The nature of user involvement in LMS selection and implementation

Given what know (see the below) about the importance of people to the implementation of information systems and also to learning and teaching, how would you characterise the involvement of uses in the selection and implementation of an LMS at most universities? What impact does it have?

The importance of people

There has been significant research within the information systems discipline – a small subset includes user participation and involvement (Ives and Olson 1984); technology acceptance and use (Davis 1989; Venkatesh, Morris et al. 2003); decision-making around system selection and implementation (Bannister and Remenyi 1999; Jamieson, Hyland et al. 2007); system success (DeLone and McLean 1992; Myers 1994); development methods (Mumford 1981); and, the social shaping of technology (Kling 2000)- around the importance and impact of people on information systems and their success. In terms of user participation and involvement, Lynch and Gregor (2004) found that previous studies were inconclusive in terms of links with system success, however, they suggest that the level of influence users have on the development process is a better indicator of system outcomes. The perceptions of the people who may potentially use an information and communication technology play a significant role in their adoption and use of that technology (Jones, Cranston et al. 2005). Information systems are designed and used by people operating in complex social contexts, consequently such a system is understood differently by different people and given meaning by the shared understanding that arises out of social interaction (Doolin 1998).

Similar findings and suggestions are evident in the educational and e-learning literature. John and La Velle (2004) argue that new technologies at most enable rather than dictate change. Dodds (2007) suggests that any excellence demonstrated by a University is not a product of technology, it is a product of the faculty, students and staff who play differing roles in the pursuit of scholarship and learning. For Morgan (2003), teaching and learning are two of the most highly personalised processes. Numerous authors (e.g. Alexander 2001; Oblinger 2003) identify understanding learners, and particularly their learning styles, attitudes, and approaches as essential to the effective facilitation of learning. For Watson (2006), it is clear that consideration of the human dimension is critical to education. Since, as Stewart (2008) observes, the beliefs held by those involved in the educational process, regardless of how ill-informed, can have a tremendous impact on the performance of both students and teachers and how effectively technology may be utilised. Personal characteristics have been found to influence e-learning implementation (Siritongthaworn, Krairit et al. 2006) and most universities are still struggling to engage a significant percentage of students and staff in e-learning (Salmon 2005). While technology may be the stimulus, the essential matters are complex and will be the purview of academics (Oblinger, Barone et al. 2001).


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

Bannister, F., & Remenyi, D. (1999). Value perception in IT investment decisions. Electronic Journal of Information Systems Evaluation, 2(2).

Davis, F. D. (1989). Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 13(3), 319.

DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information Systems Research, 3(1), 60-95.

Dodds, T. (2007). Information Technology: A Contributor to Innovation in Higher Education. New Directions for Higher Education, 2007(137), 85-95.

Doolin, B. (1998). Information technology as disciplinary technology: being critical in interpretive research on information systems. Journal of Information Technology, 13(4), 301-311.

Ives, B., & Olson, M. (1984). User involvement and MIS success: a review of research. Management Science, 30(5), 586-603.

Jamieson, K., Hyland, P., & Soosay, C. (2007). An exploration of a proposed balanced decision model for the selection of enterprise resource planning systems. International Journal of Integrated Supply Management, 3(4), 345-363.

John, P. D., & La Velle, L. B. (2004). Devices and Desires: subject subcultures, pedagogical identity and the challenge of information and communications technology. Technology, Pedagogy and Education, 13(3), 307-326.

Jones, D., Cranston, M., Behrens, S., & Jamieson, K. (2005). What makes ICT implementation successful: A case study of online assignment submission. Paper presented at the ODLAA’2005, Adelaide.

Kling, R. (2000). Learning about information technologies and social change: The contribution of social informatics. The Information Society, 16(3), 217-232.

Lynch, T., & Gregor, S. (2004). User participation in decision support systems development: Influencing system outcomes. European Journal of Information Systems, 13(4), 286-301.

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

Mumford, E. (1981). Participative systems design: Structure and method. Syst. Objectives solutions, 1(1), 5-19.

Myers, M. D. (1994). Dialectical hermeneutics: a theoretical framework for the implementation of information systems. Information Systems Journal, 5, 51-70.

Oblinger, D. (2003). Boomers, gen-Xers and millennials: Understanding the new students. EDUCAUSE Review, 37 – 47.

