Assembling the heterogeneous elements for (digital) learning

Month: December 2019

Is training the barrier to quality online learning in higher ed?


Recently there have been various suggestions that the biggest barrier to quality online learning in higher education is lack of knowledge held by teaching staff (Johnson, 2019; Mathes, 2019; Roberts, 2018). More or better training, faculty development and requirements for formal teaching qualifications are proposed as the solution.

The following argues that this is just a symptom of the real barrier. i.e. that Universities actually don’t know how to implement quality online learning. Specific evidence drawn from one of the clarion calls for more training/formal qualifications is offered. A pointer to possible solutions to the actual barrier is provided.

Note: I started writing this in late November. A week before ASCILITE’2019. Just finishing it now.


The following is sparked by personal experience (bias?) and a post on OLDaily from Stephen Downes titled More needs to be done to support teaching online in Canada. Downes’ post reports on results from a research report (Johnson, 2019) surveying Canadian, publicly funded, post-secondary institutions and reactions from Tony Bates and Clint Lalonde. Downes wonders how, after 25+ years of online learning, 79% of institutions surveyed can report that a major barrier to online learning is inadequate training for faculty? Lalonde finds “this number staggering, and a sobering wake up call”. And its not just Canada. This topic echoes the findings from a 2019 ICDE report (Mathes, 2019) that was also featured on OLDaily. That report – Global quality in online, open, flexible and technology enhanced education: An analysis of strengths, weaknesses, opportunities and threats – draw on interviews with senior leaders from ICDE member institutions from across the world from which three themes emerged. Theme #2 was professional development

Appropriate training is not always available to build the expertise and skills of faculty and staff responsible for developing and/or teaching courses in these modalities. This can result in a poor teaching experience for faculty and a poor learning environment for students. (Mathes, 2019, p. 10)

Lalonde isn’t certain why there is this apparent “massive skills gap among instructors to teach online”. Downes suggests that higher education’s problem isn’t a training problem, but a culture problem. He wonders “about the apparent inability or unwillingness of today’s professors to teach themselves how to use a computer to teach”. Bates identifies the lack of willingness amongst institutions to “make training in teaching mandatory” as a major contributor and suggests (in another post) Should all lecturers have to have a teaching certificate? Why the answer is a resounding ‘yes’. Lalonde wonders if institutional focus on training for online has become less of a priority as a feeling of “been there done that” is combined with more attention being paid to broader issues such as accessibility, inclusiveness etc. He then picks up on Bates’ formal certification solution, but expands it to include not just online learning, but any learning modality.

Is training really the barrier?

The image below is from an ASCILITE’2019 presentation I’m working on for next week (slides, paper and source code available from here). The image is from a Blackboard course site. It is not a site for a real course. However, each design decision present in this “course site” is inspired by a practice from an actual course site that was developed by someone with a formal teaching qualification. In some cases, they had more than one formal teaching qualification. Since it’s for a presentation, this example focused on limitations that were visual. A similar example could be generated focusing on design for learning.

The point is that these practices were taken from courses developed by people with formal teaching qualifications. Exactly the solution being suggested. Given we are now 20+ years into the digital/online learning revolution, this seems to suggest that more training and formal qualifications in (online) learning are not likely to help improve the quality of online learning. Suggesting that the barrier is not (just) a lack of training.

What might be the barrier?

To answer this question, the following digs a bit deeper into the report from the Canadian Digital Learning Research Association. It reveals a few more possible barriers, but each really appear to be symptoms – just like the need for more faculty training – of the real barrier to quality online learning and teaching.

An absence of strategic planning?

The following is graph won’t be found in the report, but it is drawn from data presented in the report.

It shows that 94% of the institutions responding to the survey identified online learning as being of strategic importance of the institution. A variety of reasons is given. Growing continuing/professional education, increasing student access, and attracting students from outside traditional catchment areas are reported as the most important.

However, the graph also shows that only 12% of the institutions responding to the survey had a fully implemented plan for online learning!!!!! 59% reported being in the process of developing a plan with 26% reporting that they don’t have one, but really should develop one.

Might this not create some issues? How is this the case after 25+ years of online learning?

The free text from one institution suggests the potential source of problems that this absence might create

By creating a strategy, we are hoping to provide a frame for blended learning at our institute that will help guide processes, policies, and systems that align. At a course level, we are creating more supports for instructors to create their own digital learning objects for curriculum.

In a organisation espousing a strategic management approach the absence of strategic plans creates problems all the way down.


It was interesting to note that training was NOT “the most significant barrier to the adoption of online learning” (p. 40) from institutions responding to the survey. The following graph shows the top two responses from responding institutions to the barreirs to online education (from both the 2018 and 2019 surveys)

Much of the discussion mentions the need for more support for teaching staff, but most of the discussion appears to have focused on the training. Rather than pondering if the absence of appropriate supports might be exacerbating the training problem. i.e. more training is being called for because the systems and supports currently available to teaching staff are insufficient and inappropriate for the task being asked.

The focus on the new shiny thing

Based on the responses so far, it appears that many institutions recognise the strategic importance of online learning, know they don’t have a plan, and are aware that there are significant barriers in terms of workload and preparation for our teaching staff. So, obviously institutions are focused on taking action to address these problems, right?

