Another cultural conflict

The main point of this post is to save this quote. I’m about to delete it from the thesis, can’t make it fit, and I think it is important.

(Zellweger 2005) the tasks assigned to each group bear a number of inherent conflicts. For example, the push of instructional designers for creative and flexible solutions matching a faculty member’s goals might impose a threat for well-rehearsed IT processes. The deviation of standard solutions implicates a certain risk that IT workers would rather avoid as they most of all feel responsible for the stability and security of the IT systems.

It connects with a sentence or two from an earlier post

Ayers (2004) observes that academic and information technology cultures, two of the main sub-cultures involved with e-learning within universities, do not mix together well. The differing viewpoints and subsequently the varying and competing priorities of the different sub-cultures within an organisation can lead to considerable internal tension (Luck, Jones et al. 2004).


Ayers, E. (2004). “The Academic Culture and the IT Culture: Their Effect on Teaching and Scholarship.” EDUCAUSE Review 39(6): 48-62.

Luck, J., D. Jones, et al. (2004). “Challenging Enterprises and Subcultures: Interrogating ‘Best Practice’ in Central Queensland University’s Course Management Systems.” Best practice in university learning and teaching: Learning from our Challenges. Theme issue of Studies in Learning, Evaluation, Innovation and Development 1(2): 19-31.

Zellweger, F. (2005). Strategic Management of Educational Technology: The Importance of Leadership and Management. 27th Annual EAIR Forum. Riga, Latvia.

Another BAM problem – awarding mark of 0

Following on from yesterday’s start of using the blog to record fixes to software, here comes another one.


Awarding a student a mark of 0 for a post, doesn’t work

Identify the cause

First, re-create the problem, log in and try and give the student a mark of 0 – yep doesn’t work.

Check the database, there is a mark of 0 recorded. However the textbox in which the mark should be displayed, is empty.

Let’s try changing it to a non-zero mark and then back again – I’m wondering if 0 is the default mark. Ahh, giving the student a mark of 5 and then changing it back to 0 results in the 0 appearing in the box. Seems to be some screwy code.

Looking further it seems that the following is happening

  • A post’s database entry starts with a mark of 0 and a status of Submitted.
  • When displaying this type of entry the 0.000 in the database is modified to the empty string by the view code.
    I’m assuming this is to stop the marker thinking that a mark of 0 has already been awarded.
  • The code processing the submitted form (i.e. I’ve entered a mark of 0 and hit submit) is comparing fields in form to data in database. If a mark of 0 is awarded in the form it will equal the default value in the database and hence not spark a change.


If the mark in the form is 0 and not empty, then a change must be made.

Innovation role as Trickster

Happened to watch this talk by Emily Levine at a 2002 TED conference a funny talk with some interesting insights and perspectives that I find potentially directly connected to my new role. What follows is some reflection on these.

It is interesting to see some of the negative responses to this talk that arise on the Ted talk site and on youtube.

You can’t deny another person’s reality, only build on it

Mention of this theatre sports rule is made near the beginning of the talk. Particularly important because too much of what I see in universities around learning and teaching and innovation ignores and de-values the reality held by other people.

I think is a particular symptom of the “what management does” approach to improving learning and teaching. Management sets themselves up as knowing better than the academics and mandates changes. In most cases not being aware of or respecting the view of reality held by those academics.

And certainly a feature of Model 1 behaviour and defensive routines.

Trickster makes this world

From about 13 minutes into the talk, it shifts to talk about the impact of the book Trickster makes this world by Lewis Hyde. Why? Well, I like the following quote from Hyde’s home page

Trickster Makes This World (1998) uses a group of ancient myths to argue for the kind of disruptive intelligence all cultures need if they are to remain lively, flexible, and open to change

The first chapter of the book is available here.

Back to Levine’s points:

  • Trickster is a change agent.
  • Qualities that make it possible for change to happen:
    • Boundary crossing – the value of talking about something you don’t know anything about, seeing things anew. This connects with the idea of pattern entrainment.
    • Non-oppositional strategies – forget contradiction and embrace paradox.
    • Smart luck – being prepared for the unprepared. The ability to hold ideas lightly to see contradictions and new ideas.
    • Making connections – break up associations.
    • Walking a fine line – finding a balance.
    • Doesn’t have a home.

Don’t have the time now to do more than list them. Must get Hyde’s book and revisit this. However, these qualities of trickster make for useful ideas about how to engage in and encourage innovation.

Diagnosing and recording a problem with BAM

Trying out a new approach to documentation of coding changes to BAM – i.e. writing it up in a post.

The problem

A large number of student blogs are being reported as “Not mirrored yet”. BAM is meant to report the amount of time since an individual student blog was last updated (i.e. a student made a post) and mirrored.

Diagnosing the problem

  • Is mirroring still working?
    Yes, student blogs are being mirrored as they updated. The copies of each student’s RSS feed is being kept up to date.
  • Are the new posts being “allocated” properly?
    Yes, the student I’m checking has a RSS file with a file system time stamp of “May 14 20:43”. This indicates when the file was mirrored from the student’s blog.

    The BAM_BLOG_MARKING table has a DATE_PUB time stamp for the most recent post for this student of “2009-05-14 10:43:11”. This indicates that the allocation is working, when BAM mirrors a RSS file, it goes through each student post, any new ones it attempts to allocate.

    It appears that it is using the CQU system current time to allocate DATE_PUB

    Small problem: Strictly speaking it should be using the date published value for the post as stored in the RSS.

    Actually, this isn’t what’s happening, the student had actually made a post at that time.

  • Is the “LAST_POST” field being updated?
    No, it’s set to the 0 value. This is where the problem is starting. When the display code sees this 0 value, it assumes that the blog hasn’t been mirrored yet.

Something in the allocation process is updating the LAST_POST field in BAM_BLOG_STATISTICS incorrectly. Rather than put in the timestamp for the most recent post, it’s setting it to 0.

Locating the problem

The mirror/allocation process is

  • BAM/support/ creates BAM::Mirror object and calls DoMirror
  • BAM::Mirror::DoMirror
    For each course currently being mirrored , create BAM::BlogStatistics object and call DoMIrror
  • BAM::BlogStatistics::DoMirror
    For each student in the course
    mirrorFeed (get the latest copy of the RSS file for the blog) and then parseFeed.
  • BAM::BlogStatistics::parseFeed
    • use XML::Feed to parse the local copy of the RSS file
    • use XML::Feed to get the lastModified timestamp for the blog
    • if there are more posts in the new file than the last one then
      • BAM::BlogElements->new for the student
      • updateMarking
  • if mirrorFeed returns true then update NUM_ENTRIES and LAST_POST in BAM_BLOG_STATISTICS

It appears that the likely problem is

  • the value for LAST_POST is being set incorrectly in parseFeed, or
  • the update of LAST_POST is setting it to the wrong value.

