Assembling the heterogeneous elements for (digital) learning

Month: April 2009 Page 1 of 2

First official BAM paper done

BAM – Blog Aggregation Management is a project I started in early 2006 to play around with two sets of ideas:

  1. learning; and
    Building on some ideas of using blogs for individual student reflective journals in an attempt to increase the visibility of their progress and enable increased levels of student/teacher interaction.
  2. technical.
    Extending one of the initial ideas of Webfuse (“maximise adaptability by concentrating on providing the infrastructure required to integrate existing and yet to be developed online learning tools”) into the wonderful world of Web 2.0.

The initial experiment in the second half of 2006 has been the topic of a report for a website and some blog posts. However, late last year Jo and I submitted a paper to EdMedia’2009. It was accepted, but I or the reviewers were not entirely happy with the paper, so some changes have been made.

Consequently, the next to final version of the paper is now available. It’s better than the version that was accepted, but still not great. At least it tells the story with a bit of reflection.

Not a great paper but it’s one of two Jo will present in Hawaii.

As for the future of BAM, that all depends on what’s happening with work. At the very least BAM is taking a back seat to the PhD, for a while.

Integration with professional lives of academics – why industrial e-learning fails and why post-industrial might work

I’m currently struggling with writing the “Place” component of the Ps framework as part chapter 2 of my thesis. In wondering the literature, as I tend to do while writing, I’ve come across an article (Gilbert and Geoghegan, 1995) that has some interest for me. Gilbert’s description of the paper is

The Internet is changing the way some of us develop ideas and communicate. The following, for example, is a sample of an “electronic” discussion about how to bridge the gap in higher education between the early adopters of information technology and the mainstream faculty who are yet to use technology to improve teaching and learning in their classrooms.

The initial post in this discussion is from Geoghegan and includes early versions of his ideas around why instructional technology adoption within universities were stalled, and in particular the notion of the technologists’ alliance. While I find that notion very helpful in my work, this post is about something else.

The Gilbert and Geoghegan (1995) article consists mostly of Geoghegan’s initial post and then various summaries/abstracts of the subsequent discussion on the mailing list. One of summarised responses is from Randy Bass (someone who has gone onto other things since then) titled “Professional Integration: A missing link”. The article includes the following quote from Bass’ post

I would argue that if we can’t talk about how technology integrates with the professional lives of teachers, then we can’t talk about the substantive adoption of technology in teaching among the mainstream of faculty. Therefore, to any ‘depth and pace of change’ taxonomy, I would add a category called ‘Professional Integration.’ And I pose this category as a challenge to publishers, IT support persons, and funding agencies to find ways to address the professional needs of faculty through technology, both as an end in itself and as a means to transforming teaching and learning strategies.

To me, this implies that the use of technology in learning and teaching by mainstream faculty will be in someway limited (either in numbers or quality), unless that technology becomes integrated into the professional practice of the faculty. It also implies that the LMS approach to e-learning will never be all that successful because of the difficulty of applying it to professional practice and that subsequent paradigms of e-learning might be better placed, if done correctly, to achieve this. It also raises a range of other questions (at least for me), and, finally, illustrates just how slow I’ve been to realise some implications of the work of Stephen Downes.

Professional integration and industrial e-learning

In an earlier post I suggested that there have been, so far, 6 different paradigms of e-learning within universities. The current paradigm is industrial e-learning and is characterised by the selection, installation and support of learning management systems (LMS) as “enterprise resource planning (ERP) systems for education.

How well can an LMS be integrated into the broader professional practice of an academic?

I would argue that it essentially can’t. An LMS’ primary organising unit is the course offering. It is implemented within universities based around course offerings and all of the university infrastructure that feeds and supports the offering of courses. This infrastructure doesn’t fit well with supporting research or community service. The two primary other parts of the professional practice of an academic. As an example of an even more constraining example, many institutions limit access to their LMS to people who have valid institutional user accounts.

Interestingly, when I think about it from this perspective, I have seen academics try and use the LMS to support their professional practice. I have heard academics ask for a Blackboard site for their research group or one for the ex-students. Academics have been looking for e-learning technologies to help them with their professional practice, but the LMS hasn’t helped.

I guess you could link this with the Sakai project’s claim/aim to be a collaboration platform, rather than an LMS.

Professional integration and post-industrial e-learning

In that post on the paradigms of e-learning I suggested that the next paradigm could be called “post-industrial”. An approach that arises out of “cloud computing”, social media and associated ideas. Other authors such as Stephen Downes and others have described this “paradigm” in more detail under labels such as e-learning 2.0.

Apart from any inherent advantages that these tools and approaches may have for learning and teaching, perhaps one of their greatest strengths is the ability to be used and significantly enhance the professional practice of academics. My experience has been that social media has helped my professional practice. Perhaps the key to improving learning and teaching through technologies is getting academics to eat their own dog food, to use social software in their professional practice. Once this happens, perhaps it will become natural for them to use it in their learning and teaching.

Perhaps rather than spend (and waste) vast amounts of time on special curriculum design projects, e-learning systems, professional development around learning and teaching and vast top-down projects on adopting L&T innovation “X”, institutions should focus on showing faculty how the new social software technologies and the different perspectives on knowledge embodied in them can be harnessed to improve their professional (and personal) lives. Focus on this and just wait for the changes in thought processes to filter through and start to impact learning and teaching.

This links nicely back to the view that you can only change the quality of learning and teaching in a university course by changing the conceptions of learning and teaching brought to the course by the academic.

Perhaps this is the way to deal with the problems identified in this great presentation.

I recognise that this wouldn’t at all be easy, I identify one problem in the last section. However, I also think it would likely be considerably easier and more effective than trying to convince them to improve the learning and teaching by using approaches and technologies that are not only non-applicable to the rest of their professional practice, but also consume time that they could be spending on the rest of their professional practice.

Catching up with the Downess

As I was writing the above, I realised that I’ve been somewhat slow. Taking a different tack or starting from a different perspective, this appears to be very close to what Stephen Downes has been talking about all these years. Yes, he even summarises it nicely when writing about the purpose of his website.

Oh what a slow learner I’ve been, to be nice, perhaps I’ve been aware of the dots, I just haven’t connected them. Perhaps that’s partly due to the brain-washing I’ve received by being part of the university sector for too long.

Some implications

So, what implications/questions might you draw from this perspective? Some initial attempts:

  • The L (learning) in LMS might be a significant constraining factor on the ability of the LMS to significantly improve/change learning and teaching at universities.
    At least while “learning” in this context is limited to something that students do under the direction of staff and the institution. While the people designing LMS and the folk implementing and supporting them within universities hold to this understanding, it will be too difficult for academics to integrate the LMS into the rest of the professional practice. In fact, the LMS may continue to strengthen the unhelpful distinction between learning and research within the minds of the institutions and their staff. Has some interesting implications for how the teaching/research nexus (a big focus in Oz at the moment) can be improved.
  • Moodle won’t be the saviour of learning and teaching.
    Moodle, because it is open source and said to be designed from on a social constructivist perspective, is being held up by many as the saviour of e-learning. However, since it continues, to some extent, the separation of learning and research it probably won’t be. Especially when some institutions are simply using Moodle as a replacement for the commercial LMS and consequently reinforcing in the mind of the mainstream that it really is no different from Blackboard etc. Interestingly, though, I have seen any number of examples of where Moodle has been used for professional purposes outside of university courses. I’ve always found it a bit kludgy for that purpose.
  • What about integration with personal practice?
    The Bass quote talks about integration with professional practice. But I wonder if as more and more academics are using Skype, Facebook, Flickr etc in their personal lives, if that won’t drive their tendency/desire to use those specific applications in their professional experience, including learning and teaching. Of course, this potentially raises the question of whether or not the blurring of professional and personal places/activities is a good thing.
  • Do the silos in universities encourage this separation?
    At most universities that I’m familiar with there is usually a separate senior person responsible for teaching/learning, research and community service. Or if these are combined into one person in any way, that person usually treats them as separately. Even if they wish to combine them there are usually, at some level, separate committee structures for each task.

    This would seem to make the task of getting some approach to technology to support professional practice more difficult as the different perspectives, goals and responsibilities of the different organisational structures would create additional tensions and misunderstandings.

    It makes my head hurt just thinking about what you’d have to do to get some level of understanding from the different parts of the organisation…..

There are many more.


Gilbert, S. and W. Geoghegan (1995). “An “online” experience: discussion group debates why faculty use or resist technology.” Change 27(2): 28-45.

Lessons for from past experience

This posts contains the last content of what (I hope) will become the “Past Experience” section of Chapter 2 of my thesis. Previous content for this section is already on the blog, including: History of technology-mediated learning, Paradigms of e-learning, e-learning usage – quality, and e-learning usage – quantity.

The aim of this post is to draw some lessons from the past. It won’t be exhaustive, I’m sure there are many other lessons to draw, I’d be interested in hearing them if you know of any. However, for the purposes of the thesis, I’m hoping the following will be “good enough”. As with the other posts, this is a first draft. It hasn’t been through a good proof read, but hopefully is sufficiently readable. In fact, while putting this post together I chopped, changed and added bits, which I haven’t spent a great deal of time checking.

Lessons for e-learning

The purpose of the “Past Experience” section of the Ps Framework is two-fold: examine the history of e-learning, and then draw any lessons or conclusions that may improve the implementation of e-learning within universities. The previous sections have examined the history of e-learning by examining the origins of e-learning in the history of technology-mediated learning through the 1900s (Section 2.1.2 – History of technology-mediated learning), examining the evolving paradigms observable in the history of e-learning (Section 2.1.3 – Paradigms of e-learning), and reporting on the usage of industrial e-learning in terms of quanity and quality (Section 2.1.4 – Industrial e-learning usage – quantity and quality). The purpose of this section is to identify lessons can be drawn from this history of e-learning and describe their potential implications.

This section (2.1) on “Past Experience” commenced with the following quote from Santayana (2009) (emphasis added)

Progress, far from consisting in change, depends on retentiveness. When change is absolute there remains no being to improve and no direction is set for possible improvement: and when experience is not retained, as among savages, infancy is perpetual. Those who cannot remember the past are condemned to repeat it.

This section identifies three lessons labeled using the emphasized sections of the Santayana quote. Each of the following three sections suggest that there is evidence of the three lessons. “Consisting in change” suggests that technology-mediated learning is always changing and that any approach to e-learning must embrace and respond to change effectively. “Retentiveness – or lack thereof” suggests that the history of technology-mediated learning is one where lessons are forgotten, a flaw that needs to be remedied. Lastly, “Infancy is perpetual” suggests that the history of technology-mediated learning, in terms of significant effective the practice of learning and teaching, is one of perpetual infancy. One where important insights into how to transform learning and teaching are continually forgotten.

Consisting in change

A significant feature of the history of technology-mediated learning has been that new paradigms or approaches to learning are driven, to a large extent, by the development of new technology. Each of the major applications of technology to learning covered in the History of technology-mediated learning section (2.1.2) were made possible through the advent of a new type of technology. Table 2.3 provides a summary of the technological spark that enabled each movement observed within technology-mediated learning. Table 2.4 summarises a similar connection between specific technological sparks and each of the paradigms of e-learning identified in section 2.1.3.

