Cleveland State University Gitanjali Kaul, Vice Provost Jeffrey Chen, IR Director Sowmya Tirukkovaluru, IR Application Developer AIR Annual Forum June.

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Presentation transcript:

Cleveland State University Gitanjali Kaul, Vice Provost Jeffrey Chen, IR Director Sowmya Tirukkovaluru, IR Application Developer AIR Annual Forum June 2, 2010 (No. 468)

Introduction Internal reasons for studying workload – campus audit Questions raised by the audit: Does PeopleSoft accurately depict faculty workload for non-standard instructional activities, such as team- taught courses, internships, practicum, independent studies, dissertations, etc.? Are union contract policies for workload implemented consistently across campus? Is the union contract policy for banking workload hours applied consistently among the colleges? 2

Introduction External reasons for studying workload 2008 economic downturn Budget cuts Hiring freezes Increase in centralized decision-making by the Provost’s Office 3

Goals for the Project Identify current practices in faculty workload assignments across the disciplines Examine colleges’ existing spreadsheets Identify the discipline-specific variations in teaching and research workload assignments 4

Goals for the Project (continued) Create consensus among the colleges in adopting common conventions for workload tracking while documenting discipline-specific workload practices Create an on-going system involving Deans’ Offices in the review and update of workload data for a set teaching period Build transparency into workload assignment practices 5

Sample Timeline, IR provides Fall 09 data on faculty and courses Sept 09 May 09 Jan 10 Dec 09 Oct 09 Colleges enter remaining workload fields IR update with fall final values Colleges update Research and banking details IR provides final report 6

Faculty Workload Template Faculty Details and Course Details (A – M) Fields affecting the calculation of CCH and SCH (N – S) Teaching Load Weights (T – V) by: Credit Hours Head Count Contact Hours 7

Faculty Workload Template Instructional Credit Hour Total (X) Weight CCH X CCH + Weight HC X HC + Weight ContactHrs X CCH 8

9 Teaching Research Service

Faculty Workload Template Research and Service (Y – AD) Academic Year Total Workload : (AE) InstructionalResearchService Instructional + Research + Service Banking Hours : (AF – AI) Beginning Banked Credit Hours Banked Hours used this year Expected Workload Hours AY Carry Forward Banked Credit Hours 10

Examples of Exceptional Weights College of Science – DPT graduate lecture courses are 2.5 College of Education – PED lecture courses are 1.67 (by contact hours) College of Liberal Arts and Social Sciences (CLASS) – MUS lab courses are 4.0 (by contact hours) 11

Weights by Course Credit Hour College Busi- ness Urban Engineer- ing ScienceEducationCLASS Ind./Thesis Lecture Seminar Practicum Field Service Lab Clinical Studio

Weights by Head Count Component/College EducationCLASS Lecture0.5 – Practicum0.5 – 1- Lab-0.33 Studio-0.33 Tutorial

Common Data Challenges Addressed FTE calculation Course and faculty department designation Cross-listed courses Instructor of record Team-taught courses (%) Consistency of course components across terms Faculty type 14

15

Interviews with Deans’ Offices’ Staff Assigned to Tracking Faculty Workload Selected topics addressed during the interview: Mechanisms used to calculate & track banked hours Differences in workload determination among disciplines Faculty rotation in General Education/lower division courses Cancellation policy for courses with low enrollment Back-up plans for faculty when a course is cancelled Uniformity in assigning lab credit Balance in faculty assignments among teaching, research & service Written policies for course buyouts for external research Chairs and Deans’ Offices sharing of responsibility 16

Results Central tracking and maintenance of faculty workloads Colleges learn from each other’s best practices Provost’s Office receives more reliable data Greater transparency in workload assignments Consistent implementation of union contract policy 17

Challenges Colleges may fear losing autonomy Concern that the Provost’s Office will use incomplete information Additional work created for Associate Deans Resistance to change 18

Factors Supporting Success Some colleges support reliable and valid workload assessment, as they benefit from accurate comparisons Other colleges have poorly functioning tracking systems and seek an opportunity to improve them Some Deans and Associate Deans are new to their roles and have much to gain from participating 19

Questions & Comments ? Thank You! 20