From the report

institutions are experimenting with different delivery methods to better meet the needs of students. A variety of strategies are being employed: new technologies, OER, blended/hybrid learning, and alternative credentials. (p. 54)

Oh dear.

The need for careful implementation

To break the iron triangle of access, cost and quality Ryan et al (2019) propose the following “practical and pedagogical techniques”

  • High-quality large group teaching and learning;
  • Alternative curriculum structures;
  • Automation of assessment and feedback;
  • Personalising feedback at scale;
  • Peer-based learning; and,
  • Offloading administrative and technical support.

Arguably, each of these are shiny new things. The last suggestion includes one of the recent “poster boy” shiny new things – teacher bots. But the authors recognise the problem of shiny new things (arguably) with the recognition that the shiny new things “are surely part of the solution, they are by no means the entire solution”. The understand that it is important that shiny new things are

…implemented carefully and with a clear purpose…(and)…used to support good teachers, teaching practice and learning and assessment designs

As established above, it appears that many of the responders to the survey haven’t gotten there just yet. The question is whether they ever will. After all, we are 25+ years into this online learning fad.

The biggest barrier to quality online learning is actually…

Western universities don’t know how to do online learning

The real barrier to quality online learning and teaching in higher education is that they don’t know how to do this. Universities are good at the shiny new thing, but not so much at figuring out how the shiny new thing can be “implemented carefully and with a clear purpose…(and)…used to support good teachers, teaching practice and learning and assessment designs”. In the last pages of their book Ellis and Goodyear (2019) describe it this way

Over recent decades, Western universities have been very good at picking up and reproducing modish language about their purposes and methods – engaged enquiry, T-shaped graduates, being and becoming, and so on. They have been less good at ‘tooling up’ to deal with the complexity of analysing how their educational ecosystems actually function and of systematically redesigning for sustainable improvement. (p. 242)

For me, the lack of training for teaching staff is just a symptom of this broader problem. Universities are full of good people with a lot of knowledge about aspects (e.g. technical, pedagogical, content etc) of the challenge of online learning. But they are (and have been for some time) operating within organisations underpinned by a mindset that actively prevents those people from working effectively together to achieve “careful implementation”.

The fact that we are 25+ years into this online learning thing and its possible to make observations like the above seems to provide some support for this perspective.

What’s the solution?

That’s the (significantly more than) $64K question. More training, better (or even some) strategic plans, more project managers, and more shiny new things won’t provide a solution.

Ellis and Goodyear (Ellis & Goodyear, 2019) offer a research-based book that offers both diagnosis and remedy. The (second) best top-level answer to the question I’ve seen so far.

The work I describe in this year’s ASCILITE paper/presentation describes one meso-level practitioners attempt at a possible solution derived by combining some of ideas from Ellis and Goodyear (2019) with some other ideas.

Though whether these theoretical answers are good answers is waiting further work.


Ellis, R. A., & Goodyear, P. (2019). The Education Ecology of Universities: Integrating Learning, Strategy and the Academy. Routledge.

Johnson, N. (2019). National Survey of Online and Digital Learning 2019 National Report (p. 67). Retrieved from Canadian Digital Learning Research Association website:

Mathes, J. (2019). Global quality in online, open, flexible and technology enhanced education: An analysis of strengths, weaknesses, opportunities and threats. Retrieved from International Council for Open and Distance Education website:

Roberts, J. (2018). Future and changing roles of staff in distance education: A study to identify training and professional development needs. Distance Education, 39(1), 37–53.

Ryan, T., French, S., & Kennedy, G. (2019). Beyond the Iron Triangle: Improving the quality of teaching and learning at scale. Studies in Higher Education, 0(0), 1–12.


Theory of workarounds


The following is a summary of the paper Theory of Workarounds.

Alter, S. (2014). Theory of Workarounds. Communications of the Association for Information Systems, 34(1).

The paper provides “an integrated theory of workarounds that describes how and why” they are created. It is a process theory “driven by the interaction of key factors that determine whether possible workarounds are considerd and how they are executed” and is seen as useful for

  • classifying workarounds and analysing how they occur;
  • understanding compliance and noncompliance to management mandates;
  • figuring how to consider possible workarounds as part of systems development;
  • studying how workarounds may lead to larger planned changes.

My interest – digital learning and teaching

I’m interested in workarounds as a way to better understanding what’s happening around higher education’s use of digital technology to support learning and teaching, and identifying ways to improve it.

Definition and theory of workarounds

Alter (2014) offers the following definition of workarounds

A workaround is a goal-driven adaptation, improvisation, or other change to one or more aspects of an existing work system in order to overcome, bypass, or minimize the impact of obstacles, exceptions, anomalies, mishaps, established practices, management expectations, or structural constraints that are perceived as preventing that work system or its participants from achieving a desired level of efficiency, effectiveness, or other organizational or personal goals. (p. 1044)Comparisons between this and related definitions suggest this is a broader definition, including additional factors such as

  • workarounds don’t need to use digital technology;
  • workarounds may include work not formally recognised by the organisation;
  • workarounds don’t always compensate for or bypass system deficiencies;
  • workarounds may not be temporary;
  • workarounds are not necessarily examples of noncompliance;

Alter’s (2014) definition of workarounds does rely on it occuring within a work system. Another theoretical concept developed by Alter (2002). See this section from an old paper of mine for a summary of the Work System Framework.