My guess is that parseFeed is the source of the problem – though I wonder why it’s happened all of a sudden.

Checking parseFeed

Will have to write a stand alone script using XML::Feed and an existing RSS file. Can’t use the above as the mirror thing depends on a new post.

Well, it looks like the “modified” method for XML::Feed is not working. Why?

Okay, tried the same script on an “old” XML file. It seems that WordPress – possibly for an external reason – has changed the format of the RSS that it generates. This has broken the method used to get the time the blog was last updated.

The change, in the XML, appears to have been a change from the tag “pubDate” to “modified”.


The current Perl/Webfuse-based instantiation of BAM is not likely to last long. Combine this with other contextual factors and the solution will have to be a kludge.

Essentially some additional checking has been inserted into the section that tries to get the lastModified timestamp for the blog. Very kludgy

Have also modified the return code check of the mirror process. Normally it only runs the parseFeed stuff if the return code is 200 i.e. there’s been a change. Modified it (for short-term) to run parseFeed for 304 return codes – this will update the LAST_POST value.

Running this on a whole course identified another kludge that was needed to get the modified date. That’s done. Now to run the kludge script on all the current courses, remove the 304 check and then commit everything.

Quality assurance of learning and teaching

AUQA is coming. Eventually most Australian universities will receive a second visit from AUQA. As such visitations come closer increasing levels of thought are given to demonstrating quality. What does it mean to demonstrate quality of learning and teaching?

According to Biggs (2001) the answer is

The basic question then for QA is: Are our teaching programmes producing the results we say we want in terms of student learning?

This definition seems to suggest two main questions to answer:

  1. What do we say we want in terms of student learning?
  2. How do we know if our teaching programmes are producing those results?

Given what I’ve had to say about difficulties associated with measuring the effectivness of learning and teaching, I’m not confident that that the second question can be answered by many universities.

Given that level 1 smile sheets do not work what do you do?

Over emphasis on design and bugger all on maintenance

I have a quote from software engineering that I have been quoting for a long time. It’s from Glass (2001) and says that when building software, 40 to 80% of the costs are going to be for maintenance. i.e. Only from 20 to 60% of the costs are going to for the initial development or purchase.

Maintenance is something that takes more money than design.

I feel the same thing applies for courses, especially online courses, within universities, especially those with which I’m familiar with. In terms of time spent by academics on their courses I rank activities in the following order

  1. teaching the course;
  2. maintaining/modifying the course;
  3. designing the course.

Designing the course is generally the activity they do the least.

Question: How many staff have actually designed a course?

Increasingly in my context, academics are simply taking a course that someone else has created. Due to the nature of this context many of them tend to make changes only when absolutely necessary, and many don’t then. This is due to a number of courses being taught all year around – which means no one academic can have ownership of it

Question: Is there any difference in the answer to the previous question based on characteristics of the course (e.g. # times offered, # of campuses etc)?

The problem

Sometimes the processes, people, research and products intended to help academics with the courses show an unhealthy focus on design and creation of courses and little on maintenance. Which is a mismatch, if staff spend the majority of time teaching and maintaining courses.

I’ve seen this in course designs and systems that offer some support for design, but offer little support or consideration of on-going maintenance. For example, a kludge in using a LMS that achieves a design goal but requires hours of additional work each time the course is reused.

I’ve seen evidence of this in senior management who think the solution to problems in courses is to engage an instructional designer to help the academic to re-design the course. An approach that ignores the majority of what people do.

I’ve seen evidence of this in organisational processes that place emphasis on the creation of artifacts (course profiles, course websites, features of course websites) and little to no consideration of what happens for the tasks that take up the majority of time spent by academics teaching.

Ideas for more thought

  • Quantify some of the anecdotal “evidence” I’ve mentioned above, especially the questions above.
  • What are the factors that encourage/require an academic to make changes to a course?
  • What are the features provided by a LMS to support maintenance? How effective are they? e.g. the course copy feature in older versions of Blackboard had some fairly significant limitations.
  • How do the (do they?) processes and policies of an institution impact on where academics spend their time?
  • What are the impacts of all of the above on the quality of learning and teaching?

I’m sure there are many more.


Glass, R. (2001). “Frequently Forgotten Fundamental Facts about Software Engineering.” IEEE Software 18(3): 110-112.

Lessons from place

The following is the last part of the Place section of chatper 2 of my thesis. It’s not that good, but enough has been done to get it out and await feedback.

Lessons from place

The Place component of the Ps Framework aims to understand the context within which e-learning within universities operates. Organisational and societal characteristics play a role in defining the context in which tertiary education operates and frames the parameters of potential individual and organisational responses (White 2006). Previous sections within the Place component (Section 2.1) have examined the characteristics of broader society (Section 2.1.1), the higher education sector (Section 2.1.2) and the nature of individual institutions of higher education (Section 2.1.3). This section identifies, and describes in more detail below, four main lessons from this examination of Place and how it applies to e-learning within universities. Those four lessons are:

  1. Change for universities is traditional, inherent and necessary in its Place.
  2. Inconsistency is a feature of universities and their place.
  3. Universities and their place are complex adaptive systems.
  4. There is a mismatch between the place of universities and its current processes.

Change is traditional, inherent and necessary

It is not difficult to find authors commenting on the centrality of change to the modern university. The environment in which universities operate is one of intense change (McNaught 2003). Higher education continues to undergo massive change (Newton 2003). Higher education is beset by grotesque turbulence (Webb 1994). A distinctive feature of the modern world is not change per se but its character, intensity and felt impact (Barnett 2004). Within this environment the rate of change required of universities will almost certainly be more rapid than in earlier centuries refer?. Academic institutions must remain flexible enough to response to emerging social demands, technological change and economic realignments (Scott 2006). Insitutions that cannot continually change to keep up with the needs of the transforming economy will become irrelevant (Klor de Alva 2000).

It is equally easy to find evidence of universities being somewhat less than accepting of change. There is a clear strand of research that addresses higher education’s capacity for resistance, if not downright subversion, of external pressures and requirements (Brennan and Teichler 2008). Universities are one of a very few institutions that have maintained their existence since the 1500s (Kerr 1994). The pre-dominant model of a university remains the traditional combination of teaching and research suggested by Humboldt in the 19th century (Tsichritzis 1999). There is also the suggestion that teaching is one of the few human activities that does not demonstrate improvement from one generation to the next (Bok 1992).

As mentioned previously, there are alternate perspectives of the university as having a proven ability to evolve in a changing environment (Martin and Etzkowitz 2000) and fill any purpose society sets for them (Kogan 2000). The view that universities are static institutions resisting change is perhaps an artifact of analysts looking for change from the top down, rather than the bottom up (Birnbaum 2000). Change in professional bureaucracies – like Universities – does not occur from the top-down via management, administrators and major reforms, instead it sweeps in through the slow process of changing the professionals that form the operating core (Mintzberg 1979). This type of change is not highly visible as it is not introduced through master plans, ministerial bulletins or on a global scale (Clark 1983).

