Academic Workloads

Flinders University, 21 September, 2010

Academic Workloads

Changing nature of academic work

• Academic staff – Train future professionals– Conduct scholarly and applied research– Build international linkages– Collaborate with business– Generate export revenue– Create new knowledge based export products– Mentor individuals– Contribute to the create life of the broader community– Run large complex organisations– Train their own future workforce


• Hamish Coates and Leo Goedegebuure in “The real academic revolution” argue that the role consists of 5 main domains– Scholarship of discovery– Scholarship of teaching– Scholarship of Integration– Scholarship of application – Leadership and management


• Coates and Goedegebuure suggest that– Academic work should be reconceptualised– Career profiles should be more flexible – Institutions should find ways of ensuring academics get a broad range of

experience across a career– Improve measures of performance– Improve RHd training to facilitate an academic career– Universities engage more in capacity building

Issues from a professional HR perspective

Academic reward structure– Modelled on the concept of a generalist academic career– Usually contains clearly measurable standards for research – Measures for teaching excellence are more contestable– Service /Leadership standards tend to be weaker

Academic Workloads models– Hard wired measure is teaching contact hours (input)– Research “undirected” hard to measure in hours

What’s driving workload models?

• UK– Long a feature of pre 1992 institutions– Linkage with Transparent Approach to Costing

• Australia– Driven by perceptions of academic overwork– Multiple surveys of workloads of academic profession– Industrial response as a means of imposing a staff centred solution.

• US– Seen as good practice– General agreement on appropriate face to face teaching obligations

• New Zealand– Practice varies– More recent industrial issue

What’s driving the push for workload models in Australia

• Surveys of academic staff satisfaction ( 1990 – 1999)– Progressive decline in job satisfaction– Concerns about workloads– Progressive increase in the number of hours worked

• Occupational Stress in Australian Universities 2002 (Winefield et al)– Highly stressed profession– Mitigation strategies

• Fair procedures• Job security • Trust in management

• Changes in academic work, 2002 ( Anderson et al)– Pressure to perform– Lack of control over task and breadth of task– Workloads– Satisfaction less in less well funded institutions

The industrial response

• Addition of workloads management clauses in EBAs• EBAs negotiated at local level, so clauses reflect some local issues• Unlike other industrialised occupations, academic staff had no regulated set

hours of work (national maximum 38 hrs per week).• Study of progressive changes in workloads management clauses in 5

universities• Progressively more complex and more prescriptive between 1997 - 2011

What the workload clauses have in common

• Definition of what constitutes academic work– Teaching, research and service– Definitions have progressively become more detailed

• Framework approach• Workload models determined at departmental/school level• References to OHS, work life balance• Grievance or review process

Australian collective agreements

• Become progressively more prescriptive• By 2011 mandate

– Nomination of upper limit of hours ( 1800, 1725 hours per annum, or average 36 or 37.5 hours per week)

– Specific limits on teaching time, or time splits between teaching research and administration specified (40:40:20)

– Models to take into account both task, and size of task, e.g. class sizes, modes of delivery, overseas delivery etc.

– Locally determined models to be transparent, written, agreed by staff member, published to all

– More prescriptive maxima clauses, e.g. no teaching after 9.00pm• Grievances handled through standard grievance process

2009 – 2011 Linkage between WAM and performance expectations

• Workload associated with contribution to work group’s performance plan

• Performance reviews and promotion take into account annual work plan

• Allocation based on outputs, rather than inputs• Increasingly specific requirements for attendance• Work must be undertaken in line with University strategy

The US

• Workload management is a significant issue• Acceptance of a standard load of 12 hours undergraduate teaching

or 9 post graduate• Some have provision for overtime ( teaching greater than load)• Most university policies seek to balance work between teaching,

research and service by a formula based on hours or %• Some university policies recognise link between work allocation,

performance evaluation and reward• Many States have prescribed minimum contact hours for academic

staff.

UK: MAW report recommends

• Having a university policy which is highly flexible• Most issues determined at the local level

– Measures• Hours ( inputs) or Units ( outputs)• Specified maxima, or median times

– What work is included and to what level of detail– How are under and over workloads to be managed– Time frames for review– Linkage with wider faculty /university processes

• Consultation over all aspects, including meaning of transparency• Implementation on a university wide basis over an extended time frame

New Zealand

• Problem solving academic workloads management; a university response (Paewei, Mayer, Houston) ( Massey University)

• Implementation of workloads models as solution to an industrial dispute after major staff reductions

• Broad framework – Departmental development of models, review of 6 models• Lessons learnt

– Breadth and complexity of academic work– Workload models only one way to solve the workload issue– Academic units absorbed extra work, rather than looking at alternate strategies

for management– Importance of developing a template and defining at University level what an

acceptable workload is– Linear solutions are not always effective in a complex organisation– Where worked well units had been collegial and interactive, paid attention to

transparency, recognised the impact of the local environment

Have academic workload models achieve the desired aim?

