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Similar to Learning to Count - JAM 2015 - Handouts
Similar to Learning to Count - JAM 2015 - Handouts (20)
Learning to Count - JAM 2015 - Handouts
- 2. Understanding reciprocity: The impact of Data integrity on potential reporting from Jenzabar EX. Managing data requests: Do your stakeholders know what data they need? Cultivating Buy‐in: How understanding Jenzabar EX can support increased centralized reporting and data‐driven decision‐making. Topic Outline
- 3. What are the Standard Operating Procedures (SOP) for recording data? How much data depth is recorded? What are the quality assurance processes in place? (i.e. auditing, exception reports) Are the above done conscientiously, consistently, and cross‐institutionally? Data Practices and Integrity
- 5. X No Unique Identifier X No SSN X No Birth Date X No Relationships X No Degree Attainment X No Marital Status X No Gender X No Ethnicity Less Data Integrity Fewer Reporting Options
- 6. X No Unique Identifier X No SSN X No Birthdate X No Relationships X No Degree Attainment X No Marital Status X No Gender X No Ethnicity Trouble distinguishing new records from existing ones… creates DUPLICATES! Development – Minimal and inconsistent data affects mapping alumni relations. External reporting obstacles: College Board NCES / IPEDS NSC NSLDS Compounding Issues
- 9. 2 Unique Identifiers SSN Birth Date 3 Relationships Degree Attainment Marital Status Gender Ethnicity Spouse’s Employer More Data Integrity More Reporting Options
- 10. Centralized data is more robust and yields more possibilities. It is live and responsive to data entry and activity. Warehoused data or snapshots can produced static reports Database (SQL) TablesPeripheral Sources Where should my IR data live?
- 12. ? Is this an one‐time request? ? Is the data something you want to be able to access routinely or remotely? ? Does anyone else need to access the information? ? Does the data need to fit into a third‐ party’s format? ? Are their visual components (i.e. charts, graphs, or summary tables)? ? Do you have supplemental data to add from a peripheral source(s)? To query or to report…
- 13. How do data requests come in? How is workflow managed? What types of questions are asked of the requestor? Are expectations communicated? Are the above done consistently and cross‐institutionally? Managing Data Requests
- 14. + Request is recorded + Request format can be homogenized / structured (i.e. a web ticket) + Supports migration of requests to project management application ‐ Lost nuances, conversation and lost time to flesh out the request + Request may be recorded via voice mail + Tone and conversational potential (but no body language) ‐ Does not support direct migration to project management application ‐ Less format then in the computer recorded request + Tone and conversational aspects are most complete, maximum opportunity to flesh out requests ‐ Minimal formatting (more organic) ‐ Basically no recording at time of interaction How do data requests come in?
- 16. Where is the balance?How effective are requests now? Yes it is but, is this: ? For credit and non‐credit… ? For Fall, Spring, Summer, or 12 month… ? For matriculated and non‐matriculated students… Do you want to: ? Include withdrawals… ? Include drops… ? Include online course, internships, independent studies… ? Measure as of the term census dates, peak enrollment periods, or at the end of add/drop… The email is not enough, we need…
- 18. Where is the balance?Cultivating Buy‐In Stakeholders start to understand that Jenzabar EX is essentially a “collection of living spreadsheets” (SQL tables). What they enter on their screen populates those tables that we report from… Queries allow IR to filter and access my data for me LIVE… This seems powerful….
- 19. Where is the balance?Transformative Period: Mezirow Disorienting Dilemma: “Jenzabar is beyond me, I’ll just stick with my files and Excel.” Challenging core beliefs: “This really isn’t so different from what I am doing…” Restructuring worldviews: “Reallocating my time away from maintaining satellite data and towards the IDB SAVES TIME!” Evolved perspective: “The live data is much more useable now that I know how it works.” New questions: What else can it do, what types of reports can we build? Mezirow, J. (1991). Transformative Dimensions of Adult Learning. San Francisco: Jossey‐Bass.