The uncritical acceptance of claims of crisis, stagnation and the existence of turblence of a different order of magnitiude than previously seen makes institutions more receptive to management innovation, especially those that claim to be able to predict or control the environment (Birnbaum 2000). An emphasis on ‘new practices for a new age’ contributes to a misunderstanding of the past and an ignorance of what is really important in organizations (Eccles, Nohria et al. 2003). Rather than suggest change is permanent, Berg et al (2003) suggest that it is the basic condition of life. Change is traditional, inherent and necessary to universities, it is nothing new, all who work with in them must continue to deal with the ‘complex interaction between the planned and the serendipitous’ (Webb 1994).

Inconsistent requirements, tensions and paradox

The types of changes or pressures arising from place with which universities must deal are, as mentioned previously, creating inconsistent needs and outcomes. Findlow (2008) notes the significant tension that arises between place-based pressure for accountability, that creates a need for measurement and risk-reduction, and similar pressure for innovation, the nature of which often defeats measurement and requires risk taking. Webb (1994) discusses the tension arising from demands for greater coporateness and executive management with funding policies that encourage university departments to see financial rewards and expansion as ‘theirs’. Webb (1994) also highlights the tension between increasing demands to serve local communities and rewards associated with research and teaching excellence. Marginson (2007) comments on how university ranking systems, which tend to norm institutions as a single global market of essentially similar comprehensive research universities in order for comparison to be sensible, tend to work against national and institutional desires for diversity, specialist missions and strategies of innovation within higher education.

Attempts to make sense of a world that is increasingly ambiguous and ever-changing frequently leads to a simplification of reality into polarised either/or distinctions that conceal complex interrelationships (Lewis 2000). Rather than compromise between the distinctions, vibrant organizations change by simultaneously holding the two inconsistent states – a paradox – to create, not a bland halfway point, but instead an edge of chaos (Eisenhardt 2000). Meister-Scheytt and Scheytt (2005) argue that “the rationale underlying decision processes in universities is inherently paradoxical and hence change management in universities is the management of paradoxes under turbulent circumstances”.

It is complex

Higher education’s characteristic continuing change, combined with diverse nature of its students and the range of courses offered compound the complexity inherent in higher education (Jones and O’Shea 2004). The higher the social complexity, defined as the number and diversity of participants, the more difficult a design project becomes (Conklin 2005). The multifaceted disposition of the university as an organization stretched among diverse sub sub-systems of the society, causes paradoxical effects that make change in universities complex (Meister-Scheytt and Scheytt 2005) There is a need to see universities as complex and occasionally contradictory entities whose developmental trajectories are shaped by multiple historical, political and cultural characteristics (Tuunainen 2005). The higher education sector is a complex domain with many different kinds of institutions fulfilling very different roles (Berg, Csikszenthmihalyi et al. 2003).

Complexity describes a feature of systems where the interactions between elements are unclear, uncertain and unpredictable (Barnett 2004). This is more than the interconnections between elements are so complex as to be indeterminable; it suggests that the connections are so interwoven that any attempt to engage with on e strand will have repercussive and unforeseeable impacts on many, if not all, of the other strands (Barnett 2004). Under such a view organizations can be seen as systems whose goals, the necessary resources, and the interrelationships between components must all be continuously redefined (Meister-Scheytt and Scheytt 2005). In a complex context there are no right answers to discover ahead of time due to unpredictability and flux (Snowden and Boone 2007).


It appears that the current emphasis on increasing corporatisation and executive management within universities is creating a mismatch between organisational practices and the society, sector and institutions within which higher education takes place. Such a circumstance can result in ‘organisational schizophrenia’ manifesting itself as a mismatch between organisational goals and achievable practice on the ground (Lisewski 2004). A situation where success depends on adopting strategies that overcome a fundamental mismatch between context and objectives (Findlow 2008). Attempts to reduce the complexities inherent in corporatising the processes of universities creates a gap in organisational knowledge that can lead to oversights and artificial simplifications (Churchman 2006). More fundamentally, the on-going emphasis on overly rationalised accounts or organisational life (Adams 1994) and the fundamental assumption of a certain level of predictability and order (Snowden and Boone 2007) contributes to this mismatch. Achieving outcomes in a time of increasing uncertainty requires a deep understanding of place, the ability to embrace complexity and paradox and a willingness to flexibly change styles (Snowden and Boone 2007).


Adams, G. (1994). "Blindsided by the Elephant." Public Administration Review 54(1): 77-83.

Barnett, R. (2004). "Learning for an unknown future." Higher Education Research & Development 23(3): 247-260.

Berg, G., M. Csikszenthmihalyi, et al. (2003). "Mission possible? Enabling good work in higher education." Change 35(5): 40-47.

Birnbaum, R. (2000). Management Fads in Higher Education: Where They Come From, What They Do, Why They Fail. San Francisco, Jossey-Bass.

Bok, D. (1992). "Reclaiming the public trust." Change 24(4): 13-19.

Brennan, J. and U. Teichler (2008). "The future of higher education and of higher education research: Higher education looking forward: an introduction." Higher Education 56(3): 259-264.

Churchman, D. (2006). "Institutional Commitments, Individual Compromises: Identity-related responses to compromise in an Australian university." Journal of Higher Education Policy and Management 28(1): 3-15.

Clark, B. (1983). The Higher Education System: Academic Organization in Cross-National Perspective. Berkeley, CA, University of California Press.

Conklin, J. (2005). Dialogue mapping: Building shared understanding of wicked problems, Wiley.

Eccles, R., N. Nohria, et al. (2003). Beyond the Hype: Rediscovering the Essence of Management, Beard Books.

Eisenhardt, K. (2000). "Paradox, sprials, ambivalence: The new language of change and pluralism." Academic of Management Review 25(4): 703-705.

Findlow, S. (2008). "Accountability and innovation in higher education: a disabling tension?" Studies in Higher Education 33(3): 313-329.

Jones, N. and J. O’Shea (2004). "Challenging hierarchies: The impact of e-learning." Higher Education 48(3): 379-395.

Kerr, C. (1994). Higher Education Cannot Escape History. New York, SUNY Press.

Klor de Alva, J. (2000). "Remaking the Academy – 21st Century Challenges to Higher Education in the Age of Information." EDUCAUSE Review: 32-40.

Kogan, M. (2000). "Higher Education Communities and Academic Integrity." Higher Education Quarterly 54(3): 207-216.

Lewis, M. (2000). "Exploring Paradox: Toward a more comprehensive guide." Academic of Management Review 25(4): 760-776.

