Assembling the heterogeneous elements for (digital) learning

Category: eei Page 1 of 2

Japanese store front - dog and boy

What are the symbols in digital education/design for learning?

Benbya et al (2020, p. 3) argue that digitial technologies do make a difference, including this point (among others)

Digital technologies not only give rise to complex sociotechnical systems; they also distinguish sociotechnical systems from other complex physical or social systems. While complexity in physical or social system is predominantly driven by either material operations or human agency, complexity in sociotechnical systems arises from the continuing and evolving entanglement of the social (human agency), the symbolic (symbol-based computation in digital technologies), and the material (physical artifacts that house or interact with computing machines).

An argument that resonates with my (overly) digital background and predilictions, but I wonder how valid/valuable this point is, whether the socio-material/post-digital folk have written about this, and what if any value it might generate for pondering (post-)digital education?

This resonates because my expeience in L&T in higher education suggests two shortcomings of most individual and organisational practices of “digital” education (aka online learning etc.):

  1. Few have actually grokked digital technologies, and;
  2. Even less recognise, let alone respond, the importance of “the continuing and evolving entanglement” of the social, symbolic, and material of sociotechnical systems that Benbya et al (2020) identify.

Returning to symbol-based computation, Benbya et al (2020) quote Ada Lovelace

Symbol-based computation provides a generalizable and applicable mechanism to unite the operations of matter and the abstract mental processes (`Lovelace 1842).
They explain that symbol-based computation – i.e. “provide a standard form of symbols to encode, input, process, and output a wide variety of tasks” – is at the heart of digital technologies.

Which seem to beg questions like

  1. What are the variety of L&T tasks that digital technologies support?
  2. What are the symbols that those digital technologies encode, input, process and output?
  3. How do those symbols and tasks evolve over time and contribute to the “continuing and evolving entanglement” of the L&T sociotechnical system?

Symbol systems in L&T – focus on management

It’s not hard to find literature talking about the traditional, one-ring-to-rule-them-all Learning Management System as being focused largely on “management” i.e. administration. Indeed, the one universal set of tasks supported by digital technology in higher education appears to be focused on student enrolment, grade management, and timetabling. Perhaps because courses, programs, grades, and timetables are the only symbols that are consistent across the institution.

When you enter the nitty, gritty of learning and teaching in specific disiplines you leave consistency behind and enter a diverse world of competing traditions, pedagogies, and ways of seeing the world. A world where perhaps the most commonly accepted symbols are lectures, tutorials, assignments, exams, grades. Again somewhat removed from the actual practice of learning and teaching.


To deal with this diversity institutions are moving to Tech Ecoysystems aka Next-Generation Digital Learning Environments (NGDLE). The NGDLE rationale is that no one digital technology (e.g. the LMS) can provide it all. You’ll need an ecosystem that will “allow individuals and institutions the opportunity to construct learning environments tailored to their requirements and goals” (Brown et al., 2015, p. 1).

Recent personal experience suggests, however, that what currently passes for such an ecosystem is a collection of disaparte tools. Where each tool has its own set of symbols to represent what it does. Symbols that typically aren’t those assumed by other tools in the ecosystem, or commonly in use by the individuals and organisations using the tools. The main current solution to this symbolic tower of babel is the LTI standard, which defines a standard way for these disparate tools to share information. Information that is pretty much the same standard symbols identified above. i.e. student identity, perhaps membership, and marks/grades.

Consquently, the act of constructing a learning environment tailored to the requirements of an individual or a course is achieved by somehow understanding and cobbling together these disaparate symbol systems and the technologies that embody them. Not surprisingly, a pretty difficult task.

Constructing learning environments

At the other end, there are projects like ABC Learning Design that provide symbols and increasingly digitial technologies for manipulating those symbols for design for learning that could be integrated into sociotechnical systems. For example, work at University of Sydney or ways of using digital technology to harness these symbols to marry curriculum design with project management. Which appears to finally provide digital technology that is supporting symbol computation that is directly related to learning and teaching and can be used across a variety of tasks and contexts.