Table 2.3 – Technology-mediated learning movements and their technological sparks
TML movement Technological spark
Audio-visual Stereo-graphs, photos, motion pictures, radio, television
Teaching machines Mechanical machines and the industrial revolution
Computer-based learning Early computers
Computer-mediated communication Mainframes, communication software, networks
Computer-managed learning Personal computers, local-area networks

As shown in Section 2.1.3 it is possible to identify at least five different paradigms or models of e-learning since 1990 (see Table 2.1). All of these paradigms arise, to a large extent, because of the development of a new technology that promises to provide solutions to problems with previous practice. Table 2.3 provides a brief summary of the technology/paradigm connection. The current pre-dominant paradigm, industrial e-learning, appears to have been, as shown above (Section 2.1.4), somewhat less than successful in transforming learning and teaching at universities and the promise of the next paradigm is already being promoted. Learning 2.0 – the post-industrial e-learning paradigm – is challenging existing models by enabling and requiring pedagogical, organizational and technological innovation (Ala-Mutka, Bacigalupo et al. 2009). Suggesting that the cycle is starting over once again.

Table 2.3 – E-learning paradigms and their technological sparks
e-learning Paradigm Technological Spark
Text-based CMC Internet technologies provide solutions to problems with proprietary, main-frame based CMC systems.
Lone ranger Increasing availability of simple Internet-based systems to academics (not involved in existing CMC research) in their everyday practice generates interest amongst lone ranging staff in applying it to learning and teaching.
Cottage industry Lone rangers develop collections of technology, leveraging scripting languages and open-source tools – especially those associated with Web development, to make it easier for others to use the Internet in their teaching
Industrial Commercial vendors (and more recently open source communities) develop integrated systems, often adapted from those of lone rangers, of technology that are “enterprise ready”
Post-industrial The rise of social software, blogs, wikis etc. generate interest in how these can be harnessed to address problems with industrial e-learning

As described in Section 2.1.3 a paradigm embodies a particular worldview and requires a certain organizational structure and set of skills to operate effectively. Consequently, it is possible to observe institutions, heavily invested in a previous paradigm, that have been slow in adopting the next paradigm, for example, some traditional distance education institutions and the move to industrial e-learning. While a slower, more considered adoption process can be both positive and negative in its impacts, the ability to adopt new paradigms is important. It is suggested that the ability to cope with change is an important component of any approach to e-learning within universities.

A lack of retentiveness

Santayana (2009) in the quote that led off the “Past Experience” section (section 2.1) of this chapter suggests that progress depends on retentiveness, the ability to retain experience. The following provides a few examples of how e-learning has demonstrated an ability to forget or simply be ignorant of Past Experience. The examples are drawn from a number phases from the history of technology-mediated learning and are far from exhaustive.

As shown above in the work of Malikowski et al (Malikowski, Thompson et al. 2007) the quiz functionality of an LMS is the most used function for evaluating students with upwards of 20% of staff using the feature. Heines (2004) complains that he is yet to see a test item banking program that enforces even the most basic, long-established rules of test construction and bemoans LMS vendors who are not familiar with terms such as “item analysis”, “difficulty index”, “discrimation index”, and “standard deviation”. Just some of the fundamental knowledge arising out of the teaching machines, programmed instruction and computer assisted instruction movements. Another example is that Skinner (1958) establishes as one of the important features of any teaching machine the requirement that students compose their response rather than select it from a set of alternative in order to test their ability to recall, rather than recognize the answer.

One of the more dominant themes in research around e-learning has been the practice of comparison studies. Studies in which some new technology-mediated learning approach has its effectiveness compared against some other method, typically traditional face-to-face teaching. The continuation of such studies ignore the fact that much of the research tradition of the audio-visual instruction movement was based on comparison studies (Saettler 2000) and that a key finding from these studies was little or no significant difference between media and an identified need to change the focus of research (Reiser 2001). The continuation of comparison studies ignores the significant bodies of research to suggest that students lean equally well regardless of the technology or media used (Russell 1999) and that it is the instructional methods, not the technology, that influence student learning (Clark 1994).

The technology-mediated learning hype cycle – perpetual infancy

This section describes an observable technology-mediated learning hype cycle in the history given above and argues that this on-going cycle contributes directly to the on-going perpetual infancy of technology-mediated learning. The simple cycle used here consists of three steps:

  1. growing revolution;
    A new technology is created and identified as a potential solution to a number of perceived problems with learning and teaching. Interest is generated in the application of the technology and a growing technologist’s alliance – in the form of researchers, educators, professional associated, vendors and instructional technology support people – is formed. The technology promises to revolutionise education.
  2. minimal impact; and
    It is recognised that the impact of the technology has been somewhat more problematic and limited. Stories of failure and criticism of the technology arise. Use of the technology achieves a stable level of use – perhaps non.
  3. resolution of dissonance.
    The failure of the expected revolution is explained away through rationalisation and allocation of blame to poor leadership, poor implementation, intransigence of followers, limited resources or the wrong technology – which often leads to the choice of a new technology and a repetition of the cycle.

The above is a very simple description of a cycle that is talked about in more detail about a number of authors in technology in education (van Dam 1999; Reiser 2001) and in other related fields such as management fads in higher education (Birnbaum 2000), and information technology (Fenn and Raskino 2008). The cycle described above draws mostly on the work of Reiser (2001) and Birnbaum (2000). Table ?? provides an illustration of this cycle for a small sub-set of the technologies discussed in the above history. It uses quotes from associated literature to represent the different phases in the cycle for each technology.

Note: In the thesis, the following tables are joined into one large table. That doesn’t work on the web, or at least within this blog template. So the table has been split

Evidence for TML hype-cycle for Audio-visual
Stage Audio-visual
Growing revolution “Books will soon be obsolete in the schools…It is possible to teach every branch of human knowledge with the motion picture. Our school system will be completely changed in the next ten years.” Thomas Edison from Saettler (1968)
“Radio may come as a vibrant and challenging textbook of the air.” Darrow quoted in (Reiser 2001)
Minimal impact Cuban (1986) suggests that in the 20 years following the peak of expectations in the 1930s, radio had very little impact on instructional practices.
“The role played in formal education by instructional television has been on the whole a small one.., nothing which approached the true potential of instructional television has been realized in practice . . . . With minor exceptions, the total disappearance of instruc tional television would leave the educational system fundamentally unchanged.” Carnegie Commision on Educational Television quoted in (Reiser 2001)
Resolution of dissonance Resier (2001) reports on literature identifying teacher resistance, the expense of installing and maintaining television sets, and the inability of television alone to create the various conditions necessary for student learning as the reasons behind the limited adoption of instructional television

Evidence for TML hype-cycle for teaching machines
Stage Teaching machines
Growing revolution “There are more people in the world than ever before, and a far greater part of them want an education. The demand cannot be met simply by building more schools and training for more teachers. Education must become more efficient. …. In any other field a demand for increased production would have led at once to the invention of labor-saving capital equipment.” (Skinner 1958)
Minimal impact
Resolution of dissonance “The intellectual inertia and conservatism of educators who regard such ideas as freakish or absurd, or rant about the mechanization of education” Pressey quoted in (Petrina 2004)
“Pressey’s machines succumbed in part to cultural inertia; the world of education was not ready for them. But they also had limitations which probably contributed to their failure.” (Skinner 1958)
“By the 1960s, interest in “teaching machines” evolved into “programmed instruction” with the realization that program was more important than the machine” (Saettler 2000)

Evidence for TML hype-cycle for computer-based learning
Stage Computer-based learning
Growing revolution “the processing and the uses of information are undergoing an unprecedented technological revolution……One can predict that in a few more years millions of school-children will have access to what Philip of Macedon’s son Alexander enjoyed as a royal prerogative: the personal services of a tutor as well-informed and responsive as Aristotle.” (Suppes 1966)
Minimal impact
Resolution of dissonance “However, in spite of the work that had been done, by the end of the 1970s, CAI had had very little impact on education (Pagliaro, 1983)” (Reiser 2001)
“Learning management systems have emerged from the ashes of early mainframe-based CMI systems, thanks to the LAN, WAN, Intranet and Internet, driven by large databases in servers.” (Szabo and Flesher 2002)

Evidence for TML hype-cycle for personal computers
Stage Personal computers
Growing revolution “the computer is going to be a catalyst of very deep and radical change in the educational system” (Papert 1984)
Minimal impact By 1995 substantial numbers of teachers report little or no use of computers for instructional purposes and, where used, computer use was primarily used for drill and practice and the teaching of skills such as word-processing (Reiser 2001).
Resolution of dissonance

Evidence for TML hype-cycle for e-learning
Stage e-learning
Growing revolution Green and Hayward (1997) suggest it will have a profound effect on the structure of higher education. Peter Drucker suggested that within 30 years, big university campuses will be relics (Lenzer and Johnson 1997). While Duderstadt et al (2002) suggest the technology and emerging technology threaten the survival of the current form of the university. Peters (2002) suggests that e-learning will force a radical restructuring of our educational institutions.
Minimal impact “In this sense, then, I do not share the view of Harasim et al. (1995) or Peters (2002) when they argue that e-learning is a “paradigm shift.” Rather, it is old wine in new bottles, at least at present.” (Bates 2004)
“Indeed, the formal use of computer technologies in many areas of higher education could best be described as sporadic, uneven, and often ‘low level’” (Selwyn 2007)
“One step ahead for the technology, two steps back for the pedagogy” (Mioduser, Nachmias et al. 1999).
Resolution of dissonance “In particular, there is criticism that institutions and governments are not doing enough to prepare managers, teachers, instructors, and students for the organizational, institutional, and cultural changes needed to make e-learning successful” (Bates 2004)

A question that arises from the recognition of the technology-mediated learning hype cycle is whether or not it will happen with e-learning. Whelan (2005) asks won’t the same disappointment occur with web-based technologies? For Reiser (2001) and Whelan (2005) the answer is to suggest that e-learning will be different due to the improved affordances provided Internet-based technologies to support learning. In particular, Whelan (2005) suggests that the two-way interactive nature of the technology allows for learners to explore multiple perspectives, in multiple formats and puts them in charge of constructing their learning experience. There appear to be significant problems with this more positive view including, but not limited to: ignorance of the need to respond to on-going change in e-learning (see the Consisting in change section above) and forgetting the “grammar of school”.

In talking about the school system – the extension to universities seems appropriate -Tyack and Cuban (1995) propose the idea of a grammar of school as an explanation for difficulties faced when attempting to implement reforms. Papert (1995) describes school as a system in which the major components – curriculum content, epistemological framework, organisational structure and knowledge technology – have developed mutually supportive and matched forms. This grammar of school means that any change is seen as nonsensical as an ungrammatical utterance (Cavallo 2004). In addition to “feeling wrong”, Papert (1995) suggests it is possible for people that accept the grammar of school to interpret, and consequently transform drastically, the ungrammatical utterance into the nearest utterance that fits with the grammar of school.

The two traditional methods of teaching that remain at the forefront of teaching with technology are the lecture and the blackboard (Miller 2000). As shown in the usage of e-learning section (section 2.1.4) the majority of current usage of industrial e-learning focuses on content distribution, it continues to “use new technologies in traditional ways, repeating past inadequacies and constraints with the new media” (Miller 2000). Papert’s (1995) explanation for this is that the new “knowledge technology” is being pulled back by the other components in the system to maintain the grammar of the school.

Carvallo (2004) suggests that the problem is not with knowledge about learning, but with the limitations of models for growth and change at the systemic level. In terms of technology-mediated learning within universities it is not difficult to see the problems. First, universities are inherently resistant to change (Jones and O’Shea 2004). But rather engage in processes that focus on how to encourage change within the grammar of school, most approaches to e-learning concentrate on the features, technical details and pricing of different systems. (Britain and Liber 2000), and focus on technical, financial and administrative aspects (Coates, James et al. 2005). The models used view education and its reform as a sequence of depersonalized, decontextualised steps carried out by willing, receptive and non-transforming agents (Cavallo 2004). The focus has not been on the human dimensions, scaling-up and embedding of innovation and the associated management of change (Tham and Werner 2005). There has been little attention paid to thinking about systemic change or developing alternative models for the development of learning environments and making changes in the grammar of school (Cavallo 2004).


