1. Creating a Faculty Activity Database: Three Practical Solutions Chris Fastnow (cfastnow@montana.edu) James B. Rimpau (rimpau@montana.edu) Montana State University Chris Fastnow (cfastnow@montana.edu) James B. Rimpau (rimpau@montana.edu) Montana State University

2. Abstract Faculty activity data can be used for external benchmarking (e.g. the Delaware Study of Faculty Activity), promotional materials, reports to oversight bodies, and other increasingly important functions. However, collecting and reporting that information is difficult. We will discuss three methods to collect and report faculty activity data: an Excel- based survey, an Access database with a web interface, and a hierarchical database with a web or desktop interface, developed in-house. Each has benefits and drawbacks for the faculty respondent as well as the IR office, but all provide solutions to a difficult task.

3. Why Develop a Faculty Activity Database  Accountability  Decision support  Benchmarking  Annual reviews  Centralized response capacity  Expertise list  Marketing  Accountability  Decision support  Benchmarking  Annual reviews  Centralized response capacity  Expertise list  Marketing

4. Why Develop a Faculty Activity Database  Benefits of centralized collection  Common definitions  Credible data  Single intrusion  Drawbacks  Faculty resistance  Getting the right tool  Benefits of centralized collection  Common definitions  Credible data  Single intrusion  Drawbacks  Faculty resistance  Getting the right tool

5. Why Develop a Faculty Activity Database Convincing Faculty  Decrease burden on Faculty  Easy annual review reporting  Avoids duplication of effort  Decrease burden on department heads  Single format for annual reviews  Single request for information  Eases reporting requirements to central administration Convincing Faculty  Decrease burden on Faculty  Easy annual review reporting  Avoids duplication of effort  Decrease burden on department heads  Single format for annual reviews  Single request for information  Eases reporting requirements to central administration

6. Wish List Data Collection Tool  Web based  Flexible design/modification  Dummy-proof data entry  Secure login  Detailed data  Rollover of some data from year to year Data Collection Tool  Web based  Flexible design/modification  Dummy-proof data entry  Secure login  Detailed data  Rollover of some data from year to year

7. Wish List Analysis/Reporting Tool  Web based  Secure login with differential access to data  Dynamic querying  Keyword searching  Canned reports – individual annual review report, discipline Delaware Survey report Analysis/Reporting Tool  Web based  Secure login with differential access to data  Dynamic querying  Keyword searching  Canned reports – individual annual review report, discipline Delaware Survey report

8. Three Tools 1.University of Delaware’s FIPSE-funded Faculty Out-of-Classroom Activity Study Excel-based questionnaire 2.Access database with web interface 3.NeuroSys hierarchical database with web interface 1.University of Delaware’s FIPSE-funded Faculty Out-of-Classroom Activity Study Excel-based questionnaire 2.Access database with web interface 3.NeuroSys hierarchical database with web interface

9. 1. Excel Questionnaire U Del IR Office sends file to us We edit file, send to Deans (annual review cycle) Deans send to department heads Department heads send to faculty Faculty respond, return to department heads Department heads tally responses, send to us (and Deans) We create reports

10. 1. Excel Questionnaire Benefits  Easy for end users  Standardized  Flexible across units  Conforms to U Del’s protocol  Simple to tally across the university Benefits  Easy for end users  Standardized  Flexible across units  Conforms to U Del’s protocol  Simple to tally across the university

11. 1. Excel Questionnaire Drawbacks  Too many steps  Extra work for department head  Uneven interpretation  Loss of specific information Drawbacks  Too many steps  Extra work for department head  Uneven interpretation  Loss of specific information

12. 2. Access Database Benefits  Fairly easy web interface  Definitions readily available → more consistent data  More detail  Query capacity Benefits  Fairly easy web interface  Definitions readily available → more consistent data  More detail  Query capacity

13. 2. Access Database Drawbacks  User error  Difficult to modify for subgroups  Scalability over time and users  Separate databases (security)  Querying limited to Access users Drawbacks  User error  Difficult to modify for subgroups  Scalability over time and users  Separate databases (security)  Querying limited to Access users

14. 3. NeuroSys Benefits  Web interface  Flexible, customizable  Secure  “Ground floor opportunity” Benefits  Web interface  Flexible, customizable  Secure  “Ground floor opportunity”

15. 3. NeuroSys Drawbacks  Still developing  User error  Labor intensive  Lacks on-the-fly reporting Drawbacks  Still developing  User error  Labor intensive  Lacks on-the-fly reporting

16. Wish List: Collection ExcelAccessNeuroSys Web based entry √√ Flexible √√ Dummy-proof Secure login √√√ Detailed data √√ Rollover data √

17. Wish List: Reporting ExcelAccessNeuroSys Web-based reporting Secure/differential access √√√ Dynamic querying √ Keyword searching √√ Canned reports √√

18. Options  Convert Access database to MySQL  More flexible  More scalable  Develop NeuroSys further  Potential for positive influence  Look elsewhere  RFP with specific criteria  Convert Access database to MySQL  More flexible  More scalable  Develop NeuroSys further  Potential for positive influence  Look elsewhere  RFP with specific criteria

19. Challenges Across Methods  Developing useful questionnaires  Creating a culture where faculty update data regularly  Distribution of responsibility for hosting, funding – colleges, ITC, central administration  Benchmark data  Developing useful questionnaires  Creating a culture where faculty update data regularly  Distribution of responsibility for hosting, funding – colleges, ITC, central administration  Benchmark data

20. Want to see more?  University of Delaware’s Institutional Research and Planning www.udel.edu/IR/fipse/index.html  Access-Based Demo Site http://www2.montana.edu/ehhd/demo ID = msudelaware Password = workload  NeuroSys Demo Site http://neurosys.cns.montana.edu ID = guest Password = guest  University of Delaware’s Institutional Research and Planning www.udel.edu/IR/fipse/index.html  Access-Based Demo Site http://www2.montana.edu/ehhd/demo ID = msudelaware Password = workload  NeuroSys Demo Site http://neurosys.cns.montana.edu ID = guest Password = guest