But I do wonder how to bridge the final gap. While this approach promises a way to bridge curriculum design and project managing the implementation of that design. It doesn’t yet actively help with the implementation of that design. If and how might you bridge the standard symbols used by ABC Learning Design and the disparate collection of different symbol systems embedded in the tech ecosystem provided to implement it?

Learning Design tools like LAMS used something like the “one-ring-to-rule-them-all”/LMS approach and then engaged with something like the LTI approach. So either there was a single system that could define its own symbol system and ignore the rest of the world. Or, it could communicate with the rest of the world by the common universal symbols: student identity, membership, marks/grades etc and add one more disparate system to understand and try to integrate when constructing a learning environment.

Is there a different way?

What about a sociotechnical system that focused on actively helping with the task of cobbling together disparate symbol systems embedded in a tech ecosystem into learning environments? A method that actively engaged with developing a “continuing and evolving entanglement” of the social, symbolic, and material? A sociotechnical system that actively enabled relevant symbol-based computation?

What would that look like?


Benbya, H., Ning Nan, Tanriverdi, H., & Youngjin Yoo. (2020). Complexity and Information Systems Research in the Emerging Digital World. MIS Quarterly, 44(1), 1–17.

Brown, M., Dehoney, J., & Millichap, N. (2015). The Next Generation Digital Learning Environment: A Report on Research (A Report on Research, p. 11). EDUCAUSE.

Lantana flowers/network

Early steps with Gephi

A friend is in the final throes of her PhD and wants to visualise some of her qualitative findings using a network diagram. I’ve skirted around network visualisation without ever really doing anything but wanted to learn more. Following documents and reflects on my explorations and experiments trying to help out. The main focus being on figuring out how to produce a visualisation that meets requirements.

Previous work has led to the use of Gephi. In part because my current institution provides access to which provides Gephi as a container to install. Minimising the the dependency “hell” that can be the Java requirements to run Gephi.


The hardest part of all this was my old head building a conceptual model that bridged the data analysis outputs and requirements of my friend, network analysis/visualisation concepts, and Gephi’s (and other software) capabilities and operations. The biggest help in all this was various freely available tutorials (e.g. this list) developed by Gephi users.


My current understanding of the requirements, includes:

  • Data is coming out in spreadsheets that need to be visualised.
  • Data contains 19 categories (i.e. nodes) which might be mentioned together (i.e. links)
  • The number of times a node is mentioned is available and should be part of the visualisation.
  • The number of times two nodes are mentioned together is also available and should be part of the visualisation
  • Those categories can also belong to different groups and these groups need to be visualised.
  • There might be data from individual interviews and other combinations (i.e. multiple data sets to be visualised).

Getting the data into Gephi

Data from the analysis phase comes in a spreadsheet with the 19 categories in a 2×2 matrix. The cells represent either

  1. the number of times two different categories were mentioned together, or
  2. the number of times a category was mentioned in total.

One approach to get data into Gephi is to import two CSV files, that specify:

  1. Nodes; and
    Establish the node label, it’s ID and provide a range of additional attributes.
  2. Edges.
    Specify if and how two nodes (source and target) are connected, the type of edge (directed or undirected) and optionally the weight.


Four columns

  • Id – manually assigned.
  • Label – from the spreadsheet with the CoI labels combined.
  • Mentions – taken from the cell where the row/col matches the node
  • Group – whether the node belongs to context; technology-enabled design; or learning and teaching environment.


Four columns

  • Source & Target – the Ids for the nodes the edge connects.
  • Weight – how many times nodes (categories) were co-mentioned.
  • Type – undirected.

Importing and first look

With the two CSV files created, it’s a straight forward process to import and visualise. The test data gives the following visualisation out of the box. It needs some work.

