Journal of Knowledge Management Practice, June 2002

Success Factors For Development Of Knowledge Management

In e-Learning In Gulf Region Institutions

Andy Igonor, College of Business & Economics, UAE University

ABSTRACT:

Contends that Knowledge Management (KM) does not seem to have had much impact on the higher education sector so far, although there is some evidence of some Universities undertaking research in this area. Asserts that many Universities in the Gulf region, especially the United Arab Emirates are beginning to develop e-learning courses, as part of the move to integrate IT in their educational system. States that it is the intent of this paper to look at how much of knowledge is being managed and shared in the development of these online programs while keeping to the educational goal of graduating lifelong learners.

 


e-Learning Is Not Knowledge Management; Quality e-Learning Manages Knowledge

e-Learning has begun to gain popularity in almost every sector of most societies. Countries are developing initiatives to prepare their entire citizenry for participation in the so-called knowledge economy, with e-learning offering people the skills and tools needed to succeed in the “new economy”. While businesses are amassing gains in the delivery and sale of e-learning products, universities are relentless in their efforts at developing quality e-learning products that are aimed at attracting students in dispersed locations.  e-Learning offers learners the ability to learn anywhere, anytime and at their own pace.

e-Learning is instruction that is delivered electronically, in part or wholly – via a web browser, such as Netscape Navigator, through the Internet or Intranet, or through Multimedia platforms such as CD-ROM or DVD. Increasingly – as higher bandwidth has become more accessible – it has been identified primarily with using the web, or an intranet’s web, leveraging the web’s visual environment and interactive nature. The Bank of America in Gaede (2002) defines e-learning as the convergence of learning and the Internet, while Cisco systems defines e-learning as “Internet-enabled Learning”. Also e-learning is seen as the delivery of individualized, comprehensive, dynamic learning content in real time, aiding the development of communities of knowledge, linking learners and practitioners with experts. If well developed, e-learning has the ability to deliver accountability, accessibility and opportunity allowing people and organizations to keep up with the rapid changes that define the Internet world.

While the emphasis on e-learning centers around the “e” promising the learner the ability to learn anywhere and anytime due to the power forces of computer and communications technology, other derivable benefits for the developers of e-learning products include – cost reduction, increase in effectiveness, increased retention, increased consistency and increased flexibility and access (Gaede, 2002)

According to Webster’s Dictionary, knowledge is "the fact or condition of knowing something with familiarity gained through experience or association". In practice, though, there are many possible, equally plausible definitions of knowledge. A frequently used definition of knowledge is "the ideas or understandings which an entity possesses that are used to take effective action to achieve the entity's goal(s). This knowledge is specific to the entity which created it."  (Denning, 2000). Denning further explains that an understanding of knowledge requires some grasp of its relationship to information. In everyday language, it has long been the practice to distinguish between information — data arranged in meaningful patterns — and knowledge — which has historically been regarded as something that is believed, that is true (for pragmatic knowledge, that works) and that is reliable. In the words of Drucker (1993) Knowledge is like the sound of the tree that falls in the forest when no one is there: it doesn’t exist unless people interact with it. Knowledge is information that changes something or somebody – either by becoming grounds for actions, or by making an individual (or an institution) capable of different or more effective action. Fleming (1996) traces the Knowledge from Data processed into information in Figure 1.

Figure 1

From this diagram Fleming concludes that:

                  Information relates to description, definition, or perspective (what, who, when, where).

                  Knowledge comprises strategy, practice, method, or approach (how).

                  Wisdom embodies principle, insight, moral, or archetype (why).

Alain Godbout (1999) further explains the hierarchy meanings attached to the data-information-knowledge-wisdom cycle in Figure 2.

Figure 2

According to the American Productivity and Quality Centre (2001), Knowledge Management is the broad process of locating, organizing, transferring, and using the information and expertise within an organization. Four key enablers support the overall knowledge management process: leadership, culture, technology, and measurement. Perhaps, one may say one of the goals of e-learning is to package chunks of knowledge and get them to the needed audience as quickly as possible. Despite the fact that similarities between e-learning and KM are beginning to evolve – especially in the technology that drives them – some important differences will need to be resolved for them to be effectively integrated (Barron, 2001)

KM in e-learning – What is that?

Tom Barrron (2001) reviews the marriage of e-learning and Knowledge Management as follows: Take an e-learning course. Chunk it into discrete learning bites. Surround it with technology that assesses a learner's needs and delivers the appropriate learning nuggets. Add collaborative tools that allow learners to share information. What do you get? Something that looks a whole lot like knowledge management. “.  A further review of Barron’s proposition reveals what the ideal e-learning course should look like as against the reality. In other words, quality e-learning should indeed manage knowledge. Alternatively, e-learning should have knowledge filtered and delivered to the right audience. This filtering process according to Godbout (1999) is typically exemplified in Figure 3:

 

Figure 3

The important question to answer here then is: Do e-learning courses filter information this way? And very specifically do they provide answers to the following questions:

                  How much knowledge is captured and retained by a learner?

