Assembling the heterogeneous elements for digital learning

Challenges in employing complex e-learning strategies in campus-based universities

The following is a summary of McNaught et al (2009). This is one of three papers that from the same institution around the LMS that I’ve looked at recently.

The abstract for the paper is

Despite the existence of a significant number of established interactive e-learning tools and strategies, the overall adoption of e-learning is not high in many universities. It is thus important for us to identify and understand the challenges that face more complex e-learning projects. Using a qualitative method that gathered together the reflections of experienced practitioners in the field, this paper outlines many types of challenges that arise in the planning and development, implementation and evaluation stages of e-learning projects. Some of these challenges are related to human factors and some are associated with external factors such as technological infrastructure, university policy and support and the teaching and learning culture as a whole. A number of models are presented to assist our understanding of this situation – one on understanding the nature of innovation, a grounded model of the challenge factors we have encountered in our own experience and one to show possible future directions.

The paradox of e-learning

Lot’s of e-learning conferences full with presentations about digital resources and tools. But reality of institutional adoption of e-learning very different. “..this paper was born out of a desire to ‘come clean’ and see if we can advance e-learning from its often mundane position as the repository for lecture notes and PowerPoints” (McNaught et al, 2009, p. 268).

The context of campus-based universities

The cases arise from campus-based universities in Hong Kong, though “we believe our ‘story’ is more generally applicable” (p. 268). The authors do suggest that the “dynamic of distance universities are quite different” given that distance may provide more of an incentive for better e-learning strategies.

Note: I really don’t think that the distance dynamic plays much of a role at an overall level. There is perhaps more thought, but I wonder how much of that translates into action?

Even writing in 2009, the authors suggest that most of the success stories arise from pioneering teachers. The early adopters. References a 1998 paper by Anderson et al as support. Gives some statistics from CUHK from 2004 to show limited use. This draws on some of the previous papers.

More interactive uses of technology is often “development-intensive and/or administrative-intensive. They require teachers to spend a great deal of time in planning and creating the online resources, and then usually sustained significant effort in monitoring and regulating the online strategies while they are in progress”. Cites Weaver’s (2006) challenge to “encourage quality teaching practices…that seamlessly integrates the technical skills with the pedagogical and curricular practices… and does not promote transfer of existing poor teaching practices to the online environment”

Examples of unsuccessful complex e-learning

Appears to draw on literature to give examples of complex e-learning projects that failed in various stages of the development process

  1. During development – “getting it finished” – Cheng et al (2006).
  2. “Getting it used”

A model to show why innovation is challenging

Going to present two ways of “representing the challenges that face innovation and change – in this case we are considering a complex interactive use of e-learning in campus-based universities”.

The first is the J Curve. i.e. things will get worse before they get better “because of the expenses and challenges that occur early on in the innovation cycle”.

Note: But like much of the innovation literature this simplification doesn’t capture the full complexity of life, innovation and e-learning. If innovation is in something that is rapidly changing (e.g. university e-learning) then is there ever an upward swing? Or does the need for a new innovation – and another downward spiral – occur before you get the chance to climb out of the trough? For example, does the regular LMS migration phase in most universities (or the next organisational restructure) prevent any ability to climb up the J curve?

The second is the S curve (a related representation below). i.e. diffusion occurs through innovation, growth and maturity. With the transition from “innovation” to “growth” phase being the most important. And it’s hard

Leading innovation through the bottom of the J-curve or through the transition from ‘innovation’ to ‘growth’ in the S-curve is not easy as this process often requires people to rethink their beliefs and reformulate their ways of working; this is difficult. (p. 271)

Now brings in Lewin’s ideas about conceptual change process as a way of thinking about the challenge of changing beliefs and practices (a model the authors have used previously). This process has three stages

  1. “a process for diagnosing existing conceptual frameworks and revealing them to those involved;”
  2. a period of disequilibrium and conceptual conflict which makes the subject dissatisfied with existing conceptions; and
  3. a reforming or reconstruction phase in which a new conceptual framework is formed” [Kember et al. (2006), p.83]

Note: A few years ago I expressed some reservations about the applicability of Lewin’s model. I think they still apply.

To some extent this quote from the author’s gets at some of my reservations about this perspective on encouraging change with e-learning (emphasis added) “The process of demonstrating to teachers that there might be a better way forward with their use of e-learning requires evidence and this is why evaluation is so critical” (p. 271).