Visualising node and edge weights

The first visualisation has many limitations, next step is to address the following:

  • Node size isn’t being shown.
  • Node labels aren’t being shown.
  • It’s all black and white.
  • Is the layout as good as it can get?

This tutorial provides an in context explanation of how to make these fixes.

Showing node labels is a simple switch.

Scaling node size uses the appearance dialog and allows changes to colour, node size etc based on various factors, including node attributes. In this case, select mentions.

Appearance also allows colouring of nodes based on node attributes. In this case, group will be used.

Random experimentation with layouts reveal the Fruchterman Reingold layout doing a reasonable first pass. All that combined gives the following image.

Visualising groups

As illustrated in the previous diagram, colouring nodes based on group membership provides some representation that helps see this relationship. However, relying on colour for a this might be problematic.

Is there a layout/method that co-locates nodes of the same group?

This blog post illustrates something similar by grouping according to organisational membership. Though it appears this is done manually, perhaps with a bit of post Gephi touching up. Time to explore different layouts in more detail.

Start with this tutorial, which begins with the installation of some new layout plugins (and shows some important Gephi interface actions e.g. dragging).

The circular layout generates the following image. Which may be getting close. Would be good if the labels didn’t overlap, but that’s for another day.

What’s next?

It appears that Gephi (perhaps combined with some post-visualisation manual image editing) can be used.

The next major question will be how to automate/manage the process for converting analysis data into visualisations that are then integrated into publications.


“Lantana camara plant NC3” flickr photo by Macleay Grass Man shared under a Creative Commons (BY) license

three frogs

Three mashup types for digital learning and teaching


Over the last 12 months my work helping improve digital learning and teaching environments has relied heavily successfully integrating a variety of technologies. It has relied on mashing up different technologies into effective learning and teaching environments and experiences. The following reflects on that work and identifies three different types of mashups:

  1. Mashup within the LMS.
  2. Mashup to change the LMS.
  3. Mashup to embed the LMS into the broader work system.


This type of work is important because there are suggestions that the perceived poor quality of learning and teaching at Universities can be fixed simply by re-allocating people and resources away from administrative business functions to learning and teaching. The problem is that interviews with university leaders (Ellis & Goodyear, 2019) find that they don’t yet know how to effectively merge learning, teaching, technology and facilities; privilege quality assurance and compliance over enhancement and innovation; focus on simple measurable outputs; and, have an under-developed capacity to analyse and explain the how to achieve those outcomes (p. 329).

The following uses experience to identify successful (perhaps necessary) mechanisms for merging technology with learning and teaching. The list suggests limitations in the current processes, technologies, and assumptions underpinning how universities go about developing quality learning and teaching. Limitations, which if not addressed, will limit any potential improvement that can come from throwing more resources at the problem.

For example, the list and the following explanation

  1. Illustrates the limitations of the current conception of integration that underpins current enterprise digital education practice.
  2. Suggests that the trend of hobbling or not supporting existing Web standards by contemporary digital learning applications (e.g. Blackboard Ultra, some phone-based apps etc) is making it very difficult to engage in the types of integrations necessary to achieve quality digital learning and teaching environments.
  3. Argues that the value generated by these types of mashups means that new applications should be evaluated on how well they support these mashups, not just on whether or not they provide LTI support.

Reconising the need for a diversity of tools

EDUCAUSE’s vision for the future of digital learning and teaching is the Next Generation Digital Learning Environment (NGDLE). It’s an idea based on the recognition that “no single application can deliver” (Brown et al., 2015, p. 1) all the functionality required by the diversity inherent in digital learning and teaching. Consequently, the suggestion is that the LMS will no longer be the single application for digital education. Instead, there will be an ecosystem of components available that “allow individuals and institutions the opportunity to construct learning environments tailored to their requirements and goals” (Brown et al., 2015, p. 1).