It is argued that this reliance on the work system framework provides a “broader and more comprehensive view of the changes that can be included in workarounds” (Alter, 2014, p. 1046)

Figure 1 is a representation of Alter’s (2014) theory of workarounds. It is positioned as a process theory that describes how and why workarounds are created. A brief description follows the figure.

Alter’s theory of workarounds draws on a number of theories and concepts, including:

  • Theory of planned behaviour;
  • Improvisation and bricolage;
  • Agency theory;
  • Work system theory

Figure 1 – Alter’s (2014) Theory of Workarounds (p. 1056)

Workarounds arise from a context that includes each work system participant’s personal goals, interests and values. Communication and sharing of these goals/values between participants may be flaws or incomplete leading to misalignment in the work system. It also includes the structure of the work system that includes architecture, characteristics, performance goals and also emergent change.

From this context arises the perceived need for a work around.

Which triggers a process of trying to identify possible workarounds. Often starting with the obstacles in the current situation and the perceived need combined with consideration of the costs, benefits, risks of being identifed, and possible ramifications. An essential component is the knowledge available to those involved.

Eventually this leads to a decision to select a workaround to pursue, if any.

If going ahead, then development and execution of the workaround is driven by factors such as attention to current conditions, intuition guiding action, testing of intuitive understanding, and situational decision making.

Subsequently, there are local consequences and broader consequences. Locally, may lead to elimination of the obstacles that initiated the process, but may also include failure of the workaround or various unintendended consquences. More broadly, these types of consquences might be felt or pushed into other locations.

Temporality of workarounds

Alter also makes a point of outlining the temporality of workarounds as outlined in Figure 2.

Figure 2: Temporality of Workarounds (adapted from Alter, 2014, p. 1058)

Five voices in the workarounds literature

Alter performed a literature review on the workarounds literature. He gather 289 papers and used that to derive his theory. He summarises that work by using five “voices” which in turn include topics, including:

Phenomena associated with workarounds;

  • Obstacles, exceptions, anomalies, mishaps and structural constraints
  • Agency
  • Improvisation and bricolage
  • Routines, processes and methods
  • Articulation work and loose coupling
  • Technology misfits
  • Design and emergence
  • Technology usage and adaptation
  • Motives and control systems
  • Knowledge
  • Temporality

Types of workarounds;

  • Overcome inadequate IT functionality
  • Bypass an obstacle built into processes or practices
  • Respond to a mishap or anomaly with a quick fix
  • Substitute for unavailable resources
  • Design and implement new resources
  • Prevent future mishaps
  • Pretent to comply
  • Lie, cheat, steal for personal benefit
  • Colluse for mutual benefit

direct effects of workarounds;

  • Continuation of work despite obstacles, mishaps or anomalies
  • Creation of hazards, inefficiencies or errors
  • Impact on subsequent activities
  • Compliance or non-compliance with management intentions

perspectives on workarounds; and,

  • Workarounds as necessary activities in everyday life
  • Workarounds as sources for future improvements
  • Workarounds as creative acts
  • Workarounds as add-ons or shadow systems
  • Workarounds as quick fixes that won’t go away
  • Workarounds as facades of compliance
  • Workarounds as inefficiencies of hazards
  • Workarounds as resistance
  • Workarounds as distortions or subterfuge

organisational challenges and dilemmas related to workarounds.

  • Ability to operate despite obstacles
  • Enactment of interpretive flexibility
  • Balance of personal, group and organisational interests
  • Permitting and learning from emergent change

He uses these 5 voices then to group and establish some sense of causality within the “breadth of ideas and examples that were found in the literature” (p. 1047).

Usefulness and Further research

Since the theory is developed based on a literature search, it is limited by anything that hasn’t made it into the literature. e.g. accounts of workarounds that were considered, but never attempted.

Each step in the process theory could inform survey and/or case study research to explore how well the theory maps onto reality and lead to discoveries of factors/relationships not currently in the theory.

The workaround literature identifies fundamental limtiations in assumptions underpinning traditional approaches to organisational and system analysis and design (e.g. that prescribed business processes will be followed consistently). Theory of workarounds can be used to analyse systems in organisations, reveal conditions that lead to workarounds, provide opportunities to incorproate learning from workaround into emergent/planned change. Helping reveal insights into whether or not intended methods are followed; how systems in organisations evolve over time, how implementation evolves over time..

Starting from alternate theoretical foundations (e.g. Actor Network Theory, activity theory, socio-materiality etc) might lead to different outcomes and insights.

The conceptualisation of e-learning: Lessons and implications

The following is the content of my first solo journal article.

Jones, D. (2004). The conceptualisation of e-learning: Lessons and implications. Best Practice in University Learning and Teaching: Learning from Our Challenges.  Theme Issue of Studies in Learning, Evaluation, Innovation and Development, 1(1), 47–55.

I’m posting this because: sadly the journal is no more; the only version I had on my blog was the original PDF; this paper is the only public thing I’ve written on Alter’s Work System Framework; and, I wanted to reference that in another post. PDF isn’t accessible hence the HTML version.