The assumption here is that there is a better way for the teacher to teach. We – the smart people who know better – just need to show them. Given the paucity of quality technology available within universities; the diversity of teachers, students and pedagogies; and the challenge from Weaver above I wonder if there is always a better way to demonstrate that is – to employ some Vygotsky – within the Zone of Proximal Development of the particulars of the learning/teaching context?

The author’s model for understanding the challenges facing e-learning, innovation and change is

  1. An understanding that change is not easy and always meets resistance (J-curve).
  2. An appreciation that there will be no significant gains unless significant numbers of teachers begin to adopt the innovation – in this case, complex e-learning (S-curve).
  3. A suggestion that the process of implementation should model the three stages of the conceptual change process. Evaluation is integral to this process.

Note: Are people all the change averse? Sure, we are/can be creatures of habit. However, when it comes to e-learning and that sort of “innovation” the change is often done to students and staff, rather than with them. i.e. the particular tool (e.g. a new LMS) or pedagogical approach (e.g. MOOC, flipped classroom etc) is chosen centrally and pushed out. Systems that are developed with people to solve problems or provide functions that were identified as needed are different (I think).

Note: I find #1 interesting in that it takes the J-Curve to suggest that there will always be resistance. From their introduction to the J-Curve the point seems to be that innovation brings challenges and expense that mean ROI will drop initially. This doesn’t seem to be about resistance.

Note: #2 is also interesting. The requirement that there be significant levels of adoption prior to significant gains arising from an innovation is a problem if you accept good quality L&T being about contextually appropriate approaches. The sheer diversity of learners, teachers etc – no to mention the rapid on-going change – suggests that this model of “significant gains == significant levels of adoption” may not fit with the context. Or at least cause some problems.

The study

Qualitative method to collect reflection of practitioners in the field “regarding the challenges in the various stages of development and use of complex e-learning strategies”. 5 authors – 3 from central L&T and 2 were pioneering teachers.

Note: Would appear that the sample is biased toward the “innovators”, involving other folk may have revealed very different insights.

Three sources of data

  1. Detailed interviews with teachers and programmers and analysis of email communication logs for projects that were never implemented.
  2. Publications about the work of one of the authors.
  3. Similar from another author.

Findings

Iterations of reflection and discussion led to a table of challenges.

Teachers Students Supporting staff Technology/Environment/Culture
Planning and development Limited time and resources Miscommunication Restrictions in university resources and support
Necessity of new skills Different perception of tasks with teachers Technology being inflexible
Miscommunication Limitation in resources and expertise Idiosyncratic nature of development
Different perception of tasks with support team Idiosyncratic nature of development
Implementation New to strategies
Unwillingness to learn differently
New to strategies Sustainability
Cost-effectiveness
Dissemination Unwillingness to share
Unmotivated to learn new technologies
Strategies do not match teaching styles
Contrary to existing T&L practice
Evaluation Lack of cases Lack of appreciation Question about effectiveness

These are elaborated more with examples.

Discussion

Taking the four sources from the above table, the authors propose the idea of a “mutual comfort zone”. An e-learning project needs to have all of the factors in this MCZ for it to be successful. The paper illustrates this with the obligatory overlapping circle diagram.

Cases of successful complex e-learning strategies, thus, seem to be limited to the instances when all the factors noted in Figure 4 work in unison. It is therefore easy to see why successful cases of complex e-learning are not all that common and are restricted to highly motivated pioneering teachers who are comfortable with innovative technologies and may also be in an innovation-friendly environment. (p. 281)

Note: resonating with the mention of ZPD above.

Becoming more optimistic, the future is promising because

  • The tools are getting more “e-learning friendly”.
  • LMSs are “now more user-friendly and more flexible” makes mention of open source LMSs like Moodle.

    Note: But doesn’t more flexibility bring complexity?

  • Teachers now have better IT skills are want to use technology.
  • Supporting services are proving based on accumulated experience.

    Note: I wonder about this. Organisational restructures and the movement of people aren’t necessarily helping with this. I can point to a number of situations where it has gone the other way.

  • Institutions are adopting e-learning, so the policy problem is solved.

    Note: Assumes that the policy is done well and actually can and does have an impact on practice. I’m not sure those conditions are met all the tie.

Given all this “E-learning might then reach a critical mass and so that e-learning will progress beyond the valley bottom of the J-curve and will start climbing the growth phase in the S-curve”.

I wonder if this is evident? This links very nicely with some of the ideas in my last post.

References

Mcnaught, C., Lam, P., Cheng, K., Kennedy, D. M., & Mohan, J. B. (2009). Challenges in employing complex e-learning strategies in campus-based universities. International Journal of Technology Enhanced Learning, 1(4), 266–285.

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