GOOD GOVERNANCE FOR SUSTAINABLE QUALITY UNIVERSITY EDUCATION IN TANZANIA CHALLENGES IN WORKLOAD MODELS AND HUMAN RESOURCE MANAGEMENT IN UNIVERSITIES Joseph A. Kuzilwa – Mzumbe University Nicholas Bangu – Tumaini University – Iringa University College Naura Springs September 13 th 2012

PRESENTATION 1. INTRODUCTION: Key challenges to workload management 2. BIRDS EYE VIEW: Higher Education Space in Tanzania and implications on workload management 3. EXPERIENCES of Cases of Workload Frameworks 4. IMPLICATIONS of TCU Guidelines and Tools on HR (Our Interpretation) 5. HARMONIZATION of the Workload Framework and Performance Agreements 6. CONCLUSION

1. Introduction KEY ISSUES / CHALLENGES KEY QUESTION: How to appropriately and sustainably manage the academic wing of human resources and attain excellence in the core result areas of the university (Teaching, Research and Public Service) under prevailing circumstances

1. Introduction Cont.: Issues Posing a Challenge to Workload Management

2. Some of key features of HE Space in Tanzania 2004/52011/ /15 Secondary School Enrolment 433,0001,790,000 University Enrolment 38,000140,000 No of Universities 2450 HE Gross Enrolment Rate 3%4% HEDP Projected HE GER 10%

RESEARCH  SSA's contribution to the world's expenditure on Research and Development (R&D) is no more than 0.6%, a significant proportion of which is contributed by just one country – South Africa.  SSA also has the lowest number of researchers per million of population: 79, compared with 442 for Latin America and the Caribbean and 526 for India.  SSA produces just 1.1% of the world's publications and 0.1% of global patents. Implications for Tanzania universities and workload allocation??? Some Indicators of Research Space in Africa

3. Selected Workload Frameworks Cases in Europe: Spain and Britain – A, B,C,D 3 Cases in Tanzania : E, F, G All Provide for activities for Teaching, Research ++ Two Dominant philosophies: Fixed and Varying Teaching weights across ranks Partial and Integrated Approaches in assessment of workload

Observations in the Workload Models European CasesTanzanian cases Attribute ABCDEFGTCU 1. Workload Approach Integrated PartialIntegrated Partial N/A 2. Weight to teaching Constant Varying Varying– 3. Weight to Research Constant Varying 4. Preparation per hour of teaching 0.5 hours3 hours1 hourNA2 hours 5 hours3 hours 0.5 hours 5. Academic year N/A 26 wks30 wks34 wks32 wks 34 wks

TAs / Assistant Lecturers Lecturers / Senior Lecturers Associate Professor / Professor Teaching weight Constant teaching Allocation Model Varying teaching allocation Model Figure 1: Constant and Varying Teaching Load allocation

4. TCU Guidelines and Tools for Human Resource Management 1.Workload Model: Integrated model: On average Teaching: 12.5% to 25% (Low for Senior Ranks) Related Tasks:10% to 13% Research:35% to 45% (High for Senior Ranks) 2. Use of OPRAS for ALL Universities

5. Harmonization of the Workload Framework with Performance Management Implication of TCU Guidelines: harmonization of Workload Frameworks and OPRAS Importance of this linkage: Trace workload to the Strategic Objectives and Targets of University’s SP through Performance Agreements (jointly agreed between a faculty member and HoD): CASCADING PROCESS Requires that an annual (not just semesters) picture and integrated approach is taken in workload allocations

Strategic Objectives / Targets Teaching, Researc Public Service Strategic Objectives / Targets Teaching, Researc Public Service

7. Conclusion

7. Conclusions Cont.

Thank you for your kind attention