Reading your old work is painful and occasionally surprising

As with many people reading my prior work is painful. Not sure I understood the notion of a paragraph. These issues continue into the short Lessons and Implications section but there are some bits that seem to have stood the test of time, including:

  1. Great diversity and continual change is common across the entire e-learning work system.
  2. No one single system can integrate all requirements and existing attempts to do so sacrifice contextual capabilities that contribute to strategic advantage.
  3. The penalty for not catering for future change and diversity…are limiting innovation, transformation and adoption of new approaches.
  4. Some of this is due to simplistic top-down approaches that don’t effectively harness bottom-up potential.
  5. IT has been viewed as fixed, neutral and independent of context rather than as one of a number of components that contribute to an emergent process of change.

The NGDLE link

Strong echoes of Point #2 can be seen in EDUCAUSE’s 2015 proposal of the NGDLE (Brown, Dehoney, & Millichap, 2015) in particular the following quote

although the NGDLE might include a traditional LMS as a component, it will not itself be a single application like the current LMS or other enterprise applications. Rather, the NGDLE will be an ecosystem of sorts

For more on the NGDLE idea, take a look the 2015 responses from Tony Bates and Jon Dron. Both critique the use of Lego as a metaphor for the NGDLE, which resonates strongly with me. As does Dron’s recommendation of glue or Velcro as better analogies. Back in the day, the “LMS” I (and many others) built and maintained was called Webfuse because

Webfuse was positioned as the glue used to “fuse” together widely different services and tools into an integrated whole (Jones, 2012)


The implementation of e-learning within an institution of higher learning can be seen as a design problem. A first step in a design problem is the generation of an appropriate representation of the initial state. The nature of this representation has significant influence over the characteristics and suitability of any solution derived from it. This paper uses the work systems framework to present a shortened conceptualisation of this initial state. This conceptualisation reveals lessons and implications to improve future institutional approaches to e-learning.


There is no question that institutions of higher education will make some use of e- learning1 The questions about e-learning have become how, why and with what outcomes (Hitt & Hartman, 2002). There is evidence that existing answers are not particularly innovative, demonstrate limited quality, tend to limit future possibilities and have a high likelihood of failure (Alexander, 2001; Jones, 2000).

Implementing an e-learning approach is a design problem. Design is the core of all professional training (Simon, 1996). There is growing interest in design research in fields such as management (Boland, 2002), information systems (Hevner, March, Park & Ram, in press) and education (Collective, 2003). Design can be seen as a transformation from some known situation, deemed to be problematic by some interested parties, to a more desirable target state (Jarvinen, 2001).

The formulation of the initial state into an effective representation is crucial to finding an effective design solution (Weber, 2003). Representation has a profound impact on design work (Hevner et al., 2004), particularly on the way in which tasks and problems are conceived (Boland, 2002). How an organisation conceptualises the e-learning problem will significantly influence how it answers the questions of how, why and with what outcomes.

The paper starts by offering an introduction to the work systems framework (Alter, 2002). This framework and the e-learning literature are used to develop a conceptualisation of the existing state facing institutions of higher education adopting e-learning. This conceptualisation is then used to identify lessons and implications that could be used to improve the design of e-learning.

The aim of this paper is not to generate the best and only conceptualisation of the initial e-learning state. Instead it seeks to demonstrate that existing conceptualisations of the e-learning problem are limited, that consequently so are many of the organisational approaches to e-learning and that the work system framework provides a useful approach to generating a deeper understanding.

The work system framework

A work system is a system, not necessarily computer-based, in which human participants perform business processes using information, technologies and other resources to produce products and services for customers (Alter, 2002). The work systems method includes both a static and dynamic view of the work system. This paper focuses on the static view of the e-learning work system.

The static view of a work system, the work system framework, identifies the basic elements for understanding and evaluating a work system and is useful in describing the system, describing possible changes, identifying problems and opportunities and tracing the likely impacts of changes to the system (Alter, 2002). Figure 1 provides a representation of the structure and components of the work system framework. Table 1 offers a brief description of the components.

Figure 1 – The Work System Framework (Alter, 2002)

Table 1: Components of the work system framework




People who perform the work


Created and used by the participants


Tools and techniques

Business processes

Steps used to perform the work

Products and services

Physical objects, intangibles, and services produced


Those who receive direct benefit from the products


Organisational, cultural, competitive, technical and regulatory environment within which work takes place


Resources relied upon but managed from outside the work system


Plans used to achieve the goals

The e-learning work system

The aim here is not to generate the most complete conceptualisation of the initial e- learning state. The aim instead is to introduce the use of the work system framework and to demonstrate how this can help generate a more complex and suitable conceptualisation. It is hoped that future work might lead to the generation of a more complete conceptualisation in both general and institutionally specific forms.

Such conceptualisations, even if targeted at a specific institution, would need to draw upon multiple perspectives in order to approach completeness. Any description authored by an individual cannot hope to achieve completeness.

However, in the generation of the following example conceptualisation, an attempt to include multiple perspectives has been made by drawing on a broad range of literature. While it is recognised that this is still somewhat limited, owing to its reliance on a single author and his knowledge of the literature, it is believed that this is sufficient to achieve the aims of this paper.


Teacher-centred, classroom education is the predominant form of learning within universities (Piccoli, Ahmad & Ives, 2000). Teachers’ conceptions of learning are a major influence on the planning of courses and on the development of teaching strategies (Alexander, 2001). Technology serves whichever goals motivate the people guiding its design and use (Lian, 2000). Teacher customisation of an online course can be vital to self-esteem and commitment (Brown, 1999).

