Learning Management Systems (LMS) such as Blackboard, Moodle, SAKAI, and
Desire2Learn (D2L); are now nearly ubiquitous in Higher Education. These platforms represent
a suite of technologies, tools, and processes; when implemented and utilized skillfully, can have
a positive effect on teaching and learning. Traditionally a LMS is defined as an Internet-based
application that creates and distributes course content, manages student enrollment, tracks
student performance, include tools that allow easy access to digital resources, and enable a wide
range of collaboration activities within the LMS environment.
Here at the University of Arizona, D2L is the selected LMS for teaching and learning.
While the University has remained consistent in upgrades to the D2L system, it is acknowledged
that these changes may or may not be keeping pace with the changes in pedagogical demands of
students and Instructor (M. Felix, personal communication, March 8, 2013). The goal of this
study is to determine if there is a correlation between the D2L tools used by instructors and the
number of attended consulting hours. These hours of consultation are provided by the Office of
Instruction and Assessment (OIA) on campus. In the next section, I will highlight the current
literature on D2L tool usage and their effectiveness in teaching and learning.
Literature Review
Significant use of LMS platforms at thousands of institutions by hundreds of thousands
of Instructor members and students might be taken as apparent evidence that the technology adds
value to teaching and learning. However, usage patterns suggest that the LMS is primarily a tool
set for administrative efficiency rather than a platform for substantive teaching and learning
activities. These concerns have been exacerbated by rapid growth in LMS-related spending over
the past decade, which has led many to question whether the benefits of the technology are worth
the cost (Bush & Mott, 2011).
Several reports confirm that instructors overwhelmingly use content distribution and
administrative tools in the LMS while using interactive learning tools only sparingly (Morgan &
Hill, 2009). These studies indicated a variation in use of quiz and gradebook tools over time and
across institutions. However, they were consistent in the conclusion articulated by Morgan:
"Instructor use the CMS primarily as an administrative tool … rather than as a tool anchored in
pedagogy or cognitive science models." This is true, Morgan (2003) argued, because the LMS is
"fundamentally a conservative technology ... [for] managing groups, providing tools, and
delivering content." (p. 1). Also Richlin (2006) concluded that LMSs have become little more
than "storage facilities for lecture notes and PowerPoint presentations." (p. 2). This usage profile
of the LMS is troubling because, as Arvan (2009) argued, it reinforces the status quo:
The LMS serves as an affirming technology of traditional teaching. The instructor
doesn’t challenge the LMS very much, and, in turn, the LMS doesn’t challenge the instructor.
The student gets the convenience benefit from electronic distribution of documents (and grades)
but little more.
Arvan lamented the fact that the LMS has come to be viewed as the educational
equivalent of an enterprise application like PeopleSoft. PeopleSoft, created by the company
Oracle®, is designed to provide comprehensive business and industry solutions, enabling
organizations to increase productivity, accelerate business performance, and provide a lower cost
of ownership (Oracle, 2013). The problem with this perception, Arvan argued, "teaching and
learning are not fundamentally transactional." The transactional pull of the LMS, however, draws
instructors into its content-centric tendencies. When instructors start with the LMS, Lane (2009)
claimed, they are engaged in a "backward process … creating a course piecemeal" instead of
thinking about their teaching approaches firsthand, and then selecting the right tools to
implement them (p. 2). The tendency to use the LMS for administrative purposes should not be
surprising. Cuban’s (2001), exhaustive study of the effects of technology spending on K–20
education in Silicon Valley concluded that "traditional forms of teaching seem to have been
relatively untouched by the enormous investment in technologies that the university has made
since the 1960s (p. 134). A recent U.S. Department of Education report echoed this conclusion as
the report listed that technology has been applied to the outside of the education process, rather
than as a critical tool in revamping the process itself (USDOE, 2008).
