Rachel A.Smith, SIT Conference 2010
Acknowledgements
“Only Connect”:
A Mixed Methods Study of How
First-Year Students Create
Residential Academic and Social
Networks
Rachel A. Smith
Baruch College, CUNY
[email protected]
„
„
„
Conference on
Students in Transition
November 14, 2010
Introduction
„
„
First-year college students: new environment,
need to create academic/social relationships
College administrators structure environments
where students are more likely to create certain
relationships (e.g. learning communities)
Littl iis kknown about
Little
b th
how th
these specific
ifi ““networks”
t
k ”
of relationships facilitate educational outcomes
Funded through the 2009-2010 Paul P. Fidler
Grant from the National Resource Center for
The First-Year Experience and Students in
Transition
Thank you to my participants and staff in
residence life and the learning communities
office
Inside the Box
Social
Integration
Learning
Communities
Institution
Student
Characteristics
Student
Outcomes
Gender
Persistence
Race
Completion
Family Income
Transfer
HS GPA
Learning
Involvement
Theoretical Framework
„
Academic and/or Social Integration (Tinto, 1993)
-If students are connected to the institution
academically and/or socially, they will be less
likely to leave it
„
“Involvement” & “Engagement” as a proxy for
learning & a measure of student success (Kuh,
Astin, etc.)
Academic
Integration
Theoretical Framework
„
Learning Community definitions & research
-Participation in LCs is generally associated
with positive educational outcomes, although
effect sizes may be relatively small
„
Social Network Analysis
(Wasserman & Faust, 1994; Thomas, 2000)
-Homophily can be a predictor of tie formation
(McPherson, Smith-Lovin, & Cook, 2001)
-Position in network associated with
outcomes
1
Rachel A.Smith, SIT Conference 2010
Research Questions
„
„
„
Methods
What is the structure of students’ residential
academic and social networks? Why? What
relationship does structure have with a
learning community environment?
What institutional structures influence
network formation?
Are students’ positions in their residential
networks related to educational outcomes?
„
-Arts-themed learning community (“ProArte”)
-Random-assignment
R d
i
t residence
id
hall
h ll flfloor (“Tyler
(“T l 2”)
„
„
„
„
„
„
Two paper surveys
(Fall 2006, Spring
2007)
Based on common
network questions,
roster style
Response rates: 92%
and 85%
76 LC students
64 random-assignment
students
Methods: Qualitative
1. On average, how many hours
per week have you recently spent
socializing with each person?
Name
„
„
„
„
Number of
Hours
Lastname, Firstname
„
Lastname, Firstname
Lastname, Firstname
Methods: Research Population
„
Mixed methods (“triangulation”)
-Paper surveys
-Individual Interviews
-Participant observation
(first-semester GPA & second-semester involvement)
Methods: Surveys
Case study: two residential communities at
one institution (mid-size private in the NE)
over 1.5 years
Generally reflected demographics of
institution (Qualitative)
50% men; 50% women (50% / 50%)
Race/Ethnicity:
- 72.1%
72 1% White (75.1%)
(75 1%)
- 15.7% Asian/Asian-American (15.9%)
- 6.4% Latino (4.5%)
- 5.7% Black (4.5%)
80% First-year students (82%)
„
Individual Interviews (30-60 minutes each)
-45 in Fall 2006
-42 first follow-up in Spring 2007
-20
20 second
d ffollow-up
ll
i F
in
Fallll 2007
Participant Observation
-Floor meetings, field trips, classes, hanging
out
My Identity
Methods: Analysis
„
„
„
Quantitative: survey data computerized and
analyzed using Ucinet1, NetDraw2,& SAS
Qualitative:
-interviews recorded and transcribed
-field notes typed
-data categorized into 235 codes
-analyzed for themes
Brought types of data together for joint
analysis
1
(Borgatti, Everett, & Freeman, 2002)
2
(Borgatti, 2002)
2
Rachel A.Smith, SIT Conference 2010
Methods: Social Network
Analysis
„
„
„
„
„
„
Density as an Indicator of
Student Integration
„
“Network”: actors + relations
Actors or Nodes
Relational tie
Tie strength/value
Directionality
Sociogram
„
„
„
Results: Social, Fall 2006
„
„
Results: ProArte Social
Fall 2006
ProArte denser than Tyler 2
Densities: ProArte – 0.1740 Tyler 2 – 0.1587
Red: Female
Blue: Male
Measures the amount of student interaction
in a particular community
Density
y = reported
p
/p
possible ties ((normalized
to account for differential network size)
Symmetrized & dichotomized ties
Greater density = greater integration
„
Asian American
Asian International
Black
Latino/a
White
Add networks and
quotes
Most of my friends are people in the
[ProArte] learning community, like
right now. There was a lot of forced
stuff
in of
the
beginning,
we floor
all just
It’s
kind
divided
I thinkthen
on the
of between
made friends
anyway. … I
atkind
least,
the learning
Itguess
was, Iitmean
least
the
girls’
floor
was
little
necessary,
when
community
kidsaatand
the
other
kids.
was
afind
family.
we
were
almost
we Iwere
first…
starting
out out
here,
Like
myself
hanging
with
with,like
the
aeveryone
sorority,
though
it wasn’t
was
like
“Yeah!
