of Wisconsin-Madison, Madison, USA
EMILY PARROTT
Teaching Trust , Dallas, Texas USA
PA HER
University of Wisconsin-Madison, Madison, USA
Internships are widely promoted as a “high-impact” practice, yet the literature is limited by insufficient attention to
the impacts of program format on student outcomes. In this mixed-methods study survey (n=1,129) and focus group
(n=57) data from students in three U.S. colleges were analyzed using inductive thematic analysis, chi-square, and
hierarchical linear modeling to document intern characteristics, access-related problems, program structure, and
impacts on student outcomes. Results indicate that internship participation varied significantly by race, institution,
enrollment status and academic program, and that high degrees of supervisor support, supervisor mentoring, and
relationship between internships and academic programs were significant predictors of students’ satisfaction with
internships and perceived value for their career development. Consequently, colleges and universities should work to
ensure equitable access to internships and that additional research be conducted on how individual, institutional, and
programmatic factors influence student participation in internships and their subsequent outcomes.
Keywords: Internships, program structure, access, student outcomes
Internships are widely perceived around the world as an influential type of work-based learning (WBL)
that provide benefits to students, educators, and employers alike (McHugh, 2017; Rose, 2013; Silva et al.,
2018). The advocacy behind internships for college and university students is often predicated on the belief
that these off-campus experiences provide students with valuable professional experience and networks,
enable educators a venue for their students to translate academic knowledge to real-world situations, and
provide employers with a pipeline of new talent - sometimes described as a “win-win-win” situation
(Bailey, Hughes & Barr, 2000; National Association of Colleges & Employers, 2018a). In the U.S., interest
in internships has risen dramatically since the early 2000s with their designation as a “high-impact” practice
that leads to students’ academic and career success (Kuh, 2008; Parker, Kilgo, Sheets & Pascarella, 2016),
leading many state governments, colleges and universities, and workforce development boards to promote
internship programs as a desirable solution to regional education-to-employment problems.
However, while the international research literature on internships is promising, the fields of higher
education and work-based learning (WBL) understanding of internships is limited in several ways. First,
terminological inconsistencies such as poor or nonexistent definitions and/or compound questions make
problematic the reported internship participation rates, as well as the validity and reliability of empirical
studies (Silva et al., 2018; National Survey of Student Engagement, 2018). Second, in the U.S., little research
exists on internships outside of 4-year universities, with little known about these programs in 2-year
institutions and minority-serving institutions such as Historically Black Colleges and Universities
1 Corresponding author: Matthew Hora, matthew.hora@wisc.edu
HORA, CHEN, PARROTT, HER: Internship access, program design, and development outcomes
International Journal of Work-Integrated Learning, 2020, 21(3), 235-252 236
(HBCUs). Third, although scholars and analysts have raised legal and ethical questions regarding unpaid
internships (Curiale, 2009; Perlin, 2012), few studies have examined the nature of specific barriers to
internship participation, particularly with respect to low-income, first-generation, and/or minoritized
college students. Fourth, while long-term labor market outcomes such as wages and employment status
are important outcomes of internships to investigate, near-term effects on student satisfaction and career
development are equally important yet rarely studied (McHugh, 2017). Finally, while work-integrated
learning (WIL) differs from WBL in its being focused on campus-based learning experiences, there are
enough similarities for insights into what constitutes high-quality WBL can also shed light on how to design
effective WIL opportunities for college students (Atkinson, 2016; Jackson, 2018).
To address these gaps in the literature, the research team launched a mixed-methods translational research
project in the Spring of 2018 in partnership with three institutions in the U.S.a comprehensive university
that is also a predominantly white institution (PWI), a technical college, and a historically black college and
university (HBCU). Data from an online survey (N = 1,129) and focus groups (N = 57) with students nearing
graduation were analyzed to answer the following research questions: (1) how many students are
participating in internship programs, and does participation vary by student demographics, academic
status, or life/employment situation? (2) what barriers exist for students to participate in internship
programs? (3) what is the structure and format of internship programs? and, (4) how, if at all, is program
structure and format associated with student satisfaction with their internships and their estimation of the
value of the internship on their career development?
BACKGROUND
What is known about internships and their impacts on college students? First, the influential National
Survey of Student Engagement (NSSE) survey in the U.S. indicates that 49% of seniors in 4-year institutions
completed, or are in the process of completing, an internship (National Survey of Student Engagement,
2018). However, the NSSE survey uses a compound question to inquire about participation, asking students
to report their involvement in an “internship, co-op, field experience, student teaching, or clinical
placement” – each of which has unique formats, regulations, and educational goals, rendering them distinct
(and incomparable) types of co-curricular experiences (Hora, Wolfgram & Thompson, 2017; Silva et al.,
2016). Thus, claims based on NSSE data that internships are a high-impact practice that lead to student
engagement and success (Kuh, 2008) should be interpreted with caution, given that the survey item
encompasses a diverse array of (undefined) experiences that can be interpreted in a myriad of different
ways by survey respondents.
Despite these methodological issues, researchers have long examined the question of which students are
participating in internship programs. For example, Knouse, Tanner and Harris (1999) showed that higher
achieving students are more likely to get an internship compared to students who are lower achieving,
while other scholars have found that internship participation varies by student characteristics such as
gender, race/ethnicity, socioeconomic status, and achievement levels (Binder, Baguley, Crook, & Miller,
2015). A related issue is whether or not barriers exist for some students particularly low-income students
to access these opportunities in the first place a concern that led Curiale (2009) to argue that the growing
HORA, CHEN, PARROTT, HER: Internship access, program design, and development outcomes
International Journal of Work-Integrated Learning, 2020, 21(3), 235-252 237
labor market advantage of completing an internship and the rising number of unpaid opportunities was
contributing to a class divide in the U.S. (see also Parks-Yancy, 2012). However, little research exists on the
barriers that inhibit access to internships.
Another question facing the field pertains to the structure and format of internship programs themselves.
Too often, internships are viewed as a singular event that students take or not, with little clarification about
specific features of an internship. Consequently, internships risk becoming a “black box” whose interior
mechanisms are poorly understood (Loeb et al., 2017; Silva et al., 2018). Several structural features of
internships have been identified as especially influential: compensation, supervisor support and
mentoring, task clarity, and links to academic programs (McHugh, 2017). For instance, researchers have
shown that supervisor mentoring (i.e., providing clear directions and feedback) and supervisor support
(i.e., how well the supervisor cares about employee well-being) are positively related to students’ career
development and satisfaction with their internship (D’Abate, Youndt, & Wenzel, 2009).
Researchers have also examined the impacts of the work that interns perform. Beenen and Rousseau (2010)
found that task clarityor providing interns with clear expectations for tasksenhances learning and
pursuit of careers in the same field as the internship. Additionally, the stronger a student’s coursework is
linked to internship tasks, the more students will gain from the experience (Narayanan, Olk & Fukami,
2010). Each of these studies highlights a key issue in the world of WIL and internships that simply making
them available does not guarantee that the experience will have a strong and positive impact on student
outcomes. Instead, much depends on how they are structured by educators and employers, and
experienced by students (O’Neill, 2010).
In terms of the potential impacts an internship may have on college students, many scholars focus on
employment status, engagement and completion (Kuh, 2008), post-graduation wages (Saniter & Siedler,
2014), and the desirability of former interns in the job market (Nunley, Pugh, Romero, & Seals, 2016).
However, scholars examining non-monetary or employment-related outcomes of internships and related
practices have found they contribute to positive academic outcomes such as improved grades (Parker et
al., 2016), the quality of classroom discussions (Weible & McClure, 2011), and improvements in what some
call the developmental value of an internship, or students’ vocational self-concept and their confidence in
their future careers (Knouse et al.,1999; McHugh, 2017). These studies highlight the need to conceptualize
the potential impact of internships in ways that go beyond employment and wages.
CONCEPTUAL FRAMEWORK: A DEVELOPMENTAL PERSPECTIVE
The potential economic, psycho-social, and academic outcomes of internships are not guaranteed simply
because an institution makes them available and/or mandatory, as student experiences can range from an
abysmal summer spent pouring coffee and making copies to transformational experiences that embody the
best practices of experiential education (Perlin, 2012; O’Neill, 2010). This is one reason why treating
internships as a simple binary question (i.e., did you take an internship during college yes or no?) is both
an empirical and conceptual mistake.
A process-oriented perspective on internships was advanced by management scholars Narayanan, Olk and
Fukami (2010) in a study of internship programming at a Portuguese university. Based on the contention
that most internship research ignores the interplay among the three actors involved in the experience
HORA, CHEN, PARROTT, HER: Internship access, program design, and development outcomes
International Journal of Work-Integrated Learning, 2020, 21(3), 235-252 238
students, university, and the company a framework is presented in this paper that enables the testing of
specific antecedent and processual factors that may contribute to particular student outcomes. Sweitzer
and King (2013) outlined four stages of internship experience that included anticipation, exploration,
competence and culmination. In focusing on how students themselves construct meaning of their
experiences, and also the importance of interns being introduced into new (and potentially jarring) socio-
cultural and professional contexts, this framework is consistent with developmental perspectives in
counseling and vocational psychology that also emphasize constructivist and processual accounts of
development (Savickas et al., 2009).
In this paper, these developmental and process-oriented approaches are built upon by conceptualizing
internships as an experience that is strongly shaped by initial access (or lack thereof) and program structure,
with impacts that include both cognitive (i.e., satisfaction and perception of personal development) and
career-related outcomes. The goal in advancing such an approach is to move beyond an uncritical
acceptance of internships as a high-impact practice, by problematizing the act of acquiring an internship
and the structure of the internships themselves, both of which may or may not lead to positive student
outcomes.