Oblinger, D., Barone, C., & Hawkins, B. (2001). Distributed education and its challenge: An overview. Washington DC: American Council on Education.

Salmon, G. (2005). Flying not flapping: a strategic framework for e-learning and pedagogical innovation in higher education institutions. ALT-J, Research in Learning Technology, 13(3), 201-218.

Siritongthaworn, S., Krairit, D., Dimmitt, N., & Paul, H. (2006). The study of e-learning technology implementation: A preliminary investigation of universities in Thailand. Education and Information Technologies, 11(2), 137-160.

Stewart, D. P. (2008). Technology as a management tool in the Community College classroom: Challenges and Benefits. Journal of Online Learning and Teaching, 4(4).

Venkatesh, V., Morris, M., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.

Watson, D. (2006). Understanding the relationship between ICT and education means exploring innovation and change. Education and Information Technologies, 11(3-4), 199-216.

BIM, missing students and Moodle groups

The following is a description of a common “problem” with BIM.


The problem manifests itself along the lines of this:

  • There are students enrolled in the Moodle course you are using BIM for.
  • You’ve set up BIM, allocated student groups to markers.
  • However, some or all of the students aren’t showing up on the “Manage Marking” or “Your students” screens.
  • This might only be for one of the teaching staff, it might be for all.
  • The lead/coordinating teacher can probably find them using “Find student”.


The “Manage marking” and “Your students” tabs in BIM rely on students being members of Moodle groups. If the students aren’t in the Moodle groups that are allocated to the staff, then the staff can’t easily see them.


Some of the potential steps in a solution include:

  • Check that all students are in groups.
    Go to the Moodle “Groups” functionality for your course and make sure that all the students have been allocated to the groups appropriately.

    In an institutional setting this should be done automatically, but if this process is broken you might be having problems.

  • Check that groups have been allocated to staff.
    Go (as the coordinating/lead teacher) into BIM and use the “Allocate markers” tab to allocate the groups to staff as necessary.

Dilbert as an expository instantiation

A few recent posts have been first draft excerpts from my Information Systems Design Theory (ISDT) from emergent university e-learning systems. Being academics and hence somewhat pedantic about these things there are meant to be a number of specific components of an ISDT. One of these is the expository instantiation that is meant to act as both an explanatory device and a platform for testing (Gregor and Jones, 2007) i.e. it’s meant to help explain the theory and also examples of testing the theory.

The trouble is that today’s Dilbert cartoon is probably as good an explanation of what is currently the third principle of implementation for my ISDT.

I’m sure that most folk working in a context where they’ve had to use a corporate information system have experienced something like this. A small change – either to fix a problem or improve the system – simply can’t be made because of the nature of the technology or the processes used to make the changes. The inability to make these changes is a major problem for enterprise systems.

The idea from the ISDT is that the development and support team for an emergent university e-learning system should be able to make small scale changes quickly without having to push them up the governance hierarchy. Where possible the team should have the skills, insight, judgement and trust so that “small scale” is actually quite large.

An example

The Webfuse e-learning system that informed much the ISDT provides one example. Behrens (2009) quotes a user of Webfuse about one example of how it was responsive

I remember talking to [a Webfuse developer] and saying how I was having these problems with uploading our final results into [the Enterprise Resource Planning (ERP) system] for the faculty. He basically said, “No problem, we can get our system to handle that”… and ‘Hey presto!’ there was this new piece of functionality added to the system… You felt really involved… You didn’t feel as though you had to jump through hoops to get something done.

Then this is compared with a quote from one of the managers responsible for the enterprise system

We just can’t react in the same way that the Webfuse system can, we are dealing with a really large and complex ERP system. We also have to keep any changes to a minimum because of the fact that it is an ERP. I can see why users get so frustrated with the central system and our support of it. Sometimes, with all the processes we deal with it can take weeks, months, years and sometimes never to get a response back to the user.

Is that Dilbert or what?

The problem with LMS

Fulfilling this requirement is one of the areas where most LMS create problems. For most universities/orgnaisations it is getting into the situation where the LMS (even Moodle) is approaching the “complex ERP system” problem used in the last quote above. Changing the LMS is to fraught with potential dangers that these changes can’t be made quickly. Most organisations don’t try, so we’re back to a Dilbert moment.