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Bates, T. (2004). The promise and myths of e-learning in post-secondary education. The Network Society: A Cross-cultural Perspective. M. Castells. Cheltenham, UK, Edward Elgar: 271-292.

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

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Phd Update #8 – steaming ahead

The week since my last PhD update has been a good one. The most productive (in terms of completed first drafts of thesis sections) since I started this series of updates. I feel I’m getting into a routine and slowly developing pragmatic ideas and techniques for producing a thesis that is “good enough”. In reality, I’m probably still to far up the scale towards “too good”, but I’m getting there. It’s a journey.

What I’ve done

I almost completed all of what I predicted I would complete. I said I wanted to have posted to this blog material on:

  • paradigms of e-learning. DONE!
  • Usage of e-learning: quantity and quality (which has had a couple of comments – including a typo fix). DONE!
  • Lessons from past experience
    This one is just about complete, a couple of paragraphs to go. I got sidetracked by this. I aim to post this section tonight, or at the latest tomorrow night.

In addition to the above, I’ve authored the following blog posts that are somewhat related:

What I’ll do for next

Essentially, I have finised the “Past Experience” component of the Ps Framework. Time to pick another component. So, “Place” it is and probably “Purpose” after that. The aim is that by the end of next week I will have:

  • Nutted out a structure for “Place”.
  • Posted a first draft for “Place”.

I’m also going to try and aim for having similar completed for “Purpose”. It’s time to speed this process up quite a lot. Not sure I can do it, but the intent needs to be there. Two components of the Ps Framework is still probably too slow. We’ll see next week.

Models of growth – responding to the grammar of school

This post serves as a brief placeholder of ideas and also to remind me to follow up further on this paper (Cavallo, 2004). The paper seems to offer a very interesting and informed perspective on issues that are of great interest to me, including the “Process” used in implementing e-learning within Universities and the “grammar of school”.

Even though I’ve only skimmed the paper, I would suggest that anyone currently involved in a Moodle implementation should really take the time to read this paper.

Some quick quotes follow

The problem

David Tyack and Larry Cuban postulated that there exists a grammar of school, which makes deviation from our embedded popular conception of school feel as nonsensical as an ungrammatical utterance [1]. They describe how reform efforts, whether good or bad, progressive or conservative, eventually are rejected or denatured and assimilated. Reform efforts are not attempted in the abstract, they are situated in a variety of social, cultural and historical contexts. They do not succeed or fail solely on the basis of the merit of the ideas about learning, but rather, they are viewed as successful based upon their effect on the system and culture as a whole. Thus, they also have sociological and institutional components — failure to attend to matters of systemic learning will facilitate the failure of the adoption of the reforms.

Telling people they are bad

Just as one cannot merely tell a child his thinking is incorrect
and then expect everything to fall into place, so too we cannot expect simply to tell a school, a school system, a country, that its schools are wrong and how to fix them.

Take this to the middle level, you can’t go along to an academic and say his/her use of e-learning is bad, and expect them to change it.

How to improve the practice of learning and teaching

As we see it, real change is inherently a kind of learning. For
people to change the way they think about and practice education, rather than merely being told what to do differently, we believe that practitioners must have experiences that enable appropriation of new modes of teaching and learning that enable them to reconsider and restructure their thinking and practice. The limitations inherent in existing systems based upon information transfer models are as impoverished in effecting systemic development as they are in child development.

This perspective connects nicely to the ideas of reflective alignment

So obviously, the author is intelligent, he agrees with me! The fact he was/is co-director of the MIT Media Lab’s Future of Learning group also suggests a modicum of intelligence.

Usage of e-learning – quantity

The following post is a continuation of posts from the “Past Experience” section of chapter 2 of my thesis. This part of chapter 2 is looking at the usage of e-learning within higher education. A previous post provided the introduction to the section and also covered usage from a quality perspective – i.e. how good is the learning and teaching.

The aim of this post is to briefly examine what is known about the quantity of usage of e-learning within institutions. It does this by focusing on three different perspectives:

  • Institutional – how many universities have adopted an LMS (just about all).
  • Course of faculty – how many courses/staff are using an LMS (was low, but now increasing)
  • Service or feature – how many of the features of an LMS are being used in those courses (predominantly content distribution).

As with the previous posts this is a summary. Consequently I have probably missed aspects and nuances. If you have any suggestions please fire away.

Also, as with other posts, I have not done a good proof-reading job on the content before I post them on the blog. At the moment, my emphasis is getting the content done as quickly as possible. Proof-reading will need to wait until later, when I have the energy and state of mind. If you pick up any, let me know.

Quantity – how much is done

The previous section provided an overview of the quality of usage of industrial e-learning. This section seeks to examine the quantity of usage of industrial e-learning and will do so at three levels: organisational, courses and academics and features. The organisational section briefly examines what level of adoption industrial e-learning, in the form of LMSes, has amongst individual universities. The primary unit of teaching within a university and the primary organising construct within the LMS is that of a course. Typically the design and nature of each course is the responsibility of a particular academic. The course and academics examines adoption of LMSes at this level. Finally, each LMS provides a broad array of features and services that can be used to support learning. The features section examines how broadly these features are adopted within courses.


The almost universal approach to the adoption of e-learning at universities has been the implementation of Learning Management Systems (LMS) such as Blackboard, WebCT, Moodle or Sakai (Jones and Muldoon 2007). Despite the associated complexities and risks almost every university seems compelled to have one (Coates, James et al. 2005). CMS have become perhaps the most widely used educational technologies within universities, behind only the Internet and common office software (West, Waddoups et al. 2006). Harrington, Gordon et al (2004) suggest that higher education has seen no other innovation result in such rapid and widespread use as the CMS. By 2005 almost every higher education institutions is or has plans to make use of a CMS (Salmon 2005). West, Waddoups et al (2006) express surprise at how quickly CMS have been adopted by universities, institutions which are know for reluctance towards change. Oblinger and Kidwell (2000) comment that the movement by universities to online learning was to some extent based on an almost herd-like mentality. Even though the perceived drivers for CMS are contestable, the perceived need for a CMS seems to be entrenched in the higher education sector (Wise and Quealy 2006).

Course Management Systems (CMS) are an essential feature of instructional technology at universities (Warger 2003). The 2003 Campus Computing project reports that more than 80% of United States universities and colleges utilize a CMS (Morgan 2003). Elgort (2005) cites work that indicates that 86% of 102 UK universities are using a CMS; all 18 surveyed New Zealand based institutions used a CMS; and all 33 Australian universities participating in a survey also used a CMS. Smissen and Sims (2002) found that 34 of the 37 Australian universities were using one of two CMS – Blackboard or WebCT. The almost universal adoption within the Australian higher education sector, a sector that has traditionally aimed for diversity and innovation, of just two commercial LMSs, which are now owned by the same company, is somewhat surprising (Coates, James et al. 2005). The mindset in recent times has focused on the adoption of the one-size-fits-all LMS (Feldstein 2006).


Even with the universal implementation of the LMSs, the level of adoption of those systems within many institutions has been limited (Jones and Muldoon 2007). In 2002, Lynch, reported in Shea et al (2005), estimates that while eighty percent of US-based four year colleges provide faculty access to LMSes, only twenty percent of staff use them in their courses. Vodanovich and Piotrowski (2005) report that of the 74% of faculty surveyed as being positive towards using the Internet for education, 70% view it as effective but only 47% actually used it for education. Other best practice implementations, recommended by LMS vendors, report no more than 55% staff adoption rates (Sausner 2005). Most universities are struggling to engage a significant percentage of students and staff in e-learning (Salmon 2005).

Even with a concerted effort to encourage adoption of the LMS, less than two-fifths of faculty in some disciplines use the LMS, and even then usage is limited to a small number of tools (Yohon, Zimmerman et al. 2004). Experience from one Australian university shows that as late as the second half of 2006, after over six years of institutional use of an LMS, only just over half of all courses offered had course websites (Jones and Muldoon 2007). Badge et al (2005) report about sixty percent adoption amongst staff but use is almost entirely for content distribution with some limited use of online assessment.


Coates et al (2005) suggest that it is the uptake and use of features, rather than their provision, that really determines their educational value. While there is not sufficient research into LMS usage for a formal meta-analysis, patterns have begun to appear (Malikowski 2008). A pattern that fits with the content-centric focus of the quality of industrial e-learning observed in the previous section. The usage pattern observed by West et al (2006) is that instructors rarely adopt all of the features of an LMS. Malikowski (2008) found the nearly half of all faculty members use one feature or less with those using multiple features significantly more likely to have experience with interactive technologies. Rather than adopt all features of an LMS, instructors face many smaller adoption decisions as they perform a cost/benefit analysis of each individual feature (West, Waddoups et al. 2006).

Malikowski et al (2007) propose a model for synthesising research into LMS feature usage that consists of five categories of feature, a suggested order in which features are adopted and an indication of how often features are used. The model is shown in Figure 1.

Malikowski Flow Chart

Figure 1 – Flowchat of LMS feature usage research categories (adapted from Malikowski, Thompson et al. 2007)

The five categories in the Malikowski et al (2007) model are:

  1. transmitting course content;
    Including the provision of files, grade information, and announcements to the entire class.
  2. Creating class interactions;
    Interaction between course members either synchronously or asynchronously including LMS email, discussion forums, interactive chat etc.
  3. Evaluating students;
    Tools, such as quizzes and assessment drop boxes, that aid in the evaluation of student learning.
  4. Evaluating courses and instructors;
    Features, primarily surveys, that enable the evaluation of the course or instructor.
  5. Computer-based instruction;
    Based on very simple features, when compared to much earlier research mentioned in a previous section. Features in current LMS relate to the adaptive release of content or other services based on student activity.

The Malikowski et al (2007) model also identifies these categories based on level of observed use with transmitting content most used; evaluating students and creating class interactions moderately used; and evaluating courses and instructions and computer-based instruction rarely used. This is illustrated through a series of tables that draw on usage figures from research literature. Table 1 is an adaptation and summary of this work. The last two categories are not shown in Table 1 due to extremely limited reported data on usage.

Note: In the thesis this is one table. However, that doesn’t work on the narrow confines of the blog. So I have to break it up into 3 different tables – which is what Malikowski et al (2007) did. They actually discussed in much more detail each category.

Location N Transmitting content
>38 American institutions (Woods, Baker et al. 2004) 862 86% Not reported 59%
University of Wisconsin-Milwaukee (Morgan, 2003) 342 80% 81% 57%
University of Wisconsin-Whitewater (Morgan, 2003) 276 67% 87% 47%
University of Wisconsin-Stout (Morgan, 2003) 166 71% 67% 58%
University of Nebraska at Lincoln (Ansorge and Bendus 2003) 192 69% not reported not reported
Private US University (Dutton, Cheong et al. 2004) 191 1st and 2nd of 17 5th of 17 9th of 17

Table 1 – Summary of LMS usage for transmitting content (adapted from Malikowski, Thompson et al. 2007)
a Results were provided for multiple semesters, only the most recent semester (spring 2002) shown here.
b Results presented as a ranked list of 17, most used features first.

Location N Creating class interaction
Asyncrhonous Synchronous
38 American institutions (Woods, Baker et al. 2004) 862 25% 3%
University of Wisconsin-Milwaukee (Morgan, 2003) 342 28% “Low levels”
University of Wisconsin-Whitewater (Morgan, 2003) 276 28% “Low levels”
University of Wisconsin-Stout (Morgan, 2003) 166 24% “Low levels”
University of Nebraska at Lincoln (Ansorge and Bendus 2003) 192 17% 1%
Private US University (Dutton, Cheong et al. 2004) 191 5th of 17 Last of 17

Table 2 – Summary of LMS usage for creating class interaction (adapted from Malikowski, Thompson et al. 2007)

a Results were provided for multiple semesters, only the most recent semester (spring 2002) shown here.
b Results presented as a ranked list of 17, most used features first.