Teaching is increasingly a team-based activity, with great diversity in the backgrounds, perspectives and roles of the team members. Course development with teams can be difficult in cultures with a different emphasis on peer review or entrenched academic hierarchies (Calder, 2000). Team members often have limited understanding or appreciation of the fields represented by other members.


Academics can spend upwards of 90% of their planning and development creating information (Oliver, 1999) as the primary focus of learning. Contemporary views of teaching require information that is authentic, provides multiple perspectives and is not seen as the focus (Oliver, 1999).

Contemporary learning environments should integrate academic and administrative support services directly into the students’ environment (Segrave & Holt, 2003).

Information supporting these services is generated and consumed by people, from different fields, performing different roles and belonging to different parts of the organisation, and this information is stored in a variety of computer- and non- computer-based systems. This diversity leads to problems such as information ownership, version control, limited reuse and many others.


The selection of a Course Management System (CMS), such as WebCT, is a common institutional response to e-learning. The primary use of CMSs tends to be as an administrative tool to facilitate classroom tasks and not as a tool anchored in pedagogy (Morgan, 2003). No CMS supports student critical thinking, generation of knowledge and collaborative teamwork (Bonk & Dennen, 1999). Most CMSs support more or less the same pedagogy (Robson, 1999). CMSs provide little support for usage monitoring and reporting at an institutional level across multiple courses (Morgan, 2003). CMSs alone may not be sufficiently conducive to supporting the design, development and operation required within contemporary learning environments (Segrave & Holt, 2003). CMSs are structured with little capability for customisation (Morgan, 2003).

CMSs are claimed to encapsulate a view of ‘best practice’, as defined by the vendor, that may not match an institution’s interests. The dominance within Australia of a small number of CMSs raises concerns that these systems are becoming embedded in the operational culture of higher education institutions and that uncompetitive pricing structures could evolve (Paulsen, 2002).

A typical university makes use of a large number of software applications, partly because creating a single application to run a complete business is virtually impossible. There is a general lack of integration amongst these systems (Paulsen, 2002). It appears, however, that maximum benefit from e-business is obtained when it is integrated throughout applications within the organisation (Marshall & Gregor, 2002). It is hypothesised that institutions implementing integrated systems will improve their chances of becoming successful, large-scale e-learning providers (Paulsen, 2002).

E-learning technologies are undergoing a continual process of change, presenting an ongoing challenge to management (Huynh, Umesh & Valacich, 2003). Any frozen definition of ‘best’ technology is likely to be temporary (Haywood, 2002). Increasing consumer technological sophistication adds to demand for sustained technological and pedagogical innovations (Huynh et al., 2003).

One view is that technology can help with automation and provide efficiency effects (Sproull & Kiesler, 1991) which may improve existing practices (Hannafin & Kim, 2003). Alternatively, technology is seen as a source of strategic advantage and as an enabler of previously impossible practices (Sproull & Kiesler, 1991) and of significant transformation (Hannafin & Kim, 2003). Managers tend to concentrate on the efficiency effects (Lacity & Hirschheim, 1993; Sproull & Kiesler, 1991).

It is most likely that technology will reinforce the old systems rather than the new paths (Lian, 2000). Educators are likely to use the technology to do things the way they have always been done, but with new and more expensive equipment (Dutton & Loader, 2002). Universities have not, despite many obvious exceptions, employed technology to the same degree or effect as the business community (Piccoli et al., 2000).

Business processes

Universities’ teaching processes include content production, packaging content, credentialing programs, presentation to students, marketing, registration, payment, record keeping and assessment (Marshall & Gregor, 2002). Using e-learning to facilitate routine transactions and services can be critically important both to the efficiency of services and in shaping the choices of students (Dutton & Loader, 2002).

Teaching and learning are two of the most highly personalised processes (Morgan, 2003). Academics, as knowledge workers, have considerable autonomy about how they perform tasks (Jones, Gregor & Lynch, 2003), a fact that encourages diversity. Many universities seem reluctant to cease using learning processes that predate the information revolution by centuries (Piccoli et al., 2000). Increasing commercialisation in higher education is leading to certain processes being enshrined in business contracts.

Products and services

The teaching products of a university include diverse products such as career counselling, athletic and social facilities, library services (Agre, 2000), credentialing, curriculum development, instructional delivery and student evaluation. Responsibility for these products is often distributed amongst the organisation without a single point of delivery and often with separate information technology (IT) systems.


Customers for the ‘teaching products’ of a university can be seen as including students, the general community, government, business and professional bodies. The following examines only students. The term ‘customer’ is used, as defined in Table 1, to mean someone who receives benefit from the product. Any deeper implications about what this term implies for the student–teacher relationship is not considered in this paper.

An essential component of facilitating learning is understanding learners, and particularly their learning styles, attitudes and approaches (Alexander, 2001; Oblinger, 2003). Students are no longer insulated from external pressures and they have to deal with real world concerns, including student loans, poor accommodation and part-time-working, yet many students still aspire to the assumed richness of campus-based education (Haywood, 2002). A large group of students, with significantly different characteristics, find asynchronous e-learning highly suited to their lifestyles and requirements (Hitt & Hartman, 2002).