Hence, I think there are two problems facing universities trying to fulfil principle #3:

  1. Having the right people in the support and development team with the right experience, insight and judgement is not a simple thing and is directly opposed to the current common practice which is seeking to minimise having these people. Instead there’s reliance on helpdesk staff and trainers.
  2. The product problem. i.e. it’s too large and difficult to change quickly and safely. I think there’s some interesting work to be done here within Moodle and other open source LMS. How do you balance the “flexibility” of open source with the complexity of maintaining a stable institutional implementation?


Behrens, S. (2009). Shadow systems: the good, the bad and the ugly. Communications of the ACM, 52(2), 124-129.

Gregor, S., & Jones, D. (2007). The anatomy of a design theory. Journal of the Association for Information Systems, 8(5), 312-335.

The office and more procrastination

Today has not been a good day for progress on the thesis. Have posted a few things I’ve already written and there are some folks reading bits of it thanks to Stephen Downes and OLDaily. That these folk find the work vaguely interesting enough to click on the link is a comforting thing, if not a motivating one for today.

Entering a nascent meme?

So, instead of writing, I thought I’d procrastinate a bit more and attempt to enter what might be a nascent meme. Lisa Lane started it by posting this annotated photo of her office. I came across this, via Mike Bogle’s post showing off his more spartan office. Not sure if there are other examples, but it’s enough of an excuse for me to waste some time.

So here it is, a photo of where I’m sitting at the moment not working on the thesis. Unlike Mike and Lisa, I’m in the very lucky position of not having an office at work, as I’m not currently working. An experience I’m increasingly enjoying, but realise will have to end soon. Which is a bit like the PhD only that I’m not really enjoying it at all.

The Office

Of course one of the reasons for doing this was to play with mbedr, but it won’t work on this blog as strips object and iframe tags. You’ll have to go here to see the mbedr version or the Flickr original.

Justificatory knowledge

The following is a first version of the justificatory knowledge section of my ISDT for emergent university e-learning systems. Still fairly uncertain just how information is meant to go in here and also just how far I should go with the reference to other theories (there are lots) and how much time should be spent looking at the interactions between them.

If you have some literature/theories which support or contradict this approach, will be really happy to hear about it.

Justificatory knowledge

The purpose of the justificatory knowledge component is to provide an explanation of why the ISDT is structured as it is and why it should be expected to work appropriately. Much of the justificatory knowledge that underpins this ISDT has been described previously within the literature review (Chapter 2), the first Webfuse action research cycle (Chapter 4), and earlier in this chapter. To avoid repetition this section provides a summary and brief discussion of the justificatory knowledge underpinning the ISDT for emergent university e-learning systems. This summary is linked specifically to the ISDT’s principles for form and function, and principles of implementation.

The justificatory knowledge described below arose from the experiences obtained and literature read during the design and support of Webfuse. This knowledge described below is not necessarily complete or the only established knowledge – theoretical or otherwise – that could be used to justify the principles of the ISDT. Hovorka and Germonprez (2009) identify as a weakness of design research, the lack of guidance around the interaction between the various kernel theories that make up justificatory knowledge and how the influence of these kernel theories may change during use. To some extent, the context-sensitive, emergent nature of the approach embodied by this ISDT – and its kernel theories – means that such advice is embedded in the justificatory knowledge that supports the ISDT.

Justificatory knowledge for principles for form and function

Table 5.20 provides a summary of the justificatory knowledge and is followed by a brief description. For each the three categories of principles of form and function for this ISDT, Table 5.20 provides pointers to sections of this thesis and references to literature that describe the justificatory knowledge in more detail.

Table 5.20 – Summary of justificatory knowledge for principles of form and function
Principle Justificatory knowledge
Integrated and independent services Section 2.3.2 – Software wrappers (Bass, Clements et al. 1998; Sneed 2000)
Adaptive and inclusive architecture Systems of Systems (Perrochon and Mann 1999)
Section 2.3.2 – Best of breed (Light, Holland et al. 2001; Lowe and Locke 2008), Service Oriented Architectures (Chen, Chen et al. 2003; Weller, Pegler et al. 2005), End-user development (Eriksson and Dittrich 2007)
Section 4.4.4 – Micro-kernel architecture (Liedtke 1995)
Scaffolding, context-sensitive conglomerations Constructive templates (Nanard, Nanard et al. 1998) , End-user development (Eriksson and Dittrich 2007)

As summarised in chapter 4, a software wrapper is a type of encapsulation that enables software components to be encased in an alternative abstraction that enables clients, often in a new context, to access the wrapped components services (Bass, Clements et al. 1998; Sneed 2000). As such software wrappers are one example of an approach that provides integrated and independent software services.