Location N Evaluating students
Quiz Drop box
38 American institutions (Woods, Baker et al. 2004) 862 75% never in exams
59% never for quizzes
56% never use
University of Wisconsin-Milwaukee a (Morgan, 2003) 342 25% used assessments Not reported
University of Wisconsin-Whitewater a (Morgan, 2003) 276 21% used assessments Not reported
University of Wisconsin-Stout a (Morgan, 2003) 166 27% used assessments Not reported
University of Nebraska at Lincoln (Ansorge and Bendus 2003) 192 Not reported Not reported
Private US University b (Dutton, Cheong et al. 2004) 191 15th of 17 Not reported

Table 3 – Summary of LMS usage for evaluating students (adapted from Malikowski, Thompson et al. 2007)
a Results were provided for multiple semesters, only the most recent semester (spring 2002) shown here.
b Results presented as a ranked list of 17, most used features first.


Ansorge, C. and O. Bendus (2003). The pedagogical impact of course management systems on faculty, students, and institution. Web-based learning: What do we know? Where do we go? R. Benning, C. Horn and L. PytlikZillig. Greenwich, CT, Information Age Publishing: 169-190.

Badge, J. L., A. J. Cann, et al. (2005). "e-Learning versus e-Teaching: Seeing the Pedagogic Wood for the Technological Trees." Bioscience Education E-Journal 5.

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

Dutton, W., P. Cheong, et al. (2004). "An ecology of constraints on e-learning in higher education: The case of a virtual learning environment." Prometheus 22(2): 131-149.

Elgort, I. (2005). E-learning adoption: Bridging the chasm. Proceedings of ASCILITE’2005, Brisbane, Australia.

Feldstein, M. (2006). Unbolting the chairs: Making learning management systems more flexible. eLearn Magazine. 2006.

Harrington, C., S. Gordon, et al. (2004). "Course Management System Utilization and Implications for Practice: A National Survey of Department Chairpersons." Online Journal of Distance Learning Administration 7(4).

Jones, D. and N. Muldoon (2007). The teleological reason why ICTs limit choice for university learners and learning. ICT: Providing choices for learners and learning. Proceedings ASCILITE Singapore 2007, Singapore.

Malikowski, S. (2008). "Factors related to breadth of use in course management systems." Internet and Higher Education 11(2): 81-86.

Malikowski, S., M. Thompson, et al. (2007). "A model for research into course management systems: bridging technology and learning theory." Journal of Educational Computing Research 36(2): 149-173.

Morgan, G. (2003). Faculty use of course management systems, Educause Centre for Applied Research: 97.

Oblinger, D. and J. Kidwell (2000). "Distance learning: Are we being realistic?" EDUCAUSE Review 35(3): 30-39.

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.

Sausner, R. (2005). Course management: Ready for prime time? University Business.

Shea, P., A. Pickett, et al. (2005). "Increasing access to Higher Education: A study of the diffusion of online teaching among 913 college faculty." International Review of Research in Open and Distance Learning 6(2).

Smissen, I. and R. Sims (2002). Requirements for online teaching and learning at Deakin University: A case study. Eighth Australian World Wide Web Conference, Noosa, Australia.

Vodanovich, S. J. and C. Piotrowski (2005). "Faculty attiudes towards web-based instruction may not be enough: Limited use and obstacles to implementation." Journal of Educational Technology Systems 33(3): 309-318.

Warger, T. (2003, July 2003). "Calling All Course Management Systems." University Business  Retrieved 30 December, 2006, from

West, R., G. Waddoups, et al. (2006). "Understanding the experience of instructors as they adopt a course management system." Educational Technology Research and Development.

Wise, L. and J. Quealy. (2006, May, 2006). "LMS Governance Project Report." from

Woods, R., J. Baker, et al. (2004). “Hybrid structures: Faculty use and perception of web-based courseware as a supplement to face-to-face instructions.” Internet and Higher Education 7(4): 281-297.

Yohon, T., D. Zimmerman, et al. (2004). "An exploratory study of adoption of Course Management Systems and accompanying instructional changes by faculty in the Liberal Arts and Sciences." Electronic Journal of e-Learning 2(2): 313-320.

E-learning usage – quality

The following post is a continuation of posts from the “Past Experience” section of chapter 2 of my thesis. It follows on from previous posts including: Ps Framework, History of technology-mediated learning, and the paradigms of e-learning.

I’m currently working on the “e-learning usage” section. The aim here is to look at the quality and quantity of usage of e-learning over the last 10 years or so – i.e. in the industrial e-learning paradigm. The quality and quantity overviews are part of the same section, so the following includes the current introduction to the overall section and then gets into the discussion of quality. Hopefully the quantity section will be up ASAP.

As always, I’m more than happy to here suggestions for improvement, disagreement or any comments in general.

Eventually, at some stage in the thesis, I will be arguing that the reason behind the less than stellar quality of most industrial e-learning is due to a combination of over-emphasis on the technology and its promise; and an on-going ignorance of what it takes to improve the majority of learning and teaching at a university. In particular, I think I’ll argue that this is the same ignorance that results in the majority of face-to-face teaching suffering from the same limited quality and that the current practices around industrial e-learning, rather than helping, are actually making things worse. At least for the majority of academics, though not the “long rangers” or Edupunks.

Industrial e-learning usage – quantity and quality

This section seeks to summarise what is known about the usage of e-learning within higher education. As shown in the previous section, the use of e-learning within higher education can be traced back to around the early 1990s. Rather than examine the entire history of e-learning, this section will focus on the usage of the predominant and current e-learning paradigm – industrial e-learning. This section examines usage of industrial e-learning from two perspectives. The first perspective is that of the quality of the learning experience for all participants. The second perspective is in terms of the quantity of usage, in terms of number of staff and students, organizations and the tools they use. In summary, while there has been widespread adoption of industrial e-learning by institutions, the quality of the e-learning is questionable and the level of use, while growing, is still not deep nor broad.


Research into teaching within higher education has developed a rich body of knowledge that links the quality of student learning outcomes with the conceptions of learning and a link between the conceptions of teaching held by academics and their approaches to teaching (Kember and Kwan 2000; Norton, Richardson et al. 2005; Eley 2006; Gonzalez 2009). Kember (1997) identified two main orientations to teaching and five underlying conceptions positioned as well-defined points on a continuum. The two main orientations are:

  1. teacher-centered/content-oriented; and
    The focus is on the content to be taught and most associated with a focus on what the teacher does. Students are considered to be passive recipients of information.
  2. student-centered/learning-oriented.
    The focus is on the learning process and most associated with a focus on what the student does. Students are seen as actively involved in the construction of their own learning.

Figure insert cross ref is a representation of Kember’s (1997) multiple-level categorisation model. An important point is that a transition from content-oriented to learning-oriented is a significant transition, while moving along the spectrum between the two conceptions under-pinning each orientation is relatively easy (Kember 1997).

Kember categorisation model of conceptions of teaching

Figure 1 – A multiple-level categorisation model of conceptions of teaching (Kember 1997)

In terms of which of these orientations is of the higher quality, it seems that the research literature is in increasing agreement. Herrington et al (2005) offer a 1974 quote from Olson and Bruner: “The acquisition of knowledge as the primary goal of education can be seriously questioned”. A model of learning that focuses on the deep engagement of students with complex and realistic tasks is preferable to a model that focuses on information provision (Herrington, Reeves et al. 2005). Theories of learning that currently hold greatest sway are those based on constructivist principles that suggest learning occurs through the active construction of knowledge supported by various perspectives within meaningful contexts with social interactions playing a critical role (Oliver 2000). These theories fit directly within Kember’s (1997) student-centred/learning-oriented orientation to teaching.

Given this recognition and fit it would be expected that the primary use of e-learning would be to support a student-centered/learning oriented orientation to teaching. In fact, it appears that the teacher-centred/content oriented dominants the practice of industrial e-learning. Much of the current research shows that academics use LMSes primarily to transmit course documents to students (Morgan 2003; Dutton, Cheong et al. 2004; Malikowski, Thompson et al. 2006). In the rush for universities to place courses on the Internet it is evident that the acquisition of knowledge remains the paramount goal for many educators (Herrington, Reeves et al. 2005). With few exceptions, almost all universities that have adoped a VLE have taken an approach where the VLE substitutes for existing media and have retained existing pedagogy (Salmon 2005) based on information distribution. For example, Dutton et al (2004) founding their study that most uses were anchored in traditional approaches to teaching with the technology primarily used as a substitute for the copier or projector.

Reeves, cited in Nichols (2003) describes the use of technology in education as far from innovative. From the evidence it is clear that there is an increasing use of industrial e-learning, however, there is not widespread change in pedagogy (Browne, Jekins et al. 2006). Industrial e-learning, for the most part, has involved fairly unsophisticated use of the available tools (Benson and Palaskas 2006). What limited use of technology there has been has sought to extend classroom pedagogy, either through the modest addition of resources or to extend the physical reach of the seat time-based teaching paradigm (Duderstadt, Atkins et al. 2002). Evidence suggests that universities are primarily using the LMS for administrative purposes with only a limited impact on pedagogy (OECD 2005). The vase majority of e-learning uses the same design and delivery model as on-campus courses (Twigg 2001).

Consequently, it is possible to suggest that the impact of industrial e-learning on the quality of learning has been somewhat limited. Harrington et al (2004) There is no evidence to suggest that adoption of an LMS leads to any increase in student learning to increases in the quality of teaching. Instead, the primary advantage behind use of an LMS was considered to be convenience to students (Harrington, Gordon et al. 2004). The value of e-learning is in maximising access to training opportunities and falls short of the potential for engaging learners in new ways (Pittard 2004). On most campuses the LMS is used to supplement traditional classroom courses (Warger 2003). In stark contrast to the imaginative and informal uses that students and faculty make of technologies, formal use of technology in most of higher education can be best described as sporadic, uneven and often low-level (Selwyn 2007).

However, given that web-based teaching is still less than ten years old, the application of the web to teaching and learning is still evolving (Bates 2004). Research into how people learn online is still in its infancy and more research is needed in order to understand the design of online learning that is engaging and effective (Herrington, Reeves et al. 2005). Research into the pedagogical issues that arise from the implementation of an LMS is still in its infancy (Coates, James et al. 2005). There is a need for further research to refine strategy dimensions defining approaches to teaching using the web (Gonzalez 2009). There are suggestions that no one approach, theory or solution is adequate for the design of e-learning (McLoughlin and Luca 2001).


Bates, T. (2004). The promise and myths of e-learning in post-secondary education. The Network Society: A Cross-cultural Perspective. M. Castells. Cheltenham, UK, Edward Elgar: 271-292.

Benson, R. and T. Palaskas (2006). "Introducing a new learning management system: An institutional case study." Australasian Journal of Educational Technology 22(4): 548-567.

Browne, T., M. Jekins, et al. (2006). "A longitudinal perspective regarding the use of VLEs by higher education institutions in the United Kingdom." Interactive Learning Environments 14(2): 177-192.

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

Duderstadt, J., D. Atkins, et al. (2002). Higher education in the digital age: Technology issues and strategies for American colleges and universities. Westport, Conn, Praeger Publishers.

Dutton, W., P. Cheong, et al. (2004). "The social shaping of a virtual learning environment: The case of a University-wide course management system." Electronic Journal of e-Learning 2(1): 69-80.