Lisewski, B. (2004). "Implementing a learning technology strategy: top-down strategy meets bottom-up culture." ALT-J, Research in Learning Technology 12(2): 175-188.

Marginson, S. (2007). "University mission and identity for a post-public era." Higher Education Research & Development 26(1): 117-131.

Martin, B. and H. Etzkowitz (2000). "The origin and evolution of the university species." Journal for Science and Technology Studies 13(3-4): 9-34.

McNaught, C. (2003). "Supporting the global e-teacher." International Journal of Training and Development 7(4): 287-302.

Meister-Scheytt, C. and T. Scheytt (2005). "The complexity of change in universities." Higher Education Quarterly 59(1): 76-99.

Mintzberg, H. (1979). The Structuring of Organizations. Englewood Cliffs, NJ, Prentice-Hall.

Newton, J. (2003). "Implementing an institution-wide learning and teaching strategy: lessons in managing change." Studies in Higher Education 28(4): 427-441.

Scott, J. (2006). "The mission of the University: Medieval to postmodern transformations." The Journal of Higher Education 77(1): 1-39.

Snowden, D. and M. Boone (2007). "A leader’s framework for decision making." Harvard Business Review 85(11): 68-76.

Tsichritzis, D. (1999). "Reengineering the University." Communications of the ACM 42(6): 93-100.

Tuunainen, J. (2005). "Hybrid practices? Contributions to the debate on the mutation of science and university." Higher Education 40(2): 275-298.

Webb, A. (1994). Two Tales from a Reluctant Manager. Introducting Change from the Top in Universities and Colleges: 10 personal accounts. S. Weil. London, Kogan Page: 41-56.

White, N. (2006). "Tertiary education in the Noughties: the student perspective." Higher Education Research & Development 25(3): 231-246.

Phd Update #11 – very short week

Well, this week was a very short week. All up 4 days were lost with illness, work and a burst pipe at childcare requiring some additional babysitting duties. That said, I’m feeling pretty happy about the thesis mostly because on major hurdle is out of the way and it went fairly quickly. Hopefully this can continue – the progress, not the short weeks.

What I’ve done

Last week I suggested I would aim to:

  • Have completed and posted the section on “Place”.
  • Be close to doing the same thing for “Purpose”.
  • Perhaps make some headway for another component of the Ps Framework – perhaps either People or Pedagogy.

I haven’t really looked at “Purpose” or any other component of the Ps Framework. I’ve only been able to work on Place. On last week’s summary I outlined the following as sections required to complete “place”:

  • InstitutionDONE
  • Types of systems – DONE
    No post for this section, I’ve worked it into the institution section in a much reduced form.
  • Lessons from place – not done
    I have much of the structure of what I want to say.

In terms of PhD related blog posts in the last week, I’ve posted:

  • What don’t we (e-)learn relating my introduction to Argyris and Schon’s notions of Model 1 and Model 2 behaviours and defensive routines.
  • Everything old is new again – sparked by one of the texts I used in the Institution section. It examines how much of the concern shown today about universities, has been going on for sometime.

What will I do for next week?

I’m going to keep the same aims as for last week:

  • Have completed and posted the section on “Place”.
  • Be close to doing the same thing for “Purpose”.
  • Perhaps make some headway for another component of the Ps Framework – perhaps either People or Pedagogy.

Institution – another part of place

For longer than I care to remember, I’ve been working on the Place component of the Ps Framework for chapter 2 of my thesis. This post brings the penultimate section for the Ps component – institution. The last section will be the “lessons from place” section that attempts to draw some lessons from the Place component for the practice of e-learning. Who knows when that will arrive.

As with previous parts of the thesis, this is a first draft with only a modicum of re-reading. There are likely to be mistakes. More in-depth editing will wait for a later time.


The previous sections have focused on the nature of changes to the society (2.1.1 – Society) and the impact of these changes on the higher education sector (2.1.2 – Sector). This section moves toward examining the factors associated with individual institutions that can enable, hinder and inform the implementation of e-learning. The institutional context plays a dominant role in shaping the content and process of user participation and change management in systems development (Butler and Fitzgerald 2001). An understanding of the driving and restraining forces within an individual academic context is important to determining whether a broad-scale e-learning strategy is feasible (Parchoma 2006). In terms of the adoption of e-learning, institutional context is all important (Nichols 2007).

This section examines institutional factors through three parts. First, it examines the differences that are visible between different approaches to understanding universities and organizations more broadly. Finally, the nature and features of the culture and sub-cultures within higher education are examined. The next section (2.1.4 – Lessons from Place) seeks to draw on the information presented as part of the Place component of the Ps Framework to identify some lessons for e-learning implementation within universities.

Types of institution – points of difference

New ideas in business, many of which become fads, are often presented as universally applicable quick-fix solutions (Birnbaum 2000). Ideas that have universal applicability (Snowden 2005), which regardless of obvious differences between sectors and organizations assume, at some level, that there is sufficient similarity so as to not negatively impact the migration of the idea and its success from one context to another. As observed in the previous section there is a trend towards the standardisation of universities to enable interoperability, comparison and ranking that increasingly illustrates this assumption of similarity. At the same time there is an on-going and long standing push to perceive and manage universities in ways very similar to other commercial organizations. Birnbaum (2000) provides examples of attempts to treat universities as commercial businesses throughout the 20th century.

However, writing in the preface to Cooke (1910) Henry Pritchett suggests “college is partly a business, and partly something very different from a business”. This is suggestive that there are differences and one of the main aims of this section to illustrate those differences. The assumption is that these differences suggest that migration of ideas between different organizations may be more problematic than apparently accepted in some of the literature. The particular differences highlighted here include differences: in abstractions for understanding organizations; in types of organizations; and between universities.

Differences in abstractions for understanding organizations. It has been suggested that, at least theoretically and anecdotally, there is evidence to suggest that organisational science has a conceptual bias at the level of their key object of research and practice, the organisation (Adams and Ingersoll 1985). There is an over-emphasis on organisational metaphors that seek to structure and understand organizations as rational, stable and purpose driven entities (Behrens 2007). This fits with the current age and culture which is one of technical rationality with a pre-disposition to the use of scientific-analytic lenses that provide overly rationalised accounts of organisational life and keep much of the nature of organizations invisible (Adams 1994). Organisational science has been criticised for an over emphasis on metaphors that view organizations as machines or organisms in a preference to the culture metaphor (Behrens 2007).

