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Towards Estimating Academic Workloads for UKZN. Glen Barnes (MSc Agric, MGSSA) Director, Management Information, UKZN May 2006. Objectives.
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Towards Estimating Academic Workloads for UKZN Glen Barnes (MSc Agric, MGSSA) Director, Management Information, UKZN May 2006
Objectives • To estimate academic staff workload demand based on the commitment to teaching and supervision, research, community involvement or outreach, and administration. • To enable a more objective method of estimating the staff teaching load using quantitative data through the medium of module notional study hours, and limitations placed on student delivery by class sizes and group study.
The Outcome … • The construction of a decision support system addressing the most important variables • The incorporation of these ideas into a computerized decision support framework currently known as the School Planning Decision Support System (SPDSS).
Procedure • Initial pilot study • Special Senate Task Team • Identify the important variables • Determine a set of default values • Roll out to Schools • Establish ‘buy-in’ of the Schools • Foster ownership of the data • Integration with other tools
Academic Endeavours • Teaching • Research • Community Development & Outreach • Administration
Inputs & Assumptions • High-level Assumptions • Module Enrolment Data • Detailed Module Assumptions • Staff Assumptions • Research Data • Graduate Data
Institutional targets • Working year : 219 days • Working day : 8 hours • Proportional allocation • Teaching : 45% • Research : 40% • Admin/Outreach : 15% • Research productivity : 60 PUs/yr • Minimum SAPSE proportion : 50%
Inputs & Assumptions • High-level Assumptions • Module Enrolment Data • Detailed Module Assumptions • Staff Assumptions • Research Data • Graduate Data
Inputs & Assumptions • High-level Assumptions • Module Enrolment Data • Detailed Module Assumptions • Staff Assumptions • Research Data • Graduate Data
Inputs & Assumptions • High-level Assumptions • Module Enrolment Data • Detailed Module Assumptions • Staff Assumptions • Research Data • Graduate Data
Default Values & Norms • Quantified by the Senate Task Team • Initial deployment of the system • Form the basis of comparison • Determine differences between Schools • Evaluate inputs from the Schools
Reporting Objectives • Highlight data errors • Summarize the data into ratios and performance indicators • Generate a number of scenarios for planning
Outputs & Reports • Time & Staff estimates • School Summary Analysis • Summary Tables • Four Scenarios • Scenario summary
Outputs & Reports • Time & Staff estimates • School Summary Analysis • Summary Tables • Four Scenarios • Scenario summary
Outputs & Reports • Time & Staff estimates • School Summary Analysis • Summary Tables • Four Scenarios • Scenario summary
Constant Increase Decrease Scenario Two – revised Admin/Outreach
Constant Increase Decrease Scenario Three – revised Admin/Outreach & Research
Constant Increase Decrease Scenario Four – institutional targets
Outputs & Reports • Time & Staff estimates • School Summary Analysis • Summary Tables • Four Scenarios • Scenario summary
Data Integration • Data inputs are from: • ModMan; Modules for Handbooks • MIDB; Enrolments, Graduates • IRMA; staff productivity • Scenario outputs become inputs into: • Affordability model • Academic viability model • School Business Plan
Conclusions • An attempt to address the very sensitive issue of staff workloads • Considered the limitations of previous investigations and propose enhancements • Through a collaborative approach assist the School planning process • Facilitate a system of monitoring into the future