METHODS
The study reported in this paper employs a concurrent mixed-methods design, where both qualitative and
quantitative data were collected and analyzed simultaneously to address the research questions (Teddlie
& Tashakkori, 2003). The dataset used includes both a survey and focus groups with students at three
postsecondary institutions: a comprehensive predominantly white institution (PWI) with an
undergraduate headcount of 4,168 students (hereafter named Institution A), a technical college with 20,801
students (Institution B), and an HBCU with 2,038 undergraduates (Institution C). To focus on students’
experiences in internships and not on related programs, students from programs with a required clinical
practicum (e.g., teacher education) or apprenticeship programs were excluded from the sampling frame.
Based on resource constraints the size of the study sample was capped at each institution at 1,250 students.
DATA SOURCES
Data collection was conducted during Spring 2018. The procedure for administering the online survey
began with a letter and cash incentive ($5) mailed to students in the sampling frame (1,250 at Institution A,
1,250 at Institution B, and 885 and Institution C). The survey was completed by a total of 1,129 students
525 students (42% response rate) at Institution A, 395 students (31.6%) at Institution B, and 207 students
(23.4%) at Institution C.
After completing the survey, the students were asked if they were willing to participate in a focus group.
A total of 57 students participated in focus groups, for which attendees received $20. These focus groups
or interviews were separated between students who had participated in an internship and those who had
not. Students who had an internship experience answered questions primarily about the nature of their
experience, while non-participants were asked questions about their reasons for not participating.
Information about the composition of both the survey and focus group sample are shown in Table 1.
HORA, CHEN, PARROTT, HER: Internship access, program design, and development outcomes
International Journal of Work-Integrated Learning, 2020, 21(3), 235-252 239
TABLE 1: Study sample characteristics by institution.
Student Characteristics
Total
(n = 1129)
Institution
A (n=525)
Institution B
(n=395)
Institution
C (n=207)
Focus
Group
(n=57)
Student Demographics
Age in years, mean (SD)
27.26 (8.85)
25.81 (7.12)
30.95 (10.64)
23.91 (6.32)
25.88 (7.73)
Gender
Male (%)
408 (36.14)
196 (37.33)
171 (43.29)
41 (19.81)
17 (29.8)
Female (%)
685 (60.67)
318 (60.57)
211 (53.42)
156 (75.36)
39 (68.4)
Race
Asian (%)
72 (6.38)
37 (7.05)
31 (7.85)
4 (1.93)
4 (7.0)
Black or African American (%)
243 (21.52)
35 (6.67)
19 (4.81)
189 (91.30)
19 (33.3)
Hispanic or Latino (%)
85 (7.53)
66 (12.57)
18 (4.56)
1 (0.48)
1 (1.8)
White or Caucasian (%)
673 (59.61)
361 (68.76)
312 (78.99)
0 (0)
30 (52.6)
First-generation student (FGS)
FGS (%)
432 (38.26)
245 (46.67)
110 (27.85)
77 (37.20)
21 (36.8)
Not FGS (%)
670 (59.34)
273 (52.00)
276 (69.87)
121 (58.45)
36 (63.2)
Life and Employment Situation
Having paid employment
Yes (%)
871 (77.15)
425 (80.95)
323 (81.77)
123 (59.42)
38 (66.67)
No (%)
247 (21.88)
97 (18.48)
70 (17.72)
80 (38.65)
19 (33.33)
Working hours, mean (SD)
26.49
(13.44)
25.35
(12.37)
29.64 (14.40)
22.11
(12.65)
14.07
(12.14)
Annual income, mean (SD)
16603.56
(18658.36)
16729.45
(18733.35)
20978.14
(19503.73)
7390.48
(12418.95)
9933.52
(13802.98)
Receiving food assistance
Yes (%)
58 (5.14)
21 (4.00)
28 (7.09)
9 (4.35)
4 (7.14)
No (%)
1044 (92.47)
498 (94.86)
357 (90.38)
189 (91.30)
52 (92.86)
Not paying bill
Yes (%)
84 (7.44)
23 (4.43)
35 (8.86)
26 (12.56)
3 (5.36)
No (%)
1017 (90.08)
496 (95.57)
350 (88.61)
171 (82.61)
53 (94.64)
Academic Status
Enrollment Status
Full-time (%)
827 (73.25)
422 (80.38)
197 (49.87)
206 (99.52)
44 (77.19)
Part-time (%)
302 (26.75)
103 (19.62)
198 (50.13)
1 (0.48)
13 (22.81)
GPA: 1(D+) to 10 (A), mean (SD)
8.09 (1.74)
7.82 (1.73)
8.54 (1.67)
7.86 (1.73)
8.64(1.57)
Academic program
Arts and Humanities (%)
139 (12.31)
70 (13.31)
56 (14.29)
13 (6.17)
5 (8.77)
Biosciences, Agriculture, & NR (%)
144 (12.76)
80 (15.21)
8 (2.04)
56 (26.54)
12 (21.05)
Business (%)
113 (10.01)
2 (0.38)
106 (27.04)
5 (2.37)
5 (8.77)
Communications, Media, & PR (%)
311 (27.55)
153 (29.09)
118 (30.10)
40 (18.96)
6 (10.53)
Engineering (%)
46 (4.07)
30 (5.70)
7 (1.79)
9 (4.27)
1 (1.75)
Health Professions (%)
46 (4.07)
23 (4.37)
14 (3.57)
9 (4.27)
1 (1.75)
Physical Sciences, Math, & CS (%)
75 (6.64)
48 (9.13)
22 (5.61)
5 (2.37)
4 (7.02)
Social Sciences (%)
118 (10.45)
42 (7.98)
61 (15.56)
15 (7.11)
9 (15.79)
Social Service Professions (%)
137 (12.14)
78 (14.83)
0 (0)
59 (27.96)
0 (0)
Internship Required
Yes (%)
135 (44.85)
24 (20.17)
69 (67.65)
42 (52.50)
17 (29.82)
No (%)
166 (55.15)
95 (79.83)
33 (32.35)
38 (47.50)
38 (66.67)
Internship Participation
Yes (%)
332 (29.41)
137 (26.10)
106 (26.84)
89 (43.00)
32 (56.14)
No (%)
795 (70.42)
388 (73.90)
289 (73.16)
118 (57.00)
25 (43.56)
Note: NR = natural resources; CS = computer science; PR = public relations
HORA, CHEN, PARROTT, HER: Internship access, program design, and development outcomes
International Journal of Work-Integrated Learning, 2020, 21(3), 235-252 240
SURVEY MEASURES
The survey instrument included questions about respondent demographics, academic and life situations
(e.g., employment status), and the students were also asked whether or not they had participated in an
internship in the last 12 months. The following definition of internships was provided:
An internship is a position held within an established company or organization while completing a
college degree, certificate, or diploma program. It involves working at the company or organization
and performing tasks similar in nature and skill-level to tasks done by entry-level employees in the
organization.
This definition was derived from examples of existing definitions and field-tested with a group of career
advisors and experiential learning professionals prior to data collection.
Students who answered "no" to having an internship answered questions about barriers to their
participation, while students who answered "yes" were presented with a series of questions about the
characteristics of their internships. Four scales were based on instruments used by McHugh (2017) and
Beenen & Rousseau (2010), and included four items measuring supervisor support (Cronbach’s
alpha=0.9),five items measuring supervisor mentoring (Cronbach’s alpha=0.83), two items measuring goal
clarity (Cronbach’s alpha=0.89), two items measuring autonomy (Cronbach’s alpha=0.76) and one item
measuring the relationship between academic learning and the internship.
In this study two potential short-term outcomes of internships were examinedsatisfaction and perceived
developmental value. Satisfaction with the internship was assessed by a single question asking how
satisfied respondents were with their internship experiences on a five-point Likert scale ranging from one
(not at all satisfied) to five (extremely satisfied). Perceived developmental value captures the degree to
which respondents consider their experiences to have enhanced their career development (Beenen &
Rousseau, 2010; McHugh, 2017). Three items asked about the skills or knowledge students gained during
the internship, and whether the internship helped them clarify their career objectives measured perceived
developmental value. These items were measured using a scale ranging from one (not at all) to five
(extremely), and the Cronbach’s alpha using the current sample was 0.82.
Focus Group Protocol
Focus group sessions lasted about one hour and were moderated by one to two researchers. For students
who had taken an internship, questions were asked about their motivations for pursuing an internship, the
nature of their work in the internship, the type of mentorship they received in their internship, and other
related questions. Students without an internship experience were asked about obstacles to pursuing
internship opportunities and general concerns about internships and their future careers.
Analytic Strategies
To answer research question one regarding participation, R statistical analysis software was used to
conduct a series of chi-square tests of independence and logistic regression analyses to explore
relationships between student characteristics and internship participation. Next, to address research
question two about barriers to internships, descriptive statistics from the survey item on that point are
HORA, CHEN, PARROTT, HER: Internship access, program design, and development outcomes
International Journal of Work-Integrated Learning, 2020, 21(3), 235-252 241
reported. To answer research question three regarding program structure, descriptive statistics of program
features are reported and compared among institutions using chi-square test of independence and one-
way analyses of variance (ANOVA). Finally, to address research question four on the relationship between
program structure and student outcomes, a two-step hierarchical regression analysis examined the amount
of variance explained in students’ internship outcomes (i.e., satisfaction and developmental value) by
student characteristics and program-related factors. In the first model for both satisfaction and perceived
developmental value, individual-level factors that included students’ demographics (e.g., age, gender,
race), life and employment status (e.g., annual income, food assistance), and academic characteristics were
entered as control variables in step one. Then, program-specific characteristics (e.g., industry areas,
internship length) were added to the second model as a second step. This approach allowed the researchers
to report the level of significance for each individual independent variable and to determine the change in
𝑅2 and F created by the second block of variables (Petrocelli, 2003).
Focus group transcripts were analyzed in MaxQDA software to address RQ2 (i.e., barriers to internships),
RQ3 (i.e., program features), and RQ4 (i.e., program format and their impacts on student outcomes). The
first step involved two researchers reviewing the focus group protocol and then coded two transcripts in
parallel, reconciling the few discrepancies, whereupon the rest of the interviews were segmented by one
researcher (Campbell, Quincy, Osserman, & Pedersen, 2013). The researchers then engaged in analytical
coding that involved engaging in inductive, open coding of two transcripts, noting recurrent phrases and
observations related to notable features of internships, especially obstacles related to accessing an
internship (Corbin, Strauss, & Strauss, 2014). The analysts then coded separate interviews using the
preliminary codebook, reviewed their results and reconciled differences in code definition and application,
and developed a final coding scheme, which one analyst applied to the entire corpus.