Variety means that there is no one student experience of e-learning (Alexander, 2001). How to deal with the variety of backgrounds and expectations of students is one of the greatest challenges facing higher education today (Oblinger, 2003).


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). A critical strategy for effective e-learning is to recognise the different cultures of learning among and within organizations (Lea, 2003). 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, Lynch & Plummer, 1999).

The higher education industry is subject to the same pressures as other industries, including market, technological and societal pressures (Marshall & Gregor, 2002). Ultimately, the enterprises that are able to adapt to changes in the environment, while keeping the costs under control, will be successful (Huynh et al., 2003).

Uncertainty about the future and other developments highlight the importance of building institutions that are responsive to change. Innovation within higher education is constrained by a lack of competition, habits, values and traditions, and institutional arrangements and policies such as incentive structures, copyright and intellectual property rights (Dutton & Loader, 2002).


Existing technological infrastructure requires modification to fulfil the performance, scalability and availability requirements of e-learning (Hitt & Hartman, 2002). Institutions need to reorient their infrastructures from their existing state, designed to support departments, to a user-centric state (Moul, 2003). Information systems infrastructure that is flexible and adaptable can be a powerful enabler of innovation, but rigid, inflexible systems are serious obstacles to organisational effectiveness and success.

Senior management often perceive infrastructure and IT as costs to be minimised. Users see it as a service to be customised for their idiosyncratic requirements. IT organisations are caught in the middle, since best practices associated with reducing costs are in direct conflict with best practices necessary to maximise service levels (Jones, 2000).


The adoption of e-learning requires a revisiting of existing strategies, especially those associated with program development and instructional technology (Hitt & Hartman, 2002). An organisational culture that provides appropriate rewards is a success factor when implementing change in teaching and learning (Collis, 1998). While 74.5% of campuses have IT development programs, and 66.6% have campus support centres, only 13.4% have a formal, institutional program to recognise and reward the use of IT as part of the formal faculty review process (Green, 1999).

Too much of e-learning staff development focuses on the level of teachers’ strategies – how to use a particular tool – rather than on their conceptions of learning (Alexander, 2001).

Transformational change through e-learning requires institutional leaders to articulate a clear, bold vision, demonstrate a broad understanding and acceptance of that view, apply the focused use of resources and encourage widespread collaboration throughout the institution (Hitt & Hartman, 2002). Top–down planning often falters at the operational level because implementation throws up a range of messy human factors that need to be addressed with the same resolution that fuelled the initial policy enthusiasm (Haywood, 2002).

Technology projects fail because the innovators underestimate the consequences of new technologies (Sproull & Kiesler, 1991) and fail to accommodate environmental and contextual factors affecting implementation. The realities and subtleties of a comprehensive conception of a learning environment, which integrates virtual and physical and also academic and administrative, have eluded education policy-makers and designers (Segrave & Holt, 2003). Those who support a social shaping perspective of e-learning in universities emphasise that there are many paths that can be followed by the developers of e-learning (Dutton & Loader, 2002).

Alternate conceptualisations of the world raise doubts about whether it is possible to make sensible strategic and policy decisions in the traditional sense. This is particularly true when the world is seen as non-deterministic, evolutionary and highly complex – a world where the most desirable outcomes are unknown but there may be many possible acceptable outcomes, where change is characterised by both path dependence and unpredictability and where there are many diverse components, interaction and feedback among components, and multiple dimensions of each problem (Carlsson, 2002).

Lessons and implications

Great diversity and continual change are common characteristics across most of the nine components of the e-learning work system. As such, any response should be designed to cope with diversity and ongoing change. This has not always been the case. The most important policy objective is to remove obstacles to creativity and to foster entrepreneurship, rather than to take new initiatives: systematic planning should not replace the imaginative spark that creates innovation (Carlsson, 2002).

Diversity without integration creates problems. Integration across diverse systems, processes and organisational units is important in generating a customer-focused approach and an efficient operation. No one single system can integrate all requirements and existing attempts to do so sacrifice contextual capabilities that contribute to strategic advantage. An approach that enables diversity but achieves a customer-focused interface should provide greater strategic advantage.

The penalty for not catering for future change and diversity can be seen in the examples provided of how existing conceptions, infrastructure and organisational structures are limiting innovation, transformation and the adoption of new approaches. Some of this is due to simplistic top–down approaches that don’t effectively harness bottom–up potential.

IT has been taken for granted or assumed to be unproblematic. This results in a narrow conceptualisation of what technology is, how it has effects and how and why it is implicated in social change (Orlikowski & Iacono, 2001). Such limited conceptualisations often view IT as fixed, neutral and independent of context.

Alternatively, IT is one of a number of components of an emergent process of change where the outcomes are indeterminate because they are situationally and dynamically contingent (Markus & Robey, 1988). Ongoing change is not solely “technology led” or solely “organisational/agency driven”, instead change arises from a complex interaction among technology, people and the organization (Marshall & Gregor, 2002).


This paper has generated a shortened representation of the initial state within universities wishing to adopt e-learning. Even this limited representation has helped identify a number of lessons and implications that could be used to improve the future design of e-learning. A deeper, broader and more institutionally specific representation could enable even greater improvements.


1 ‘e-learning’ is one of many terms currently used to describe the use of information technology to support teaching and learning. Rather than argue about the ambiguities and differences among the various terms, this paper will use ‘e-learning’.