Yeah!
only
peopleeven
I hang
out
with
on
the floor
really
a sorority,
it’scommunity,
just
thatwhat
we
[ProArte]!
We don’t
know
it
are
in the
learning
and
were
all there
together,
doing
means.”
everyone
else is
off doing
theirart.
ownIt
was cool.
thing.
-Cindi
-Georgina
-Diego
(November 10, 2006)
(November
2007)
(October
20,2,
2006)
- Group Identity
- Women’s floor cohesion
ProArte
Tyler 2
Results: Tyler 2 Social
Fall 2006
It’s like everyone is each other’s
best friend. We have pride in our
floor. We’re like “[Tyler 2]”! And,
uh, I tell people, everyone goes
to the lounge. I mean so many
Lauren as
hada acrew
“sarcasticmember,
sense
Abigail,
people, you
know, team
everyone’s
of humor
…bed
that kind of
gets
had
to go
to
and
spent
friendly
with
eachearly
other
other.
ontime
people
sometimes”
alost
lot of
off the
Everyone
seems
tofloor.
get along.
(September
29, 2006)
It’s
nice. It’s positive
energy. I
like that. I’ll just walk to the
lounge and just hang out with
other people that hang out there.
- Men’s floor divisions
Results: Academic, Fall 2006
„
„
„
ProArte denser than Tyler 2
Academic networks less dense than social networks
Densities: ProArte – 0.0853 Tyler 2 – 0.0497
-Derek
- The “Lounge Group”
- Feeling peripheral
(September 29, 2006)
ProArte
Tyler 2
3
Rachel A.Smith, SIT Conference 2010
Results: Tyler 2 Academic
Fall 2006
Results: ProArte Academic
Fall 2006
I get like
distracted
and I get
excited.
Well
last weekend
I had
to do,
I’m
like,foundation
“Yeah! People!”
all the
classes And,
have to
then,
I’ll
like
talk
about
something
do their sketch book of 50
else. … I don’t
think
anyone
else
drawings
of stuff
around
campus.
on
is taking
any of the
So this
she floor
[Becky]
went around
with
same
classes
that
I’m
taking.
I
me like taking pictures of all the
knowlike
there’s
there
s a few
stuff
helping
me[art
findand
things.
things
performance]
people,
like
Becky.
And then this weekend I have to
She,
know,
homework’s
makeyou
a video
forher
one
of my
doing
the
color
and like,
classes
and
umwheel,
she’s going
to I
don’t
really,
you
know,
have
a
come with me and be in
it. And
color
wheel.
like she had a, she has to do like
- Studying with others doesn’t work
- A few with compatible majors
worked together
pictures and I would do stuff and
-Lauren
she’d take pictures of it.
(September 29, 2006)
-Kathy
(November 10, 2006)
„
- Role of space
-Elizabeth
-Sarah
(November
11,15,
2006)
(November
2006)
Results: Academic Networks
Spring 2007
ProArte denser than Tyler 2
ProArte – 0.1449 Tyler 2 – 0.1215
Both networks less dense than their respective Fall social
networks (Tyler 2 not significant difference)
ProArte
- Studying via LC courses
- Competition / feedback in arts majors
Results: Social Networks
Spring 2007
„
We’ll
all go
in to
ourtheir
lounge,
and we’ll
Iwork
just
walk
You
together,
you[classmates’]
workbut
aswe’re
a
do door
it [homework]
together,
and
we like
work things
group,
know,
because
you out
nottogether.
likeyou
actually
working
together,
And we
actually
are
want
to
help
each
other.
Because
like,doing
somebody
will be sewing,
group
inyou’re
English
from
helping
thatprojects
person,
somebody
building
now.
Sowill
it’sasbe
like
I’m withyou
Stacey
going
to grow
a person,
something
g
for
3-D,
y will be
and
Oriana,
like somebody
they
all it’s
live,
kdrawing
know.
