Minimum course presence and the tension between centralisation and de-centralisation

Am finding this HBR article to have an interesting take on the centralisation verse de-centralisation argument. However, still reading through it.

It particularly resonates with me at the moment because of the discussions I’ve had/seen this week around individual universities implementing minimum course presence policies. Essentially, it seems the next big fad for universities to be able to ensure that every course has a standard minimum course website.

This seems to me to be a prime example of a move to centralisation, and thus suffers from all of the problems associated with centralisation. In particular, how it removes the ability for the “person on the spot” (the teaching academic) to respond to the local context. I believe this to be an important factor in university learning and teaching because of the diversity of learning.

The tension here is that there are at least three separate requirements around a minimum course presence:

  1. An institutional quality assurance requirement;
    i.e. to ensure that all courses have some minimum standard, that all students can be assured at least this minimal level of service. Perhaps the most important requirement is that senior management need to be certain that this is the case.
  2. The learning within the course; and
    A key characteristic of each course, its teachers, and students is diversity. They are all different. They need to learn in a different way. An online course presence has to be able to engage with this diversity.
  3. The learning of the teaching staff and the organisation.
    It’s my argument that in order for an institution to improve the quality of its learning and teaching, the delivery of teaching must include a focus on learning about that delivery. i.e. when I use a minimum course site in a course for the first time, I am going to gain insights into what works and what doesn’t. I am going to learn. The minimum course presence needs to be able to change based on that learning. Not to mention that because of the diversity of teaching staff, courses and students, that learning is going to be very different.

Am wondering if the minimum course presence movement has been ruined by an over-focus on the first requirement and too little of a focus on the other two. Is there any evidence of approaches to a minimum course presence that recognises the other two requirements?

Amplify’d from
Therefore, individuals who have on-the-spot knowledge must be allowed to figure out what to do.
Discerning the appropriate balance between top-down command and control, on the one hand, and individual initiative and judgment, on the other, will always be a challenge for our society and our organizations.Read more at

Off to see the dinosaurs

And now for something completely different, leaving the dinosaurs of academic development within universities behind, it’s time to move on to some real dinosaurs, or at least their fossilised remains. In a few weeks, the two boys and I are off out west. In particular, we’re off to “ride” the Dinosaur trail of Western Queensland. Both boys are going through the dinosaur phase, with the 5 year old certain he wants to be a paleontologist when he grows up.

This and any following posts are really intended to outline some planning for the trip and gather feedback from my family, but feel free to add insight if you have any.

The basic route

The plan is something like:

  • Rockhampton to Longreach – 696 Km;
  • Longreach to Winton – 180Km;
  • Winton to Richmond – 233Km;
  • Richmond to Hughenden; – 120Km and
  • Hughenden to Proserpine – 600Km.
  • Proserpine to home – 495Km

Potential Attractions

Now to try and gather what there is to do at the three main Dinosaur destinations: Winton, Richmond and Hughenden.


  • Australian Age of Dinosaurs
    10 minutes the Longreach side of Winton. Working Museum, looks good for at least a couple of hours.
  • The Lark Quarry Trackways
    100+Km south-west. Umm, quit a long way. Maybe a tour, the ADT brochure suggests you can do both these in a day.


  • Kronosaurus Korner
    This is the one that has the boys most excited. Comes associated with a space to dig for their own fossils.


This might be just a brief drive by.

The curse of simple diagrams

There is a lot I like about within this discussion of a “systems approach to e-learning”. However, there is also much that I dislike.

I think the source of my dislike is the typical engineers (or business analyst/project management) assumption that you can develop in-depth knowledge of a complex organisation/activity/set of processes like e-learning within a university. i.e. that the gant chart or e-learning strategic plan captures everything that you need to know about the activity.

A part of this is the “simple diagram” below that is meant to represent “How technology fits into an organisation”. It’s just too tidy, not to mention linear. The influence is just one way from culture “down” the line, it’s much more complicated and multi-faceted than that. Different tools can enable radically different or previously unthought of processes that can lead to changes in culture.

Amplify’d from

Lessons learned from Webfuse: 2000 onwards

The following is an early draft of the “lessons learned” section of chapter 5 of the thesis, the third last section that needs to be completed (to first draft stage). It still needs some work and completing the last two sections will probably lead to some changes, but it’s a start.