Some of the relative advantages and limitations more tightly integrated systems is provided by the enterprise software literature. In this literature, comparisons between tightly integrated systems and best-of-breed approaches have argued that integration involves centralisation of processes and a consequently a tendency to reduce autonomy, increase rigidity, and reduce competitiveness (Light, Holland et al. 2001; Lowe and Locke 2008). The best-of-breed approach, focusing on a more inclusive integration of appropriate packages, increases system flexibility while at the same time requires greater time, skills and resources to integrate diverse applications (Light, Holland et al. 2001). Perrochon and Mann (1999) argue that traditional approaches to system architecture, even those with a focus on adaptivity, are appropriate for greenfield developments due to their reliance on the assumption of design (specify architecture) and then implement. The rise of component-oriented software has created the problem of systems of systems that require the combination of well-engineered components or systems into an overall system they were never, and could never be, designed for (Perrochon and Mann 1999).

The concept of constructive templates (Catlin, Garret et al. 1991; Nanard, Nanard et al. 1998) was developed in response to the difficulty faced by content providers in developing hypermedia structures that followed the known principles of interface and hypermedia design. Constructive templates helped content experts to create well designed hypermedia (Catlin, Garret et al. 1991).

Justificatory knowledge for principles of implementation

The justificatory knowledge for this ISDT’s principles of implementation – summarised in Table 5.21 and briefly described below – draws heavily on what is down about alternatives to traditional, plan-driven software development methodologies as discussed in Section 2.4 and Sections 5.3.1 and 5.3.2 of this chapter.

Table 5.21 – Summary of justificatory knowledge for principles of implementation
Principle Justificatory knowledge
Multi-skilled, integrated development and support team Job rotation, multi-skilling etc (Faegri, Dyba et al. 2010), Organisational learning (Seely Brown and Duguid 1991), Situated learning, Situated action, Communities of practice (Seely Brown and Duguid 1991), Knowledge-based theory of organizational capability (Grant 1996)
An adopter-focused, emergent development process Section 2.4 examines the topic of processes, including a comparison of traditional plan-driven processes (e.g. the SDLC) and learning-focused processes such as emergent development. Additional discussion occurs in Section 5.3.2
Section 5.3.1 introduces the conception of adopter-focused development.
A supportive organisational context Organisational fit (Hong and Kim 2002), Strategic alignment (Henderson and Venkatraman 1993), Bricolage (Chae and Lanzara 2006), Mindful innovation (Swanson and Ramiller 2004)

Seely Brown and Duguid (1991) argue that the tendency for education, training and technology design to focus on abstract representations that are detached from practice actually distort the intricacies of practice and consequently hinder how well practice can be understood, engendered, or enhanced. The idea of the development team integrated and embedded in the everyday practice of e-learning seeks to improve the learning of both academics and students about how to harness e-learning, and also improve the learning of the development team (and the organisation) about how e-learning is being used. The ISDT seeks to establish a process for supporting and developing e-learning which is situated in shared practice with a joint, collective purpose.

Faegri, Dyba et al (2010) argue that turbulent environments increase the importance of employee skills and competences and that having employees cycle through different jobs – such as developers being on helpdesk – can improve knowledge redundancy, organizational knowledge creation, and other benefits. Faegri, Dyba et al (2010) also cite Keil-Slawik (1992) as arguing that full understanding of software requires experience developing the software. The traditional hierarchical structures associated with the division of labour around the e-learning within universities – e.g. helpdesk and developers organized into separate units within an IT division; learning and teaching experts located in another division focused on learning and teaching; and, faculty academics located academic units – are seen by Grant (1996) to inhibit the ability to integrate knowledge from members of an organisation. Such integration is seen as fundamental to the organisation’s ability to create and sustain competitive advantage (Grant 1996).