RESULTS
RQ1: Characteristics of Students Participating in Internships
Of the 1,129 students who responded to the survey, 332 reported having an internship (29.4%), with
considerable differences across institutions: 137 at institution A (26%), 106 at institution B (26%), and 89 at
institution C (43%). Next, an analysis was conducted to determine whether demographic, academic status,
and life/employment characteristics of students were associated with internship participation. Results
showed that internship participation significantly varied by race, 𝜒2 (3, N =* 1,073) = 8.88, p = .03; institution
type 𝜒2 (2, N = 1,127) = 22.42, p < .001; enrollment status, 𝜒2 (1, N = 1,129) = 15.65, p < .001; and academic
program, 𝜒2 (16, N = 1,128) = 35.19, p = .004.
Given the influence of race and institution type on participation, and the study’s inclusion of group of
institutions with distinct missions and student bodies (e.g., a historically black college or university, a
logistic regression analysis was conducted to examine the relationship between internship participation
and the continuous variables in Table 1 (i.e., annual income, working hours, and grade-point average) while
holding institution type and race constant. Results indicate that students who worked fewer hours at their
main job (odd ratio = 0.97, 95% CI = [0.96, 0.98], p < 0.001) and students who reported a higher grade point
average (odd ratio = 1.21, 95% CI = [1.08, 1.34], p < 0.001) were more likely to participate in internships.
Collectively, these analyses indicate that participation in internships is not universal and equitable across
HORA, CHEN, PARROTT, HER: Internship access, program design, and development outcomes
International Journal of Work-Integrated Learning, 2020, 21(3), 235-252 242
all students, but instead varies according to a range of demographic, academic, and life/employment
situations and characteristics.
RQ2: Barriers to participation in internship programs
Next, the critical issue of access was examined, with a focus on the barriers that students report as inhibiting
participation in internships. For survey respondents who had not taken an internship in the past 12 months
(N = 797), a follow-up question asked if they had been interested in pursuing one, and 64% (N = 509) stated
that they had intended to obtain an internship but could not for a variety of reasons. The most common
reasons preventing students from taking an internship included the need to work at their current paid job
(58%), a heavy course load (52%), and a lack of internships in their discipline or field (42%) (see Figure 1).
The 57 focus group participants provided additional detail on the nature of these barriers. In thi s section
the two most frequently reported issues are discussed in detail: compensation and scheduling.
Students who reported compensation as a barrier highlighted the need to consider their financial stability
and their subsequent preference for a paid internship. Some students had not taken an internship simply
because they could not find any that paid enough for them to consider leaving other paid employment.
One student had found some internships with stipends, but explained that they were not large enough to
even pay for the gas it would take to get to and from the internship. Besides the issue of compensation, the
costs associated with applying for these opportunities were problematic for some students. One student
observed that, “I looked at the application, but you’ve got to pay $50 for the application fee—I mean, people
don’t have money like that to just be giving out!”
Another concern voiced by students involved balancing the scheduling demands of their paid
employment, coursework, and an internship. As one student observed, the time students spend working
at an internship, studying for their coursework, and managing “normal jobs” can be a tenuous balancing
act. When students did find internships that were promising, some found that the hours needed for an
internship conflicted with their time available for study, personal and family obligations, and paid
employment, which ultimately resulted in them not pursuing internship leads. Given that internship pay
(if available) was often not enough money to cover tuition and other basic needs, several students explained
that they had little choice but to continue working at their “main” job.
RQ3: What is the structure and format of internship programs?
For the 323 students in the study who reported their internship program features, features of thestructure
and format of their internships are reported in Table 3.
For internship participants, more students were in academic programs that required an internship in order
to graduate than those with no such requirements (45% vs. 55%), more were compensated for their work
than those taking unpaid internships (67% vs. 33%), and the average internship was approximately 14
weeks long. Students assigned relatively high ratings to the quality of supervisors’ provision of support
(M = 4.21, SD = 0.86), especially in comparison to the quality of mentoring during the internship (M =
3.38,SD = 0.86). Students also reported that the relationship between their internship and their academic
HORA, CHEN, PARROTT, HER: Internship access, program design, and development outcomes
International Journal of Work-Integrated Learning, 2020, 21(3), 235-252 243
program was relatively strong (M = 4.03, SD = 0.99), and that the clarity of task-related goals (M = 3.96, SD
= 0.90) and their degree of work autonomy (M = 3.88, SD = 0.95) was also relatively high.
TABLE 2: Descriptive statistics and chi-square tests by internship participation.
Internship Participation (n=1129)
𝜒2
p
φ
No (n=797)
Yes (n=332)
Student Demographics
Gender
Female
475 (-1.39)
210 (1.39)
1.92
.17
-0.04
Male
299 (1.39)
109 (-1.39)
Race
Asian
54 (0.79)
18 (-0.79)
8.88*
.03
0.09
Black or African American
154 (-2.95)
89 (2.95)
Hispanic or Latino
63 (0.68)
22 (-0.68)
White or Caucasian
490 (1.76)
183 (-1.76)
First-generation student
Not FGS
473 (-0.25)
197 (0.25)
0.06
.80
-0.01
FGS
308 (0.25)
124 (-0.25)
Life and Employment Status
Having a job
Yes
259 (1.05)
612 (-1.05)
1.09
.30
0.03
No
65 (-1.05)
182 (1.05)
Academic Situation
Institution
A comprehensive PWI (Inst A)
388 (2.31)
137 (-2.31)
22.42***
< .001
0.14
An HBCU (Inst C)
118 (-4.73)
89 (4.73)
A technical college (Inst B)
289 (1.42)
106 (-1.42)
Enrollment Status
Full-time
557 (-3.96)
270 (3.96)
15.65***
< .001
-0.12
Part-time
240 (3.96)
62 (-3.96)
Academic program
35.19**
.004
0.16
Arts and Humanities
88 (-1.82)
50 (1.88)
Biosciences, Agriculture, & NR
83 (-3.45)
58 (3.14)
Business
239 (3.12)
68 (-3.33)
Communications, Media, & PR
28 (-1.37)
18 (1.52)
Engineering
85 (1.29)
28 (-1.08)
Health Professions
28 (-1.15)
17 (1.29)
Physical Sciences, Math, & CS
50 (-0.64)
25 (0.82)
Social Sciences
104 (1.62)
31 (-1.80)
Social Service Professions
84 (0.31)
34 (-0.90)
Note: Internship Yes was coded as 2, and internship No was coded as 1.
*p < .05, *p < .01, ***p < .001.
Adjusted standardized residuals appear in parentheses on the right of group frequencies.
HORA, CHEN, PARROTT, HER: Internship access, program design, and development outcomes
International Journal of Work-Integrated Learning, 2020, 21(3), 235-252 244
FIGURE 1: Types of barriers to internship participation.
Given the observed variation in mean values across institutions on these measures, chi-square and one-
way ANOVA tests were used to examine whether these features varied across the three study institutions.
Results showed that all program features, except task autonomy, significantly varied across the institutions
A, B, and C. For instance, whether internships being paid or not paid varied statistically significantly across
the three institution types, 𝜒2(4, 323) = 15.29, p = .004 with students in institution B and C reporting higher
percentages of paid internships (75% and 76% versus 55%).
The 34 students who had taken an internship in focus groups described several features of their programs.
Some students described different kinds of supervision that varied in their amount of autonomy. Some
students described their work as highly autonomous while others experienced more hands-on training and
supervision. For example, one student said that his supervisor was, “there to answer questions and to fix
issues that came up,” while others described situations where they worked with almost complete
autonomy. Similarly, students also discussed varying levels of mentoring, with some supervisors actively
coaching interns’ performance, whereas others had little mentoring. As one student said, “that's the part
that's concerning—it’s just that I want to know how I’m doing in my job.”
Putting their internship experience in the context of their career development, some students felt that their
work was directly related to their future careers. This often referred to honing their technical skills, but
some students also described acquiring socio-emotional or “non-cognitive” skills that they felt would
benefit them in their future employment (e.g., communication, teamwork, self-confidence). Finally, most
students talked about their internship as complementary to their university work, explaining that some of
what they learned in class was related to their internship, but that their internship gave them a better grasp
on how these concepts worked in the real world: “I had the basic knowledge, but being able to sit there
first hand and say, ‘Okay, this is how a retirement account really works’ has definitely taught me even
more than what you can learn in a classroom.”
HORA, CHEN, PARROTT, HER: Internship access, program design, and development outcomes
International Journal of Work-Integrated Learning, 2020, 21(3), 235-252 245
TABLE 3: Descriptive statistics of internship program features and tests of institutional differences.
Internship program Characteristics
Total Sample
(n = 323)
Institution
A (n=135)
Institution B
(n=103)
Institution
C (n=85)
𝜒2
Being required
63.46***
Required to graduate (%)
135 (44.85)
24 (20.17)
69 (67.65)
42 (52.50)
Not required to graduate (%)
166 (55.15)
95 (79.83)
33 (32.35)
38 (47.50)
Being paid or unpaid
15.29**
Paid internship (%)
216 (66.87)
74 (54.81)
77 (74.76)
65 (76.47)
Unpaid internship (%)
107 (33.13)
61 (45.19)
26 (25.24)
20 (23.53)
Weeks of internship (SD)
13.89 (7.18)
15.21 (6.91)
14.80 (7.72)
10.68 (5.90)
12.42***
Supervisor support (SD)
4.21 (0.86)
4.22 (0.84)
4.02 (0.98)
4.41 (0.70)
4.91**
Mentoring (SD)
3.38 (0.86)
3.43 (0.83)
3.00 (0.89)
3.78 (0.73)
22.05***
Goal/task clarity (SD)
3.96 (0.90)
3.99 (0.97)
3.72 (0.93)
4.19 (0.84)
6.80**
Autonomy (SD)
3.88 (0.95)
3.93 (0.95)
3.75 (0.99)
3.96 (0.87)
1.49
Relatedness (SD)
4.03 (0.99)
4.12 (0.92)
4.23 (0.93)
3.66 (1.09)
9.02***
Note: *p < .05, *p < .01, ***p < .001.