The basic aim of this section is to draw out reasons why the intervention (in this case the Webfuse system I designed) succeeded or failed. As I write this, pretty sure I haven’t finished.

Lessons learned

Before attempting to describe the final ISDT arising from this work, this section seeks to reflect on the outcomes of the intervention in an attempt to understand how well the intervention achieved the changes sought and to understand the observed success and failures.

Relative unimportance of the technical product

From the perspective of data structures, algorithms, and bleeding edge technology Webfuse was not at all innovative. Use of scripting languages, relational databases, and open source applications to construct websites was fairly common and widespread. Nor would much of its implementation be considered theoretically correct by researchers focusing on relational databases, software engineering or computer science. For example, the schema used by Webfuse databases could not be described as being appropriately normalised. In addition, a common complaint about Webfuse has been that it was using technology that would not scale and that was not “enterprise-ready” (even though it could and did scale and support the enterprise). The questions of technical novelty, technical purity, or fulfilling arbitrary scalability guidelines had little or no effect on the success of Webfuse. The success of Webfuse arose from becoming, and being able to stay, an integral and useful part of the everyday life of the students and staff of the institution.

Webfuse was not a product

This emphasis on the characteristics of the technical product was also evident in the continual queries from colleagues asking when Webfuse would be sold or made available to other institutions. The ability and adoption of Webfuse as a product by other institutions was seen as a way for proving its success. This was based on the assumption that Webfuse, like all software, was a product that could be reused regardless of the organisational context. This was also the assumption that underpinned the development of Webfuse during the first phase of its development (1996 though 1999). One example of this is the observation that Webfuse was made available as an open source project for people to download in 1997.

A key characteristic of the second phase of Webfuse development was the recognition that the product and its features was not as important as how well its features matched the needs of the local context and continued to evolve in response to those needs. The most important part of Webfuse was the process, not the product. It was through this process of contextual adaptation that Webfuse became part of the way things were done at CQU, it became part of the culture. This tight connection with the institution meant that while the principles behind Webfuse and some of the applications might be useful at other institution, it was impossible to distribute Webfuse as software product. An understanding of this distinction improved the implementation of Webfuse. However, an inability to explain the importance of this distinction to various stakeholders contributed to the eventual demise of Webfuse and especially its ateleological process.

The importance of the pedagogue

Coates et al (2005) suggests that a recurrent message from educational technology research is that “it is not the provision of features but their uptake and use that really determines their educational value”. This message matches well with the experience of Webfuse. During the initial phase of Webfuse development described in Chapter 4, the provision of features in terms of various page types was not sufficient to generate use by academic staff and consequently any impact in terms of educational value. If the teaching staff responsible for a course did not use the provided features, or did not integrate them effectively into a course, there was no educational value. The pedagogue was of central importance in terms of any educational value arising from e-learning. It was through understanding and using this principle that Webfuse was able to become and everyday part of the practice of teaching academics.

Change takes time, familiarity, need, support, and adaptation

Many, if not all, teaching staff did not make decisions to adopt new educational practices and technologies immediately upon their release. Such adoption decisions occurred over varying periods of time as a result of a combination of individual contextual factors. Effective use of novel practices and technologies often lagged adoption by a number of years. The introduction of novel practices into an organisation generated a need for changes in organisational practices and support in order to become widely adopted and appropriately used. For example, the use of the course barometer feature was highest and most appropriate in 2002 and 2008 (see Figure 5.12) when use was encouraged and supported by organisational resources. In addition, as novel features become more widely used, there is a need to adapt those features to the requirements in response to lessons learned and changing requirements.

Helping people increases trust and knowledge

From 2000 onwards the Webfuse development staff also fulfilled the roles of system trainers and frontline helpdesk staff. Each of these roles are inherently challenging and attempting to balance the competing demands of each role adds further to the complexity. However, there were also a number of significant benefits that arose from this multi-skilling. These benefits included:

  • Helpdesk staff with increased knowledge of the systems;
    The helpdesk staff handling user problems had deep understandings of how the systems worked, what they could do, and how they could be manipulated. This deep level of knowledge enabled quicker and more flexible responses to problems.
  • Increased ability for rapid changes; and
    In some cases, those flexible responses involved quick modification of the Webfuse code to correct a problem or add a new feature. Such minor problems did not have to rise through a helpdesk escalation process before being remedied.
  • Developers with increased knowledge of the needs and capabilities of the users.
    The offering of helpdesk support and training sessions provided a deeper understanding of the capabilities and needs of both staff and student users that could drive the on-going design and development of Webfuse.