There is significant literature (March 1991; Baskerville, Travis et al. 1992; Mintzberg 1994; Bamford and Forrester 2003) in a variety of disciplines that identifies plan-driven processes as the dominant approach in most organizations. This and related literature also examines the limitations this over-emphasis suffers, especially in contexts with rapid change or significant diversity (see Section 2.4). Consequently there is significant literature identifying both the theoretical basis and guidance (Introna 1996; Truex, Baskerville et al. 1999) and practical implementation methods (Beck 2000; Schwaber and Beedle 2002) for more emergent or adopter-based development processes.

An emergent, university e-learning information system is a large-scale information system. In this context, “large-scale” is used in the sense adopted by Chae and Lanzara (2006), as referring to systems that involve both organisational technologies and technological innovations that “comprise and connect multiple communities of practice within an organisation or between organistions”. Literature examining success factors with information systems development (e.g. Ewusi-Mensah 1997; Scott and Vessey 2002) has long considered it vital for senior management to be supportive of and committed to systems development. Brown et al (2007) identify commitment – defined as the resources dedicated to IT, organisational dedication to change procedures, and top management support – as one of two most cited problems in the IS projects they examined and identified it as the factor most cited within the literature.

Organisational fit (Hong and Kim 2002) and strategic alignment (Henderson and Venkatraman 1993) between various aspects of an organisation and its information technology systems and processes have long been argued as critical success factors. A similar importance on having an organisational context that is committed and appropriate to information systems development is also found in approaches that are less traditional or teleological (e.g. bricolage and mindful innovation) and have more in common with the emergent, adopter-focused approach advocate in this ISDT. Collective or organisational bricolage requires the combined effort of several individuals and groups (Chae and Lanzara 2006). An organisation which is mindful in innovating with IT, uses reasoning grounded in its own organisational facts and specifics when thinking about the innovation, the organisation recognises that context matters (Swanson and Ramiller 2004). Within mindful innovation, management have a responsibility to foster conditions that prompt collective mindfulness (Swanson and Ramiller 2004).


Bamford, D., & Forrester, P. (2003). Managing planned and emergent change within an operations management environment. International Journal of Operations and Production Management, 23(5), 546-564.

Baskerville, R., Travis, J., & Truex, D. (1992). Systems without method: the impact of new technologies on information systems development projects. In K. E. Kendall (Ed.), The Impact of Computer Supported Technologies on Information Systems Development (pp. 241-251). Amsterdam: North-Holland.

Bass, L., Clements, P., & Kazman, R. (1998). Software Architecture in Practice. Boston: Addison-Wesley.

Beck, K. (2000). Extreme Programming Explained: Embrace Change: Addison-Wesley.

Brown, S., Chervany, N., & Reinicke, B. (2007). What matters when introducing new information technology. Communications of the ACM, 50(9), 91-96.

Catlin, K., Garret, L. N., & Launhardt, J. (1991). Hypermedia Templates: An Author’s Tool. Paper presented at the Proceedings of Hypertext’91.

Chae, B., & Lanzara, G. F. (2006). Self-destructive dyamics in large-scale technochange and some ways of conteracting it. Information Technology & People, 19(1), 74-97.

Chen, M., Chen, A., & Shao, B. (2003). The implications and impacts of web services to electronic commerce research and practices. Journal of Electronic Commerce Reseaerch, 4(4), 128-139.

Eriksson, J., & Dittrich, Y. (2007). Combining tailoring and evolutionary software development for rapidly changing business systems. Journal of Organizational and End User Computing, 19(2), 47-64.

Ewusi-Mensah, K. (1997). Critical Issues in Abandonded Information Systems Development Projects. Communications of the ACM, 40(9), 74-80.

Faegri, T. E., Dyba, T., & Dingsoyr, T. (2010). Introducing knowledge redundancy practice in software development: Experiences with job rotation in support work. Information and Software Technology, 52(10), 1118-1132.

Grant, R. (1996). Prospering in dynamically competitive environments: organizational capability as knowledge integration. Organization Science, 7(4), 357-387.

Henderson, J., & Venkatraman, N. (1993). Strategic alignment: Leveraging information technology for transforming organizations. IBM Systems Journal, 32(1), 4-16.

Hong, K.-K., & Kim, Y.-G. (2002). The critical success factors for ERP implementation: an organizational fit perspective. Information & Management, 40(1), 25-40.

Hovorka, D., & Germonprez, M. (2009). Tinkering, tailoring and bricolage: Implications for theories of design. Paper presented at the AMCIS 2009.

Introna, L. (1996). Notes on ateleological information systems development. Information Technology & People, 9(4), 20-39.

