slide1 l.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
AAU Graduate Education Taskforce: Progress, Plans, Issues PowerPoint Presentation
Download Presentation
AAU Graduate Education Taskforce: Progress, Plans, Issues

Loading in 2 Seconds...

play fullscreen
1 / 19

AAU Graduate Education Taskforce: Progress, Plans, Issues - PowerPoint PPT Presentation


  • 211 Views
  • Uploaded on

AAU Graduate Education Taskforce: Progress, Plans, Issues. Presented to: AAUDE Annual Meeting May 2005. AAU/AAUDE groups and projects focused on data, spring 2005 You can’t tell the players (and groups) without a scorecard! . Presidents John Wiley (chair), Wisconsin John Casteen, Virginia

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'AAU Graduate Education Taskforce: Progress, Plans, Issues' - jacob


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
slide1

AAU Graduate Education Taskforce:

Progress, Plans, Issues

Presented to:

AAUDE Annual Meeting

May 2005

slide2
AAU/AAUDE groups and projects focused on data, spring 2005You can’t tell the players (and groups) without a scorecard!
the institutional data committee idc meetings april october
Presidents

John Wiley (chair), Wisconsin

John Casteen, Virginia

Scott Cowen, Tulane

Larry Faulkner, Texas

Richard Levin, Yale

Richard Herman, Illinois

Provosts

John Anderson, Case Western

Paul Courant, Michigan

Debbie Freund, Syracuse

Marty Wyngaarden Kraus, Brandeis

Dave Shulenburger, Kansas.

The Institutional Data Committee (IDC)Meetings April, October
  • Institutional Researchers/AAUDE

Rana Glasgal, Stanford

Bill Hayward, Northwestern

Dennis Hengstler, UC-Berkeley

graduate education data task force meetings march late august
Graduate Deans

Dick Attiyeh (chair), UCSD

Karen Klomparens, Mich State

Lawrence Martin, Stony Brook

Lewis Siegel, Duke

Bob Thach, Washington U

Graduate School Reps

T. Jim Matthews, NYU

Judi Sui, UC Berkeley

Harvey Waterman, Rutgers

Researchers on Graduate Ed

Maresi Nerad, UWashington

Rachelle Brooks, Maryland (also AAUDE)

Institutional Researchers/AAUDE

Julie Carpenter-Hubin, Ohio St

Bernard Lentz, Penn

Jed Marsh, Princeton

Lou McClelland, Colorado

Lydia Snover, MIT

Kendrick Tatum, Duke

Graduate Education Data Task ForceMeetings March, late August
grad ed taskforce subcommittees reports due august 1
Program, institutional data

Lawrence Martin, chair, Stony Brook

Karen Klomparens, Mich St

Lewis Siegel, Duke

Harvey Waterman, Rutgers

Bob Thach, Washington U

Julie Carpenter-Hubin, Ohio State, AAUDE

Lou McClelland, Colorado, AAUDE

Student experience, student reported surveys

Rachelle Brooks, chair, Maryland (AAUDE)

Judi Sui, Berkeley

Lydia Snover, MIT, AAUDE

Kendrick Tatum, Duke, AAUDE

Outcomes, placement, alumni

Maresi Nerad, chair, UW

Jim Matthews, NYU

Barney Lentz, Penn, AAUDE

Jed Marsh, Princeton, AAUDE

Grad Ed Taskforce SubcommitteesReports due August 1
goal id core data elements to be shared by aau member institutions
Goal: ID core data elements to be shared by AAU member institutions
  • Used by members to guide institutional and program policy decisions and practices
  • Not for prospective students or the public
  • Not for rankings
  • Data may be used to inform national discussions of graduate education and outcomes
emphasis doctoral education
Emphasis: Doctoral education
  • Master’s programs or awards associated with doctoral programs included for completeness.
  • Professional degrees, MBAs, and stand-alone master’s programs not an explicit focus
program level data
Program level data
  • Unit of analysis/comparison: Programs or departments, often by degree level
  • Issue: Need the division into programs be
    • Mutually exclusive?
    • Exhaustive?
  • Issue: Should campus totals come from
    • Summing over all programs
    • Separate report
priority topics subcommittees
Priority topics = subcommittees
  • Student experience, from student surveys
  • Student placement, outcomes, alumni
    • Not just immediately after the degree, but later
  • Institutional or program data
    • Admissions
    • Retention, graduation rates and time-to-degree
    • Financial support
    • Enrollment/ demographics
emphasis data to answer questions use in management examples
Emphasis: Data to answer questions, use in management Examples:

Placement

  • Where graduates go
  • Correlation between admission credentials and first professional placement

Program

  • Time to complete a doctoral degree
  • Fraction of students graduating with a PhD
  • Changes in the demographic profile of students applying for doctoral programs

