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Tips to Handle a Complex Data Request/Report with Less Anxiety

Tips to Handle a Complex Data Request/Report with Less Anxiety. TAIR Conference February 2008 Presenter: Salma Ferdous Office of Institutional Research The University of Texas at San Antonio . Overview. Data Processing in Absence of Data Warehouse IR Responsibilities

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Tips to Handle a Complex Data Request/Report with Less Anxiety

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  1. Tips to Handle a Complex Data Request/Report with Less Anxiety TAIR Conference February 2008 Presenter: Salma Ferdous Office of Institutional Research The University of Texas at San Antonio

  2. Overview • Data Processing in Absence of Data Warehouse • IR Responsibilities • Steps of Data Analysis • Don’t be Stressed out • Data Request Example • Data Processing Methods • Questions/Answers

  3. What to Expect as an Institutional Researcher? • Institutional Researchers Often Get Complex Requests From Different Sources. • Institutional Researchers Often Face Multiple Demands With Tight Deadlines. • Institutional Researchers Obligated to Provide Quality Information, Research, and Analysis.

  4. Potential IR Responsibilities • Student Enrollments • Credit Hours Generated • Degrees Awarded • Retention and Graduation Analyses • Admission-related Analyses • Analyses of Teaching Loads and Class Size • Analyses of Grades • Analyses of Faculty • Analyses of Staff • Analyses of Levels of Research Support • Administration and Analysis of Surveys • Administration of Focus Groups of Students, Faculty, and/or Staff • Reports Summarizing Comparative Data of Peer Institutions • Requests for Ad Hoc Reports from Outside Agencies

  5. Good IR Professional Requires: • Familiarity with Fundamentals of IR (Students, Faculty, Finance, Facilities) • Technological And Analytical Skills (Research Design, Sampling Procedures, Statistics, Use of Excel, Word, Statistical Software) • Issues Intelligence (Knowledge of Major Issues or Decisions That Face Your Institution) • Contextual Intelligence (Understanding The Culture of Higher Ed and Your Particular Campus) • Communication Skill (Establish Friendly, Professional Relationship with Coworkers and with Important Campus Persons) (Dizinno and Gardner: 2007)

  6. Stages of Data Analysis • Identification - of Data And Data Sources • Acquisition - of The Needed Data • Conversion - to Readable, Usable Format • Auditing - Determining Data Accuracy & Validity • Preliminary Analysis • Full Analysis • Summary - Summarizing The Results • Presentation – Presenting The Results (Dizinno and Gardner: 2007)

  7. You should not be Stressed Out There is Good stress and Bad stress. Good stress helps keep us alert, motivates us to face challenges, and drives us to solve problems. Good stress increases our strength, speed and reaction time. Bad stress or distress occurs when our bodies overreact to events. We react to many daily situations as if they were life or death issues. As survivors in the field of Institutional Research, we would like to provide some of the insights and coping methods we have developed to manage the stress related to this line of work. (Chrestman, James and Swink: 2003)

  8. UTSA IR Data Sources Raw Data • CB Reports • Banner DataMart • Define HR System • Various UTSA Servers Published Data • UTSA Fact book • THECB Accountability Website • UT System Accountability Website • THECB PREP Query Tool • IPEDS Peer Analysis System • Census Data • Texas State Data Center and Office of the State Demographer

  9. UTSA Data Manipulation Methods • MS Access • To pull the data from different Databases • To link different tables to get desired data • To use different criteria in the queries • To get Pivot Table View of the required data • MS Excel • To generate statistical data using formulas • To get Pivot Table View of the required data • To deliver final results • SPSS • To generate statistical data specially for huge datasets • To get custom outputs of the required data • To handle data programmatically

  10. Let’s Work on a Data Request These are the Portions of a Data Request: • Ph.D. student enrollment for each of the 20 doctoral degree programs offered at UTSA for the last 5 years and then the breakdown of that total number by Gender, Ethnicity, Department and College. • Total number of Ph.D. students Applied and Accepted for the past 5 years and then the breakdown of that total numbers by Gender and Ethnicity. • Graduation Rate of Ph.D. students in each department for the past 5 years and then the breakdown of that total number by Gender and Ethnicity.

  11. Form Before • Data Request Form

  12. Form After

  13. Questions to Ask Yourself • What are the items being requested? • What sources of data can you use to get the information you need? • Do you have all the tables updated to be used for the request? • Are you familiar with all the data requested?

  14. What are the Items this Request Asking for? • Student Enrollment in Doctoral Level for 5 Years • Doctoral Degree Programs Offered at UTSA • Total Numbers by Departments and Colleges • Total Numbers by Gender and Ethnicity • Number of Ph.D. Students Applied, Accepted • Graduation Rates of Ph.D. Students

  15. What Sources of Data can You Use? • Need to have a Cumulative CBM001 table • Need to have a Validation/Crosswalk table of the Programs, Departments and Colleges • Need to have Cumulative Admission table • Need to have Cumulative Graduation table

  16. Are You Familiar with Rules of the Data Requested? • Enrollment • Correct Level of Students • Correct Term Codes • Exclude Flex (Katrina) Students • Programs • Correct College Structures • Admission • Correct Level of Students • Select students with Decision Made • Exclude “Denied” Students • Graduation • Correct Level of Students • First-Time Full-Time Students (for Undergraduate) • 4, 5, 6 yrs graduation rates • Exclude Deceased Students

  17. Procedures to Compile Data • Start with CBM001 for 5 Academic Years Enrollment in Ph.D. Level • Gender and Ethnicity data should come from CBM001 • Link CBM001 with Program/Department/College table for Program Codes, Names, Department and College • Use CBM00B or Admission Data Table to get number of students Applied and Accepted. • Use CBM009 or Graduation Data Table to obtain number of students graduated within last 5 Academic Years

  18. Write a Memo • Write the data sources used for the request • Write major steps needed for the request • Write reports that are easy to understand • Keep reports brief and concise • Save all Memos for future references.

  19. Tips To Handle Complex Requests • Learn Basic Higher Education Rules • Learn Your Institution’s Decisions • Keep Your Primary Data Sources Updated • Make Cumulative Data Tables • Keep Historical Data Saved • Maintain Data Request Database with Job Numbers • Write the Procedures for Future Reference • Try to Use Statistical Software • If you have Data Warehouse, you know how the data is being executed

  20. References • Strategies for the Practice of Institutional Research by Gerry Dizinno and Denise Gardner: 2007http://www.utsa.edu/ir/ofc/SAIR2007newcomersworkshopfinal.ppt • Survival Skills for Institutional Research by Ronnie Chrestman, Nancy James and Jessica Swink: 2003 http://www.clemson.edu/oir/Presentations/AIR2003SurvivalSkillsPaper.doc

  21. Questions?

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