Keil-Slawik, R. (1992). Artifacts in software design. In C. Floyd, H. Zullighoven, R. Budde & R. Keil-Slawik (Eds.), Software Development and Reality Construction (pp. 168-188). Berlin: Springer-Verlag.

Liedtke, J. (1995). On micro-kernel construction. Operating Systems Review, 29(5), 237-250.

Light, B., Holland, C., & Wills, K. (2001). ERP and best of breed: a comparative analysis. Business Process Management Journal, 7(3), 216-224.

Lowe, A., & Locke, J. (2008). Enterprise resource planning and the post bureaucratic organization. Information Technology & People, 21(4), 375-400.

March, J. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71-87.

Mintzberg, H. (1994). The rise and fall of strategic planning: Reconceiving roles for planning, plans, planners. New York: Free Press.

Nanard, M., Nanard, J., & Kahn, P. (1998). Pushing Reuse in Hypermedia Design: Golden Rules, Design Patterns and Constructive Templates. Paper presented at the Proceedings of the 9th ACM Conference on Hypertext and Hypermedia.

Perrochon, L., & Mann, W. (1999). Inferred Designs. IEEE Software, 16(5), 46-51.

Schwaber, K., & Beedle, M. (2002). Agile Software Development with Scrum. Upper Saddle River, NJ: Prentice-Hall.

Scott, J., & Vessey, I. (2002). Managing risks in enterprise systems implementations. Communications of the ACM, 45(4), 74-81.

Seely Brown, J., & Duguid, P. (1991). Organizational learning and communities-of-practice: Toward a unified view of working, learning, and innovation. Organization Science, 2(1), 40-57.

Sneed, H. (2000). Encapsulation of legacy software: A technique for reusing legacy software components. Annals of Software Engineering, 9(1-4), 293-313.

Swanson, E. B., & Ramiller, N. C. (2004). Innovating mindfully with information technology. MIS Quarterly, 28(4), 553-583.

Truex, D., Baskerville, R., & Klein, H. (1999). Growing systems in emergent organizations. Communications of the ACM, 42(8), 117-123.

Weller, M., Pegler, C., & Mason, R. (2005). Students’ experience of component versus integrated virtual learning environments. Journal of Computer Assisted Learning, 21(4), 253-259.

Principles of implementation

The following is the other main component of the ISDT for e-learning I’m working on. A prior post focused on the principles of form and function (i.e. the structure of an information system, the product), the following focuses the principles of implementation (i.e. the process).

While both these posts are based on a bit of prior work, the current formulation of the principles are very much a first draft (not only the principles themselves, but the expression as well). I’ll be coming back to them and welcome feedback.

The biggest worry I have at the moment with the following is that it doesn’t express strongly enough the need for “end-user development” (i.e. enabling academics/students to do much of this themselves), while balancing that with a need (or perhaps the point) of having a specific support team. Need to work on this.

Much of the following is based on experience, but there are also theoretical justifications, that’s another section that is coming.

Principles of implementation

As defined by Gregor and Jones (2007) the principles of implementation specify “the means by which the design is brought into being”. The previous iteration of this ISDT described in Chapter 4 was extremely limited in terms of principles of implementation. This represented the implicit and naïve use of traditional software development methodologies during the initial implementation of Webfuse from 1997 through 1999. As described in this chapter a significant amount of work associated with Webfuse after 1999 has been aimed at developing more appropriate principles of implementation for university e-learning. The result is a rejection of more traditional, plan-driven approaches to information systems implementation, and, instead a set of implementation principles that are founded heavily on the ideas of adopter-focused and emergent approaches to information systems development. The following principles of implementation for the “ISDT for emergent university e-learning systems” are grouped and described in the following three sub-sections.