Financial Support

  • Cost to support a PhD student

Student surveys

  • How students assess their doctoral experience
operating principles endorsed by the grad data taskforce
Operating principles endorsed by the Grad Data Taskforce
  • Sufficient safeguards must be in place to ensure the privacy of individuals
  • Self-reported student data should be use only when institutional data are not available
  • Whenever possible data should be collected by degree level at the academic program level.
  • The reporting of summarized data (e.g., percentages) should avoided as much as possible
    • Even unit record data under consideration
  • Data should be submitted electronically in a disaggregated format that facilitates inclusion in the data warehouse, in data files not in Excels.
  • Each data element should be clearly defined and documented in a data dictionary that compares and contrasts similar data elements commonly available to the public.
known needs and issues
Known needs and issues
  • Definitions, especially for graduation rates and time to degree
  • Discipline crosswalks and rollups among the NRC, IPEDS, NSF-SED, CGS, and other data collection systems.
    • Grad deans realize there’s no right answer, want just to do something and not get bogged down on this.
    • Programs vs. departments vs. disciplines
    • Labeling vs. grouping; level of detail
  • Rules about data release, including rules that appropriately limit the reporting of small cell sizes
  • Ways of ensuring that data collected will allow meaningful aggregation
known needs and issues continued
Known needs and issues (continued)
  • Relationship to NRC, and NRC plans and timing both for scheduled review and further updates
  • Fit to, extension of, exploitation of ongoing large-scale required or high-coverage data collections
    • SED – Confidentiality agreements, local capture with supplemental questions, utility for things also in records.
      • Already in warehouse for MIT, Florida, Colorado.
    • IPEDS completions and enrollment
    • CGS/GRE survey of grad enrollment
    • CGS PhD completion project
    • AAUDE exchanges such as grad stipends
    • NSF Survey of Graduate Students and Postdocs
timing deliverables
Timing, deliverables
  • Subcommittee reports due August 1
    • Prioritized list of at least five key questions of interest to policy makers
    • Set of data elements required to address the questions
  • Circulate to entire Taskforce
  • Meet late August or early September to discuss the sub-committee reports and prepare a draft report
  • Report to provosts, AGS, and IDC before presidents’ meeting in October
aaude reps accomplishments
AAUDE Reps: Accomplishments
  • The “white paper”
    • ftp://aaude.mit.edu/IDC/Grad/graded_paper20050320.doc
    • Official name Graduate Student and Graduate Education Data Needs
  • The glossary
    • ftp://aaude.mit.edu/IDC/Grad/graded_glossary.doc
  • Concordance of items on various student surveys
  • Grad stipend exchange item
  • Grad CDS
  • This presentation!
white paper useful for you
White paper: Useful for you
  • Julie, 2003, augmented by Julie, Jed, Lydia, Lou, 2005, used at 3/05 task force meeting
  • Topics: numbers and demographics; credentials; financial support; student experience including graduation rates and time to degree; career track; policies.
  • Sources discussed re coverage, availability, issues, recommendations
white paper sources covered
CGS/GRE Survey of Graduate Enrollment

Survey of Earned Doctorates (SED, to the DRF Doctoral Research File)

Self-reports by students of records-type info

IPEDS Fall Enrollments

NSF Survey of Graduate Students and Postdoctorates in Science and Engineering

Thomson Peterson’s Annual Survey of Graduate and Professional Institutions

IPEDS Completions

US News & World Report America’s Best Graduate Schools

GRE Summary Statistics Reports

Rutgers Graduate Education Survey (collection from selected PhD programs at 6-8 AAU’s, with both student survey and records information)

Graduate CDS

AAUDE Graduate Student Stipends Survey

Rutgers and Duke/MIT student surveys

CGS PhD Completion project

NAGPS National Doctoral Program student survey

Placement surveys by academic associations and other researchers, including the “Ph.D.’s-Ten Years Later Study”

NSF Survey of Doctoral Recipients re science and engineering doctoral graduates.

Institutional or program collections of placement data

Responsive PhD, Re-envisioning the PhD, and Carnegie Initiatives on the Doctorate

White paper: Sources covered
aaude reps endeavors
AAUDE Reps: Endeavors
  • Paper on cohort definition, time to degree, grad rates, etc.
    • Build on work by Colorado, Maryland, and Wisconsin, especially for the CGS completion project
  • Analysis of SED re time to degree for the schools with data in the warehouse.
  • Making Penn’s mechanisms available to others, for collecting postdoc and first professional placement
  • Possibilities for release of SED data from all AAU’s to the warehouse, and/or local or coordinated web administration with data to the warehouse
  • Work on crosswalks, rollups, level of detail, etc. for PhD programs in particular.
slide19

AAU Graduate Education Taskforce:

Progress, Plans, Issues

Presented to:

AAUDE Annual Meeting

May 2005