Even with the over-emphasis on the purpose-driven, the literature does contain a number of examples where organisational diversity is shown. Handy (2005) identifies four different types of organizational culture – role, achievement, power and support. Mintzberg (1993) grouped organizational structures into five clusters (see Table 2.3) based on the prime coordinating mechanism, the key level within the organisation and the type of decentralization. Maister (1993) suggests that professional firms differ from other business enterprises in that they provide highly customized services in highly personalized ways. Differences that mean many of the management principles such as standarisation, routinisation, and supervision difficult to apply (Maister 1993). In addition, it is not structure, culture or systems alone that determine outcomes, human agency means that individuals and groups within the organisation have a choice about how they act and respond (Knight and Trowler 2000).

Table 2.3 – Mintzberg’s structural configuration of organizations (adapted from Unger, Macq et al. 2000)
Structural Configuration Prime coordinating mechanism Key part of organisation Type of decentralization
Simple structure Direct supervision Strategic apex Vertical and horizontal centralisation
Machine bureaucracy Standardisation of work processes Technostructure Limited horizontal decentralisation
Professional bureaucracy Standisation of skills Operating core Vertical and horizontal decentralisation
Adhocracy Mutual adjustment Selective decentralisation

The ability of human systems to shape their perception and consequently to co-evolve concept and practice in order to create a new reality is one of the insights that arise from social complexity (Snowden and Stanbridge 2004) and is one of the factors that leads Snowden and others to develop a landscape of management (Figure 2.1) and the Cynefin framework (Snowden and Stanbridge 2004; Snowden 2005; Snowden and Boone 2007). Snowden and Stanbridge (2004) suggest that the dominant ideology of management – discussed above as the over emphasis on technical rationality – arises from a focus on a single-ontology approach to sense making that assumes that through proper investigation things are known or knowable and that once cause and effect relationships are discovered, they repeat. This view is not seen as incorrect or denied, but it is, however, seen as only appropriate in certain bounded circumstances (Snowden 2005).

Landscape of management
Figure 2.1 – Landscape of Management (adapted from Snowden and Stanbridge 2004)

The reliance on this single-ontology perspective and it’s overgeneralization has subsequently led to an absence of understanding of different perspectives that may be more appropriate for different circumstances. As an alternative Snowden and others develop models (Figure 2.1 and Figure 2.2) based on a multi-ontology sense-making model of decision-making. Within these models there is a space for traditional business oriented approaches that assume ordered systems that have clearly identifiable cause and effect relationships that enable prediction of future events (Snowden 2005). However, there is also recognition of different types of system that demonstrate un-order. Un-ordered systems do not demonstrate a lack of order, but instead demonstrate an “emergent” order that is understandable in retrospect, but cannot be predicted (Snowden and Stanbridge 2004). Within the landscape of management (Figure 2.1) order and un-order are seen as disjoint domains, whereas epistemology is presented as a continuum from very specific rules through to heuristics, guiding principles or implicit rules of thumbs with high levels of ambiguity (Snowden and Stanbridge 2004).

Cynefin domains
Figure 2.2 – Cynefin Domains (adapted from Kurtz and Snowden 2003)

The Cynefin framework establishes five different domains (Figure 2.2). The four named domains in Figure 2.2 require diagnosis and action in contextually appropriate ways, while the fifth – disorder – implies that it is not know which of the four other contexts is predominant (Snowden and Boone 2007). The major benefit underpinning both the landscape of management and the Cynefin Framework is that it draws attention to the possibility of different ontologies or contexts (e.g. types of organizations) and the consequences of applying an ill-matched epistemology (e.g. decision-making or other process).

Difference in types of organizations. There is a long history of government and business seeking to apply management insights and practices from the broader business community to universities. An early example of this is Cooke (1910) that aims to offer insight into the operation of universities from “those who conduct industrial enterprises”. There exist a number of problems with this practice. Not the least of which is that the adequacy of such techniques has been challenged in business (Meister-Scheytt and Scheytt 2005). Such an approach also assumes that there is sufficient similarity to enable the successful transference of practices between different organizations.

One example of the differences between business and higher education is the question of success and measurement. Success in conventional businesses is more easily defined with objective performance criteria, predicted outcomes and clearer causal performance relationships than in universities where the definition of success is open to interpretation and identity-related attributes (Churchman 2006). While approaches from business should not be regarded as false in principle, they appear to be insufficient when examined against the model of universities as knowledge-intensive organizations (Meister-Scheytt and Scheytt 2005). Unlike private enterprises which relate primarily to one societal subsystem – the economy (Meister-Scheytt and Scheytt 2005) – a university is a meta-institution which interacts and is intertwined with the professions, governments, social movements, business, ethics and morality, education, culture, science, art (Agre 1999; Meister-Scheytt and Scheytt 2005). Universities can be characterized by distributed decision making, a high degree of local autonomy and distributed resource allocation (Dodds 2007). Kezar (2001) describe a non-exhaustive list of thirteen features that are distinctive to universities and suggests that mistakes in analysis and strategy may result if these factors are overlooked and that concepts foreign to the academic will fail to engage those who must bring about change.

Differences between universities. In terms of university species, Martin and Etzkowitz (2000) identify four: the classical university, the technical university, the regional university, the teaching university and a number of hybrids. Based on the extent to which policy is defined and operations controlled, McNay (1995) identify four distinct types of university – collegiate, bureaucracy, corporate and enterprise – all four of which co-exist, with different balances between them, in most universities. Danaher et al (2008) discuss two types of institutions: survivalist – which perceive higher education as a competition resulting in the survival of the fittest, and; remedialist – oriented to a more inclusive culture. Valimaa and Hoffman (2008) distinguish between older, established universities and other types of institutions in terms of their ability to resist, even generate change. Even between universities, there are differences.


The practice of e-learning is enterprise-wide and involves many different departments and sub-units within an organization. Consequently it involves many parties which magnifies traditional problems of politics, management expectations, hidden agendas, disruption to the balance of power, technical concerns and differences in cultural values (Gregor, Jones et al. 1999). The structure of an organisation – which in human systems includes how decisions are made, the operating policies, norms, and actions – influences behavior (Senge 1994). Adoption of an innovation, like e-learning, can be hindered if it does not fit within the structure of the social system or challenges the system’s established behaviour patterns and beliefs (Jones, Jamieson et al. 2003). Implementation of e-learning will require organisational realignments (Hitt and Hartman 2002).

Fragmentation is a common characteristic of university structures with institutions typically composed of nearly autonomous schools and faculties and individual academics within these that decide what to teach and how (Green 1997). As a result central support units are faced with a need to facilitate new practices within a context with a wide heterogeneity of needs and potentialities (Zellweger 2005). These central units are growing in importance as influential gatekeepers between the university and its external stakeholders; and also acting as a bridge between management and academic staff (Jongbloed, Enders et al. 2008). Provision of adequate support for educational technology involves many support units including information technology, libraries and faculty development between which it is possible to observe latent cultural conflicts (Zellweger 2005).

