A New Context Supporting Ph.D. Completion: A Longitudinal Study of 20 Doctoral Programs A New Context Supporting Ph.D. Completion: A Longitudinal Study.

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Presentation transcript:

A New Context Supporting Ph.D. Completion: A Longitudinal Study of 20 Doctoral Programs A New Context Supporting Ph.D. Completion: A Longitudinal Study of 20 Doctoral Programs Howard E. Jackson University of Cincinnati Council of Graduate Schools December 10, 2004

Acknowledgements: Robert Frank Associate Dean Eleanor Buczala Senior Assistant Dean

Comments for CGS … We are data driven… Some simple data Some simple data re-examined Some simple data not in place Some more complex data we wish

Some Simple Data University of Cincinnati Ph.D. completion data for entering cohorts (as of 9/04) English …………… 69.2% College of Medicine (8 departments) … 66.8% Psychology % Criminal Justice % College of Engineering (9 programs) %

Simple Data – displayed differently

Simple Data Reexamined …

Astonishing: 32 students completed in 3 years! Implies Terrifically talented engineering students Or a difficulty – a definitional difficulty – with the data

Simple Data Reexamined: COE Does one count from year of entry into the University? Does one count from time of Masters degree completion? University database does not have a field for when a student is admitted to candidacy(!)

More Complex Data Longitudinal Data Change over time can be observed Quantitative data Qualitative data Data collection by a neutral third party: Institute for Policy Research

More Complex Data Longitudinal Data - Quantitative Student demographics, admissions, academic data, et al. Survey data from students on attitudes, expectations goals, … Information on student progress from graduate program directors and major professors.

More Complex Data Longitudinal Data - Qualitative Taped in-depth individual interviews with 50 entering students Interviewed by specially trained Graduate Research Assistants Graduate Program Directors will be interviewed by IPR staff Data will be analyzed using qualitative methods

Presently Imagined Interventions …

In Summary … Data is good! Good data is better! Complex longitudinal data is best!