It’s
It’Oriana
very
competitive,
titi
it’live
for
foundation,
like
I’ll be
Stacey
lives
right
next door
and
intense,
but
you,
you
make
the
best
doing
my 2-D
stuff.
it’s fun.
Soso
like
twoSo
doors
down,
ofwe’re
it.Oriana’s
the lounge
until like
we always
can likeinwork
in the lounge
or
twoininone
the of
morning,
all just
there.
-Juan
our rooms
or whatever.
Because
none
of
ustocan
do people
art work
It’s
a
way
to
get
know
(December
1, 2006)
in our
rooms
some
reason, it’s
on the
floorforthat
I probably
such
a smallget
cramped
wouldn’t
to knowspace.
on my own.
„
Tyler 2
Results: Change Over Time
According to Students
ProArte density decreased (0.0505), while Tyler 2
density increased (0.0600, not significant)
ProArte
Tyler 2
Results: Change Over Time
According to Students
Social change:
Academic change:
„
„
„
Set group of
friends real
friends—“real
friends”
Too busy to make
new friends
Larger groups
fractured
„
„
P At
ProArte—need
d tto focus
f
on profession/major
Tyler 2—understand
academic expectations,
need to study moreÆ
use friends on floor
4
Rachel A.Smith, SIT Conference 2010
Results: Change Over Time
ProArte Multiplex Ties
Results: Change Over Time
Tyler 2 Multiplex Ties
Fewer multipurpose (red) ties
More divided by academic (green) and social (blue)
„
„
153
145
149
143
129
137
154
142
155
139 140 125 117 121 124
128 133
119
113
107
148
149
136
132
134
167
166
123
144
145
120
115
111
104
165
118
101
114
103
112
116
122
127
110
126
102
138
108
130
105
131
141
147
146
151
150
152
178
169
161 163
164
160 157 159 176
162
156
158
174
170
117
143
141
131 109 164 163 166 167
154 111
155
153
142
140
135
150
144
109
135
182
148
106
180
172
168
„
132
134
133
136
139
146
225
147
116
128
261
162
127
125
114
108
105
103
174
172
104
176
180
178
107 102
122
106 118 120 121
119
160
158
152
169
165
159
101
170
161
168
151
241
254
242
223
245
203
205
208
253
269
209
265
230
255
207
208
250
263
246
236
225
234
240
245
231
237
206
244
216
214
224
212
228
205
238
255
223
232
210
240
239
221
220
224
226
217
233
232
227
235
237
213
256
247
251
238
259
211
218
246
207
230
215
204
236
249
228
244
202
203
201
227
263
234
Spring 2007
214
253
229
250
226
221
204
212
211
216
206
265
257
202
218
220
Fall 2006
Discussion
249
229
235
258
261
219
242
251
254
267
257
248 247
252
241
Spring 2007
Possible Role of Homophily in
Network Formation
In this study, LC (even in a simple form)
seemed to influence the speed of academic
integration
LC: academic & social ties in first semester,
semester
-LC:
then emphasis on major in second semester
(no LC courses)
-Tyler 2: social ties in first semester, turn to
multiplex ties in second semester, emphasis
on major in second year
Results: Homophily
„
„
„
“Homophily” = being “like” someone
(e.g. same gender, race, major, class year)
Do students create academic or social
relationships based on homophily? If so,
what kind(s) of homophily?
Analysis: MRQAP regression
(matrices predict a resulting matrix)
Summary of Results: Homophily
Social Ties
MRQAP Analysis Using Homophily to Predict Existence of Network Ties in the Learning
Community, Fall 2006
Social Network
Variable
Gender
Race
Income
M j
Major
Class Year
Learning Community Member
Enrollment in LC Music Appreciation
Enrollment in LC Writing
b
0.15***
0.05*
0.01
0 19***
0.19***
0.15***
0.11***
-
R2
0.13***
*p <.05; **p <.01; ***p <.001.