Eley, M. (2006). "Teachers’ conceptions of teaching, and the making of specific decisions in planning to teach." Higher Education 51(???): 191-214.

Gonzalez, C. (2009). "Conceptions of, and approaches to, teaching online: a study of lecturers teaching postgraduate distance courses." Higher Education 57(3): 299-314.

Harrington, C., S. Gordon, et al. (2004). "Course Management System Utilization and Implications for Practice: A National Survey of Department Chairpersons." Online Journal of Distance Learning Administration 7(4).

Herrington, J., T. Reeves, et al. (2005). "Online Learning as Information Delivery: Digital Myopia." Journal of Interactive Learning Research 16(4): 353-367.

Kember, D. (1997). "A reconceptualisation of the research into university academics’ conceptions of teaching." Learning and Instruction 7(3): 255-275.

Kember, D. and K.-P. Kwan (2000). "Lecturers’ approaches to teaching and their relationship to conceptions of good teaching." Instructional Science 28(5): 469-490.

Malikowski, S., M. Thompson, et al. (2006). "External factors associated with adopting a CMS in resident college courses." Internet and Higher Education 9(3): 163-174.

McLoughlin, C. and J. Luca (2001). Quality in online delivery: What does it mean for assessment in e-learning environments? 18th Annual Conference of the Australian Society for Computers in Learning in Tertiary Education, Melbourne.

Morgan, G. (2003). Faculty use of course management systems, Educause Centre for Applied Research: 97.

Nichols, M. (2003). "A theory for eLearning." Journal of Educational Technology and Society 6(2): 1-10.

Norton, L., J. Richardson, et al. (2005). "Teachers’ beliefs and intentions concerning teaching in higher education." Higher Education 50(????): 537-571.

OECD (2005). E-Learning in Tertiary Education: Where do we stand? Paris, France, Centre for Educational Research and Innovation, Organisation for Economic Co-operation and Development.

Oliver, R. (2000). When teaching meets learning: Design principles and strategies for Web-based learning environments that support knowledge construction. ASCILITE’2000, Coffs Harbour.

Pittard, V. (2004). "Evidence for E-learning Policy." Technology, Pedagogy and Education 13(2): 181-194.

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.

Selwyn, N. (2007). "The use of computer technology in university teaching and leanring: a critical perspective." Journal of Computer Assisted Learning 23(2): 83-94.

Twigg, C. A. (2001). "Innovations in Online Learning: Moving Beyond No Significant Difference."   Retrieved 30 December, 2006, from

Warger, T. (2003, July 2003). "Calling All Course Management Systems." University Business  Retrieved 30 December, 2006, from

Pedagogy of the impressed – how teachers become victims of technology vision

I’ve just skimmed through a recent paper by Convery (2009) titled “The pedagogy of the impressed: how teachers become victims of technology vision”. This paper resonates quite strongly with a growing sense of concern I have about simplistic, ill-informed practices around e-learning. In particular, there are (for me at least) direct connections with some of my recent posts about how a new LMS will improve L&T, the paradigms of e-learning, the fad cycle in higher education and its application to technology-mediated learning, the technologists alliance (more on this soon) and the idea of technological gravity and technology I, II and III.

The final paragraph of Convery (2009) includes the following

Perhaps the most important single step we could take in researching technology so that it enables rather than oppresses teachers’ practices and professional identities is to avoid engaging with – and thus endorsing – the simplistic rhetoric of makeover politics, and such discourse is frequently apparent in explanations about how ICT can ‘transform’ education. Casual use of the term ‘transformation’ ensures any discussion becomes irrationally polarised, as it incites a totalising vision of an ICT-enriched world, offering technology as the simple and immediate remedy for current inadequate practice. It is the duty of researchers to be sceptical, and informed scepticism is the basis for recognising how technology can make a significant contribution to a learning experience Thus, one must resist subscribing to the easy refrain that ICT can ‘transform’ education as this simply creates a dualistic framework, in which writers simplistically link manifest problems with hypothesised solutions, and invite readers to see ICT as providing ‘the answer’. There are many practical methodological steps to be taken in ensuring the quality of educational ICT research, and rejecting seductive but disabling rhetoric is fundamental to ensuring improved research findings are considered in their human context and educational complexity.

I am seeing an increasing rise of a “technologists alliance” that is adopting Technology I or II views and claiming that X will radically improve learning and teaching. It’s almost becoming a paradigm in places, it is excluding alternate perspectives.


Convery, A. (2009). “The pedagogy of the impressed: how teachers become victims of technology vision.” Teachers and Teaching 15(1): 25-41.

The paradigms of e-learning

I’m currently working on chapter 2 of my thesis – the literature review. Mine is using the Ps Framework as the organising structure and also as part of the contribution of the thesis. I’m currently working on the “Past Experience” component of the Ps Framework. Recently, I posted the History of technology mediated learning section. It provides a brief overview of technology-mediated learning prior to e-learning – defined as using the Internet.

In writing that section it became readily apparent from the waves of different technology-mediated learning that nothing is ever forever, and yet many of the folk writing within a particular wave seem to think it will. At the same time, I’ve been reading and observing folk talking about the current wave of e-learning focusing on learning management systems (LMS) in the same way. The assumption that there is no other way to approach e-learning.

This strikes me as troubling and very short-sighted. So I’ve been tempted to include the following in the literature review to highlight that the current LMS approach to e-learning is just one of a collection of paradigms. That we will move onto something different and that a responsible and informed organisation would be aware of and planning for this paradigm change.

Not sure whether this will end up in the thesis. Still has some significant room for improvement. For example, connecting the increasing pressures towards the corporatisation of universities with the rise of the industrial paradigm. Or perhaps whether the Edupunk movement fits with post-industrial paradigm or whether it is a continuation of the lone ranger paradigm. Not to mention I haven’t given the text a thorough proof read.

Paradigms of e-learning

E-learning, as defined here, rose to widespread use during the 1990s with, as shown in the previous section, connections with a range of different and prior movements within the history of technology-mediated learning. This section identifies and seeks to understand a number of different paradigms, movements or discourses within the rise of e-learning. The aim is to illustrate that the models and perspectives underpinning and informing e-learning, like those of the various movements within technology-mediated learning, are changing and that with this change comes different perspectives about what is appropriate, what works and importantly how to best support e-learning. The six paradigms described here are meant as illustrative examples to achieve the purpose of recognising that different paradigms of e-learning have and will continue to exist and that understanding this offers insight for the design and support of e-learning. It is likely that it may be possible to identify additional paradigms and additional dimensions of these paradigms, but that is beyond the scope of this thesis.

A “paradigm” can be defined as the set of assumptions adopted by a professional community in order to allow its members to share perceptions and engage in commonly shared practices (Hirschheim and Klein 1989). The paradigm selects the ideas to accepted and rejected and grants privilege to certain logical operations to the deteriment of others (Morin 1999). Similarly, a discourse organises and constrains what can be said and done. Different discourses, like paradigms, may contain a distinctive set of rules and procedures which govern what counts as meaningful or senseless, true or false, normal or abnormal (Davis and Sumara 2006). Paradigms and discourses provide a particular framing for the problem and how it is understood. The common set of assumptions held by a community of a problem provide a vision of what the technology should and how progress should be measured (Allen 2000).

Not being aware of the existence and significant difference between paradigms can hinder evolution. Apart from embodying a particular way of understanding the world, the influence of a paradigm to e-learning also creates an inertia within organistions that can slow down moving from one paradigm to another. Allen (2000) makes the point that communities, such as organizations, make a social commitment through decisions to employ resources that are difficult to reverse and can explain how particular innovation paths are enabled, and others are constrained. For example, Bates (2008) suggests that universities with a history of operating within the paradigm of large scale autonomous distance education have been slower in adopting e-learning.

The following table provides a summary of the six paradigms that are described in more detail below. The time period for each paradigm provides a broad indication of when the particular paradigm was most dominant within e-learning. It is possible to find evidence of some paradigms, or aspects of some paradigms, throughout the history of e-learning. It is suggested that the “post-industrial” paradigm has not yet achieved, and may not achieve, a level of dominance.

Period Title Description
Late 1980s-late 1990s Text-based CMC Arising out of the CMC movement. Focus on using Internet for collaboration/communication by using the Internet to address issues with proprietary systems. Proprietary CMC systems ported to the Internet.
Early 1990s to mid-1990s Lone ranger Individual academics, generally not from a CMC paradigm, start using Internet tools as part of their teaching. Including pre and post Web.
Cottage industry mid-1990s-1999/2000 Lone ranger attempts leveraged by the construction of small-scale systems to support the use of e-learning. Often many systems per institution.
Industrial Late 1990s to TBA Inefficiency, duplication etc lead to adoption of single enterprise system.
TBA-?? Post-industrial Problems with monolithic, institutional focus of industrial lead to development of alternatives

Text-based CMC

The computer-mediated communications (CMC) movement outlined in the previous section (Section Error! Reference source not found.) support communication through the use of large time-shared computers to which all participants would log on to via terminals of phone lines. By the early 1990s there were over 900,000 hosts on the Internet and the number was growing by over 1000 per day and accelerating (Press 1992). The rise of the Internet, its availability to universities and a growing range of text-based communication tools such as Usenet news and Internet email enabled the CMC based learning practices to move to the Internet and address some perceived problems such as cost and support (Atkinson and Castro 1991; Gregor and Cuskelly 1994). The Internet offered alternatives to the three main services of CMC identified by Kaye (1989): electronic mail through Internet-based email; Computer conferencing through Usenet news and mailing lists; and information banks through a combination of these and services such as FTP. Arising out of the origins of the CMC movement, the emphasis in this phase was on the use of the Internet to enable communication and collaboration.

By no means was the use of the Internet for CMC within universities widespread. By 1994, using the Internet for any purpose was limited to a fraction of academics at US universities with significant differences in usage between academic disciplines (Goodman, Press et al. 1994). As late as 1993 the Internet still did not play a central role in consideration of the future of CMC. In an article (Holden and Wedman 1993) examining the future issues associated with CMC the Internet is mentioned a handful of times and is positioned as one of three widespread networks enabling CMC. Moving from existing CMC system to the use of the Internet as a medium for CMC was, to some extent, a paradigm shift for those institutions already heavily invested in non-Internet CMC.

Lone ranger

Many, if not most, innovations around learning and teaching are created by “lone rangers” (Jones, Stewart et al. 1999). The “lone ranger” approach is by far the most common model of e-learning course development (Bates 2004). The lone rangers are individual academics who are energetic and early adopters of innovation motivated by a desire to improve the accessibility and quality of their teaching (Taylor 1998). At its best the lone ranger approach lays a foundation for new teaching methods based on technology, however, it often happens in spite of institutional interest, tends to produce pockets of isolated activity and often fails to have any impact or recognition at the institutional level (Taylor 1998).

The invention of the World-Wide Web and its capabilities to present multimedia made online education increasingly accessible and expanded the range of disciplines that could be offered online (Harasim 2000). The rise of the web made it clear that e-learning that used the Web as the primary interface were becoming the most successful (Stiles 2007). The relative ease of web-publishing encouraged lone-ranging academics from a range of disciplines to experiment with the new interface in a variety of ways. This contributed to the development of the second of the models for online courses identified by Harasim (2000), and perhaps the current primary model, based around information publishing.

Cottage industry

A limitation of the lone ranger approach is that quality teaching with technology requires expertise in a range of tasks, not just learning design and it is difficult for teachers to gain this breadth of knowledge without workload or quality impacts (Bates 2004). There is a gap between the lone rangers and the majority of academic staff that is unlikely to be bridged without assistance (Jones, Stewart et al. 1999). The mid to late 1990s saw widespread recognition that the majority of academic staff simply did not have the skills or time to individually design their use of Internet technologies (Goldberg, Salari et al. 1996; Jones and Buchanan 1996).

