Talking Stick - September/October 2017 - 42

of state, Marie believed that students
getting to know one another was a
priority. What if she could determine,
from the data, that social programming was not happening during those
first critical weeks of the semester?
She could take action and direct the
staff to provide more. Through the
card swipe data, Marie could also
know which residents were not being
reached. She could identify those students holed up in their rooms, not connecting to anyone, and direct the RAs
to reach out to them. As this idea grew
in her head, she imagined a database
full of attendance and outcomes data,
but she also imagined a place where
the responses from those one-on-one
meetings could be stored. With help
from the department's information
technology staff, she set about creating
a web portal where those responses
could be recorded by the RA staff.
First, the number of questions RAs
asked was cut in half, and RAs were
trained to ask these questions without
prompting from a book. At the end of
the conversation, away from residents,
RAs would log in and enter two to
three sentences for each question.
Those qualitative responses could
then be analyzed by the hall directors
using technology to track the frequency of red flag words like "homesick,"
"suicide," "lonely," "academics," and
other key indicators. This would be a
much faster way to gauge the overall
tone of the hall without having to
wade through books recording resident responses. Marie had yet another
idea: to use the data to help identify
students who were struggling as well
as those who were blossoming. If she
could identify students who were not
engaging in programming through
their individual meeting responses,
she could target them for early intervention. Conversely, students who
were attending events regularly could
be pursued for leadership positions
such as hall government, the residence hall association, and serving as
future RAs.

TALKING STICK

As her work progressed, Marie
recognized that, for it to be fully realized, she would need to gain credibility
for the impact of her residence life
program. Her first step was to begin
a card swipe protocol that linked
program attendance to programming
forms with intended outcomes. To
transmit relevant data back to her
residence life staff more quickly, she
began sharing programming information at her weekly staff meetings.
Two of the three complexes she
supervised were making great strides.
They had a number of programs, they
were directed at the right outcomes for
that time of year, and programming
was spread amongst the priorities
for the department. In one complex,
though, the numbers were abysmal. The assistant director of that complex, Stan, was not convinced about
the value of the assessment information. He dug in his heels and said this
assessment stuff was busy work that
took time away from serving residents.
However, when Marie shared the
assessment data at the staff meeting,
Stan was embarrassed because the
data showed that his complex had
very few programs. It turned out that
programming was happening in his
area, but he had not emphasized with
his staff the importance of following
through with programming forms
and card swipes. While the other two
assistant directors were busy analyzing
their data and evaluating the implications, Stan had no data to consider.
The next month, when the programming data were shared, however, Stan
had data to which he could refer. He
was committing to the program.
In the meantime, Ronald, a graduate
student with a background in computer
programming, started working in the
assessment department. He started
looking at the data and realized that
he could connect all of it through a
relational database that would connect
multiple spreadsheets together for a
new understanding of the data. He
discovered pivot tables that could create

dashboards of charts and graphs of
information that were interactive to the
end-users: in this case, hall directors.
Those dashboards allowed the HDs to
arrange the data in ways that were most
useful to them in their individual halls
and learning communities.
Marie was ecstatic. She had gained
buy-in at the assistant director level because they could use the programming
data to help inform the types of decisions about what programming would
happen through the rest of the year:
in this case, since it was the second
semester, more programs on academic
support and fewer social programs.
This latest development, that the HDs
could check their programming, was
taking buy-in one step further. Not only
could they check overall programming,
but they could also view the data in a
variety of ways, such as by learning
community, gender, class standing,
programming type, academic major,
building the attendees lived in, and
more. Marie also understood that she
could share this programming data
with the faculty and staff stakeholders in the communities. She could tell
them how many students they were
reaching, what outcomes were targeted,
whether or not they were reaching the
students they wanted to reach, and
more.
Much like the assistant directors,
some of the HDs bought into the
assessment program and others did
not. Those with data were excited to
measure results and realized they could
change gears mid-stream and adjust
programming to meet student needs.
This new programming data, combined
with the qualitative data from individual student meetings, meant that
programming would be created from
strategic documents that contained
the proposed timing and content of
residence hall programming, as well
as relevant and timely feedback from
the residents. Much like what occurred
with the assistant directors, the HDs
who had little programming data realized the importance of having good and

Talking Stick - September/October 2017

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