Transcript Slide 1 - Flinders University

Academic Workloads
Flinders University, 21 September, 2010
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
Changing nature of academic work
•
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
Changing nature of academic work
•
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
“There is a long way to go with something that is conceptually so
simple”
Director, Workloads Management.
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
University wide implementation
•
•
•
•
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
2500
2000
Service/Lea
dership
Research/S
cholarship
Teaching
1500
1000
500
0
A C E G I
K
University wide implementation
•
•
•
•
•
•
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
Academ
ic%
Teachin
g
RHD
supervi
sion
Researc
h
Service
Professi
onal
Develop
ment
External
Engage
ment
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
NZ
F2F hour
lecture
2-3
2.3 – 3.23
1.25xn 4
RHD
supervision
per student
1.1 – 3.75
Course
coordination
9.4 xn
1.08 - 3
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 /
Allocation
Developme
nt
30
0
0
Service
Prog.
Coordinati
on
Allocationx
number
32
0.1
0
Manageme HOD
nt
Allocation
1035
0
0
Supervisio
n
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