LTI: the problematic “lego approach” metaphor of integration

The current dominant method for tailoring this ecosystem of components into a learning environment that meets requirements and goals is the Learning Tools Interoperability (LTI) standard. When considering a new digital L&T technology it has become common practice to check for LTI support. As if LTI is the be all and end all of integration. I find this problematic.

The major problem is embedded in the name, Learning Tools Interoperability. LTI enables the (somewhat limited) seamless interoperability and integration of the tools. In my experience, LTI is not so good at helping develop a learning environment that seamlessly the integrates the experience and activity of the learners and teachers working within that environment.

LTI seems to be the type of enabling technology that the proposers of the NGDLE had in mind when they suggested that a ‘Lego approach’ would be necessary.

Legos work because of a design specification that ensures the pieces will interlock, while enabling a wide variety of component parts. For the NGDLE to succeed as we describe here, a similar set of specifications and services will need to be defined that constitute the conformance needed to make the Lego approach workable (Brown et al., 2015, p. 9)

Tony Bates questions (read the comments) whether Lego are the right metaphor for a learning environment.

A next generation digital learning environment where all the bits fit nicely together seems far too restrictive for the kinds of learning environments we need in the future. What about teaching activities and types of learning that don’t fit so nicely?

With LTI the Lego metaphor becomes two or more separate applications – e.g. LMS (Blackboard) and ePortfolio (PebblePad) that are entirely self-contained. They are connected by the LTI set of specifications, but they are distinct applications. The LTI specification makes the technical transfer of information between them seamless. But, LTI doesn’t help with the transition of the learners and teachers engaged in the learning environment created with these applications. The two separate applications have very different interfaces, terminology, and underpinning models. Making the transition less than seamless.

Not that everything needs to be seamless. There are times when a clear distinction is useful and important. It’s not a case of replacing LTI with mashups. It’s the case of having LTI and enabling mashups in order to achieve the following from Tony Bates

I have much more faith in the ability of learners, and less so but still a faith in teachers and instructors, to be able to combine a wide range of technologies in the ways that they decide makes most sense for teaching and learning than a bunch of computer specialists setting technical standards (even in consultation with educators).

Mashups: integration beyond lego bricks

In proposing the NGDLE, Brown and colleagues (2015) do appear to have recognised that this is required when they suggested that

the model for the NGDLE architecture may be the mash-up. A mash-up is a web page or application that “uses content from more than one source to create a single new service displayed in a single graphical interface (Brown et al., 2015, p. 3)

As defined in this quote mashups not only support the integration of different tools. Mashups – by integrating these tools into a single interface – offer the potential of developing a learning environment that seamlessly integrates the experience and activity of learners and teachers.

The following provides examples of the different types of mashups that I’ve been involved with over the last 12 months within the Blackboard Learn 9.1 LMS. But first,

What is a mashup?

Mashups originate in the practice of disc jockeys combining music from multiple artists to create new material (Beemer & Gregg, 2009). A practice made for YouTube as illustrated by the following video (and the rabbit warren YouTube will take you down, if you let it).

The brave new world of Web 2.0 brought that practice into the software sphere with the evolution of mashup to refer to software applications that merged functionality from multiple sources into a unified user interface (Kulathuramaiyer, 2007; Zang et al., 2008). An important feature was that anyone, just not software developers, could create mashups (Beemer & Gregg, 2009; Hoyer & Fischer, 2008; Zang et al., 2008). Thereby enabling the development of mashups that could respond quickly to specific contextual needs (Beemer & Gregg, 2009).

Echoing directly the NGDLE idea of using mashups to enable “individuals and institutions the opportunity to construct learning environments tailored to their requirements and goals” (Brown et al., 2015, p. 1).

The mash-up list

The following list meant to be illustrative of types of integration/mashup that are different from that enabled by LTI. LTI generally allows to two different applications to communicate and share information.

Mashup within the LMS

The simplest example use of the <embed> tag that is a standard part of HTML. The description of the embed tag from the standard explicitly makes the connection with mash-ups.