To address this gap, the mid to late 1990s saw the development of a diverse collection of intranet-based systems, home-built virtual learning environments, off-the-shelf products and customized groupware solutions by different schools, faculties or research initiatives (Dron 2006). At their best these systems were tailored to the needs of the learners and teachers in their original context. At their worst they were often unreliable, poorly maintained and each academic grouping having their own system contributed to issues around duplication, scalability and consistency. The de-centralised origins of many of these systems meant that few integrated with central management systems which led to duplication of user databases and often led to inconsistencies and disparities (Dron 2006).


As use of e-learning increases institutional management start to identify concerns around quality, duplication, lack of standards, and costs; and consequently start the process of setting priorities, establishing technical standards, providing support and controlling budget and workload (Bates 2007). A number of institutions questioned whether they needed to be in the business of building e-learning systems. The need for management to address these issues, the arrival of commercial Learning Management Systems (LMS – further explanation of the LMS in the Product section insert cross ref) vendors and the rise of enterprise software contributed to the adoption of the LMS as an enterprise system. The LMS shifted from being based on the bottom-up work of the loan rangers into the very embodiment of a top-down institutional strategy, to a dominant element of higher education’s information technology capability (Katz 2003).

By 2006, Browne et al (2006) to see two key trends in e-learning in the UK higher education system: the first is the on-going preference of institutions to use commercial systems; and an emerging trend towards open source systems. Eventually the market for LMS matured with a range of mergers and takeovers resulting in the overwhelming domination of the market by two products: a commercial product in Blackboard and an open source product in Moodle (Stiles 2007). It will be argued within the Product section (insert crossref) that an open source LMS does not represent a paradigm shift, but instead simply allows a university to continue the existing industrial paradigm by using ERP-based methodologies to maintain the LMS.

Browne et al (2006) suggest that the on-going preference by institutions for commercial systems could be “interepreted as inertia due to expensive ‘lock in'”. Landon et al (2006) suggest that user dependency on these systems signals an end to the “exuberant exploration of competing systems” and suggests a future focused on meeting user demand and making systems ever more efficient to use. Wilson et al (2006) suggest that the focus in recent years on the improvement of the technology of the LMS has lead to the marginalization of software and techniques that do not fit within the LMS patter. The industrial VLE model represents a hegemony in which the institution controls the environment (Stiles and Yorke 2006).


The limitations of industrial e-learning, the subsequent negative experiences of students and academic staff and the development of alternate technologies has contributed to the evolution of e-learning practice into e-learning 2.0 (Downes 2005). An evolution that can be seen as a change in paradigm or discourse around e-learning as it questions the assumptions of the industrial paradigm of e-learning (Jones 2008). Apart from the limitations of the industrial model, Stiles and Yorke (2006) identify three developments that are helping create the post-industrial challenge to industrial e-learning. These are the growth of:

  1. service-oriented architectures and cloud computing;
    These technologies enable a post-industrial approach to e-learning systems where parts can be included as and when needed and control can also be granted when and where needed (Dron 2006).
  2. systems, such as ePortfolios, where the question of information ownership is less than clear; and
    The ePortfolio is a personal place that belongs to the student to create and showcase their work (Downes 2005). Increasingly ePortfolios, like other applications, exist outside of the institution’s LMS.
  3. Web 2.0 and social software.
    The evolution of the Web into Web 2.0, has resulted in a Web that is no more open, personalised, participative and social (Ravenscroft 2009). Social software and informal instant communication technologies can help spread control move evenly through the learning system (Dron 2006).

These developments challenge the institutional approach in terms of ownership of processes, systems and information and create uncertainties around institutional strategy and policy (Stiles and Yorke 2006). These changes represent a major challenge to the hegemony of the LMS (Stiles 2007). It is clear that social software is part of an evolving paradigm that has contributed to a new and important family of technology-mediated learning practices that require conceptualised and investigated (Ravenscroft 2009). There is a need to consider how learning can be reformulated to address the tension between a highly structured and authority driven view of learning and the more collaborative and volatile nature of the social web (Ravenscroft 2009). In order to be ready for the changes ahead, there is a need for institutions to be reconsidering their strategies and policies now (Stiles 2007). However, it is still early days and it is arguably time to focus on projects that stimulate reflection and asking of questions, rather than jumping prematurely to specific solutions (Ravenscroft 2009).


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Performance degradation – impact of new LMS implementation

Anyone who knows me, knows that I have a particular disdain for the perspective that e-learning within a university can be treated as an IT project and in particular as the implementation of an Enterprise Resource Planning (ERP system). i.e. the LMS is an ERP and should be implemented as one. Some previous rants can be found on this blog, including:

Another flaw in current practice

Time for another argument against the view that LMS implemetation and consequently the support and development of e-learning within a university should not be treated as an IT project and certainly not as an IT project implementing an ERP. Actually, the following is probably not exactly an argument against that. It’s probably better characterised as an illustration of just how disconnected institutional strategies around LMSes and elearning are from research about the implementation of ERP systems.

The LMS implementation will improve L&T and solve all ills

The implementation of new enterprise level software is really hard and expensive. In order to justify this organisations have to make all sorts of claims. Some examples I’ve seen include:

  • Adoption of {insert LMS name} will aid the institution in becoming a recognised leader in flexible learning.
  • This is an opportunity to improve e-learning experiences for both staff and students by planning for course redesigns upfront.
  • The transition can be utilised to establish quality check and reviews process and focus on producing quality online course delivery.

ERP implementation results in performance degradation

I’ve always thought that these sorts of views are just plain silly and ignore the reality of what people have to go through when a new system, especially when around something as variable and important as teaching, is introduced. Apart from personal experience, I’m also aware that this is one of the common findings from the ERP literature. In my thesis wanderings, I’ve come across a quote to illustrate this from Katz (2003)

In late 2002, the EDUCAUSE Center for Applied Research (ECAR) conducted research on enterprise systems in higher education, focusing on the big three administrative systems: student, financial and human resources. Among the many findings of the study is the observation that implementers of these systems initially experience a loss of functionality and a degradation of performance as employees grapple to come to terms with the new technologies and processes that these systems force.

Further down

In the context of course management systems, recent ECAR research suggests a similar socialization curve. The implementation of new software is often accompanied by a short-term loss in productivity as new tools, methods and processes are assimilated. Teaching and learning are inherently and historically social activities and, as such, are even more subject to dislocations associated with new techniques and technologies.

Katz goes onto report that ECAR findings that once the users and the organisation become familar with the new ERP system that productivity gains are reported. However, does this mean that the adoption of a new LMS will provide gains in terms of productivity or improvement in the learning and teaching experience?

You have to remember that the ECAR report focused on “greenfield” implementation of ERP systems. i.e. the institution had non-ERP systems and then implemented their first ERP system and consequently found productivity gains. By 2009, most universities have already implemented e-learning ERPs (i.e. an LMS). They are replacing one LMS with another.

I don’t believe the replacement of one LMS with another LMS will provide any significant increase in productivity. It is widely accepted that all LMS are essentially the same (and yes, I don’t think Moodle is all that different from Blackboard).

If the new ERP is essentially the same as the old ERP, then there will be no gains. Unless of course there were problems with how the old ERP was used or supported. And I don’t think implementing a new ERP is going to solve those problems.

PhD Update #7 – a fortnight in review

It’s now been 2 weeks since my last “weekly” PhD update. The public holidays, minor surgery and a general malaise contributed to by on-going issues at work have meant that work hasn’t progressed as quickly as I’d hoped and it would have been pretty pointless to post an update last week.

Of course, all that is going to change from now on.

Yea, right. At the last I’ll be out at work tomorrow (saturday) doing more PhD stuff. Perhaps I might even make some progress.

What I’ve done

Last week, I said (not very clearly), that I would aim to have one blog post for each of the following

  • “History of technology-mediated learning”
    Done but took a lot long than I hoped.
  • “History of e-learning”
    This section has changed to become the “Paradigms of e-learning”. Much of the structure and initial content is in place, but not ready to be posted. Real soon now, have been working on it.
  • “Quantitative use of industrial e-learning”
    I’m suggesting that the current, predominant paradigm of e-learning is “industrial e-learning”. i.e. use of single “enterprise” systems i.e. LMSes. I’ve got a huge collection of quantitative stats about this paradigm. But nothing I’ve put together for posting. Haven’t worked on it.

In addition to the above, I’ve also gathered a fair bit more literature (would be nice if Endnote had a “view references ordered by date” feature) and incorporated some real nice quotes from some of that literature into various other sections of the thesis. Ready for culling and re-organisation.

In terms of blog posts, over the last couple of weeks I’ve contributed the following posts out into the blogosphere

  • Fad cycle in L&T – historical view
    A key result of the history section of the thesis and some associated reading is the recognition that there is a clear cycle at work with the application of technology to learning and teaching. This post started to express some of these ideas. The cycle will be one of the “lessons” arising from the “Past Experience” section of Chapter 2.
  • Measuring the design process
    While not directly related to the PhD in content, the intent is. The “People” section of chapter 2 will make a similar point to this post. i.e. that the common understanding/practice of IT professionals and “corporate” management are inappropriate for something like e-learning.
  • Snowden quotes connected with e-learning
    Picks up a couple of quotes from Dave Snowden that connect with two of my views – one each from Product and People sections of the Ps Framework – about the mismatch between what university-based e-learning needs and what it actually gets.
  • Fad cycles
    Follows on from a post above about cycles in higher education. Talks in some detail about Birnbaum’s fad cycle and the Gartner technology hype cycle.
  • Blame the student
    Picks up on a quote from 1912 – early days of educational technology – that embodies the “blame the student” or “can’t trust the student” approaches to teaching.
  • Edupunk rules
    A post that combines some insights from McDonald and Gibbons (nd) with the Edupunk movement. Both fit with the fundamental perspective from my design theory.
  • Disruption and the mythic technologies of education
    Combines insights from Shirky, Papert, Postman and Campbell to talk about the nature of e-learning (in transition), the nature of universities and how to move forward.
  • Theory and practice quote
    Picks up on a good quote that I’m planning to use as a lead in for Chapter 1.

What I’ll do for next week

The plan is to have completed and posted to the blog material on:

  • The paradigms of e-learning.
  • The use of industrial e-learning: quantity and quality.
  • Lessons for e-learning from past experience.

If I achieve that, I will have completed the Past Experience section. Perhaps only 4 weeks or so after I thought I might first complete it. I hope these sections start getting finished faster.

A history of technology-mediated learning

The following is a section from my PhD thesis. It is part of the “Past Experience” section of the Ps Framework. It aims to give a potted history of technology-mediated learning and show how it connects with e-learning. Since these terms are somewhat overused, it starts with some definitions. The plan is that this history will be used to identify lessons from history, which e-learning (generally) hasn’t learned.

I’ve been working on this for at least a month. I have been doing other work on the thesis, but the fact that this has take soooo long is not all the heartening. I think perhaps may sights are set a little high. The alternatives are that I’m either a crap writer or I’m currently not in the mood to write. We’ll see where we go from here.

The following has not been proof-read thoroughly. I’m leaving that for a later task. If you have any suggestions for improvement, fire away.

A major area of improvement could be in coverage. This is meant to be a minor part of one chapter of my thesis. It’s already probably longer than it should have been. Almost certainly in the search for some brevity there will have been contributions that were missed or others that were over-emphasised. Not much I can do about that, but if it’s important….

For more detail on this see Reiser (2001) or even more detail Saettler (2000). The Saettler book is in Google Books, so you can get a preview – sorry to tired of this to add in the link.