Agre, P. (2000). Commodity and community: Institutional design for the networked university. Planning for Higher Education, 29(2), 5-14.

Alexander, S. (2001). E-learning developments and experiences. Education and Training, 43(4/5), 240-248.

Alter, S. (2002). The work system method for understanding information systems and information system research. Communications of the Association for Information Systems, 9(6), 90-104.

Boland, R. J. (2002, June 14-15). Design in the punctuation of management action.

Paper presented at the Frontiers of Management workshop, Weatherhead School of Management, Case Western Reserve University, Cleveland, OH.

Bonk, C., & Dennen, V. (1999). Teaching on the Web: With a little help from my pedagogical friends. Journal of Computing in Higher Education, 11(1), 3-28. Brown, C. (1999). From the what and why to the how of course support systems –

the value of the teacher’s perspective provided by these systems. Paper presented at the WWW-Based Course Support Systems seminar, EdMedia ’99, Seattle, WA.

Calder, J. (2000). Beauty lies in the eye of the beholder. International Review of Research in Open and Distance Learning, 1(1).

Carlsson, B. (2002, June 14-15). Public policy as a form of design. Paper presented at the Frontiers of Management workshop, Weatherhead School of Management, Case Western Reserve University, Cleveland, OH.

Collective, T. D.-B. R. (2003). Design-based research: An emerging paradigm for educational inquiry. Educational Researcher, 32(1), 5-8.

Collis, B. (1998, July 8). Implementing change involving WWW-based course support across the faculty. Keynote address presented at the annual conference of the Australian National Computers in Education, Adelaide, SA.

Dutton, W., & Loader, B. (2002). Introduction. In W. Dutton & B. Loader (Eds.), Digital academe: The new media and institutions of higher education and learning (pp. 1-32). London: Routledge.

Green, K. (1999). The continuing challenge of instructional integration and user support: 1999 national survey of information technology in higher education (summary). Encino, CA: The Campus Computing Project.

Gregor, S., Jones, D., Lynch, T., & Plummer, A. A. (1999). Web information systems development: Some neglected aspects. Paper presented at the International Business Association conference, Cancun, Mexico.

Hannafin, M., & Kim, M. (2003). In search of a future: A critical analysis of research on web-based teaching and learning. Instructional Science, 31, 347- 351.

Haywood, T. (2002). Defining moments: Tension between richness and reach. In

W. Dutton & B. Loader (Eds.), Digital academe: The new media and institutions of higher education and learning (pp. 39-49). London: Routledge.

Hevner, A., March, S., Park, J., & Ram, S. (in press). Design science in information systems research. Management Information Systems Quarterly.

Hitt, J., & Hartman, J. (2002). Distributed learning: New challenges and opportunities for institutional leadership. Washington, DC: American Council on Education.

Huynh, M., Umesh, U. N., & Valacich, J. S. (2003). E-Learning as an emerging entrepreneurial enterprise in universities and firms. Communications of the Association for Information Systems, 12, 48-68.

Jarvinen, P. (2001). On research methods. Tampere, Finland: Opinpajan Kirja.

Jones, D. (2000). Emergent development and the virtual university. Paper presented at the Learning 2000 conference, Roanoke, VI.

Jones, D., Gregor, S., & Lynch, T. (2003). An information systems design theory for web-based education. Paper presented at the Web-Based Education symposium at the Computers and Advanced Technology in Education conference, Rhodes, Greece.

Lacity, M., & Hirschheim, R. (1993). Information systems outsourcing: Myths, metaphors and realities. Chichester, UK: John Wiley & Sons.

Lea, P. (2003). Understanding the culture of e-learning. Industrial and Commercial Training, 35(4/5), 217-219.

Lian, A. (2000, July). Knowledge transfer and technology in education: Toward a complete learning environment. Educational Technology & Society, 3(3).

Markus, M. L., & Robey, D. (1988). Information technology and organizational change: Causal structure in theory and research. Management Science, 34(5), 583-598.

Marshall, S., & Gregor, S. (2002). Distance education in the online world: Implications for higher education. In M. Khosrow-Pour (Ed.), Web-based instructional learning (pp. 110-124). Hershey, PA: IRM Press.

Morgan, G. (2003). Faculty use of course management systems. Educause Center for Applied Research.

Moul, B. (2003, March-April). Creating a unified digital campus to satisfy the needs of 21st century learners. The Technology Source.

Oblinger, D. (2003, July-August). Boomers, Gen-Xers and Millennials: Understanding the new students. EDUCAUSE Review, 38(4), 37-47.

Oliver, R. (1999). Exploring strategies for on-line teaching and learning. Distance Education, 20(2), 240-254.

Orlikowski, W., & Iacono, C. S. (2001). Research commentary: Desperately seeking the IT in IT research: A call to theorizing the IT artifact. Information Systems Research, 12(2), 121-134.

Paulsen, M. F. (2002, October). Online education systems in Scandinavian and Australian universities: A comparative study. International Review of Research in Open and Distance Learning, 3(2).

Piccoli, G., Ahmad, R., & Ives, B. (2000). Knowledge Management in Academia: A Proposed Framework. Information Technology and Management, 1, 229- 245.

Robson, R. (1999). WWW-based course-support systems: The first generation.