The embed element represents an integration point for an external (typically non-HTML) application or interactive content.

If you’ve ever embedded a YouTube video, you’ve used the embed tag and produced a mash-up. You’ve mashed up external content within the LMS.

The embed tag enabled mashup is much more than a link. A link takes you outside of the existing environment/page. An embed enabled mashup is embedded within the LMS page.

Another example is illustrated in the following image. It is from a Blackboard site for a program in the Creative Industries. Embedded within this LMS page is styled list of the latest articles from a discipline specific journal. Some site specific Javascript is used to retrieve and display the journal’s RSS feed within the LMS-hosted program site.

Another example is work by folk at QUT where they integrated the disqus comment plug-in into the Blackboard 9.1 LMS to provide a discussion experience that improves upon that offered by Blackboard’s native discussion forum.

Mash-up to change the LMS

The previous mash-up examples took content/functionality from outside the LMS and embedded it within the LMS. The examples here bring in functionality from outside the LMS, to modify how the LMS appears and/or operates. Such work is done to address some limitation or inappropriate feature of the LMS. As the EDUCAUSE folk identified, one application can never cater for all the diversity associated with learning and teaching (Brown, et al., 2015).

For example, Blackboard 9.1 is known wide and far for ugly web pages (even Stephen Downes has experienced it). At almost it’s best, standard Blackboard 9.1 looks like the following.

Again, folk at QUT saw this as a problem and developed a plugin for the Blackboard LMS that could automatically transform the above to the something a bit better, like the following.

Over the last year we’ve gone a step forward and developed some Javascript/CSS that can be embedded in Blackboard and produce something like the following.

This approach has also been extended to work with Blackboard functionality such as review status.

There are many other examples of how the existing functionality/interface of an LMS is inappropriate for a given educational purpose. The JS Hack building block made use of the architecture of Blackboard 9.1 to enable institutions to develop (and share) modifications for the Blackboard 9.1 user interface. Both administrative (e.g. displaying a warning to administrators) and user interface.

The following Tweet is a recent example of the clash between pedagogical intent and technological design. Exactly the type of clash this type of mashup is meant to prevent.

Mashup to embed the LMS into the ecosystem

The previous mashups have the user experience occurring within the LMS. The problem is that – as the NGDLE idea suggests – the LMS is only one tool from the ecosystem of applications that are required for learning and teaching. At least some (arguably most) of those applications will be personal, i.e. not chosen by the institution. How well the LMS can work well with other applications is important.

For example, when creating content Blackboard 9.1 – like most LMS – provides the ability to either upload files (e.g. Powerpoint, PDF, Word documents) or edit HTML using the TinyMCE editor. Uploading files means you can use tools purposefully designed to support content creation and link to their own ecosystem of tools. Using the TinyMCE editor you give up all that. Meaning you give up version control, citation management, and collaborative authoring (comments, track changes) etc to produce web content. It’s no surprise that the majority of content in an LMS is in documents.

This type of mashup fixes this type of problem by more effectively embedding the LMS in the broader ecosystem of digital technology.

The animated GIF below demonstrates that use of a mashup we’ve developed that embeds the LMS within the broader content authoring ecosystem commonly used at our institution, including OneDrive/SharePoint, the Office365 applications and more broadly, web technologies. It starts with where the authors are, using Word and Powerpoint to author (perhaps collaboratively) content. But then uses other technologies to solve various problems with the existing process, embeds additional authoring functionality (version control, collaborative editing and commenting etc.), and provides teachers with an improved authoring experience and learners with an improved learning interface.

Not only that, in essence the mashup provides a simple headless content management system for Blackboard. Meaning the content (now in Word documetns) can be quickly re-used for different purposes. e.g. when we migrate to a different LMS, or in different course sites.