There already exists some debate and uncertainty about terms and definitions used to describe e-learning, technology-mediated learning (Alavi and Leidner 2001), networked learning, online learning, telematics, Internet-based learning, computer conferencing, computer-mediated communications (Romiszowski and Mason 2004), web-based education (McCormack and Jones 1997), asynchronous learning networks (Spencer and Hiltz 2003) and many others. The description of a history stretching back over more than 100 years only tends increase these problems. Different eras have had similar problems with an explosion of competing terms. For example, in the 1980s the use of computers in education might be referred to as computer-based learning (CBL), computer-based education (CBE), computer-aided (or assisted) instruction (CAI), computer-managed learning (CML) or computer-managed instruction (CMI) (Friesen 1991). Adding to the chance of confusion is the likelihood that in the past, modern terms have been used for different purposes and some terms had definitions that have unexpected nuance not immediately clear through the prism of history.

Rather than engage with an arguably necessary and interesting debate about appropriate terms and their definition, this section takes the pragmatic approach of defining a small set of terms that it will seek to use consistently. These terms are chosen to fit with the focus of the thesis and its topic. The concern of those who prefer precise and nuanced understanding of terms and their implications is acknowledged, but beyond the scope of this thesis. It is recognized that each of the selected terms, from certain perspectives, have weaknesses. However, both are deemed sufficiently useful to serve the requirements of this thesis. Anohina (2005) provides an analysis of terms used to describe the use of technology in learning.

The two terms to be used are:

  1. technology-mediated learning, and
    Technology-mediated learning is used as the broader term to encompass the use of any form of technology is used to mediate learning interaction or materials. As described in the next section, this will used primarily to describe the use of technologies from the 1900s onwards.
  2. e-learning.
    E-learning is used specifically to encompass the use of digital computers and the Internet to support learning and teaching. Generally, this is primarily from the early 1990s onwards.

History of technology-mediated learning

If the definition of technology is expanded to its most inclusive the use of paper and books are early examples of technology-mediated learning. In fact, some argue that every form of instructional delivery is in someway mediated with some form of technology (Reiser 2001). Bates (2008) suggests that technology has always been a defining feature of distance education. In terms of print-based distance education, Holmberg (2005) identifies early examples of correspondence study, entirely by the postal service, in 1728 and 1833. Saettler (2000) cites educational technology antecedents going back to the fifth century B.C and beyond.

Most descriptions of the history of technology-mediated learning, however, categorise the three main technologies of pre-20th Century instruction – the teacher, chalkboard and textbook – separately from other technologies (Reiser 2001). Following this practice, this section starts provides a brief history of technology-mediated learning through 20th century until the rise of internet-based learning. Subsequent sections attempt to draw some lessons for the practice of e-learning from this history.

It is possible to observe two separate streams of technology-mediated learning that arise during the early 1900s: the audiovisual instruction movement and teaching machines. Both these streams continue to have much the same emphasis throughout the century, but continue to evolve in line with increasing theoretical understandings and changes in the available technology. The presence and impact of both streams continues to be in evidence in many of the practices associated with e-learning. Though it is suggested that this on-going evidence does not include a complete and nuanced understanding of the findings from the earlier work. The following seeks to describe these two streams, how they have evolved and where they can be seen within e-learning.

Audio-visual instruction

Early, in 1909, a short story by E.M. Forster called “The Machine Stops” describes the use of a type of video-conferencing network to deliver a lecture. By this time the audiovisual instruction movement has taken its first steps through the use of silent visual media such as stereographs, charts and photographs housed in school museums (Hew 2004). Over the next 20 years the movement grows significantly through the availability of and an interest in the application of a range of related technologies including motion pictures, radio and television (Reiser 2001). The rise of Internet-based e-learning sees a continuation of this work through net-based audio and video, and currently services such as YouTube.

Much of the work around audio-visual instruction has emphasized the value of audio-visual material in their ability to present concepts in a concrete manner, as opposed to more abstract descriptions possible with media such as a lecture and book (Reiser 2001). From the start the theoretical rationale for audio-visual instruction was as an antidote for verbalism (Saettler 2000). The research tradition of the audio-visual instruction movement was largely confined to comparison studies of the effectiveness of the audio-visual media against other methods (Saettler 2000). A key finding arising from these studies is that given a paucity of significant differences there is a need to change the focus of research (Reiser 2001). Saetler (2000) identifies a disconnect between the audio-visual instruction movement and the rest of the educational technology discipline, which is illustrated the absence of any connection for four decades between audio-visual instruction movement and that of teaching machines.

Teaching machines

The second stream, teaching machines also known as programmed instruction, has a foundation in the industrial revolution, automation and the possibility for the application of machinery to solve problems. Thorndike (1912) expresses one of the early problems that underpin the rise of the teaching machine.

If, by a miracle of mechanical ingenuity, a book could be so arranged that only to him who had done what was directed on page one would page two become visible, and so on, much that now requires personal instruction could be managed by print.

From 1900 through 1920s there were a number of attempts to develop machines to automate the application of multiple-choice tests (Petrina 2004). Pressey (1926) develops a mechanical machine that provides drill and practice items for students. Skinner (1958) suggests that Pressy appears to have been the first to propose a system that placed importance on immediate feedback, allowed students to self-pace and the required the student to play an active role in learning. It is on this basis that Skinner (1958) criticises the audiovisual instruction movement as aiding in presentation of material but contributing little towards student/teacher interaction. Skinner (1958) suggests that and widespread use of such material creates the potential problem of the student becoming little more than a “mere passive receiver of instruction”.

It is Skinner’s work during the 1950s that contributes to the rise and establishment of the programmed instruction movement. The key goals of this work included individualized and self-paced learning, application of a science of behaviour to teaching and learning through the principles of reinforcement of learning, and the construction of carefully programmed sequences of learning that lead to pre-determined learning goals (Galloway 1976). Skinner (1958) describes a number of mechanical teaching machines.


By the late 1950s early computers were available and promised to offer a better platform than mechanical devices for teaching machines, however, it was the 1980s before there was widespread interest in the computer as an instructional tool (Reiser 2001). Many early applications of computers to education were demonstrations to show the potential of computers in education (Molnar 1990). The first adaptive teaching system to enter commercial production was the Self-Adaptive Keyboard Instructor (SAKI), developed by Gordon Pask and Robin McKinnon-Wood in 1956 (Patel, Scott et al. 2001). The Programmed Logic for Automatic Teaching Operations (PLATO) projected commenced at the University of Illinois in 1959 (Molnar 1990).

Early interest in the application of computers to education is based on the dual beliefs that instruction adapted to the needs of the learner is good and that the computers makes this individualization of instruction easier as it can store and use each student’s own performance as a basis for selection the new problems or concepts for the student (Suppes 1966). Researchers extended Skinner’s work and used sophisticated mathematical models of student learning to help design instructional materials and strategies to achieve the a level of individualization (Molnar 1990). By the late 1960s, the PLATO system was using time-sharing computers to allow large numbers of people interact with lesson modules created by the TUTOR programming language (Molnar 1990).

Programmed instruction arises from perspectives influenced by behaviourism and cognitive science, which tend to reject or downplay the role of conscious will as a dominant element of human behaviour (Bates 1995). Such approaches limits response to within pre-defined boundaries and constrains the ability to personalize the learning or to create knowledge unanticipated in the design of the teaching material (Bates 1995). By 1973 the instructional uses of computers were listed as drill, skills practice, programmed and dialog tutorials, testing and diagnosis, simulation, gaming, and various forms of information processing, storage, management and display (Zinn 1973). Computers were not being used to enable communication between people.

Computer-mediated communication

The use of technology to enable human-to-human dialogue, commonly referred to as computer-mediated communication (CMC) during the 80s, was one approach to address this limitation. In the late 1960s the Office of Emergency Preparedness in the USA introduced systems that led to the first generation of CMC systems such as EIES (Zorkoczy 1989). By 1974 an online community began to emerge on the PLATO system through the availability of a number of online tools equivalent to email, chat rooms, groupware and instant messaging (Woolley 1994). CMC encompassed three types of online services, which were generally seen as discrete elements serving different types of clientele: electronic mail, computer conferencing and online databases and information banks (Kaye 1989). As early as 1982 researchers in computer-mediated communication had developed and published knowledge about CMC including: important considerations in designing or choosing CMC systems; factors influencing success; impacts of CMC systems on individuals, groups and organizations; and appropriate evaluation strategies (Kerr and Hiltz 1982).

Computer-managed learning

During the 1980s The rise of the powerful personal computers and local area networks encouraged rapid growth in computer-managed instruction systems (Friesen 1991). By 1983 40% of elementary schools and 75% of all secondary schools in the United States were using computers for instructional purposes (Reiser 2001). Much of this interest was in the use of computer-managed instruction (CMI) an approach that has origins in teaching machines and programmed instruction. During the 80s there was growing interest and use of Computer-Managed Learning (CML) systems, which manage both the learning sequence and related educational and administrative functions (Friesen 1991). These systems ranged from software design to “teach” a particular topic through to more general CML systems such as Plato.

Connections with e-learning

Kaye (1989) talking from a focus on computer-mediated communications suggested

In the future, it is likely that there will be much more convergence of CMC for interpersonal communication with database access and with local, stand-alone, elements (e.g. CAL, hypertext, audio, video etc.) to form components of a new generation of interactive multimedia and hypermedia systems which will have powerful educational applications

Currently, the most common institutional response to e-learning is the adoption of a Learning Management System (LMS) (Jones 2004). Such systems do provide an integration of the features identified by Kaye, and that have a direct connection with the history of technology-mediated learning. The ability to provide access to audio and video via the Web connects with audio-visual instruction. The provision of features such as quizzes and adaptive release, provide a primitive connection to programmed instruction and CAL. In fact, some authors (Sheridan, Gardner et al. 2002; Szabo and Flesher 2002) suggest that LMSes are simply the next generation of CML systems. Finally, access to information via the Web and the provision of email, discussion forums and other communication means offer a connection to computer-mediated communications.

This section has offered a brief history of technology-mediated learning and identified connections between this history and the current practice of e-learning. Section Error! Reference source not found. – Error! Reference source not found. draws upon this history to identify a number of lessons for the implementation of e-learning. First, the next section seeks to identify and understand in more detail the different paradigms of e-learning.


Alavi, M. and D. E. Leidner (2001). "Research commentary: technology-mediated learning – a call for greater depth and breadth of research." Information Systems Research 12(1): 1-10.

Anohina, A. (2005). "Analysis of the terminology used in the field of virtual learning." Educational Technology & Society 8(3): 91-102.

Bates, T. (1995). Technology, Open Learning and Distance Education. London, Routledge.

Bates, T. (2008). Transforming distance education through new technologies. The International Handbook of Distance Education. T. Evans, M. Haughey and D. Murphy. Bingley, UK, Emerald Press: 217-235.

Friesen, V. (1991). A critique of computer-managed instruction in the light of key principles of adult education, Simon Fraser University. M.A.

Galloway, C. (1976). Psychology for learning and teaching. New York, McGraw-Hill.

Hew, K. F. (2004). Past Technologies, Practice and Applications: A Discussion on How the Major Developments in Instructional Technology in the 20th Century Affect the Following Qualities ? Access, Efficiency, Effectiveness, and Humaneness. 27th Conference of the Association for Educational Communications and Technology. Chicago, AETC.

Holmberg, B. (2005). The Evolution, Principles and Practices of Distance Education. Oldenburg, Bibliotheks- und Informationssystem der Universitat Oldenburg.

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.