Each of these benefits combined to increase trust in the system and its direction, as evidenced by the increased use shown above and the following quote from a member of academic staff

my positive experience with other Infocom systems gives me confidence that OASIS would be no different. The systems team have a very good track record that inspires confidence

You can’t keep all the people happy

The experience with Webfuse from 2000 through 2009 has highlighted just how difficult answering the question – “Was Webfuse a success?” – actually is and how dependent it is upon the experiences and position of the person answering the question. In terms of success, it is possible to point to the statistics showing much higher levels of usage by staff and students. It is also possible to point qualitative comments from staff around trust and confidence and to formal management reports describing Webfuse as “[t]he best thing about teaching and learning in this faculty in 2003”. At the same time, it’s possible to point to consistent arguments from central IT staff that Webfuse was a shadow system that duplicated existing systems and was subsequently inefficient and wasteful (Jones, Behrens et al. 2004). There were also comments from one senior member of staff in 2004 suggesting that Webfuse had made no significant difference to learning and teaching at CQU.

Ateleological processes don’t fit in a teleological environment

Webfuse experienced its greatest levels of support and improvement during the period from 2000 through 2004. During these years the Faculty of Informatics and Communication (Infocom) – which supported Webfuse – was undergoing significant growth in student numbers, complexity, and available resources. At the same time, Infocom had a Dean who had publicly expressed support (Marshall 2001) for a more ateleological approach to organisational and systems development, and was comfortable with that approach within Infocom.

From 2004 onwards there were a number of changes within CQU, including: (1) changes in faculty and institutional leadership; (2) changes in student enrolment profile raising concerns about faculty and institutional funding; and, (3) an organisational restructure resulting in increased centralisation and/or out-sourcing of services. These changes led the institution toward a much more teleological approach to systems development and support. Under these conditions the ateleological Webfuse process was seen as wasteful of resources and, to some extent, nonsensical.


Coates, H., R. James, et al. (2005). "A Critical Examination of the Effects of Learning Management Systems on University Teaching and Learning." Tertiary Education and Management 11(1): 19-36.

Jones, D., S. Behrens, et al. (2004). The rise and fall of a shadow system: Lessons for enterprise system implementation. Managing New Wave Information Systems: Enterprise, Government and Society, Proceedings of the 15th Australasian Conference on Information Systems, Hobart, Tasmania.

Marshall, S. (2001). Faculty level strategies in response to globalisation. 12th Annual International Conference of the Australian Association for Institutional Research. Rockhampton, QLD, Australia.

Learning with an open course – a case study?

It seems the open educational resources and open courses are one of the next big fads. I realise that they’ve been around for a long time. There is the formalisation of open courses arising out of the MIT and similar projects leading to the OCW consortium and more recently there’s been idea of a MOOC idea arising from work by Seimens, Cormier, Downes and others. Even before all that there were various ad hoc examples of open courses (of different types) made available through the work of various “lone rangers”. The fad cycle around OER/OCW has been in an upswing for a while, lots of formal institutional interest and increasingly there are grants being awarded. In fact, it appears that including OER/OCW in a grant title seems to be a good thing at the moment. Sure sign of a fad?

Personal aside

I was one of those lone rangers way back in the mid-1990s with the courses in systems administration and operating systems I designed and taught at CQU. The websites for these courses were open to everyone. As part of that openness, I made archives of the Systems Administration course available for download and was happy for folk to put up mirrors of the site. An interesting side effect of this practice is that while I can no longer find any record of those course sites on institutional servers, I can find the mirrors of the courses elsewhere. Sadly though, most of the links seem to be broken and pointing to the wrong place. Well that was a copy of the course site from 2000. In trying to find a better mirror I came across this nice comment. You can still find the study guide/book from the course online.