RQ4: How, if at all, is program structure associated with student outcomes?
Finally, results from the analysis of the relationship between structural features of internship programs and
their effect on student satisfaction and perceived developmental value are discussed. Supervisor support,
mentoring, goal clarity, autonomy, and relatedness to academic programs were correlated with each other
as well as with satisfaction and students’ perceived development value, with correlation coefficients
ranging from .11 to .69. Table 4 includes the results of the hierarchical regression analysis, which indicates
the contributions of student characteristics (step 1) as well as the contributions of internship features (step
2) to internship satisfaction and developmental value.
With respect to satisfaction with internships, gender and annual income were two significant control
variables. However, student characteristics in model 1 only explained a small percentage of the variance
in satisfaction, adjusted 𝑅2 = .03, F(9, 313) = 2.17, p = 0.024. Variables that were significant (and positive)
predictors of satisfaction in model 2 included supervisor support (β = .43, p < .001), mentoring (β = .48, p
< .001), goal clarity (β = .10, p = .001), and relatedness to academic program (β = .12, p < .001). Beta is
standardized regression coefficient, which means every unit increase in the predictor variable, the outcome
variable will increase by beta coefficient value. For example, in the current model, every one unit increase
in supervisor support, students’ internship satisfaction will increase 0.43 controlling for other variables.
The model 2 explains 56% of the variation in satisfaction, adjusted 𝑅2 = .56, F(18, 304) = 23.33, p < .001. These
results suggest that internship industry, supervisor behavior, nature of work in terms of clarity and link to
coursework are important factors shaping how satisfied students were with their internships.
The second columns in both models include results from analyses of these predictors on the developmental
value of students’ internships. The results indicate that no step one variables were significantly associated
with developmental value and it explained little of the variance in students perceived developmental value.
Adjusted 𝑅2 = .04, F (9, 313) = 2.44, p = .01. When program features were added to model 2, internships
being compensated (β = -.15, p = .044), supervisor support (β = .17, p = .013), mentoring (β = .83, p < .001),
HORA, CHEN, PARROTT, HER: Internship access, program design, and development outcomes
International Journal of Work-Integrated Learning, 2020, 21(3), 235-252 246
and relatedness to academic program (β = .21, p < .001) significantly predicted students’ perceived value,
adjusted 𝑅2 = .54, F(18, 304) = 21.95, p < .001. Interns without compensation rated the developmental value
of their internships lower than paid interns. Conversely, supervisor support, mentoring, and an internship
closely linked to coursework positively influence students’ view of the developmental value of their
internship. It is noteworthy that supervisor mentoring played a more important role than supervisor
support, which means that supervisors’ specific direction and feedback about interns’ task performance
and career planning were perceived more beneficial towards their development.
TABLE 4. Hierarchical regression results of internship satisfaction and developmental value.
Model 1
Model 2
Satisfaction
Developmental
Value
Satisfaction
Developmental
Value
Step 1: Students characteristics
Age
-.04
.01
.01
.07
Gender_Male
-.12*
-.09
-.07
-.07
Race (reference group: Asian)
Race_Black
.39
.57
.32
.52*
Race_Latino
.16
.14
.17
.10
Race_White
.28
-.17
.61
.05
First-gen_Yes
.01
-.10
.00
-.09
Annual income
.18*
.15*
.04
.03
Institution (reference group: comprehensive PWI)
Institution_HBCU
-.09
-.11
-.23
-.19*
Institution_Technical college
-.36**
-.85*
-.14
-.81
𝑅2
.03
.04
F
2.17
2.44
Step 2: Internship program features
Required_Yes
.02
.01
Internship being unpaid
-.13
-0.15*
Weeks
-.01
.00
Supervisor support
.43***
.17*
Mentoring
.48***
.83***
Goal clarity
.10**
.04
Autonomy
-.01
.00
Relatedness to academic program
.12***
.20***
𝑅2
.56
.54
𝛥𝑅2
.53
.50
F
23.33
21.95
𝛥𝐹
21.16
19.51
Note: *p < .05, *p < .01, ***p < .001.
The change in the R-squared value indicated that adding step 2 variables (internship program features)
significantly improved both the satisfaction model (F = 41.93, p < .001) and the developmental value model
(F = 38.81, p < .001), with the second model explaining an additional 53% of the variance in satisfaction and
50% in developmental value. Additionally, to see if the data met the assumption of collinearity, our
analysis indicated that multicollinearity was not a concern with VIF values ranging from 1.05 1.60.
HORA, CHEN, PARROTT, HER: Internship access, program design, and development outcomes
International Journal of Work-Integrated Learning, 2020, 21(3), 235-252 247
For the 34 students in the focus groups who had participated in internships, the most cited outcome of an
internship was “real-world” or “hands-on” experience. Another outcome was the opportunity to explore
the field, where students felt that they could use internships to “test out different avenues of what you
might want to go into”. For example, one student found that “I think the experience… at my internship
confirmed that this is kind of what I want to do in the future,” whereas another student found that their
internship helped them see what they did not want to do in the future. Similarly, some spoke of internships
as providing the opportunity to experience different workplace cultures, which could inform decisions
about their future.
Students also discussed how they grew personally during their internships. As one student said, “It made
me see what I was going to put up with and what I was not [going to put up with]”. Finally, many students
also felt that their internship was key for their career prospects, and that the internship experience would
get their “foot in the door,” either from the company where they interned or at other firms. Students whose
goals were to go into academia or research also explained that this was critical for having a competitive
graduate school application.
DISCUSSION
There is a widespread and growing conviction that internships are a valuable or even essential “high-
impact” practices that have positive benefits for college students, educators, and employers alike.
However, the data reported in this paper confirm that concerns regarding the quality and accessibility of
internships are warranted. The remainder of this paper discusses the need for a process-oriented
perspective and highlight key findings from the study and implications for research, policy, and practice.
Towards a Developmental and Processual Perspective on Internship Experiences
One of the primary conclusions that can be drawn from the data is that instead of viewing internships as a
singular experience that can be measured with a yes/no question about participation, a new perspective is
needed. Building upon existing processual models of internships (Narayanan, et al., 2010; Sweitzer & King,
2013), a framework is proposed for studying internships that takes account of the following stages: (1) the
demographic, academic, and life/employment situations of students, who then aim to; (2) gain access to
internship opportunities, which are influenced by geography, discipline, and local labor markets; if
successful, students then (3) participate in an experiential learning space characterized by important
structural features (e.g., quality of mentoring); which may ultimately lead to (4) a variety of outcomes that
may include employment, future earnings, and changes in vocational self-concept and sense of self (see
Figure 2).
This socio-technical perspective of internship participation complements the more developmental focus of
existing stage models that focus on students’ experiences (e.g., alienation within new workplace settings),
and together they provide a more multi-dimensional and accurate depiction of internships than is available
from a simple yes/no question of participation.
HORA, CHEN, PARROTT, HER: Internship access, program design, and development outcomes
International Journal of Work-Integrated Learning, 2020, 21(3), 235-252 248
FIGURE 2: A process model of the internship experience.
Participation Rates Are Low and Vary Across Institutions and Student Characteristics
With respect to internship participation, this study contributes to the field in two ways. First, the survey
instrument addresses key technical limitations observed with other commonly used surveys (e.g., the
National Survey of Student Engagement). Specifically, the instrument used in this study provides a clear
definition of internships, does not include other forms of work-based learning in the definition or survey
question (e.g., co-ops, clinical placements), and elicits detailed information on the structure and format of
internship programs. Future research should build upon this more fine-grained approach and national-
level instruments should be revised with respect to how internships are defined and measured.
Second, this study provides new evidence that substantial variation in internship participation exists across
diverse institution types, and also for students with particular demographic, academic, and employment
characteristics. For instance, students with longer working hours at their main jobs and who have a lower
grade point average were less likely to have an internship. Given increasing numbers of students who are
working while attending college, and the necessity to do so with the rising costs of tuition and basic needs,
these data should raise concerns about the barriers to internships for working and/or low-income students
(Perna, 2010).
HORA, CHEN, PARROTT, HER: Internship access, program design, and development outcomes
International Journal of Work-Integrated Learning, 2020, 21(3), 235-252 249
Third, the results raise questions about the relative influence of individual-level factors (e.g., student
demographics and life situation) and programmatic factors (e.g., discipline) on internship participation,
satisfaction and developmental value. For instance, the data show that internship participation varied
significantly by race, institution type, enrollment status, and academic program, which suggest to us that
future research needs to explore in depth precisely how and why these different factors impact
participation. Similarly, race, income level, and institution type were significantly associated with
internship satisfaction and developmental value, which raises the prospect that a complex combination of
student demographics, life situation, and institution or disciplinary forces intersect to shape students’
experiences in internship programs (Finley & McNair, 2013).
Barriers to Internship Participation May Exacerbate Inequality
Analyses of the data regarding barriers to participation provide additional insights into this problem of
equity and access while also raising several questions that researchers should examine in the future. The
fact that 64% of the students who did not take an internship (N = 797) had, in fact, wanted to pursue one
but could or did not, indicates that additional research about the barriers to participation should be a high
priority for the field. The data indicate that these barriers fall into three categories: scheduling conflicts
(with paid work and coursework), a lack of internships in their discipline or region, and the fact that unpaid
internships were simply not a realistic option for students to pursue given other expenses and obligations.
