Towards Estimating Academic Workloads for UKZN Glen Barnes (MSc Agric, MGSSA) Director, Management Information, UKZN May 2006
Objectives n n 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 n The incorporation of these ideas into a computerized decision support framework currently known as the School Planning Decision Support System (SPDSS). n
Procedure Initial pilot study n Special Senate Task Team n – Identify the important variables – Determine a set of default values n Roll out to Schools – Establish ‘buy-in’ of the Schools – Foster ownership of the data n Integration with other tools
Academic Endeavours n n Teaching Research Community Development & Outreach Administration
Inputs & Assumptions n n n High-level Assumptions Module Enrolment Data Detailed Module Assumptions Staff Assumptions Research Data Graduate Data
Institutional targets Working year : 219 days n Working day : 8 hours n Proportional allocation n – Teaching : 45% – Research : 40% – Admin/Outreach : 15% Research productivity : 60 PUs/yr n Minimum SAPSE proportion : 50% n
Inputs & Assumptions n n n High-level Assumptions Module Enrolment Data Detailed Module Assumptions Staff Assumptions Research Data Graduate Data
Inputs & Assumptions n n n High-level Assumptions Module Enrolment Data Detailed Module Assumptions Staff Assumptions Research Data Graduate Data
Inputs & Assumptions n n n High-level Assumptions Module Enrolment Data Detailed Module Assumptions Staff Assumptions Research Data Graduate Data
Default Values & Norms Quantified by the Senate Task Team n Initial deployment of the system n Form the basis of comparison n – Determine differences between Schools – Evaluate inputs from the Schools
Reporting Objectives Highlight data errors n Summarize the data into ratios and performance indicators n Generate a number of scenarios for planning n
Outputs & Reports Time & Staff estimates n School Summary Analysis n – Summary Tables – Four Scenarios – Scenario summary
Time & Staff estimates Module Contact Preparation Assessment Consulting Group Teach Total Acad Level Count Enrol hrs hrs hrs (%) hrs Staff 2 10 1806 662 (10%) 527 (8%) 5075 90 (1%) 0 100 6354 8. 1 4 16 871 576 (12%) 763 (16%) 2645 881 (18%) 0 100 4865 6. 2 3 8 1044 655 (14%) 640 (13%) 3367 104 (2%) 0 100 4766 6. 1 1 6 425 167 (17%) 182 (19%) 608 21 (2%) 0 100 978 1. 3 8 9 50 0 874 (100%) 0 100 874 1. 1 9 4 19 0 0 0 648 (100%) 0 100 648 0. 83 27 53 4215 2060 (11%) 2111 (11%) 11694 (63%) 2619 (14%) 0 (0%) 100 18485 23
Outputs & Reports Time & Staff estimates n School Summary Analysis n – Summary Tables – Four Scenarios – Scenario summary
Summary Tables 20 05 20 06 20 07 20 08 Student FTEs & Head Counts No of Modules 55 55 Enrolled FTEs 282 291 299 Weighted FTEs 300 308 317 Enrolled Head Count 314 323 333 FTE to HC 89. (%) 9 FTEs per 89. 9 89. 8
Summary Tables. . . 2005 2006 2007 2008 1658 1686 1693 16% 16% 2065 20% 20% 5833 5977 6122 58% 58% 59% 535 539 542 5% 5% 0 0 0% 0% 10092 10266 10422 Teaching Allocation (hrs) Contact (2004: 2500) Preparation Assessment (2004: 9862) Consulting (2004: 1218) Group teaching TOTAL (2004: 13580)
Summary Tables … 2005 2006 2007 2008 Planned Academic 16 16 Planned Support 4 4 Academic to Support Staff Ratio 4 4 Modules per Academic 3 3 Credits per Academic 102 102 Teaching hrs per week 12 12 12 13 Staff number estimates (FTEs)
Outputs & Reports Time & Staff estimates n School Summary Analysis n – Summary Tables – Four Scenarios – Scenario summary
Scenario One – the current situation 2005 2006 Teaching and Research Teaching rate (%) 36 Research rate (%) 23. 5 Admin/Outreach rate (%) 40. 5 TOTAL (%) 100 Adjusted Staff (FTEs) 16 Research output (PUs) 564. 6 All Academic Staff Adjusted Staff (FTEs) 16 Students per Academic (FTEs) 17. 6 NSH per Academic (hrs) 1020 Research output (PUs) 565 Productivity per Academic (PUs) 35 Margin over Compensation (1000 s) 1952 2007 2008
Scenario Two – revised Admin/Outreach Constant Increase 2005 Decrease 2006 Teaching and Research Teaching rate (%) 36 Research rate (%) 23. 5 Admin/Outreach rate (%) 15 TOTAL (%) 74. 5 Adjusted Staff (FTEs) 11. 9 Research output (PUs) 564. 6 Adjusted Staff (FTEs) 11. 9 Students per Academic (FTEs) 23. 7 NSH per Academic (hrs) 1369 Research output (PUs) 565 Productivity per Academic (PUs) 47 All Academic Staff Margin over Compensation (1000 s) 2995 2007 2008
Scenario Three – revised Admin/Outreach & Research Constant Increase 2005 Decrease 2006 Teaching and Research Teaching rate (%) 36 Research rate (%) 49 Admin/Outreach rate (%) 15 TOTAL (%) 100 Adjusted Staff (FTEs) 16 Research output (PUs) 1176 All Academic Staff Adjusted Staff (FTEs) 16 Students per Academic (FTEs) 17. 6 NSH per Academic (hrs) 1020 Research output (PUs) 1176 Productivity per Academic (PUs) Margin over Compensation (1000 s) 73 2101 2007 2008
Scenario Four – institutional targets Constant Increase 2005 Decrease 2006 Teaching and Research Teaching rate (%) 45 Research rate (%) 40 Admin/Outreach rate (%) 15 TOTAL (%) 100 Adjusted Staff (FTEs) 12. 8 Research output (PUs) 768 All Academic Staff Adjusted Staff (FTEs) Students per Academic (FTEs) 12. 8 22 NSH per Academic (hrs) 1275 Research output (PUs) 768 Productivity per Academic (PUs) 60 Margin over Compensation (1000 s) 2771 2007 2008
Outputs & Reports Time & Staff estimates n School Summary Analysis n – Summary Tables – Four Scenarios – Scenario summary
Scenario Summary 2005 2006 Academic Staff (FTEs) Scenario 1 16 Scenario 2 11. 9 Scenario 3 17. 6 Scenario 4 12. 8 Scenario 1 565 Scenario 2 565 Scenario 3 1176 Scenario 4 768 Productivity (PUs) Margin over Compensation (1000 s) Scenario 1 1952 Scenario 2 2995 Scenario 3 2101 Scenario 4 2771 2007 2008
Data Integration n Data inputs are from: – Mod. Man; Modules for Handbooks – MIDB; Enrolments, Graduates – IRMA; staff productivity n Scenario outputs become inputs into: – Affordability model – Academic viability model – School Business Plan
Conclusions n n 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
Thank you …
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