Eat your own dog food

I’m always skeptical of “movements” when the fad cycle has kicked in an institutions start making them part of their “strategic” plans. So, I’ve been wondering how good some of the institutional open courses are and whether there might be some insight gained from using one of the courses as a basis for learning. In my case, it’s a bit of eating your own dog food. As someone who pushes for courses to be open, perhaps I should try them more as a student.

Now I have started (but not completed) some of the Downes/Siemens MOOCs and will probably try and connect with their next one around PLEs/PLNs. In this case, I’m more interested in the open courses that are probably better termed open content. e.g. the MIT courses where the content is available, but there really is no instructor or cohort doing the course with you. What’s it like working through one of those courses on your own?

I’ve been pondering this for a while, then last weekend, I came across this course on “Empirical Research Methods” from CMU. It just so happens that this is one of my weaknesses. So, working through this course seems a good way to kill two birds with one stone.

Once the thesis is more complete, I plan to work through this course and use the blog to reflect on the experience and what I experience and what learn.

How people learn and implications for academic development

While I’m traveling this week I am reading How people learn. This is a fairly well known book that arose out of a US National Academy of Science project to look at recent insights from research about how people learn and then generate insights for teaching. I’ll be reading it through the lens of my thesis and some broader thinking about “academic development” (one of the terms applied to trying to help improve the teaching and learning of university).

Increasingly, I’ve been thinking that the “academic development” is essentially “teaching the teacher”, though it would be better phrased as creating an environment in which the academics can learn how to be better at enabling student learning. Hand in hand with this thought is the observation and increasing worry that much of what passes for academic development and management action around improving learning and teaching is not conducive to creating this learning environment. The aim of reading this book is to think about ways which this situation might be improved.

The last part of this summary of the first chapter connects with the point I’m trying to make about academic development within universities.

(As it turns out I only read the first chapter while traveling, remaining chapters come now).

Key findings for learning

The first chapter of the book provides three key (but not exhaustive) findings about learning:

  1. Learners arrive with their own preconceptions about how the world exists.
    As part of this, if the early stages of learning does not engage with the learner’s understanding of the world, then the learner will either not get it, or will get it enough to pass the test, but then revert to their existing understanding.
  2. Competence in a field of inquiry arises from three building blocks
    1. a deep foundation of factual knowledge;
    2. understand these facts and ideas within a conceptual framework;
    3. organise knowledge in ways that enable retrieval and application.

    A primary idea here is that experts aren’t “smart” people. But they do have conceptual frameworks that help apply/understand much quicker than others

  3. An approach to teaching that enables students to implement meta-cognitive strategies can help them take control of their learning and monitor their progress.
    Meta-cognitive strategies aren’t context or subject independent.

Implications for teaching

The suggestion is that the above findings around learning have significant implications for teaching, these are:

  1. Teachers have to draw out and work with pre-existing student understandings.
    This implies lots more formative assessment that focuses on demonstrating understanding.
  2. In teaching a subject area, important concepts must be taught in-depth.
    The superficial coverage of concepts (to fit it all in) needs to be avoided, with more of a focus on the those important subject concepts.
  3. The teaching of meta-cognitive skills needs to be integrated into the curriculum of a variety of subjects.

Four attributes of learning environments

A latter chapter expands on a framework to design and evaluate learning environments, it includes four interrelated attributes of these environments:

  1. They must be learner centered;
    i.e. a focus on the understandings and progress of individual students.
  2. The environment should be knowledge centered with attention given to what is taught, why it is taught and what competence or mastery looks like
    Suggests too many curricula fail to support learning because the knowledge is disconnected, assessment encourages memorisation rather than learning. A knowledge-centered environment “provides the necessary depth of study, assessing student understanding rather than factual memory and incorporates the teaching of meta-cognitive strategies”.

    There’s an interesting point here about engagement, that I’ll save for another time.

  3. Formative assessments
    The aim is for assessments that help both students and teachers monitor progress.
  4. Develop norms within the course, and connection with the outside world, that support core learning values.
    i.e. pay attention to activities, assessments etc within the course that promote collaboration and camaraderie.

