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.


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