• Attractiveness of the Australian academic profession ( Coates et al)– Progressive increase in average hours worked – 1999 (49.3 pw) – 2007 ( 50.6 pw)

• Impacts of different types of WAMs on academic job satisfaction and working life ( Vardi)– Three different WAMs in one institution

• Contact hours• Actual hours worked• Points model

– WAMs deal with work allocation not workload management– Better acceptance of all models by Heads than departmental staff– Most accepted was “contact hours” model.– More complex models not seen as attractive and resulted in more petty

disputes

Issues with workload models

• WLM not a resource allocation model• WLM models are inherently conservative, assume an accretion rather than a

reorganisation of work• Impact of new media and forms of communication on traditional workload• Difficulty of achieving internal consistency in application• Some models only measure teaching inputs and assume research is done in

residual time• Difficulty of measuring research allocation• Implicit links with promotion opportunities• What are the appropriate equivalances eg face to face teaching and

supervision• WAMs permit comparisons giving rise to claims that WAM is flawed• Disputes around the model

Comments

• Workload models are a part of university life• All systems will have problems as they cater for individuals and high levels

of complexity• Consultation on implementation important• Importance of flexibility to take account of individual circumstances• In universities, management processes are effective if perceived as

“meaningful” and “fair” by those involved• Increasingly workload management processes are linked to other university

processes which are also “meaningful” to staff• Universities will commence adapting workload models to budgets,

performance management and promotion

Different approaches to workload model implementation

Director, Workloads Management.

“There is a long way to go with something that is conceptually so simple”

Approaches to implementation

• Different approaches to model development– Hours– % of time– Weighted hours or points – No or limited measures ( allocation of tasks)

• Whole of University approach– Single system for whole University– Local flexibilities built in, but standard weighting factors– Often developed when maxima are prescribed in agreements.

• Framework approach– University develops generic standards, and Faculties/Schools implement

as they think fit.

University wide implementation

• Collective agreement– Distinguished between

• Allocated work ( teaching, work associated with teaching, administration of research)

• Unallocated work ( research, scholarship, professional development– Maximum hours ( 1645 pa. Annual hours excluding holidays) – Required workloads to be equalised– 40% ( teaching), 40% ( research), 20% ( service ) split as a guide– Required Faculty based workload development


• Created a steering group ( including Union members)• With external consultant assistance, developed a workload model• Tested the model by requiring all staff to complete the model using actual

hours worked• Test revealed large differences in workload, with Assoc Profs and Profs

carrying the highest workload

University wide model

• Result of actual hours survey

A BCDE FGH I J K L0

500

1000

1500

2000

2500

Service/LeadershipResearch/ScholarshipTeaching


• Activity bands developed– Teaching 20% – 70%– Research 10 % - 60%– Service and Professional activity 20%

• Weightings for teaching and associated duties built into system• No weightings or means of accounting for research ( to be developed)• All staff guaranteed 20% service, professional activity allocation• Seen as an annual allocation process, monitoring done through performance

development process• System being trialled in one faculty and a variety of schools

Faculty/School models - Basic

• Establishment of an expected staff work profile– Courses taught– Thesis supervision and marking– Research ( submission of articles, grant applications)– Administration

• Work allocated by reference of what is required to be done, staff member’s career and professional circumstances

• Works well if– Course offerings are static– Staff well established– Staff numbers and course offerings are small and located on one campus

• Problems– Size of staff– Multi campus institutions– Different modes of delivery

Faculty/Model - Hours

• Establish an annual contact hours requirement for teaching, research and administration to total the annual required hours

• Each activity is given a time allocation, eg. lecture 2 hours, marking papers 36min

• In some cases hourly allocation x no of students• Workload is calculated by taking components and building up the annual

required contact hours• In some cases workloads are lowered for early career academics• Most models prioritise meeting the teaching and service hours, with the

balance of the allocation for research

Faculty model - Hours

• Advantages– Simple– Easy to manage and monitor– Staff are clear about the general duties