These barriers are unfortunate for all students, but may be especially problematic for low-income, first-
generation, and/or minoritized students for whom an internship may be an especially valuable professional
experience. This is due to the fact that students in these groups are at a higher risk for dropping out of
college (Museus & Quaye, 2009), often have less robust social networks (Parks-Yancy, 2012), and are at a
disadvantage with respect to the elite and White-dominated cultural capital implicated in employers’
hiring practices (Hora, 2020; Rivera, 2012).
Finally, the issue of internship compensation cannot be ignored. It is promising that 67% of our study
sample were paid for their internships, but the fact that 33% were not remains a concern. Despite the fact
that some research has found that unpaid internships may play an important role in helping students
explore their professional interests (Crain, 2016), the results indicate a significant and negative effect on the
developmental value of an internship. Further, debates about intern compensation should not solely be
limited to their effects on developmental outcomes, but should be steadfastly focused on concerns about
equity, fairness, and student well-being. Prior research found that students from disadvantaged
backgrounds are more likely to struggle to secure paid internships (Hunt & Scott, 2017), and to ask students
who are already struggling with tuition, housing, and basic needs-related bills is in our view unethical.
Furthermore, with evidence that internships (and students) in one of the world’s largest economies and
postsecondary education systems that of China - are being exploited to fill short-term labor short-falls
and even to replace full-time workers (Chan, Pun, & Selden, 2015), it is essential that educators, advisors,
and employers must have student well-being foremost in mind when thinking about internship
opportunities on their campuses and in their organizations. While internships in China are necessarily
different from the three U.S. institutions discussed in this paper, the potential for the exploitation of college
students exists around the world and should be guarded against on a global level.
HORA, CHEN, PARROTT, HER: Internship access, program design, and development outcomes
International Journal of Work-Integrated Learning, 2020, 21(3), 235-252 250
Structure of Internship Programs and Their Impacts
Next, one of the central issues in this paper is addressedthe question of how internship program structure
is associated, if at all, with student outcomes. The findings suggest that internship programs with certain
characteristicsespecially supervisor support, supervisor mentoring, and relationship to academic
programs—can lead to greater satisfaction and perceived value of the internship to students’ career
development. These results confirm prior research that highlights the importance of good job-site
supervision, leading McHugh (2017) to state that, “for institutions that encourage and/or require
internships, screening internship providers in terms of their supervisory commitment is warranted” (p.
377).
As a result, colleges and universities should vet potential internship hosts to ensure that they have
adequate, trained supervisors on site to supervise student interns and provide regular mentoring and
feedback. The presence of high-quality supervision, along with the need for meaningful work (and not
menial tasks such as making photocopies), is a long-standing critique of internships that remains a pressing
issue to this day (Frenette, 2013; Perlin, 2012).
Another programmatic design feature that the data indicate are important for student satisfaction and
developmental outcomes is the relationship between internship tasks and students’ academic and career
trajectories, which is a core feature of effective WIL. For example, a biology major aiming to work in the
biotechnology sector is unlikely to find an internship in a bank very fulfilling. That said, the fact that some
students reported using internships to explore career opportunities suggests that the importance of a close
link between internship and major may vary from student to student. Future research in this area should
examine this issue, along with the prospect that different internship formats may impact different kinds of
students in different ways.
CONCLUSIONS
Several limitations to the study should be noted, particularly the limited focus on three institutions in a
single country. Additionally, the possibility of selection and response bias in the survey and focus group
components of the study as well as the limited sample makes generalizations or claims about college
internships in general, or the experiences of students at participating institutions untenable.
Besides guiding future research on internships, the process-oriented framework outlined in this paper can
be used by postsecondary leaders, career services professionals, and policymakers to better understand the
specific forces that shape access to and experiences with the college internship. Ultimately, the field of
higher education and WIL needs to recognize that while internships may be a vehicle for the transformation
of a person from a student to a budding professional, they may also serve to reproduce inequality by
making these experiences inaccessible to thousands of students who lack sufficient financial or social
capital to locate and pursue these opportunities.
HORA, CHEN, PARROTT, HER: Internship access, program design, and development outcomes
International Journal of Work-Integrated Learning, 2020, 21(3), 235-252 251
REFERENCES
Atkinson, G. (2016). Work-based learning and work-integrated learning: Fostering engagement with employers. Adelaide, Australia:
National Center for Vocational Education Research.
Bailey, T., Hughes, K., & Barr, T. (2000). Achieving scale and quality in school-to-work internships: Findings from two employer
surveys. Educational Evaluation and Policy Analysis, 22(1), 41-64.
Beenen, G., & Rousseau, D. M. (2010). Getting the most from MBA internships: Promoting intern learning and job acceptance.Human
Resource Management, 49(1), 3-22.
Binder, J. F., Baguley, T., Crook, C., & Miller, F. (2015). The academic value of internships: Benefits across disciplines and student
backgrounds. Contemporary Educational Psychology, 41, 73-82.
Campbell, J. L., Quincy, C., Osserman, J., & Pedersen, O. K. (2013). Coding in-depth semi-structured interviews: Problems of
unitization and intercoder reliability and agreement. Sociological Methods and Research, 42(3), 294320.
Chan, J., Pun, N., & Selden, M. (2015). Interns or workers? China’s student labor regime. AsiaPacific Journal, 13(36), 125.
Corbin, J., Strauss, A., & Strauss, A. L. (2014). Basics of qualitative research. Thousand Oaks, CA: Sage.
Crain, A. (2016). Understanding the impact of unpaid internships on college student career development and employment outcomes.
Bethlehem, PA: NACE Foundation. Retrieved from National Association of Colleges and Employers website
https://www.naceweb.org/uploadedfiles/files/2016/guide/the-impact-of-unpaid-internships-on-career-development.pdf
Curiale, J. L. (2009). America's new glass ceiling: Unpaid internships, the Fair Labor Standards Act, and the urgent need for change.
Hastings LJ, 61, 1531.
D'Abate, C. P., Youndt, M. A., & Wenzel, K. E. (2009). Making the most of an internship: An empirical study of internship
satisfaction. Academy of Management Learning & Education, 8(4), 527-539.
Finley, A., & McNair, T. (2013). Assessing underserved students' engagement in high-impact practices. Washington, DC. Association of
American Colleges and Universities.
Frenette, A. (2013). Making the intern economy: Role and career challenges of the music industry intern. Work and
Occupations, 40(4), 364-397.
Hora, M. T. (2020). Hiring as cultural gatekeeping into occupational communities: implications for higher education and student
employability. Higher Education, 79 (2), 307-324.
Hora, M., Wolfgram, M., & Thompson, S. (2017). What do we know about the impact of internships on student outcomes. Results from a
preliminary review of the scholarly and practitioner literatures. University of Wisconsin-Madison:Center for Research on College-
Workforce Transitions
Hunt, W., & Scott, P. (2018). Participation in paid and unpaid internships among creative and communications graduates (pp. 190-
209). In Higher education and social inequalities: University admissions, experiences, and outcomes, Waller, R., Ingram, N., & Ward,
M. R. (Eds.). Routledge.
Jackson, D. (2018). Developing graduate career readiness in Australia: Shifting from extra-curricular internships to work-integrated
learning. International Journal of Work-Integrated Learning, 19(1), 23-35.
Knouse, S. B., Tanner, J. R., & Harris, E. W. (1999). The relation of college internships, college performance, and subsequent job
opportunity. Journal of Employment Counseling, 36(1), 35-43.
Kuh, G. D. (2008). High-impact educational practices: What they are, who has access to them, and why they matter. Washington, DC:
Association of American Colleges and Universities.
Loeb, S., Dynarski, S., McFarland, D., Morris, P., Reardon, S., & Reber, S. (2017). Descriptive analysis in education: A guide for
researchers. NCEE 2017-4023. Washington, DC: National Center for Education Evaluation and Regional Assistance.
McHugh, P. P. (2017). The impact of compensation, supervision and work design on internship efficacy: Implications for educators,
employers and prospective interns. Journal of Education and Work, 30(4), 367-382.
Museus, S. D., & Quaye, S. J. (2009). Toward an intercultural perspective of racial and ethnic minority college student persistence.
The Review of Higher Education, 33(1), 67-94.
National Association of Colleges and Employers (2018a). Position statement: U.S. internships. Bethlehem, PA: NACE. Retrieved from:
http://www.naceweb.org/about-us/advocacy/position-statements/position-statement-us-internships/
National Association of Colleges and Employers (2018b). 2018 Student survey report. Bethlehem, PA: NACE.
National Survey of Student Engagement (2018). Engagement insights: Survey findings on the quality of undergraduate education.
Bloomington, IN: Author
Narayanan, V. K., Olk, P. M., & Fukami, C. V. (2010). Determinants of internship effectiveness: An exploratory model. Academy of
Management Learning & Education, 9 (1), 61-80.
Nunley, J. M., Pugh, A., Romero, N., & Seals Jr, R. A. (2016). College major, internship experience, and employment opportunities:
Estimates from a résumé audit. Labour Economics, 38, 37-46.
HORA, CHEN, PARROTT, HER: Internship access, program design, and development outcomes
International Journal of Work-Integrated Learning, 2020, 21(3), 235-252 252
O’Neill, N. (2010). Internships as a high-impact practice: Some reflections on quality. Peer Review, 12(4), 48.
Parker, E. T., Kilgo, C. A., Sheets, J. K. E., & Pascarella, E. T. (2016). The differential effects of internship participation on end-of-
fourth-year GPA by demographic and institutional characteristics. Journal of College Student Development, 57(1), 104-109.
Parks-Yancy, R. (2012). Interactions into opportunities: Career management for low-income, first-generation African American
college students. Journal of College Student Development, 53(4), 510-523.
Perlin, R. (2012). Intern nation. London, UK: Verso Books.
Perna, L. W. (2010). Understanding the working college student: New research and its implications for policy and practice. Herndon, VA:
Stylus Publishing.
Petrocelli, J. V. (2003). Hierarchical multiple regression in counseling research: Common problems and possible remedies.
Measurement and evaluation in counseling and development, 36(1), 9-22.
Rivera, L. A. (2012). Hiring as cultural matching: The case of elite professional service firms. American Sociological Review, 77(6), 999-
1022.