Kaye, A. (1989). Computer-mediated communication and distance education. Mindweave: Communication, computers and distance education. R. Mason and A. Kaye. Oxford, UK, Pergamon Press: 3-21.

Kerr, E. and S. R. Hiltz (1982). Computer-Mediated Communication Systems: Status and Evaluation. New York, Academic Press.

McCormack, C. and D. Jones (1997). Building a Web-Based Education System. New York, John Wiley & Sons.

Molnar, A. (1990). "Computers in education: a historical perspective of the unfinished task." Technological Horizons in Education 18(4): 80-83.

Patel, A., B. Scott, et al. (2001). "Intelligent tutoring: from SAKI to Byzantium." Kybernetes 30(5/6): 806-819.

Petrina, S. (2004). "Sidney Pressey and the Automation of Education, 1924-1934." Technology and Culture 45(2): 305-330.

Pressey, S. (1926). "A simple apparatus which gives tests and scores – and teaches." School and Society 23(586): 373-376.

Reiser, R. (2001). "A History of Instructional Design and Technology: Part 1: A History of Instructional Media." Educational Technology Research and Development 49(1): 1042-1629.

Romiszowski, A. and R. Mason (2004). Computer-Mediated Communication. Handbook of research on educational communications and technology. D. Jonassen, Lawrence Erlbaum: 397-432.

Saettler, P. (2000). The evolution of American educational technology, Information Age Publishing.

Sheridan, D., L. Gardner, et al. (2002). Cecil: The First Web-based LMS. ASCILITE’2002, Auckland, NZ.

Skinner, B. F. (1958). "Teaching Machines." Science 128: 969-977.

Spencer, D. and S. R. Hiltz (2003). A field study of use of synchronous chat in online courses. HICSS’35, Hawaii.

Suppes, P. (1966). The Uses of Computers in Education. Scientific American: 207-220.

Szabo, M. and K. Flesher (2002). CMI Theory and Practice: Historical Roots of Learning Managment Systems. World Conference on E-Learning in Corporate, Government, Healthcare and Higher Education, Montreal, Canada, AACE.

Thorndike, E. (1912). Education: A First Book. New York, Macmillan.

Woolley, D. (1994). "PLATO: The Emergence of Online Community." Retrieved 17 April, 2009, from

Zinn, K. (1973). Contributions of Computing to College Teaching and Learning Activities at the University of Michigan. Ann Arbor, Michigan University: 33.

Zorkoczy, P. (1989). CMC in distance education and training: The border context. Mindweave: Communication, Computers and Distance Education. R. Mason and A. Kaye. Oxford, UK, Pergamon Press: 259-262.

Theory and practice – quote and connection with e-learning?

Given my pre-occupation with the thesis, which involves the formulation of a design theory for e-learning. It’s of little surprise that I have an interest in the theory, practice and e-learning. Came across the following quote this morning in checking some literature, and I like it – new quote for a thesis chapter.

Theory without practice leads to an empty idealism, and action without philosophical reflection leads to mindless activism. – Elias & Merriam, 1980, p. 4

Currently this quote speaks to me because I observe the practice of e-learning within universities being performed with zero philosophical reflection.

The quote is the lead in to an article that is talked about here and more recently here


Elias, J. L., & Merriam, S. (1980). Philosophical foundations of adult
education. Malabar, FL: Robert E. Krieger

Disruption and the "mythic" technologies of education

I told myself I wouldn’t blog anything more not directly related to the PhD – I’m breaking that promise because a few things I’ve read over this weekend resonate strongly with the problems that are frustrating me the most with the current practice of higher education and its management.

The blog post connects ideas from a presentation titled “Disruption and Transformation” by Gardner Campbell (I wish the other talks in the session were available online – should look), an article titled “Why School Reform is Impossible (Pappert, 1995) by Seymour Papert, Postman’s 5th of 5 things to know about technology change – technology becomes mythic, and my own views about the roles played by consistency (bad) and diversity (good).

Gardner’s observations

In his presentation Gardner makes a number of observations around the practice of learning and teaching within universities in the context of disruption and transformation. These include:

  • LMSes suck at personalisation which is important for learning, ownership and community.
    The complete lack of any support for personalisation offered by existing learning management systems, especially when compare to social network sites such as Facebook. He mentions Blackboard, but I would suggest Moodle has just the same flaws – being open source doesn’t solve the problem, at least not yet.
  • Course synopsis/profiles suck.
    An illustration of how the common views of course synopsis/profiles can be seen very negatively. How they help set exactly the wrong type of environment for learning to occur and are a particularly bad way to start a course.
  • Pre-defined learning objectives suck.
    The idea that you can pre-determine the learning that will take place for each student is questioned. Jocene, I think you’ll like that bit.

He closes the presentation by showing video of Chris Dede comparing education with sleeping, eating and bonding. Where university education tries to treat learning as more like sleeping then bonding. This post by Derek Wenmouth talks more about the video. I find particularly relevant the bit about Dede’s last comment

he points out that the major issue is with breaking down the social and political barriers – pointing out that technology will only ever take us part of the way towards the personalised learning dream

More on this below.

Consistency has become “mythic”

In Postman’s 5 things to know about technological change”, number 5 is

Technology becomes mythic, it becomes seen as part of the natural order of things.

For me the question of “consistency”, Dede’s treating learning as sleeping, has become mythic within the Australian Higher Education system. The “course profile as contract” perspective has become unquestioned, it is part of the natural order of things. Anyone who questions the importance of the contract is seen as weird. Universities spend huge amounts of time ensuring the contract is developed on-time. I know of governing councils of institutions that have taken time to discuss the fact that x% of these contracts were not ready in time. The fact that the content of the vast majority of these contracts is questionable and that the learning experience students have under the confines of those contracts is far from good, is never considered (it’s too hard).

National auditing bodies set up by the government put tremendous value on all students receiving a consistent learning experience. The idea that learning is more like bonding than sleeping is considered woolly thinking and inappropriate.

Don’t believe me, this is what the auditing body said about my current institution in it’s report

As a University with multiple teaching sites, CQU has developed a system for ensuring the consistency of course delivery and student participation which may be amongst best practice in the Australian sector.

This irrational emphasis on consistency increases the reliance and acceptance of the learning management system. The idea seems to be that if only we can make all the course websites look the same and have the same structure and content, then the student learning experience will be okay. The LMS appears to help management achieve this goal.

Of course the fact that most LMSes are based on a model that makes it very difficult to standardise is something they don’t seem to get. The LMS model is based on individual academics creating course sites manually, which creates diversity, and then copying them across each term. It leads to organisations expending effort on kludges to automate the consistent creation of course sites.

I continue to like Oscar Wilde’s take on consistency.

Consistency is the last refuge of the unimaginative

Now is the time for experiments, lots and lots of experiments

Gardner draws upon this blog post by Clay Shirkey. I’ve heard a bit about this post in the blogosphere, but hadn’t read it. I’ve fixed that flaw, you should too. It’s important.

Personally, this particular quote resonated very strongly with my current predicament

Leadership becomes faith-based, while employees who have the temerity to suggest that what seems to be happening is in fact happening are herded into Innovation Departments, where they can be ignored en masse. This shunting aside of the realists in favor of the fabulists has different effects on different industries at different times.

Currently, in terms of e-learning at universities, I see myself as one of the realists being shunted aside by the fabulists who are peddling all sorts of unlikely visions of the future.

My take on Shirky’s article, as applied to e-learning (yes, I know that the phrase e-learning has questionable value and I should probably just use learning) within universities, goes something like this:

  • We’re living through 1500.
    How to do e-learning within universities and the how the impact of changes within society, especially the Internet, remain unanswered questions. The answers we have today are just like the failed business models used by newspapers to leverage the Internet, they are interim measures destined to fail.
  • There’s no telling what will work.
    No-one can say what model will work in the future. It’s a nature of revolution, it’s too complex to predict. We’ll only know after the fact – retrospective coherence.
  • Now is the time for lots and lots of experiments.
    Since we don’t know what will work, we need to try lots of things to find out what might.

Gardner makes the point that universities, as the supposed homes of research and learning, of knowledge generation, production and dissemination should be at the forefront of this experimentation – but we aren’t.

For me, this is because consistency has become has become mythic. The importance of sameness has become unquestioned and this gets in the way of experimentation. Experimentation means the possibility of failure and failure is to be feared and avoided. Much better to be safe and same.

Can this be done within universities

Seymour Papert in a 1995 article outlines a perspective about change in education. A perspective which I believe has some connections with the above.

In terms of “technology” becoming mythic, Papert draws on Tyack and Cuban’s (1995) idea of the “grammar of school” and links it to assimilation blindness.

The structure of School is so deeply rooted that one reacts to deviations from it as one would to a grammatically deviant utterance: Both feel wrong on a level deeper than one’s ability to formulate reasons. This phenomenon is related to “assimilation blindness” insofar as it refers to a mechanism of mental closure to foreign ideas. I would make the relation even closer by noting that when one is not paying careful attention, one often actually hear the deviant utterance as the “nearest” grammatical utterance a transformation that might bring drastic change in meaning.

Papert links these ideas back to the introduction of computers into schools and how the “deviant utterance” gets heard/transformed into the “nearest grammatical utterance”. i.e. it gets transformed into something that fits within the grammar of school. I believe Shirky makes this point in connection with how newspapers tried to deal with the Internet and I believe you can see this happening within Universities (e.g. the walled gardens of the LMS and the connection with the walls of the lecture theatre).

Papert describes the components he sees that make up schools and how they match

I see School as a system in which major components have developed harmonious and mutually supportive — mutually matched forms. There is a match of curriculum content, of epistemological framework, of organizational structure, and — here comes the trickiest point for Tyack and Cuban — of knowledge technology.

He equates a failed education reform as being similar to tweaking one of these components and then observing, like any well-equilibrated dynamic system, “when you let go it is pulled back by all the other components”.

Papert argues that reform as centralised social engineering will go wrong. He argues that

Complex systems are not made. They evolve.

and suggests that effective fostering of radical change means

rejecting the concept of a planned reform and concentrating on creating the obvious conditions for Darwinian evolution: Allow rich diversity to play itself out.

Sounds like “Now is the time for experiments, lots and lots of experiments” to me. Which brings me back to a previous post and the concept of safe-fail design from Dave Snowden.

The source of my frustration

It also brings me back to the perspective that corporate approaches to management (i.e. the top manager and/or a small group of experts/analysts make the decisions) has become “mythic” within universities. A focus on creating the conditions, letting go and seeing what happens is something they just can’t understand or appreciate.

This summarises the main source of my frustrations over the last 15 years of trying to do innovative things around learning. It’s not something I see changing anytime soon.

How do you change this social and political barrier?


Papert, S. (1995). “Why School Reform is Impossible.” The Journal of the Learning Sciences 6(4): 417-427.

Tyack, D. and L. Cuban (1995). Tinkering towards utopia: A century of public school reform. Cambridge, MA, Harvard University Press.

WordPress eating posts

This is not good. It seems that is starting to eat posts.

Earlier today I added a post about a photo of mine from Flickr, licensed under creative commons that has been picked up and used by an online mapping service. I link that with the 80/20 rule and a Ted talk by Clay Shirky

The post no long lives on the WordPress blog. However, there were a few visits to the post, so it exists (somewhat) in the stats. Even though it now points to another, much older, blog post. The post also exists in Google as originally intended.

This is not a good sign for reliance on a 3rd party.

I can hear all the SaaS, cloud computing skeptics in IT divisions across the world working up to….”I told you so”.

Post to fix the feed

It appears that this post and its use of a poll has broken the RSS feed for this blog. Am hoping that this post will knock that post out of the feed.

Yep, that worked. Tip: don’t use polls in blogs. They appear to break the RSS feed.

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