Multi-skilled, integrated development and support team

An emergent university e-learning information system should have a team of people that:

  1. Is responsible for performing the necessary training, development, helpdesk, and other support tasks required by system use within the institution and contains an appropriate combination of technical, training, media design and production, institutional, and learning and teaching skills and knowledge.
    The merging of these tasks into a single integrated unit avoids problems that arise when such responsibilities are spread across different organisational units. For example, the Infocom web team (the group supporting Webfuse from 2000 through 2004) was responsible for all these tasks and were co-located within a single building. This enabled significant opportunities for knowledge sharing and team building. It also meant that people providing training and support for the system were generally developers of the system with a much greater understanding of what was possible and what could be changed.
  2. Integrated into the everyday practice of learning and teaching within the institution and cultivates relationships with system users, especially teaching staff.
    Being regularly involved with teaching staff in their daily practice enables the building of trust through shared problem-solving and greater insight into the problems and experience of system users. A necessary foundation on which to implement an adopter-focused and emergent development approach. For example, the Infocom web team provided services, including helpdesk, that were used throughout the learning process and, as a result, they interacted with academic staff and students everyday.
  3. Are empowered to make small-scale changes to the system in response to problems, observations, and lessons learned during system support and training tasks rapidly without needing formal governance approval.
    The ability to make visible changes to systems in response to user problems or requests that provide a sense of user-involvement and lead to feelings of trust. Traditional governance processes can slow down and even prevent small-scale changes ever happening. The Infocom web team was free to make minor changes to Webfuse as soon as possible given other workload constraints. In many cases the developers would make these changes in order to prevent repeated helpdesk queries about the issues. Behrens (2009) quotes a manager in CQU’s IT division describing the types of changes made to Webfuse as “not even on the priority radar” due to traditional IT management techniques and quotes a Webfuse user as saying “You felt really involved”.
  4. Actively examines and reflects on system use and non-use – with a particular emphasis on identifying and examining what early innovators – to identify areas for system improvement and extension;
    While the Webfuse default course site approach provided an initial structure for course sites, this structure could be significantly modified through use of the page types or real course sites (Section 5.3.5). Observing what changes were being made, typically by innovative users, was a useful way of identifying improvements. For example, the addition of a study schedule page to the default course site arose from observing its use in non-default course sites.
  5. Plays a significant part of the governance process.
    This enables the governance process to harness the detailed insight into user experience with the system to inform decisions about system evolution.

    For example, governance of Webfuse was, for a short period of time, implemented using a representative committee of faculty staff that met each month. At those meetings, the Infocom web team would present a summary of what it had done in the previous month and, based on directions given by senior management (top-down) and insights gained from observation of system use (bottom-up), present a draft plan for the next month. Members of the governance group would comment and suggest changes to the plan.

An adopter-focused, emergent development process

Software development performed as part of an emergent university e-learning information system should:

  1. Adopt the goals, perspectives and techniques associated with alternate information systems development perspectives and methodologies such as emergent development (Truex, Baskerville et al. 1999), ateleological design (Introna 1996), and agile development methodologies (Highsmith and Cockburn 2001).
    As described in Sections 5.3.2, from 2000 onwards Webfuse development was increasingly informed by an emergent development approach using practices associated with eXtreme programming (Beck 1999).
  2. Use in-depth knowledge of the human, social and interpersonal aspects of the institutional context to inform the design and dissemination of new system features with the intent of encouraging greater levels of adoption by users.
    As outlined in Section 5.3.1, Webfuse development was informed by an adopter-focused approach.
  3. Maximise the ability of the system to be tailored for and by the users of the system.
    End-user development is perhaps the ultimate adopter-based development process as end-users develop applications in response to their own needs and perspectives. However, even with systems that enable end-user development there remains a need for effective and appropriate interaction between end-users, system owners and system developers (Eriksson and Dittrich 2007).
  4. Seek to establish a balance between the internal emergent process and external plan-driven processes.
    The title and the majority of the principles of this ISDT suggest that e-learning should adopt an emergent process. This ISDT seems to be heavily in what Clegg (2002) describes as the “learning school” of thought around process (see Section 2.4.1 for a discussion of the two predominant views on process). However, as shown in Section 2.4.2 the majority of processes within universities continue to adopt, or at least espouse, a heavy emphasis on plan-driven processes. While these perspectives represent divergent ways of understanding process, there are risky extremes inherent in both approaches that need to be avoided (Jones, Luck et al. 2005). An instantiation should seek to achieve an appropriate synthesis between the two approaches that enables adaptability and inclusiveness within an appropriately efficient and sufficiently resourced framework that is moving towards institutional goals.