Rose, P. (2013). Internships: Tapping into China's next generation of talent. Asia-Pacific Journal of Cooperative Education, 14(2), 89-98.
Saniter, N. & Siedler, T. (2014). Door opener or waste of time? The effects of student internships on labor market outcomes.(Discussion Paper
8141). IZA Institute of Labor Economics.
Savickas, M. L., Nota, L., Rossier, J., Dauwalder, J., Duarte, M.E., Guichard, J., Soresi, S., Van Esbroeck, R., & Van Vianen, A. (2009).
Life designing: A paradigm for career construction in the 21st century. Journal of Vocational Behavior 75(3), 239-250.
Silva, P., Lopes, B., Costa, M., Melo, A. I., Dias, G. P., Brito, E., & Seabra, D. (2018). The million-dollar question: can internships boost
employment? Studies in Higher Education, 43(1), 2-21.
Sweitzer, H. F., & King, M. A. (2013). Stages of an internship re-visited: Facilitating learning and development through engagement.
Journal of Human Services, 33(1), 56-72.
Teddlie, C., & Tashakkori, A. (2003). Major issues and controversies in the use of mixed methods in the social and behavioral
sciences. In Tashakorri and Teddlie (Ed.), Handbook of mixed methods in social & behavioral research (pp. 350). Thousand Oaks,
CA: Sage.
Weible, R., & McClure, R. (2011). An exploration of the benefits of student internships to marketing departments. Marketing
Education Review, 21(3), 229240.
About the Journal
The International Journal of Work-Integrated Learning (IJWIL) publishes double-blind peer-reviewed original
research and topical issues dealing with Work-Integrated Learning (WIL). IJWIL first published in 2000 under the
name of Asia-Pacific Journal of Cooperative Education (APJCE). Since then the readership and authorship has
become more international and terminology usage in the literature has favored the broader term of WIL, in 2018
the journal name was changed to the International Journal of Work-Integrated Learning.
In this Journal, WIL is defined as "an educational approach that uses relevant work-based experiences to allow students to
integrate theory with the meaningful practice of work as an intentional component of the curriculum". Defining elements of
this educational approach requires that students engage in authentic and meaningful work-related task, and must
involve three stakeholders; the student, the university, and the workplace. Examples of practice include off-
campus, workplace immersion activities such as work placements, internships, practicum, service learning, and
cooperative education (Co-op), and on-campus activities such as work-related projects/competitions,
entrepreneurships, student-led enterprise, etc. WIL is related to, but not the same as, the fields of experiential
learning, work-based learning, and vocational education and training.
The Journal’s main aim is to enable specialists working in WIL to disseminate research findings and share
knowledge to the benefit of institutions, students, co-op/WIL practitioners, and researchers. The Journal desires to
encourage quality research and explorative critical discussion that leads to the advancement of effective practices,
development of further understanding of WIL, and promote further research.
The Journal is financially supported by the Work-Integrated Learning New Zealand (WILNZ), www.nzace.ac.nz
and the University of Waikato, New Zealand.
Types of Manuscripts Sought by the Journal
Types of manuscripts sought by IJWIL is primarily of two forms; 1) research publications describing research into
aspects of work-integrated learning and, 2) topical discussion articles that review relevant literature and provide
critical explorative discussion around a topical issue. The journal will, on occasions, consider best practice
submissions.
Research publications should contain; an introduction that describes relevant literature and sets the context of the
inquiry. A detailed description and justification for the methodology employed. A description of the research
findings - tabulated as appropriate, a discussion of the importance of the findings including their significance to
current established literature, implications for practitioners and researchers, whilst remaining mindful of the
limitations of the data, and a conclusion preferably including suggestions for further research.
Topical discussion articles should contain a clear statement of the topic or issue under discussion, reference to
relevant literature, critical and scholarly discussion on the importance of the issues, critical insights to how to
advance the issue further, and implications for other researchers and practitioners.
Best practice and program description papers. On occasions, the Journal also seeks manuscripts describing a practice
of WIL as an example of best practice, however, only if it presents a particularly unique or innovative practice or
was situated in an unusual context. There must be a clear contribution of new knowledge to the established
literature. Manuscripts describing what is essentially 'typical', 'common' or 'known' practices will be encouraged to
rewrite the focus of the manuscript to a significant educational issue or will be encouraged to publish their work
via another avenue that seeks such content.
By negotiation with the Editor-in-Chief, the Journal also accepts a small number of Book Reviews of relevant and
recently published books.
EDITORIAL BOARD
Editor-in-Chief
Dr. Karsten Zegwaard University of Waikato, New Zealand
Associate Editors
Dr. Judene Pretti University of Waterloo, Canada
Dr. Anna Rowe University of New South Wales, Australia
Senior Editorial Board Members
Assoc. Prof. Sonia Ferns Curtin University, Australia
Dr. Phil Gardner Michigan State University, United States
Assoc. Prof. Denise Jackson Edith Cowan University, Australia
Prof. Janice Orrell Flinders University, Australia
Emeritus Prof. Neil I. Ward University of Surrey, United Kingdom
Copy Editor
Yvonne Milbank International Journal of Work-Integrated Learning
Editorial Board Members
Assoc. Prof. Erik Alanson University of Cincinnati, United States
Prof. Dawn Bennett Curtin University, Australia
Mr. Matthew Campbell Queensland University of Technology, Australia
Dr. Craig Cameron Griffith University, Australia
Dr. Sarojni Choy Griffith University, Australia
Dr. Bonnie Dean University of Wollongong, Australia
Prof. Leigh Deves Charles Darwin University, Australia
Mr. David Drewery University of Waterloo, Canada
Assoc. Prof. Chris Eames University of Waikato, New Zealand
Dr. Jenny Fleming Auckland University of Technology, New Zealand
Dr. Nigel Gribble Curtin University, Australia
Dr. Thomas Groenewald University of South Africa, South Africa
Assoc. Prof. Kathryn Hay Massey University, New Zealand
Ms. Katharine Hoskyn Auckland University of Technology, New Zealand
Dr. Sharleen Howison Otago Polytechnic, New Zealand
Dr. Nancy Johnston Simon Fraser University, Canada
Dr. Patricia Lucas Auckland University of Technology, New Zealand
Dr. Jaqueline Mackaway Macquarie University, Australia
Dr. Kath McLachlan Macquarie University, Australia
Prof. Andy Martin Massey University, New Zealand
Dr. Norah McRae University of Waterloo, Canada
Dr. Laura Rook University of Wollongong, Australia
Assoc. Prof. Philip Rose Hannam University, South Korea
Dr. Leoni Russell RMIT, Australia
Dr. Jen Ruskin Macquarie University, Australia
Dr. Andrea Sator Simon Fraser University, Canada
Dr. David Skelton Eastern Institute of Technology, New Zealand
Assoc. Prof. Calvin Smith University of Queensland, Australia
Assoc. Prof. Judith Smith Queensland University of Technology, Australia
Dr. Raymond Smith Griffith University, Australia
Prof. Sally Smith Edinburgh Napier University, United Kingdom
Dr. Ashly Stirling University of Toronto, Canada
Prof. Yasushi Tanaka Kyoto Sangyo University, Japan
Prof. Neil Taylor University of New England, Australia
Assoc. Prof. Franziska Trede Charles Sturt University, Australia
Ms. Genevieve Watson Elysium Associates Pty, Australia
Dr. Nick Wempe Primary Industry Training Organization, New Zealand
Dr. Theresa Winchester-Seeto University of New South Wales, Australia
Publisher: Work-Integrated Learning New Zealand
... Frontline employees' understanding of role/task clarity desires many aspects, including customer satisfaction, job satisfaction, organizational commitment, and job performance (Ruyter et al., 2001). Hora, Chen et al. (2019) confirmed that task clarity significantly predicted interns' satisfaction. Sawyer (1992) measured 402 mental health workers from two organizations using two role structures which are "Process" and "Goal Clarity", and reported that task clarity is positively correlated with employee satisfaction. ...
... The results of the structural model Note: *p-value <0.05, t-value in parentheses; Solid line report is significant; The dashed line reports no significance, that is, H1-H6 is significant, while H7 is not significant From Figure 2 and Table 6, the results of the structural paths can be summarized as follows: H1: Supervisor support significantly impacted task clarity with a standardized path coefficient of 0.520 and a t-value of 9.048. The hypothesis was supported by previous empirical studies (Beenan, 2007;Hora et al.,2019). University students believe that the supervisor's support in internship sites can help them better transfer their knowledge and skills to the workplace. ...
... Consequently, H2 was supported. This result was consistent with previous research (Hora et al., 2019;Gerstner & Day,1997;Maelah et al., 2014). During the educational internship period, students will have work experience under the guidance of the practice instructor. ...
Article
Full-text available
This study aims to determine the significant impact of supervisor support, task clarity, service quality, perceived value, and student expectation on art student satisfaction on educational internship. This quantitative study conducted the data collection by distributing questionnaires. Before the data collection, the item-objective congruence (IOC) index was approved by three experts at a score above 0.5, and Cronbach’s alpha coefficient value of the pilot test was acceptable at above 0.7. The sampling methods used were purposive, stratified random, and convenience samplings. The data were analyzed by confirmatory factor analysis (CFA), and the hypotheses were tested by the structural equation model (SEM). The results showed that service quality, supervisor support, task clarity, and perceived value significantly impacted art students’ internship satisfaction. Service quality had the most substantial significant impact on art students' internship satisfaction. However, there was no causal relationship between student expectation and student satisfaction. In conclusion, universities and internship sites should focus on improving service quality, providing skilled supervisors, giving higher task clarity, and promoting values of the educational internship program to ensure student satisfaction.
... It is important to study both types of employment outcomes, finding general employment versus finding employment in one's career field. Internships can be paid or unpaid (Blau & Lopez, 2020;Hora, Chen, Parrott, & Her, 2019;Jawabri, 2017). Prior college student research has not studied the relationships of paid versus unpaid internships/co-ops to anticipated employment in the early stage of the COVID-19 pandemic. ...