Application to professional learning

In the final section of the chapter, the authors state that these principles apply equally well to adults as they do to children. They explain that

This point is particularly important because incorporating the principles in this volume into educational practice will require a good deal of adult learning.

i.e. if you want to improve learning and teaching within a university based on these principles, then the teaching staff will have to undergo a fair bit of learning. This is very troubling because the authors argue that “approaches to teaching adults consistently violate principles for optimizing learning”. In particular, they suggest that professional development programs for teachers frequently:

  • Are not learner centered.
    Rather than ask what help is required, teachers are expected to attend pre-arranged workshops.
  • Are not knowledge centered.
    i.e. these workshops introduce the principles of a new technique with little time spent to the more complex integration of the new technique with the other “knowledge” (e.g. the TPACK framework) associated with the course
  • Are not assessment centered.
    i.e. when learning these new techniques, the “learners” (teaching staff) aren’t given opportunities to try this out, get feedback and even to give teachers the skills to know whether or not they’ve implemented the new technique effectively.
  • Are not community centered.
    Professional development consists more of ad hoc, separate events with little opportunity for a community of teachers to develop connections for on-going support.

Here’s a challenge. Is there any university out there were academic development doesn’t suffer from these flaws? How has that been judged?

Analysing the business model for higher education and why they can’t

Am somewhat torn between the logic of this sort of approach to applying insights from broader business practice to higher education, and a slight shudder at the history of misuse that exists as folk mindlessly adapt business practices to higher education. Mindless, ill-informed, or perhaps simply naive adoption of techno-rational management approaches such as top-down, “strategic” thinking and aspects of quality management are amongst the biggest problems for higher education at the moment.

Not to mention that these techno-rational approaches (and their mindless application) are probably the biggest barrier to the type of critical analysis Tim Kastelle is recommending. The teleological nature of these approaches seeks to excise all innovation and difference in the pursuit of the strategic goal and the efficient means of achieving it. Consequently, such organisations don’t have the capacity to perform the analysis, let alone take action to implement/investigate any effective alternatives.

To a large extent, this is the problem facing large media companies. Especially those that are led by “dear leaders”. Actually, just finished a guilty escape of a book which has Prince Harry offering the following opinion

They weren’t thinking at all, Viv. That’s the problem with leadership cults. They’re red hot on getting sh*t done, once the big man has spoken, but not so good at weighing up whether that sh*t should have been done in the first place.

There’s another comment in the post about moving from a gatekeeping to a curating role in the entertainment industry. I know George Siemens and others have been suggesting that a curating role for a teacher is a useful way of moving forward.

I am wondering how that fits with an analysis of the business model of universities? Would it make sense? How would it happen?

Amplify’d from

This is why it is so critical to analyse your business model now, so that you understand why it works (or doesn’t), and so you know which parts are essential, and which can be changed more easily.



PhD Update #27 – New context

It’s been over 4 months since my last PhD update, past time to get back into the discipline. A lot has happened in those 4 months, the grant talked about in the last post didn’t get off the ground thanks to folk leaving positions at the potential partner institution and then because I left mine. So, the new context is that I’m currently a man of leisure, thanks to a separation payout, and increasingly focused on finally finishing the thesis.

What I did last week

In the last week I have:

  • Almost completed the evaluation section for chapter 5;
    This involved a lot of data munging and then “re-munging”. Not quite complete, but very close.
  • Completed a first draft of chapter 6;
    This is the final chapter. The rough draft is intended to get the structure and content right without aiming for smooth prose. It’s been sent to the thesis supervisor for some feedback.
  • Completed an almost final draft of chapter 1;
    Much of this had been done, however, some bits were left open until latter chapters had been completed. I also had to make some tweaks based on feedback. In a couple of days, I’ll re-read this on paper, double check alignment with other chapters and starting shopping it around to other people to read.

What will I do next week

Next week will be interesting. I’m traveling for 3 days, so, may not be able to achieve all of the following, but the aim will be to move towards :

  • Completing the evaluation section of chapter 5;
  • Completing the Lessons section of chapter 5;
  • Taking some initial steps for formalising the final ISDT;
  • Start sending a final draft of chapter 1 around to folk for reading.