Theoretical Framework and Hypotheses
Theories related to education and technology are pertinent to this research and identify
similar factors. Two theories that have been applied to the area of technology use, and changes in
higher education are (a) the diffusion of innovations theory (Rogers, 1995), and (b) the change
theory as it relates to the use technological tools in education (Fullan, 2001). An analysis of each
theory revealed that one factor, administrative support and practices, is present in each theory
and it is consistent with the findings of this study.
Diffusion of Innovation Theory
The diffusion of innovation theory relates to the adoption of new technologies into the
teaching and learning process. As described by Rogers (1995), there are five adopter categories
including innovators, early adopters, early majority, late majority, and laggards. The categories
are based on the rate of adoption of an innovation and reflect the rates that university instructors
adopt technological innovations. Diffusion is influenced by four major factors including the
innovation itself, innovation information distribution, time, and the social system adopting the
innovation (Rogers & Scott, 1997). Given the recent availability and usage of LMSs, the
diffusion theory is relevant in that university instructors who are innovators or early adopters of
technologies may be among those who are likely to use several tools within the LMS. Another
theory that relates to this research is the change theory (Fullan, 2001).
Change Theory
The change theory by Fullan (2001) is associated with technology integration. Fullan
identified seven factors that influence the adoption of changes. Those factors include the (a)
access to innovation, (b) orientation to a new policy, (c) community support or pressure or
apathy for the change to take place, (d) administrative support, (e) existence and quality of
instruction and innovation that change will bring, (f) external change agent that supports and
initiates the changes; and (g) professor advocacy. Fullan asserts that there are three stages
consistent in the change theory. Stage 1 is the Consistent factors present in the diffusion of
innovations theory and the change theory are administrative policy and practices. Another
prominent factor that appears in these two theories is the innovation itself. Namely, the
innovation is a contributing factor that determines if Instructor members will adopt it into their
teaching practices. In addition to the identified theories, several research studies support similar
findings.
Conclusion
LMSs like D2L have become as commonplace as the Internet or email. Many institutions
of higher education have enabled either an open source or a commercial version of the software.
Here at the University of Arizona, D2L has occupied an ever increasing and prominent role in
the teaching and learning process, paving a new road and changing the many of the existing
methods and environments of instruction. Although D2L is a collection of tools that embody a
pedagogical vision, I believe that the successful adoption by instructors of as many of these tools
as possible is the only way the software can create an effective learning environment.
References
Arvan, L. (2009). Dis-Integrating the LMS, EDUCAUSE Quarterly, 32(2).
Bush, M. D. and Mott, J. D. (2011). The transformation of learning with technology: Learnercentricity, content and tool malleability, and network effects," Educational Technology,
49(2), pp. 3–20.
Cuban, L. (2001) Oversold and underused: Computers in the classroom. Harvard University
Press, pp. 129-138 Cambridge, MA.
Felix, M., (2013) Office of Instruction and Assessment, Director of Technology Services.
Fullan, M. (2001). The new meaning of educational change. Toronto, ON: Irwin.
Lane, L. M. (2009). Insidious pedagogy: How course management systems impact pedagogy.
First Monday, 14(10).
Morgan, G. (2003). Instructor use of course management systems, ECAR Research Bulletin, 2.
Morgan, G., & Hill, P. (2009). CSU academic technology research bulletin #4: A summary of
the learning management systems summits conducted October 2009. Retrieved August
13, 2012, from http://iacc.calpoly.edu/Document/2008-09/CSU-AT-Research-Bulletin2.pdf
Richlin, L. (2006). Blueprint for learning: Constructing college courses to facilitate, assess and
document learning. Sterling, VA: Stylus.
Rogers, E. (1995). Diffusion of innovations (4th ed.). New York: Free Press.
Rogers, E., & Scott, K. L. (1997). The diffusion of innovations model and outreach from the
national network of libraries of medicine to Native American Communities. Retrieved
November 21, 2012, from http://nnlm.gov/pnr/eval/rogers.html
U.S. Department of Education. (2008). Harnessing innovation to support student success: Using
technology to Personalize Education. Retrieved March 15, 2013, from
www2.ed.gov/about/offices/list/os/technology/reports/roundtable.html.