243
252
126
129
130
124
231
209
113
115
233
210
156
123
217
219
137
157
222
213
112
110
215
248
239
201
138
Fall 2006
„
More multipurpose (red) ties
More academic only (green) in spring than in fall
„
β
0.20
0.07
0.01
0 14
0.14
0.19
0.15
-
Academic Network
b
0.10***
0.01
-0.00
0 18***
0.18***
-0.01
-0.02
0.04**
0.07***
β
0.17
0.01
-0.00
0 19
0.19
-0.01
-0.03
0.07
Learning
Community
RandomAssignment
Floor
Academic Ties
Gender, major,
class year,
LC membership
Gender, major,
LC writing course
Race class year
Race,
Major class year
Major,
year,
gender
Changes in second semester:
-For LC, gender and class year became negative in academic model
-For RA Floor, gender not significant in academic model
Small r2 value
5
Rachel A.Smith, SIT Conference 2010
Summary of Results:
Institutional Factors
Results: Network Position and
Fall 2006 GPA
OLS Regression Predicting Fall 2006 GPA
Variable
Academic Closeness Centrality
„
„
Major socialization & decision-making
-personal & professional identity
-anxiety
-other influences (family, culture, finances)
-navigating major & other interests
Learning Community
„Academic
closeness
centrality not predictive of
GPA
„Higher GPA:
female, second-year and
above, LC writing course
„Lower GPA:
HS GPA below 3.5
Some evidence institutional regulations
constrained ties with non-majors
Results: Network Position and
Spring 2007 Campus
Involvement
Student Characteristics (%)
Gender
Female
Race/Ethnicity
Students of Color
High School GPA
Below 3.5
Class Year
Second-year
Second
year and above
Academic Major
Arts
Sciences
Enrolled in LC Writing Course
Intercept
F value
R2
Adj. R2
N
b
β
-0.00
(0.01)
0.03
(0.27)
-0.10
0.04
0.15*
(0.07)
0.17
-0.09
(0.08)
-0.10
-0.27***
(0.07)
-0.32
0.26
0
26**
(0.09)
-0.05
(0.07)
-0.17
(0.10)
0.24*
(0.11)
0 24
0.24
-0.06
-0.13
0.19
3.34***
(0.09)
4.48***
0.25
0.19
134
Notes : Standard errors are shown in parentheses.
OLS = ordinary least squares; Adj. = Adjusted
Reference groups are: Gender (male); Race/Ethnicity (White)
High School GPA (3.5 and above); Class Year (First-year);
Academic Major (Other)
*p <.05; **p <.01; ***p <.001.
Conclusions
OLS Regression Predicting Spring 2007 Semester Campus
Involvement
Variable
Social Closeness Centrality
Learning Community
„
„
„
Social closeness centrality
predictive of campus
involvement
Greater involvement:
second-year and above,
sciences
Less involvement:
HS GPA below 3.5
Student Characteristics (%)
Gender
Female
Race/Ethnicity
Students of Color
High School GPA
Below 3.5
Class Year
Second-year and above
Academic Major
Arts
Sciences
Intercept
F value
R2
Adj. R2
N
b
0.21*
(0.09)
-2.20
(1.94)
β
0.33
1.37
(1.12)
0.10
-1.40
(1.22)
-0.09
-3.50**
(1.12)
-0.27
4.25**
(1.42)
0.26
0.78
(1.19)
3.39*
(1.68)
-0.06
„
„
„
„
„
0.17
-1.11
(3.37)
3.71***
0.19
0.14
134
Notes : Standard errors are shown in parentheses.
OLS = ordinary least squares; Adj. = Adjusted
Reference groups are: Gender (male); Race/Ethnicity (White)
High School GPA (3.5 and above); Class Year (First-year);
Academic Major (Other)
*p <.05; **p <.01; ***p <.001.
Limitations & Future Directions
„
„
-0.16
Not generalizable
Student-reported outcomes; not able to use
persistence as a dependent variable
Future study with other student populations,
i tit ti ttypes, learning
institution
l
i community
it ttypes,
and other student communities;
administrative structures
Student interactions across diversity
Development of SNA as an assessment tool
„
The learning community appears to
facilitate a greater number of academic
and social ties among students during the
first semester
Some evidence suggests restrictive major
requirements
i
t iincrease iin-group
interactions at the expense of out-group
connections
Having an initially central network position
is related to having higher secondsemester campus extracurricular
involvement
References
Borgatti, S.P. (2002). NetDraw: Graph Visualization Software. Harvard,
MA: Analytic Technologies.
Borgatti, S.P., Everett, M.G. & Freeman, L.C. (2002). Ucinet for
Windows: Software for Social Network Analysis. Harvard, MA:
Analytic Technologies.
McPherson, M., Smith-Lovin, L., & Cook, J.M. (2001). Birds of a
feather: Homophily in social networks. Annual Review of
Sociology, 27, 415
415-444.
444.
National Survey of Student Engagement. http://nsse.iub.edu/
Thomas, S.L. (2000). Ties that bind: A social network approach to
understanding student integration and persistence. The Journal of
Higher Education, 71(5), 591-615.
Tinto, V. (1993). Leaving college: Rethinking the causes and cures of
student attrition, 2nd Ed. Chicago: The University of Chicago Press.
Wasserman, S., & Faust, K. (1994). Social network analysis: Methods
and applications. New York: Cambridge University Press.
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