Department-Level Data Collection and Use Chris M. Golde Stanford University.
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Transcript of Department-Level Data Collection and Use Chris M. Golde Stanford University.
![Page 1: Department-Level Data Collection and Use Chris M. Golde Stanford University.](https://reader035.fdocuments.net/reader035/viewer/2022070410/56649eca5503460f94bd9031/html5/thumbnails/1.jpg)
Department-Level Data Collection
and Use
Chris M. Golde
Stanford University
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Three Research Projects Four department attrition study At Cross Purposes
National survey of graduate students www.phd-survey.org
Carnegie Initiative on the Doctorate The Formation of Scholars, fall 2007 www.carnegiefoundation.org/cid
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Premises The department is the
unit of action and analysis
Disciplines differ Departmental
practices and culture matter and can be influenced
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Methods Four department attrition
study
“At Cross Purposes” study
Carnegie Initiative on the Doctorate
Brief ethnography of departmental culture; attrited student interviews; common themes
20-page survey: 4114 students, 11 disciplines, 27 universities
CF: observations, surveys, reports Depts: surveys, focus groups, town hall meetings
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Findings Integration into
intellectual community
Mentoring and advising
Information flows and feedback
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Integration into intellectual community
Advance information
Orientation Peer mentors Initial advising Shared courses Shared office
space
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Mentoring and advising Frequency of
communication Multiple mentors Annual reviews Safety nets
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Information flows and feedback
How is graduate school different from undergraduate
Clear expectations for & access to experiences
Career paths of alumni
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Data Collection: Recommendations
Define purpose Document and assess Impel change Inform direction of
change Keep It Manageable
(KIM) (thanks Clarice)
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Data Collection: Challenges Identifying
departmental personnel
Differences between departments
Difficult to know what is “really” happening in the department
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Data Interpretation and Use: Recommendations
Don’t just report, offer analysis
Create a storyline Use stories and
examples as evidence
Use data as starting point for asking questions
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Questions to ask from data Does the department have a vibrant intellectual
community? How are new students (postdocs, faculty)
integrated into the departmental community? Does the department have a shared definition of
“a successful student”? Are these expectations clearly conveyed to students?
What career paths do program graduates follow? Are students gaining the experiences to be successful in their chosen career paths?
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Data Use: Challenges Expect challenges to
credibility of data Doesn’t match beliefs Small sample sizes Qualitative data often
seems anecdotal Long time frames:
department today is not the department of the data
Impact of changes in departmental practices and culture are hard to assess