As a response to this conflict and also to external forces discussed above the structure of some instiutions have seen a move towards accountability, corporatisation and centralized control. Stiles and Yorke (2006) argue that centralised control and associated moves create challenges for innovation and also create conflict with the traditional structure of universities. Centralisation is a key feature of tightly coupled organizations that are also non-differentiated, highly coordinated and have a strict division of labour (Kezar 2001).

Traditionally, universities have been seen as fitting within Mintzberg’s (1993) idea of a ‘professional bureaucracy’. This traditional structure is also seen as a barrier to innovation (Stiles and Yorke 2006). Traditionally, universities are loosely coupled (Weick 1976) in that they illustrate a lack of central coordination, have greater differentiation amongst components, higher degress of specialization amongst workers and lower predictability of future action (Kezar 2001). If change occurs it is flexible, improvisational and focused on self-design with major change being less necessary as continuous change is more likely (Weick 1976). Within loosely coupled systems the diffusion of major change is difficult to achieve as diffusion, imitation and social comparison is not as are prevalent (Morgan 2006).

Adding information technology into universities changes structures, it makes existing connections closer and more complex and creates new connections to vendors and standards bodies who control IT standards (Agre 1999). Expanding the use of information technology within learning and teaching requires and creates changes to connections, especially in the form of policies. While some aspects of institutional policies can be seen as positive influences, others are seen as less helpful (Gonzalez 2009). Dutton and Loader (2002) identify institutional incentive structures and copyright and intellectual property policies. The systems and policies associated with teaching evaluation can discourage risk taking in the classroom (Dutton, Cheong et al. 2004). Parchoma (2006) identify eight potential restraining forces from the policies around e-learning, including: tinancial risk, pervasive fiscal challenges, existing residency requirements, imbalanced research and teaching reward systems, problematic intellectual property policies, inadequate levels of application of research-based distributed learning strategies, and potentially misaligned organizational structures and functions.


Though others have suggested that we still cannot define culture (Lewis 1998), Schein (1991) offers the following formal definition, culture is:

  1. a pattern of shared basic assumptions,
  2. invented, discovered, or developed by a given group,
  3. as it learns to cope with its problems of external adaptation and interal integration,
  4. that has worked well enough to be considered valid, and, therefore,
  5. is to be taught to new members of the group as the
  6. correct way to perceive, think, and feel in relation to those problems.

Green (1997) suggests that academic values such as unfettered inquiry, the pursuit of knowledge for its own sake, the quest for freedom from external interference and others contribute to the notion of a universal academic culture. However, considerable evidence exists to suggest that different academic disciplines have their own culture, language and practices which influence their learning and teaching and hence, the kind of support required for the enhancement of learning and teaching (Harpe and Radloff 2006). Indeed, it has been pointed out that the disciplines themselves may also have a fragmented nature (Knight and Trowler 2000). Notions of a universal academic culture may be obsolete within an environment in which the academic role is becoming more obsolete (Churchman 2006).

In terms of constraining innovation, the expectations and values of students can be as much of a constraint as the expectations and values of top administrators (Dutton, Cheong et al. 2004). Radical change, change that challenges existing communities, can provoke partisan reactions that create significant management problems (Stiles and Yorke 2006). In large-scale technology innovations, such as university-wide e-learning, it is likely that adoption will require an increase in dependence on other individuals or organizational units. Allen (2000) found that perceptions of the other units, rather than perceptions of the innovation, played a larger role in adoption decisions. Similarly, Ayers (2004) observes that academic and information technology cultures, two of the main sub-cultures involved with e-learning within universities, do not mix together well. The differing viewpoints and subsequently the varying and competing priorities of the different sub-cultures within an organisation can lead to considerable internal tension (Luck, Jones et al. 2004). Consequently, it is not uncommon for conflict to exist between the management, academic, technical and administrative cultures (Luck, Jones et al. 2004).

Traditionally, teaching has been a solo act with primary responsibility laying with an individual academic (Coates, James et al. 2005; Folkers 2005). However, e-learning requires a high level of expertise from a number of different fields including: content matter, technology, management, and instructional design (Jones, Stewart et al. 1999). Faculty developers, instructional designers and IT workers speak different languages, represent different values and are assigned tasks that bear a number of inherent conflicts (Zellweger 2005). While this can be empowering for staff it does raise questions about the role of academics (Folkers 2005).

Academics have considerable autonomy and often can and do resist the imposition of new technology and changes to routine (Jones, Gregor et al. 2003). Mesiter-Scheytt and Scheytt (2005) make the related point that universities are ‘knowing organisations’ and academics are experts in argument. Consequently, it is not surprising to see a variety of defensive routines (Argyris 1990) employed within universities (Tagg 2007). The professional bureaucracy emphasises authority of a professional nature – the power of the academic’s expertise – and consequently the strategies of such an organisation are largely those of the individual professionals who will resist changes that remove autonomy or drive the organisational structure to a machine bureaucratic form (Mintzberg 1993).

Existing group norms, standards, values and perceptions are potentially restraining forces in the adoption of e-learning (Parchoma 2006). The many parties involved magnify traditional problems of politics, management expectations, hidden agendas, disruption to the balance of power, technical concerns and differences in cultural values (Gregor, Jones et al. 1999). There has been inadequate recognition of the inherent differences in organisational cultures, academic cultures, education and training philosophies, and teaching and learning values and traditions within different cultural groups (Calder 2000). Even though it is the organisational culture and environment, rather than the technology, that determines the learning experience (Saunders 1998) studies of e-learning within universities have displayed unsophisticated perspectives of the nature of culture and how to achieve effective cultural change (Lisewski 2004). A critical strategy for effective e-learning is to recognise the different cultures of learning among and within organizations (Lea 2003). Accepting the view described by Trowler and Knight (1999) – that organizations can be understood by the multiple discursive practices arising from the interplay of not-necessarily compatible cultures and sub-cultures – results in the nature of the organisation being seen as political and contested.

This perspective, shared by many, suggests that managerialism is not as settled within universities as is assumed and that resistance in its many manifestation is often underplayed (Barry, Chandler et al. 2001). Consequently it has been suggested that rather than establish success factors, policy makers should focus on whether or not change is contextualised appropriately within a correct characterisation of the organisational culture (Lisewski 2004). Given the ambiguity, uncertainty and conflicts inherent within academic organizations it may be more appropriate to accept these values and focus less on rational decision-making and more on sense making and practical reasoning (Askling and Stensaker 2002).


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Some initial thoughts on e-learning and innovation

Theoretically, I’m in the process of starting a new job that is focused on encouraging e-learning and innovation within a university context. The following post is an early attempt to try and make sense of this job, what it might do and how it might do it. It’s probably of little value to others, but I’m trying to be open about this.