Situated/distributed cognition and e-learning

This quote summarises very nicely what I think will become a major research interest of mine in the future. i.e. how can we modify the environment – particularly, but not primarily, through information technology – within universities to encourage and enable improvements in teaching and learning?

I have a feeling/belief that heavyweight/top-down approaches to improving teaching (e.g. requiring all staff to have a formal teaching qualification, or specifying minimum standards of performance) simply don’t work, at least not if you closely examine the cost/benefit ratio of these approaches.

Instead, I am interested in the tools and representations that can be built into the higher education teaching environment to improve situated/distributed cognition and subsequently improve teaching.

Once the thesis is finished, I’m hoping to have the time to look more closely at this. Any suggestions on where to start reading?

This recognition that our processing uses external representations is an important component in looking at ways to support performance. When should we provide tools, whether representational or computational, instead of trying to put all information in the head? We need a richer picture of how we perform, rather than a simplistic and ineffectual model that posits we can know everything we need.



Background to the thesis

It seems like I’m in the downhill stretch with the thesis. Almost all the new material has been written, am just waiting on some feedback from my esteemed supervisor before completing the last new section (it follows the same structure as a previous section, hence the importance of feedback). So, while I’m waiting on that feedback, I’m starting the revision of the draft chapters. The following is a re-working of the first main section of chapter 1 and provides the background to the research.

Background to the research

Advanced industrial societies are currently undergoing a fundamental transformation from capital- and labour-based economies into knowledge economies (Burton-Jones 2001). In such economies knowledge, education, people and their ideas, become the key strategic resource necessary for prosperity (Duderstadt, Atkins et al. 2002). This transition to a knowledge economy is characterised by factors including globalization, increasing competition, knowledge sharing and transfer, and an information technology revolution (Zhang and Nunamaker 2003). This transition raises a number of issues for education systems, in particular how best to adapt such systems to the changes in the socio-economic landscape and provide the best educational opportunities and outcomes (Knight, Knight et al. 2006).

Schools and universities will play increasingly important roles as society enters this new age of knowledge as society becomes increasingly dependent upon the social institutions that create knowledge and educate people (Duderstadt, Atkins et al. 2002). Some believe that the university will be the central institution in post-industrial society (Bok 1990). A 2002 survey of 30 OECD countries indicated that more people than ever are completing tertiary education and that 1.9% of the combined GDP of these countries was devoted to higher education (OECD 2005). A report comparing education between the G8 countries show those countries spending between 1% and 2.7% of GDP on higher education during the year 2000 (Sen, Partelow et al. 2005).

Universities, however, are one of a very few institutions that have maintained their existence since the 1500s (Kerr 1994). The pre-dominant model of the University is still the traditional combination of teaching and academic research suggested by Wilhelm von Humboldt in the 19th century (Tsichritzis 1999). These observations are often attributed to the ability of universities to be resistant to change (Green and Hayward 1997). The nature of e-learning, to some extent, conflicts with the academic culture based on autonomy and a reward system based on research (OECD 2005). Yet, the growth of e-learning has been incremental and has not fundamentally challenged the face-to-face classroom (OECD 2005).

The emergence of the knowledge economy and the increasing influence of technology are not the only factors driving change within higher education. Indeed the last 30 years has seen a period of unprecedented change as higher education institutions across the world as they are being shaped by similar problems and forces (Green and Hayward 1997). These forces include: increased access and growth in participation, reduction in public funding, increased costs, increased calls for accountability in outcomes and subsequent arguments around autonomy, the changing nature and growth of knowledge and disciplines, industrialisation and industrial relations policy, and internationalisation (Green and Hayward 1997; Coaldrake and Stedman 1999; Cunningham, Ryan et al. 2000). The uncertainty about the future generated by these changes highlights the importance of building institutions that are responsive to change. (CRHEFP 1997). It is the institutions that are able to continually adapt to these changes that will be successful (Huynh, Umesh et al. 2003) and survive (Klor de Alva 2000).