Paper presented at the WWW-Based Course-Support Systems seminar, Seattle, WA.

Segrave, S., & Holt, D. (2003). Contemporary learning environments: Designing e- learning for education in the professions. Distance Education, 24(1), 7-24.

Simon, H. (1996). The sciences of the artificial (3rd ed.). Cambridge, MA: MIT Press.

Sproull, L., & Kiesler, S. (1991). Connections: New ways of working in the networked organization. Cambridge, MA: MIT Press.

Weber, R. (2003). Still desperately seeking the IT artifact. Management Information Systems Quarterly, 27(2), iii-xi.

It’s more than how you use the technology – authoring online content

At the recent ASCILITE’2019 there was a common refrain throughout the conference, which started with the original keynote as captured in the following tweet

While I get the intent – the ultimate goal is good learning, not good technology – “how you use it” is much more than pedagogy. How this is translated into action within higher education has always troubled me. The following is an attempt to explain some of that and the “more” that is required. It’s also a reason to show off a screen capture video that I couldn’t show at the conference.

Higher education has a long-term (and growing) interest in “improving and measuring quality in higher education” (Ryan, French, & Kennedy, 2019), but it has “an under-developed capacity to analyse and explain” (Ellis & Goodyear, 2019, p. 239) the processes used to achieve it. Much of what currently happens in higher education is focused on identifying principles etc. of good pedagogy, disseminating knowledge of those principles, and measuring whether or not they’ve been adopted. Far less attention is paid to how to implement said principles in a sustainable way. In particular, little attention appears to be paid just how difficult and time-consuming implementing said principles can be.

My argument is that the activity system – the complex combination of learner, teachers, curriculum materials, software tools and the physical environment (Greeno, 2005, p. 79) – involved in “using it” requires much more attention. I’d argue that most of these activity systems are incredibly broken and subsequently it’s no surprise that there are concerns about the quality of learning environments, experiences and outcomes. My belief is that improving these activity systems will lead to improvements in learning environments, experiences and outcomes.

Authoring online course modules in Blackboard – Integrating Word & OneDrive/Sharepoint

(The title I’ve given this section could be easily seen as focusing on the technology. Boo! Hiss!. The important word is integrating. Integrating into these technologies into the stupid existing activity system for producing online course modules in Blackboard. Figuring out how to use the technology to make it easier for others to use the technology to effectively achieve the desired “pedagogy”.)

Part of my work for the last year has been paying attention to the activity system within which online course modules are created and maintained. This work has been seen in earlier blog posts and in the ASCILITE paper. Part of this was embedding the production of online content for Blackboard within the broader authoring practices of academics. i.e. allowing them to write content in Word – thereby drawing on facilities such as citation management, track changes, grammar checking etc. – and import it into Blackboard.

Until recently, the importing into Blackboard was a bit too manual. The video below illustrates the new process. It’s an example of an on-going improvement to the activity system.

It shows:

  1. Original Blackboard module content.
    The video starts showing a Blackboard module. The top part of the page shows the module content within an accordion interface. This is what students interact with. At the bottom of the page is an item titled Tweak code. Only teaching staff see this section. This item includes a link that will open up an online version of a Word document containing the module content. Ready for editing. It also includes a green button that will update the Blackboard module content.
  2. Converting Word document to HTML.
    Clicking the green button opens up a new web page that retrieves the Word document from OneDrive/SharePoint and converts it to HTML. If successful another green button will appear that when clicked will copy the HTML content into the clipboard and open up the appropriate Blackboard edit page.
  3. Editing the Blackboard content.
    At this stage, the normal Blackboard edit process for HTML commences. The content is updated by clearing out the old HTML and pasting in the newly converted content. Save these changes and the module has been updated.

What’s the impact?

Don’t know. What’s shown above has only been completed in the last couple of weeks and is currently being rolled out. Anecdotal feedback from people working with the more manual Word/Blackboard integration has been largely positive. Though there have been comments made about the extra steps involved in the manual integration. This new and more direct integration will hopefully help.

Given the following types of comments about authoring in Blackboard

relying primarily on the Blackboard Content Editor to post materials in the course shell as HTML is a time relatively consuming process (sic) …maintaining these courses too technically challenging

There’s some hope and expectation that this will have some positive impact.

Adding more context by focusing on pedagogical model activity systems

As it stands, the above is talking about a more general online content authoring activity system. But we can do more. It’s possible to adapt the above approach to customise the Word template and the HTML conversion process in response to specific contextual needs. For example, if a particular pedagogical model (Conole, 2010) has been adopted in a course, we could develop a specific Word template/HTML conversion process to offer explicit support for elements of that pedagogical model. Moving beyond the generic content authoring activity system and to focus on an activity system specific to the chosen pedagogical model.


Conole, G. (2010). Review of Pedagogical Models and their use in e-learning. Retrieved from Open University website:

Ellis, R. A., & Goodyear, P. (2019). The Education Ecology of Universities: Integrating Learning, Strategy and the Academy. Routledge.

Greeno, G. J. (2005). Learning in Activity. In R. K. Sawyer (Ed.), The Cambridge Handbook of the Learning Sciences (pp. 79–96).

Ryan, T., French, S., & Kennedy, G. (2019). Beyond the Iron Triangle: Improving the quality of teaching and learning at scale. Studies in Higher Education, 0(0), 1–12.

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