This is still early days and the understanding will continue to grow and change. Due to the nature of human beings as pattern matching intelligences this exploration will necessarily, as arising out of my own attempts to make sense of this job, illustrate my past experiences and patterns of action. Feel free to disagree and suggest alternative perspectives.

The model

The following started out as a 2×2 framework but has evolved as I’ve been writing this post. The attempt of the model is to represent the process and two of the decisions that have to be answered went attempting a change or innovation within an organisation. In summary, the idea is that:

  • Some spark creates the need for the change or innovation.
  • This makes it necessary to decide what to do in order to respond to the spark.
  • Once what is decided it is necessary to decide how to do it.
  • How things are done can also contribute to the next or different sparks.

I’ve purposely not included numbers in the above list. Cycles can start in any of these stages and there isn’t always a cycle. In fact, some might argue a significant flaw in many organisations is a failure to draw knowledge from how things were done in order to inform the next spark. Alternatively, it may not always be possible to connect the causal cycle until after the fact.

A Change Cycle

The spark

There is generally a spark, some event, thing, or knowledge that makes it necessary to make some change or undertake some action. It might be to solve a problem or achieve a goal. The spark may not be identified prior to the change, only after. The model suggests that such a spark can arise from a spectrum with two extreme dimensions:

  1. Idealistic; and
    In this context, something at the idealistic end would generally be something created by an expert, management or government. For example last night the Australian Federal Government released it’s budget for the next year and it includes a number of projects and changes that will require strategic responses from Australian Universities. Alternatively, it might be something internal to an organisation such as the appointment of a new Vice-Chancellor.
  2. Naturalistic.
    In this context, this is understood to be something that arises from the “coal-face” of the organisation. An extreme example might be an individual academic faced with a group students not understanding a particular concept.

This is meant to be a spectrum, an example from the middle might be an institution (not a single academic) identifying long turnaround times on assignment feedback.

What to do

Given a spark, it is necessary to identify what to do. What can be done to respond to the spark? Of all the different projects that might work, how does an institution or individual identify what to do?

The model represents two extreme ends of a spectrum:

  1. Fad; and
    This is where a project is chosen simply because someone else has done it. e.g. “boys with toys” represents a lone-ranger academic adopting the use of Twitter because he saw the Oprah show on Twitter.
  2. Knowledge.
    The chosen project is identified based on some theoretical knowledge – be it organisational, learning, technical etc – and its application to the local context. For example, the adoption of constructive alignment based on the ideas of Biggs.

How to do it

Having decided what to do, it is now necessary to plan how to do it. This spectrum draws on a distinction made by Kurtz and Snowden (2007) and is one I’ve used before. The following table compares the two approaches.

Idealistic Naturalistic
Achieve ideal state Understand a sufficiency of the present in order to stimulate evolution
Privilege expert knowledge, analysis and interpretation Favour enabling emergent meaning at the ground level
Separate diagnosis from intervention Diagnosis and intervention to be intertwined with practice

Snowden’s point – and I agree – is that idealistic approaches only work in contexts in which there is a clear connection between cause and effect. i.e. you can predict that if you do X, then Y will happen. Snowden points out in his Cynefin framework and associated writing that there are other contexts, that require different approaches.

Cynefin domains

Putting the model in context

The rest of the post attempts to use the above model to begin understanding the context within which the new job takes place. The aim is to help me formulate plans for the position that I need to raise with the hierarchy to get approval. It covers

  • the spark; and
    An attempt to identify factors, both naturalistic and idealistic, that are creating a need for change or innovation within the institution.
  • a list of projects.
    Based on combination of “what to do” and “how to do it” and knowledge/prejudices around the local context identify an initial list of potential projects.

Some of the thinking that follows does (or will/should) include a range of existing projects and processes within the organisation. While the new position may not be directly connected with these projects and processes it is necessary for the position to be aware of an work with those projects and processes.

This is only an initial list – it will grow and change as time goes by.

The spark

The following aims to provide an initial list of potential sparks that might be important for the new position to either do something about or at least work with or inform. I’ve attempted to group them in some initial rough categories as a way to help brainstorm:

  • From the position description.
  • Organisational strategic plans.
  • Organisational factors.
  • Government policies and other external factors.

From the position description

The new position comes with a list of accountabilities by which the incumbent will be judged. Not surprisingly, this focuses the attention. The following are drawn from those accountabilities.

Organisational strategic plans

Like most institutions mine has developed a strategic plan, but it also has a range of other organisational goals, understandings and cultures that also have to be considered. I need to better understand these.

First, focus on the strategic plan which is divided up into 8 main sections. Many of the components of these aims are the responsibility of existing organisational units. I’ll focus on the ones that appear to connect with the new job, but leave the others in but struck through. Each component is further divided into: what we need to do; how we will do it; how will we know that we are doing it well.

  1. Learning and Teaching
    • What we need to do
      • Provide a multimodal educational platform supported by appropriate technology.
      • Ensure that programs meet future industry and community needs.
      • Provide multiple pathways and a seamless fit for articulating students.
      • Improve student retention and progression rates.
      • Support collaboration within and across campus and administrative structures to ensure successful student learning.
      • Develop and reward staff capability in innovative curriculum design, teaching and assessment, and the scholarship of learning and teaching
    • How we will do it
      • Progress the implementation of the Student Learning Journey.
      • Benchmark programs against relevant industry and labour market needs.
      • Review graduate attributes and improve integration into programs.
      • Provide formal and informal mentoring for new academic and casual teaching staff.
      • Identify, develop and support learning and teaching leaders.
      • Support staff to engage in the scholarship of learning and teaching and develop innovative practices.
    • Doing it well?
      • Improved Course Experience Questionnaire (CEQ) and Graduate Destination Survey (GDS) outcomes against benchmarked universities.
      • Improved Learning and Teaching Performance Fund outcomes.
      • Increase in the quality of Australian Learning and Teaching Council (ALTC) awards and grants applications and maintenance of success in an increasingly competitive arena.
      • Improved student engagement as measured by the Australasian Survey of Student Engagement.
      • Improved Student Evaluations of Teaching and an increase in the number of students participating.
  2. Research and innovation
    • What we need to do
      • Support research excellence in the University’s priorities for research that contribute to the Resource Industries; Community Health and Social Viability; and Intercultural Education and that this research meets the needs of the communities we serve.
      • Develop and support a vibrant research culture and intellectual environment.
      • Enhance the quality and dissemination of research outcomes.
      • Support quality research programs to enable staff and students to achieve success and realise their full potential.
      • Provide quality, relevant services and support to research stakeholders.
      • Increase the University’s research performance.
    • How we will do it
      • Increase external research income through effective policies, training and processes and focus investment for growth in the Research Institutes.
      • Provide training, staff development, networking and mentoring for staff involved in research and reward excellence and encourage exploration and innovation.
      • Research and university leaders will work strategically with industry, community, government and other stakeholders to align research priorities with industry needs.
      • Foster an environment of active enquiry, innovative development and effective dissemination
    • Doing it well?
      • External research income to increase by 50% in the next 2 years and to be benchmarked against other institutions.
        There is an interesting split between “innovation”/L&T funding and research funding.
      • Receipt of external research investments other than research project income.
      • Improvement in the quantum of quality publication outputs registered each year by category and compared with other institutions.
      • Improvement in the University ranking for external research performance funds relative to the sector.
      • Increase in the number of research active staff by 5% per annum.
      • Increase in the number of Research Higher Degree enrolments and increase in the number of Research Higher Degree students completing on time or earlier
  3. Community engagement
  4. Domestic engagement
    • What we need to do
      • Address the shortfall in domestic student enrolments as a matter of urgency through a range of strategies to build demand, attract students to CQUniversity and improve retention.
      • Develop appropriate contemporary programs and courses to meet the needs of domestic students, increasing participation, access, retention and success of students.
      • Develop new ways to attract students to CQUniversity including building on marketing initiatives, the re-branding exercise and redressing reputational issues.
      • Develop new ways to engage with industry, business and the community via new learning initiatives.
      • Develop new educational models for the future that are aligned with our broad mission “to be what you want to be”.
      • Explore ways to increase distance education offerings and enhance our reputation as a renowned distance education provider
    • How we will do it
      • Continue the development of new suites of contemporary programs in areas of demonstrated demand.
      • Implement the new brand.
      • Improve customer service led by Navigate CQUniversity.
      • Implement Alternative Pathways in 2008.
    • Doing it well?
        By achieving our student enrolment targets (not necessarily DEEWR targets).

