Defining and Measuring Faculty Workload Across Disciplines at a Comprehensive Four–

Year Institution

Cleveland State University

Gitanjali Kaul, Vice ProvostJeffrey Chen, IR Director

Sowmya Tirukkovaluru, IR Application Developer

AIR Annual ForumJune 2, 2010 (No. 468)

IntroductionInternal 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?

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IntroductionExternal reasons for studying workload

2008 economic downturnBudget cutsHiring freezesIncrease in centralized decision-making by

the Provost’s Office

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Goals for the ProjectIdentify current practices in faculty workload

assignments across the disciplinesExamine colleges’ existing spreadsheetsIdentify the discipline-specific variations in

teaching and research workload assignments

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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

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Sample Timeline, 2009 - 10

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

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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

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Faculty Workload Template Instructional Credit Hour Total (X)

WeightCCH X CCH +

WeightHC X HC +

WeightContactHrs X CCH

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Teaching

Research

Service

Faculty Workload Template Research and Service (Y – AD)

Academic Year Total Workload : (AE) 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

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Examples of Exceptional WeightsCollege of Science – DPT graduate lecture

courses are 2.5College 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)

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Weights by Course Credit HourCollege

Busi-ness Urban

Engineer-ing Science Education CLASS

Ind./Thesis

0 0 0 0 0 0

Lecture 1 1 1 1-2.5 1-1.67 1

Seminar 1 1 1 1-2 1 1

Practicum 1 0 - 0-1 0-1.33 0

Field Service 0 0 - 1 1 0-2

Lab - - 1 1-2 0-1 0-4

Clinical - - - 0-1 1.33 -

Studio - - - - 1-1.33 112

Weights by Head CountComponent/College Education CLASS

Lecture 0.5 – 1 0.1 - 0.2

Practicum 0.5 – 1 -

Lab - 0.33

Studio - 0.33

Tutorial - 0.2

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Common Data Challenges Addressed

FTE calculationCourse and faculty department

designationCross-listed coursesInstructor of recordTeam-taught courses (%)Consistency of course components across

termsFaculty type 14

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Interviews with Deans’ Offices’ Staff Assigned to Tracking Faculty WorkloadSelected 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

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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

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ChallengesColleges may fear losing autonomyConcern that the Provost’s Office will use

incomplete informationAdditional work created for Associate DeansResistance to change

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Factors Supporting SuccessSome 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

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Questions & Comments

?

Thank You!

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