The increasing importance and impact of information and communication technologies (ICTS) is seen as one of the major drivers for this need for adaptability. Zhang et al (2004) observe that the knowledge economy shows a pervasive and ever-increasing demand for innovative delivery of education, which has led to dramatic changes in learning technology and organizations The new technological possibilities and the new learning environments they enable are contributing to an unavoidable pressure for change (Tsichritzis 1999). The advancement of computer and networking technologies are providing a diverse means to support learning in a more personalised, flexible, portable and on-demand manner (Zhang, Zhao et al. 2004). These new technologies have become a major force for change in higher education institutions that will potentially have a profound effect on the structure of higher education (Green and Hayward 1997). Some suggest that the rapidly evolving technology and emerging competition puts the very survival of the current form of the university at risk (Duderstadt, Atkins et al. 2002). For example, Peter Drucker suggests, “Thirty years from now the big university campuses will be relics. Universities won’t survive. It is as large a change as when we first got the printed book” (Lenzer and Johnson 1997). Unlike previous periods of technology-driven social change the impact of information technology affects the basic activities of a university: creating, preserving, integrating, transmitting and applying knowledge, and more fundamentally changing the relationship between people and knowledge (Duderstadt, Atkins et al. 2002).

The use of ICTs in learning has a history going back at least 30 years and has been characterized by a variety of names including: computer-mediated communication (CMC), computer conferencing, computer-based training (CBT), computer-aided learning (CAL), computer-managed learning (CML), distributed learning, electronically enabled learning, online learning, web-based education, Internet-based learning, telematics and e-learning (McCormack and Jones 1997). The use of different terminologies and often different definitions for the same term makes it difficult to develop a generic definition (Ally 2004). This thesis adopts the definition provided by the OECD (2005) where e-learning is defined as “the use of information and communications technology to enhance and/or support learning in tertiary education”. In this definition, e-learning is expanded to include support for any and all tasks required to encourage and support efficient and effective teaching and learning (Jones and Gregor 2004).

The importance of e-learning in contemporary universities cannot be denied (deFreitas and Oliver 2005). Allen and Seaman (2004) report on estimates that by October, 2004 over 2.6 million students will be studying online courses at US-based universities and that over 50% of institutions agree that online education is critical to their long-term strategy. The questions about e-learning have moved from a focus on use versus non-use to how, why and with what outcomes (Hitt and Hartman 2002).

Most universities are currently answering the “how to implement e-learning” question through the adoption of a Learning Management System (LMS). These systems are also known as Course Management Systems (CMS) and Virtual Learning Environments (VLE). Learning Management Systems (LMSs) are software systems that are specifically designed and marketed to educational institutions to support teaching and learning and that generally provide tools for communication, student assessment, presentation of study material and organisation of student activities (Luck, Jones et al. 2004). There is, however, evidence to suggest that this strategy is not particularly innovative, is limited in quality and ability to integrate with other systems (Alexander 2001; Paulsen 2002). Even the most advanced institutions report little more than 50% adoption by faculty (Sausner 2005). With some exceptions universities have not employed technology to the same degree or as effectively as the business community (Piccoli, Ahmad et al. 2000). Successful implementation of LMSs in an academic environment is rather rare (Sarker and Nicholson 2005). Early adoption of e-learning by Australian universities during the 1990s was done without critical examination of the merits and led to cases of wasted resources, unfulfilled expectations, and program and organizational failure (Pratt 2005). There is considerable evidence that e-learning within universities struggles to engage a significant percentage of students and staff, and has limited success in moving development beyond projects by innovators (Salmon 2005). Van der Klink and Hochems (2004) suggest that high-level ambitions with poor implementation is the best description for most institutions in terms of e-learning implementation.

It is not all that surprising that difficulties exist in the implementation of e-learning within universities. The application of information technology within universities is highly complex, confusing and raises issues that are almost over-whelming in nature (Duderstadt, Atkins et al. 2002). E-learning remains a novel and immature activity (OECD 2005). The transformation promised, or threatened, by e-learning is in reality a very fundamental transformation process, driven by technology but involving people, organizations, and cultures that must be addressed both systemically and ecologically (Duderstadt, Atkins et al. 2002). Scholars in Information Systems can offer vision on structures and processes to effectively implement technology-mediated learning initiatives (Alavi and Leidner 2001). Keller (2005) agrees that perspectives from information systems research and organisation theory can help better understand the implementation of e-learning. Salmon (2005) has called for more research to develop theories, principles, and methodologies of change related to the sustainability of e-learning within universities.


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