A supportive organisational context

The organisational context in which an emergent university e-learning information system is used should:

  1. Have senior management and an organisational culture that understands, accepts, and actively enables and encourages an emergent approach to e-learning.
    As briefly described in Section 5.5 the emergent development of Webfuse was most effective when the faculty Dean recognised and supported and the benefits of emergent development and what is means and requires. A leader or organisational culture that places significant value on consistency, efficiency and more plan-based processes will not value the characteristics of emergent development.
  2. Use an approach to governance that encourages decentralised control while maintaining an appropriate, but minimal, level of top-down control.
    A description of the governance process used by Webfuse is provided in


Beck, K. (1999). Embracing change with extreme programming. IEEE Computer, 32, 70-77.

Clegg, S. (2002). Management and organization paradoxes. Philadelphia, PA: John Benjamins Publishing.

Eriksson, J., & Dittrich, Y. (2007). Combining tailoring and evolutionary software development for rapidly changing business systems. Journal of Organizational and End User Computing, 19(2), 47-64.

Gregor, S., & Jones, D. (2007). The anatomy of a design theory. Journal of the Association for Information Systems, 8(5), 312-335.

Highsmith, J., & Cockburn, A. (2001). Agile software development: Business of innovation. IEEE Computer, 34(9), 120-122.

Introna, L. (1996). Notes on ateleological information systems development. Information Technology & People, 9(4), 20-39.

Jones, D., Luck, J., McConachie, J., & Danaher, P. A. (2005). The teleological brake on ICTs in open and distance learning. Paper presented at the Conference of the Open and Distance Learning Association of Australia’2005, Adelaide.

Truex, D., Baskerville, R., & Klein, H. (1999). Growing systems in emergent organizations. Communications of the ACM, 42(8), 117-123.

Alan Kay and some reasons why the educational technology revolution hasn’t happened

While reading a recent post from Gardner Campbell I was taken by a quote from Alan Kay

The computer is simply an instrument whose music is ideas

A google search later and I came across this interview with Kay for the Scholastic Administrator magazine. The article is titled “Alan Kay still waiting for the revolution” and there are some, for me, interesting perspectives. A smattering below.

The difficult part is helping the helpers

Kay identifies the greatest obstacle to his work as being “helping the helpers”. i.e. the teachers. In talking about Logo, Kay a key failure being that the second and third waves of teachers were not interesting in Logo and didn’t have the math skills to teach well with Logo.

I see this as the biggest problem around e-learning (or blended, flexible, personal etc learning if that’s your buzz word of the moment) within universities, helping the helpers.

The tokenism of computers

On computers and tokenism

But I think the big problem is that schools have very few ideas about what to do with the computers once the kids have them. It’s basically just tokenism, and schools just won’t face up to what the actual problems of education are, whether you have technology or not.

Again there’s some resonance with universities. For a lot of senior and IT management in universities there’s an idea that we must have an LMS, but there’s not always a good idea of what the organisation should do with it once it has it. The most important part of that “idea”, is being able to identify what about the policies and practices of the institution needs to change to best achieve that idea.

For example, with the LMS the institution can increase interaction between staff and students via discussion forums, e-portfolios etc. But we won’t change the workload or funding model for teaching, or recognise the need to change the timetable to remove the traditional 2 hour lecture, 2 hour tutorial model.

The difference between music and instruments

In talking about some of the limits or potential problems associated with the trend to one-to-one computer

Think about it: How many books do schools have—and how well are children doing at reading? How many pencils do schools have—and how well are kids doing at math? It’s like missing the difference between music and instruments. You can put a piano in every classroom, but that won’t give you a developed music culture, because the music culture is embodied in people……The important thing here is that the music is not in the piano. And knowledge and edification is not in the computer. The computer is simply an instrument whose music is ideas.

The provision of the LMS or some other “instrument” is the simple task. Helping the people figure out what you want to do with it and how it can be done well, is the hard part.

Helping everyone find their inner musician

Why educational computing hasn’t lived up to the potential?

So computers are actually irrelevant at this level of discussion—they are just musical instruments. The real question is this: What is the prospect of turning every elementary school teacher in America into a musician? That’s what we’re talking about here. Afterward we can worry about the instruments.

How do you encourage and enable university academics to become musicians? I don’t think you can forget about computers, e-learning or the LMS. They are already in universities. There’s a need to look out how you can change how academics experience these technologies so that they can start developing their musical ability. Sending them to “band camp” (e.g. Grad Cert in Higher Education) isn’t enough if they return to a non-musical family. The environment they live in has to be musical in every aspect.