      • Increase in domestic student retention rates by 1% per annum.
      • 5% increase per annum in number of students entering bridging programs and progressing to award studies.
      • Increase in access and participation rates for equity students.
      • Increase the access and participation of Aboriginal and Torres Strait Islander students
  5. International engagement
    • What we need to do
    • How we will do it
      • Build staff capability in learning and teaching related to international students, especially curriculum design and culturally inclusive teaching practices which meets the needs and expectations of international students.
      • Establish priorities and encourage engagement in research through IERI (Intercultural Education Research Institute) that informs international education in areas of policy, systems, planning, pedagogy and others.
      • Develop and implement the new CQUniversity/CMS interface and maximise the benefits resulting from 100% ownership of CMS by expanding the range of academic programs at the Australian International Campuses.
      • Explore low risk delivery mechanisms and pathway linkages.
      • Increase student and staff mobility through improved Study Abroad and Exchange programs.
    • Doing it well?
  6. People and performance
    • What we need to do
      • Fully integrate the human resource strategy with the organisational strategy, via the implementation of the Management Plan – Human Resources.
      • Invest in the development of staff to ensure that they have the requisite skills and abilities to support the attainment of the University’s strategic objectives.
      • Develop whole of University strategies in support of improved staff morale.
      • Facilitate opportunities for collaborative projects across organisational boundaries. – this is interesting
      • Provide a safe workplace for staff and students and meet all Workplace Health & Safety legislative requirements.
    • How we will do it
      • Complete the organisational restructure process by end 2008.
      • Implement revised PRPD processes.
      • Develop workforce planning and succession planning tools.
      • Develop recruitment strategies to attract and recruit high performing staff.
      • Provide management and leadership training for all managers and supervisors.
      • Negotiate a new Union Collective Agreement prior to the nominal expiry date of the current agreement.
      • Encourage active staff involvement in professional bodies.
      • Conduct focus groups with staff on ways to improve staff morale.
      • Facilitate greater opportunities for meaningful communication between staff and University managers at all levels across the University.
      • Develop Service Level Agreements for the delivery of human resources services across the University.
      • Reduce the number of staff and student injuries on University property through a range of strategies.
    • Doing it well?
  7. Resources, systems and infrastructure
    • What we need to do
      • Increase revenue and decrease costs.
      • Ensure an appropriate linkage between the planning and budget functions of the organisation.
      • Ensure management has access to the appropriate and timely information and reporting tools.
      • Ensure the University has a Strategic Asset Management Plan to support our strategic initiatives.
      • Ensure the University has an ICT Management Plan which supports our strategic initiatives.
      • Ensure campus development plans are in place to support the future operational and strategic needs of the university.
      • Ensure the University has a Financial Management Plan which supports the strategic direction of the University.
      • Work towards sustainable resource management and leadership in environmental outcomes from our operations
    • How we will do it
    • Doing it well?
  8. Governance and quality

Need to find out which parts of the organisation are responsible for the above and what they are doing.

Organisational factors

Perhaps the most open to debate, given lack of agreement amongst stakeholders and some of the points about Model 1 behaviour, but just as important. Some of the following connect with strategic plans.

  • Evaluation of learning and teaching – beyond just course based and other limitations.
  • Flexibility and quality of learning platforms and technologies.
  • Actual quality of learning and teaching, administration, e-learning.
  • An emphasis on fad and idealistic dimensions.

Government strategies

  • Teaching funding linked to performance outcomes on quality, particiaption and completion rates.
  • Student centred funding.

List of projects

An early version of the model in this post was a traditional 2×2 model (with slightly different labels). While I’ve moved on from there and think the two dimensions are spectrums the 2×2 model offers some help in understanding what could be done. The following table summarises.

Sector Description What can be done
Idealistic-fads The pre-dominant mode within organisations. This position will probably have little influence on these projects as they are driven by senior management. The best that can be hoped is to provide evidence and insight to those making decisions. Focused on nature of the organisation and the experience of students and staff. Helping increase the quality and quantity of the feedback to these folk. Make them aware of the limitations of the chosen approaches. Make sure that the knowledge generated from these projects is available and used to inform subsequent projects. Be aware of the fads/trends that are rising and become familiar with them. Perhaps attempt.
Idealistic-knowledge Generally limited use at the organisational level, some use in isolated areas The insights from the projects are likely to be useful. Ensure that the knowledge is disseminated and informs subsequent projects. Be aware of the types of knowledge that can help inform proejcts and their implementation.

This is probably where traditional university “innovation” grants sit. Probably have to engage with these but the cartoon below stikes me as saying a few things about these grants and there’s also the work of Findlow.

Naturalistic-fads A common approach – often seen in lone rangers No point, ability or benefit in stopping these. Better to help inform their implementation and learn their lessons. How to do this effectively is another question. There are some connections here or perhaps in the next sector with incremental, cumulative improvement arising out of the work of the Teaching, Learning, Technology group.
Naturalistic-knowledge Rarely used and the sector I feel most appropriate for innovation around learning and teaching. Have talked previously about the idea of reflective alignment. Something I’d like to try. Perhaps there are others.

Innovation in Corporate America