• Disadvantages– Does not nuance for large classes, different forms of delivery– Research time allocation is based on inputs ( i.e. hours) rather than

productivity

Faculty model - Points

• Annual hours established for teaching, research, service converted to total points required

• Base hourly time allocation established for teaching and service, eg for face to face lecture

• Hourly rates multiplied by factors reflecting level of complexity, size of class, nature of delivery etc to generate a points score

• Points allocated for service, professional development etc. • Research points developed based on

– Previous outputs as measured – Projected activity

Faculty model - Points

• Disadvantages– Very complex– Involves consideration of past performance– Time consuming

• Advantages– More nuanced, takes account of class size, marking etc– Teaching allocations may be perceived as being more fair– Does measure research and research time

Faculty model – Percentages

• Percentages of time to be allocated to each class of work adopted, eg 40/40/20

• Some models identify fixed percentages of time to be allocated to a particular activity

• Sliding scale of acceptable percentage of time allocation to each major area of work developed, sometimes by level

• Time allocated by Head of School after consideration of– Tasks to be done– Strengths/ interests of the staff member– Expectations of the level of appointment

Faculty model - Percentages

T and R Academic%

Teaching

RHD supervision

Research

Service Professional Development

External Engagement

Total

Asst Lecturer

30% – 50%

nil 30% - 60%

nil 10% – 15%

nil 100%

Lecturer 30% – 60%

0% -5% 30% - 60%

0% - 5%

0% - 10%

0 – 5% 100%

Snr Lecturer

30% - 60%

5% - 10%

30% - 60%

5% - 10%

5% 0% - 5%

100%

Assoc Prof

20% - 60%

10% - 15%

40% - 60%

5% - 20%

5% 0% - 10%

100%

Prof. 10% - 50%

10% - 15%

40% - 60%

10% – 20%

5% 0%- 10%

100%

Faculty model - Percentages

• Advantages– More flexible– Able to be tailored to specific career levels and individual aspirations– Does not involve complex calculations

• Disadvantages– Could be perceived as unfair as allocations are more fluid– Harder to demonstrate “equity”

Implementation issues

Issues

• Lack of consistency in data collection and approach• Core data re courses and programs may be poor• Effort in maintaining data• Ambiguity gives rise to potential

– Perceptions of managerial manipulation– Flexibility in work allocation

People issues

• Equity– Most aim for parity not equity

• Transparency– Practices differ as to who can see what

• Different attitudes to work and career stages• Leadership capacity/experience of Head of School• Workload models surface existing problems• Gaming?

Metrics and weightings - teaching

• Hours allocation varies markedly• Comparisons difficult across countries• Sample comparison hours per week

Activity Australia UK NZF2F hour lecture

2 - 3 2.3 – 3.23 1.25xn -4

RHD supervision per student

1.1 – 3.75 1.08 - 3

Course coordination

9.4 xn 0.2 – 1.17 1.7 – 3.5

Teaching metrics

Domain Activity Weighting Allocation Enrolment Hours multiplier

Service New staff Allocation 60 0 0

Service Training / Development

Allocation 30 0 0

Service Prog. Coordination

Allocationx number

32 0.1 0

Management

HOD Allocation 1035 0 0

Supervision

PhD No hours 0 75 0

Teaching Workshop No hours 0 0 1.5

Teaching Lecture No hours 0 0 3

Metrics and weightings - research

• Research counted in some Australian and New Zealand systems• Allocations determined by

– Prior measured research performance over a nominated period of years, and

– Supervision of RHD students, and– Projected research plan for forthcoming year including projected outputs

Links to performance

• Workload allocation models have implicit or explicit links to – Performance appraisal– Promotion

• Normal approach is work allocation is managed through the WAM, and performance issues through appraisal.

• RMIT ( and others) has integrated work plans based on workload allocation, performance appraisal and incremental advancement

Decisions re implementation

• University wide approach, local approach or hybrid• USQ has a hybrid approach, with a University wide data base which allows

for local differences in weightings• Access - who can see individual workload allocations • Equity or parity ?• Controls ( double dipping)• Use for broader purposes, eg resource allocation, resource requests

Future trends

• Complexity of WAMs finely nuanced to equity will mean that they become less relevant

• WAM will become the basis for assessment for performance appraisal• WAMs will become more finely nuanced to individual careers and career

aspirations• WAMS may become part of the university’s employee value proposition• May be an industrial ‘backlash’ against WAMs

Documents

Academic Workloads