... Students in this study more likely to report having at least one paid (272/405 = 67%) paid versus unpaid (108/405 = 27%) internship experience. These percentages are similar to prior studies (Hora et al., 2019;Jawabri, 2017). Despite the potential for gained knowledge and networking as advantages, affordability for students to take an unpaid internship/co-op, even if gives college credit, is one major drawback (Lei & Yin, 2019). ...
... Without additional data it would be difficult to generalize these results. For example, Hora et al. (2019) surveyed n = 1,1,29 undergraduates across three different US colleges, with a follow-up focus group (n = 57). Results indicated that internship participation varied significantly by institution (smaller rural campushighest internship participation rate), enrollment status (part-time enrollment statuslower internship access), and academic program (lower GPAlower internship access), and that 64% of students who did not take an internship had desired to do so but could not due to scheduling conflicts with work, insufficient pay, and lack of placements in their disciplines. ...
Article
Full-text available
This study investigated the relationships of paid and unpaid internships to anticipated employment outcomes for graduating college business students. It also investigated the self-reported source(s) by which these students had obtained their internship(s). In May of 2020, 445 graduating business undergraduates filled out an online survey, for which there was complete data for 405 students. Although most of the internships were pre-pandemic, the anticipated employment outcomes by graduation were in the early stage of the COVID-19 pandemic. Three dichotomous response anticipated employment outcomes were measured: securing a full-time job; securing a full-time job that consistent with one’s major; and being self- employed. Results were that students with at least one paid internship were more likely to anticipate securing a full-time job and securing a full-time job consistent with their major versus students without a paid internship. In addition, students with at least one paid internship were less likely to see themselves being self-employed versus students without a paid internship. However, there were no relationships for students having at least one unpaid internship, versus no unpaid internship, to these anticipated full-time employment outcomes. Students with at least one unpaid internship were more likely to see themselves being self-employed by graduation versus students without an unpaid internship. Surprisingly, the general source of “on my own” was the dominant method reported by students for obtaining both paid and unpaid internships. These results are further discussed, and study limitations noted.
... Students bene t from internships and other experiential learning opportunities because they allow students to apply knowledge, gain skills, interact with role models and mentors, and work on interprofessional teams (2,(12)(13)(14). Internships also present challenges, as well as opportunities, in terms of equity and access (15). ...
Preprint
Full-text available
This report arises from the intersection of service learning and population health at an academic medical center. At UCSF, the Office of Population Health and Accountable Care (OPHAC) employs health care navigators to help patients access and benefit from high-value care. In early 2020, facing COVID-19, UCSF leaders asked OPHAC to help patients and employees navigate testing, treatment, tracing, and returning to work protocols. OPHAC established a COVID hotline to route callers to the appropriate resources, but needed to increase the capacity of the navigator workforce. To address this need, OPHAC turned to UCSF’s service learning program for undergraduates, the Patient Support Corps (PSC). In this program, UC Berkeley undergraduates earn academic credit in exchange for serving as unpaid patient navigators. In July 2020, OPHAC provided administrative funding for the PSC to recruit and deploy students as COVID hotline navigators. In September 2020, the PSC deployed 20 students collectively representing 2.0 full-time equivalent navigators. After training and observation, and with supervision and escalation pathways, students were able to fill half-day shifts and perform near the level of staff navigators. Key facilitators relevant to success reflected both PSC and OPHAC strengths. The PSC onboards student interns as institutional affiliates, giving them access to key information technology systems, and trains them in privacy and other regulatory requirements so they can work directly with patients. OPHAC strengths included a learning health systems culture that fosters peer mentoring and collaboration. A key challenge was that, even after training, students required around 10 hours of supervised practice before being able to take calls independently. As a result, students rolled on to the hotline in waves rather than all at once. Post-COVID, OPHAC is planning to use student navigators for outreach. Meanwhile, the PSC is collaborating with pipeline programs in hopes of offering this internship experience to more students from backgrounds that are under-represented in healthcare. Other campuses in the University of California system are interested in replicating this program. Adopters see the opportunity to increase capacity and diversity while developing the next generation of health and allied health professionals. 1 Introduction: Description of the nature of the problem being addressed and rationale for the proposed innovation This case study reports on a collaboration that represents the intersection of two major trends: service learning in education (1–4) and population health in health care (5, 6). Service learning programs involve students in experiential learning outside of classroom settings. Population health programs target an entire population or panel of patients and attempt to address their health and wellness in an integrated and holistic fashion. The past decade has seen a steady increase in the proportion of patients cared for under accountable care or other risk sharing programs. Such programs create alignment for all parties for the provision of high quality and affordable health care, and create opportunity for health systems to innovate with new models of care delivery. In early 2020, population health programs faced an influx of demand from patients who were potentially exposed to coronavirus infection and who needed help with testing, treatment, and tracing services related to COVID-19 (7). Population health programs needed to expand their capacity to address this demand. At the same time, health care delivery systems were dealing with a reduction in revenue, and many had instituted hiring freezes. Meanwhile, undergraduate institutions have launched service learning programs to ensure that students are exposed to high impact practices such as internships (8–11). Students benefit from internships and other experiential learning opportunities because they allow students to apply knowledge, gain skills, interact with role models and mentors, and work on interprofessional teams (2, 12–14). Internships also present challenges, as well as opportunities, in terms of equity and access (15). In principle, service learning programs can extend the workforce capacity of population health programs, including during a surge in demand due to a pandemic. This case study describes one such innovative collaboration at an academic medical center where students helped increase the capacity of a COVID hotline.
... Table 1 shows WIL participation rates by student characteristics, noting that the overall average participation rate is 37.4% (451,263 of 1,206,585 students had a WIL experience). Equivalent data are not available from the United States, our other study site, however it is estimated that around 49% of senior students take part in an internship while in college in the United States (Hora et al., 2020). Students from diverse backgrounds face challenges in accessing WIL, such as financial barriers and distance from workplaces (Universities Australia, 2019, pp. ...
Article
Full-text available
Students from diverse backgrounds report that time pressures, financial responsibilities, caring commitments, and geographic location are barriers to their uptake of work integrated learning (WIL). Through interviews with 32 students and 15 educators who participated in online WIL, we investigated whether online WIL might be one way of overcoming these barriers. Benefits of online WIL for students included employability skills, meaningful work, affordability, and flexibility when coping with health issues. Challenges for students included missing out on workplace interactions, digital access, and finding a private space in which to work. Students from diverse backgrounds were viewed by educators as bringing positive contributions to the workplace. Educators found challenges in giving feedback and not being able to replicate some aspects of in-person workplaces. We conclude with recommendations on how online WIL might be enhanced to better meet the needs of students facing equity issues. Implications for practice and policy: All participants in online WIL should be encouraged to intentionally view diversity as a strength. Educators need to create explicit opportunities for formal and informal interaction and network building during online WIL. Educators should provide engaging and purposeful work during online WIL. Students may need additional financial or material support to undertake online WIL, for example to enable digital access and access to a private workspace.
... Although literature supporting the argument that work-based learning facilitates transitions from education to work has mainly been focused on vocational education and training, there is evidence on positive effects of work-based learning in higher education on the individuals' labour market outcomes (e.g. [3], [4], [5], [28], [33], [34], [35], [36]). ...
Conference Paper
Full-text available
Every organization has the internal capacity to innovate, the only question is whether it will use that capacity or not. Unfortunately, most ideas are never realized. Managers are the ones who need to create a working environment, i.e. an organizational culture that encourages and supports a high-level innovation of employees, because competitiveness and market recognition today are built on this particular ability of the organization. Therefore, the paper discusses the strategic aspect of innovation of economic entities by size in the Republic of Serbia, in terms of: the trend of innovative activities; the share of innovators; rank of the Republic of Serbia within the Global Innovation Index; the most significant shortcomings of the innovation policy in the Republic of Serbia; as well as desirable innovation policies. Special emphasis is placed on the importance of learning for innovation and the role of managers in that, with a focus on lifelong learning and strengthening the culture of learning and application of acquired knowledge. Key words: organization, innovation, strategic management, employees, education, Republic of Serbia
... Although literature supporting the argument that work-based learning facilitates transitions from education to work has mainly been focused on vocational education and training, there is evidence on positive effects of work-based learning in higher education on the individuals' labour market outcomes (e.g. [3], [4], [5], [28], [33], [34], [35], [36]). ...
Article
Full-text available
This paper examines the relationship between study-related working experience or internship and early career outcomes of higher education graduates in eight European countries. The objective is to test the hypothesis that the odds of getting a first job upon graduation are increased by having study related work experience or internship during the studies. The hypothesis was drawn on the theoretical perspectives of the human capital theory and built on previous research on work-based learning experienced through internship and integrated in the curriculum. The results off the odds ratio analysis, applied on the whole sample and separately on each country participating in the EUROGRADUATE 2019 pilot survey, support the hypothesis.
... Additionally, it enables instructors to create settings where students may put their academic knowledge to use in real-world situations while simultaneously giving students access to invaluable professional networks and experience. Then, it provides firms with a constant flow of new personnel with innovative ideas from academia (Hora, Chen, Parrott, & Her, 2019;National Association of Colleges and Employers, 2018;Maertz, Stoeberl, & Marks, 2014). Furthermore, undergraduate internship training gives students the chance to advance their academic understanding, improve their soft skills, and learn other abilities that are crucial for employment after graduation (Sahrir, et al., 2016). ...
Article
Full-text available
The study aimed to analyze and determine the effectiveness of the implementation of Northwest Samar State University based on CMO No. 104 s. 2017. I used a descriptive-evaluative research design employing the use of an e-questionnaire to gather relevant data. These data were analyzed and collated with suitable statistical tools and were interpreted and discussed consequently. The results of the study revealed that the SIPP coordinators’ and student interns' perception of the implementation of the SIPP is “effective”. However, there is a significant difference in the perceptions of the two groups of respondents. Irregular inspection/monitoring of coordinators because of the difficulty in the mobility of the coordinators is considered a problem encountered in the implementation. The findings of the study suggested that the University should implement more services for the effective and efficient implementation of SIPP.