Challenges to mashups

Even the most basic of mashups – embed within the LMS – is challenging if you have no background with web authoring. For example, in the last year I’ve had to explain how to embed a YouTube video numerous times. The remaining two mashup types are more complex again, generally outside the realm of the standard teacher.

But the ability to implement even the simplest of mashups is being curtailed by technological trends. Increasingly, most LMS prevent end-users from including Javascript and CSS. Web standards that are important enablers of mashups on the web. But the constraints are going further again. The design of the new Blackboard Ultra LMS constrains what HTML is accepted. Placing limits on even what can be achieved with the <embed> tag. Making chances of supporting web components limited.

In part, the espoused reason for this trend arises from the limited digital literacy of users mentioned in the previous paragraph. The flexibility offered by embedding Javascript/CSS combined with the perceived lack of knowledge means that disasters can happen. Closing this capability appears to be easier than providing the necessary training and support to leverage this functionality.

But at what cost?


Bartuskova, A., Krejcar, O., & Soukal, I. (2015). Framework of Design Requirements for E-learning Applied on Blackboard Learning System. In M. Núñez, N. T. Nguyen, D. Camacho, & B. Trawinski (Eds.), Computational Collective Intelligence (pp. 471–480). Springer International Publishing.

Beemer, B., & Gregg, D. (2009). Mashups: A Literature Review and Classification Framework. Future Internet, 1(1), 59–87.

Brown, M., Dehoney, J., & Millichap, N. (2015). The Next Generation Digital Learning Environment: A Report on Research (A Report on Research, p. 11). EDUCAUSE.

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

Hoyer, V., & Fischer, M. (2008). Market Overview of Enterprise Mashup Tools. In A. Bouguettaya, I. Krueger, & T. Margaria (Eds.), Service-Oriented Computing – ICSOC 2008 (pp. 708–721). Springer.

Kulathuramaiyer, N. (2007). Mashups: Emerging Application Development Paradigm for a Digital Journal. 13(4), 531–542.

Martin, G. (2017). Scaling critical pedagogy in higher education. Critical Studies in Education, 58(1), 1–18.

Wu, J. (1999). Hierarchy and Scaling: Extrapolating Information along a Scaling Ladder. Canadian Journal of Remote Sensing, 25(4), 367–380.

Zang, N., Rosson, M. B., & Nasser, V. (2008). Mashups: who? what? why? CHI’08 Extended Abstracts on Human Factors in Computing, 3171–3176.

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’.


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Testing out h5p interactives and tracking

Feel free to play around with the following h5p interactive (one of the examples provided on the h5p site). I’m testing out if and how it tracks people’s engagement with the interactive. What does it do when someone who doesn’t have an account on this blog (and/or doesn’t login) interacts? What data can I see?

By default it appears that h5p/wordpress doesn’t really provide anything useful and a quick search didn’t reveal any possibilities.

This post provides a bit more detail on broader possibilites with xAPI and h5p, including this WordPress plugin (h5pxAPIkatchu). This plugin catches all the xAPI statements emitted by h5p interactives and stores them in the WordPress database for downloading for analysis.

[h5p id=”10″]

Digital learning templates – adding context and configuration

My last post introduced some early steps in exploring how to increase the reuse of design knowledge in design for digital learning (i.e. designing course websites). That post outlined the specific problem, the solution and linked it to work on constructive templates and patterns from the Hypermedia Design literature (Nanard, Nanard and Kahn, 1998). It closed with observing how the current solution was limited. It only provided scaffolding for the act of creating/implementing the specific design. It didn’t offer any affordances for the local context or design for configuration. This post details some early work to address this.

Reminder of the card interface “template”

Figure 1 shows the particular “template” that I’ve been working on. At the top of Figure 1 is the the card interface which the template generates. Below the card is the “normal” Blackboard content. This content is what the course designer provides. The “template” transforms that content into the card interface. If you were viewing (rather than editing) this page in Blackboard, then you would only see the card interface.

All well and good, it’s pretty and contemporary enough, but there’s a problem.