... Although literature supporting the argument that work-based learning facilitates transitions from education to work has mainly been focused on vocational education and training, there is evidence on positive effects of work-based learning in higher education on the individuals' labour market outcomes (e.g. [3], [4], [5], [28], [33], [34], [35], [36]). ...
Chapter
Full-text available
STRATEGIC EMPLOYEE MOTIVATION AND CREATING PRODUCTIVE WORK M Radovic-Markovic, S Vujicic, Z Medic
Chapter
This chapter describes a qualitative study of how organizations use information to evaluate and hire graduating students into entry-level positions from one pre-professional undergraduate program. The study investigates how campus recruiters and hiring managers make sense of student job applicants' cognitive, non-cognitive, and technical abilities from data presented in résumés, academic transcripts, and through various interview techniques. The findings provide insight into the opportunities and challenges to incorporating alternative representations of learning—Comprehensive Learner Records—into the recruitment and hiring process. The findings also reveal how information about learning and learners is used to establish pipelines for recruiting and hiring recent college graduates. The study informs the design of future assessment and credentialing infrastructures, with the goal of expanding how “learning” is measured, defined, and represented in higher education to enhance diversity, equity, and opportunity for learners.
Article
Internships are a common way for firms to hire college-educated workers, prompting concerns about how internship hiring affects various forms of inequality in the transition from school to work. Some of these concerns center on whether internships might be less accessible for workers from non-white racial groups. In this paper, I examine racial disparities in internship hiring and argue that, relative to full-time hiring, in internship hiring firms have less information about candidates’ qualifications and are also less motivated to screen candidates intensely. Therefore, group-based status beliefs play a larger role in the screening of intern candidates than in the screening of full-time candidates, leading to larger disadvantages for low-status workers (i.e., non-white workers). I examine these claims using data from a Silicon Valley software firm recruiting for both software engineering internships and entry-level software engineering positions. I find evidence consistent with such “cursory screening” of intern candidates leading to non-white (i.e., Asian, Hispanic, Black) job candidates being more strongly disadvantaged relative to white candidates in competing for internships as compared with full-time positions.
Article
Full-text available
With the rising price of college and anxiety about graduates’ job prospects, the employability of graduates is a dominant narrative shaping postsecondary policy and practice around the world. Yet, completion and the acquisition of a credential alone do not guarantee employment, and research on hiring reveals its subjective aspects, particularly when cultural signals of applicants are matched to those of organizations. In this qualitative study of 42 manufacturing firms in the US state of Wisconsin, cultural capital theory is used to investigate the prevalence of hiring as “cultural matching” using thematic and social network methods to analyze interview data. Results indicate that 74% of employers hire for cultural fit, but, contrary to prior research, this matching process is not simply a matter of fitting applicant personalities to monolithic “organizational cultures” or interviewer preferences. Instead, employers match diverse applicant dispositions (e.g., personality, attitude) and competencies (e.g., cognitive, inter-personal, intra-personal) to the personalities of existing staff as well as to industry-specific norms that are dominant within specific departments. The paper explores implications of these findings for college students, faculty, and career advisors, especially in light of the potential for discriminatory practices during the job search and hiring process.
Article
Full-text available
In the summer of 2010, Taiwanese-based Foxconn Technology Group—the world's largest electronics manufacturer—utilized the labor of 150,000 student interns from vocational schools at its facilities all over China. Foxconn is one of many global firms utilizing student intern labor. Far from being freely chosen, student internships are organized by the local state working with enterprises and schools, frequently in violation of the rights of student interns and in violation of Chinese law. Foxconn, through direct deals with government departments, has outsourced recruitment to vocational schools to obtain a new source of student workers at below minimum wages. The goals and timing of internships are set not by student educational or training priorities but by the demand for products dictated by companies.
Article
Full-text available
Internships are a growing, yet controversial, labour market phenomenon. In particular, the issue of unpaid internships has been the source of legislative, judicial and ethical debate. Some have criticised colleges and universities for promoting an expansion of internships for undergraduate students – with little regard for internship characteristics such as compensation, quality of supervision and work activities. Meanwhile, there is a paucity of research examining the role internship characteristics, such as compensation, supervisor behaviours and work design have on internship efficacy. Based on a survey of undergraduate students in the US, the results showed that supervisor mentoring, the developmental value of the internship and the job pursuit intentions of the intern with the host employer were lower for those reporting on their unpaid internship vs. paid internship. Meanwhile, supervisor support and supervisor mentoring are significant predictors of internship efficacy regardless of internship compensation, while work design has much less of an impact on internship efficacy. The implications of the findings for educators, employers and prospective interns are highlighted.
Article
There is broad acknowledgement that higher education should produce career-ready graduates and the role of practical experience - such as part-time employment, unregulated extra-curricular internships and work-integrated learning (WIL) - in achieving this. WIL is critical for developing the non-technical skills, disciplinary expertise and career self-management competencies required to prepare graduates for the world-of-work. Although Australia appears committed to growing WIL, many employers engage in extra-curricular internships while there is a lack of industry partners available to meet student demand for WIL. Extra-curricular internships may, therefore, be considered the 'black market' to WIL and could be constraining the achievement of targeted growth in Australia's National Strategy for WIL. This paper highlights that extra-curricular internships may not be governed by the good practice principles critical to a quality work-based learning experience. It explores possible reasons for stakeholder preference for unregulated, extra-curricular internships and presents strategies to shift their engagement to WIL. © 2018 International Journal of Work-Integrated Learning. All rights reserved.
Article
Higher education institutions are increasingly concerned with the professional insertion of graduates in the labour market and with the design of institutional mechanisms to facilitate students’ transition from higher education to work, particularly given the context of scarcity of financial resources and the rise of graduate unemployment. This issue has been addressed, inter alia, through the creation of study programmes with internships. Despite the public discourse encouraging the use of such strategies, there is a general consensus regarding the absence of empirical studies on the professional value of these strategies. This article aims to assess two interrelated questions: the extent to which measures of graduate unemployment rate tend to decrease after the introduction of internships in Portuguese study programmes; and the extent to which this effect applies to the different institutions that comprise the Portuguese tertiary education landscape. It also seeks to contribute to the debate on the relevance of the structure and nature of internships, which are factors frequently neglected in the literature.
Article
Recent college graduates face more uncertainty in finding employment today than they have in the past (Spreen, 2013). Colleges and universities encourage students to participate in internships to increase their employment potential. Participation in internships is one of 10 practices that the Association of American Colleges and Universities has designated as “high-impact” for their promise in fostering engagement, persistence, and learning among undergraduate students (Brownell & Swaner, 2010; Kuh, 2008). Although no consensus for the definition of internship exists, O’Neill (2010) suggests that internships are generally experiential learning opportunities that include reflection, onsite guidance, and the ability to gain exposure to a career a student is considering in a real-world setting. Despite the rising popularity of internships and other high-impact practices in college curricula and cocurricula, until recently, little empirical research had been conducted to confirm anecdotal evidence suggesting the power of this educational experience for student learning (Brownell & Swaner, 2010). Prior research on internships confirms the long-held belief that internship participation offers students an advantage in the job market (Jones, 2002; Keller, 2012) as well as other work-related skills such as students’ increased understandings of the types of jobs that are good matches for them (Brooks, Cornelius, Greenfield, & Joseph, 1995; Fernald & Goldstein, 2013; Jones, 2002; Keller, 2012) and students’ increased confidence in navigating their workplaces (Fernald & Goldstein, 2013; Keller, 2012; Simons et al., 2012). In addition, recent studies have demonstrated that participation in internships has been associated with students’ enhanced interpersonal skills such as listening (Fernald & Goldstein, 2013), collaborating with peers (Fernald & Goldstein, 2013; Jones, 2002; Miller, Rycek, & Fritson, 2011), communication skills (Jones, 2002), multicultural skills (Simons et al., 2012), and time management skills (Simons et al., 2012), as well as students’ academic growth as measured by improved critical thinking skills (Jones, 2002), perceived learning gains (Finley & McNair, 2013), and cumulative GPA (Knouse, Tanner, & Harris, 1999). In a study testing the impact of high-impact practices on liberal arts educational outcomes, Kilgo, Sheets, and Pascarella (2015) found that participation in internships was positively associated with several college outcomes, including increased need for cognition (i.e., how much one enjoys thinking and cognitive activities), intercultural effectiveness, and socially responsible leadership. A follow-up study exploring the conditional, or interaction, effects of participation in an internship and being a student of color found that participation in an internship was the only high-impact practice tested that had a positive and significant effect on need for cognition for students of color as compared to White students (Kilgo et al., 2014). A limitation of the Kilgo et al. (2014) study was that, due to a low number of students of color in the sample, they were unable to disaggregate students’ racial and ethnic backgrounds, so it was unclear whether differences existed among distinctive racial and ethnic groups in the benefits received from internship participation. A study by Fischer (2007) found differences in predictors of GPA according to race, suggesting the importance of considering the impact of participation on racial groups individually. Absent from the literature, however, is consideration of how students’ racial and ethnic backgrounds may affect internship participation outcomes, particularly academic ones. Grade point average in particular is important to examine for students participating in internships, due to both its link to retention (see Bean, 2005) and the link between retention and gainful employment. While the rationale for internships is focused on career-related outcomes, GPA plays an essential role in the link between internship participation and the job market. While internship experiences often have GPA requirements, we feel it is essential to examine the effects of internships on end-of-fourth-year GPA. We employ Astin’s (1993) I-E-O Model to explain how students develop in college as a result of participation in internships. The “I” refers to inputs, or what students bring to college in terms of background characteristics and experiences. The “E” stands for environment—specifically, the college environment and all of the programs, people, and experiences students encounter during their college years. And the “O” represents outcomes, or students’ characteristics after being shaped by their environment. The I-E-O Model provides a conceptual explanation of how...