                  How do we measure the amount of knowledge that is acquired in an e-learning process?

                  How do we design e-learning courses that indeed manage knowledge following the definition of knowledge management?

                  What standards define a knowledge-centric e-learning course?

                  How do we keep in touch with learners after going through an e-learning program to determine the applicability of what they have learnt in the outside world?

These are pertinent issues which hitherto remain unresolved.

Denning(2000)’s Knowledge Management framework reviews a work originally done by Van der Spek and de Hood in which he covers such issues as:

                  Identifying what knowledge assets a company (perhaps, a learner) possesses

                  Analyzing how the knowledge can add value

                  Specifying what actions are necessary to achieve better usability and added value

                  Reviewing the use of the knowledge to ensure added value

The work of David Harris (1996) may shed some light on making the transfer of knowledge support possible, including the filtering of information identified above in Figure 3. According to Harris, to support a knowledge-centric approach in an IT environment (the e-learning environment could be well adapted here), a system needs to be implemented that will integrate knowledge transfer into everyday activities. The system needs to encourage use without being obtrusive. The system needs to be flexible. As the system is used, the system will constantly change and evolve (Bohn, 1994). Harris further explains that the system must allow for the extension of previous knowledge, a declaration of the context of the original knowledge, as well as the context for each increment. Harris concludes that for successful integration of knowledge into everyday activities, the support structure needs 3 important elements: an organizational component, a process component and a technology component. The organizational component, in Harris’s words, includes the adjustments to management philosophy, group member interaction and individual responsibilities. The process component includes changes to problem solving processes, decision-making processes and communication processes. The technology component requires the implementation of the technology that will become the knowledge base repository as well as the any other required support technology.

I strongly believe that the above views regarding the successful transfer of knowledge support structures – essential ingredients – for the successful knowledge-centric e-learning programs hold extreme relevance, especially if we are to develop quality, perhaps measurable e-learning programs in the Gulf region.

Gulf experience – Integrating Knowledge Management in e-Learning

Steve Denning (2000) presented the six laws of Knowledge Management as:

                  Knowledge sharing is key to survival

                  Communities: heart and soul of KM

                  Virtual communities need physical interaction

                  Passion drives communities of practice

                  Knowledge need inside-out and outside-in

                  Storytelling ignites knowledge sharing

Denning states that knowledge sharing is key to organization survival. Hence organizations need to develop a knowledge sharing culture and processes. Failure to have this in place leaves room for grave consequences. The University as an organization also has a big role to play in this. If KM is to be integrated into the development of e-learning programmes, then an establishment of a knowledge sharing culture needs to be proven. Its has been proven that capturing and sharing existing knowledge is not only timesaving but also cost saving for any organization. The formation of learning communities, according to Denning allows the acceleration of learning and knowledge transfer. Denning further states that the absence of a periodic face-to-face meeting of virtual communities may lead to the eventual death of such communities, due to a lack of energy. Denning elaborates that communities of practice only flourish when their members are passionately committed to a common purpose, whether it be the engineering design of water supply systems, the pursuit of better medical remedies, or more efficient economic techniques. According to Denning, starting and implementing knowledge sharing must be done from the inside – the implication been that people who already have an understanding of the culture, requirements and knowledge base of the community – are been used. It is necessary albeit, that such knowledge be validated through outside links. Steve Denning concludes his laws of KM stating that telling stories that build on real knowledge sharing situations, enables individuals to gather in some of the understanding of the storyteller as well as recast the story into their own contextual work environment; hence adding their own understanding to the process.

Universities like many other institutions are currently grappling with the dilemma of the use of technology in teaching and learning and developing strategic plans and processes that will take them forward in sustainable ways (Oliver, 2001). Gulf institutions are not exactly different in this respect. I agree with Oliver that technology will indeed play a large role in the planning, development and delivery of the curriculum of the contemporary university. While this paper looks at the integration of KM in e-learning, this issue is further corroborated by Biggs (Oliver, 2001) on developing quality assurance in online learning, where he discusses 3 important elements: quality as value for money; quality as fit for the purpose on the institution and quality as transforming. Biggs argues (Oliver, 2001) that while the first of these is a retrospective measure, the remaining are pivotal parts of any quality assurance process aimed at maintaining and enhancing the quality of teaching and learning in the institution. I believe as contended by Oliver (2001), the development of knowledge-centric, quality e-learning programs, will require a look at a number of factors including the following:

                  Teacher expertise

                  Student readiness

                  Technology infrastructure

                  Reusable learning objects

                  Reusable learning design

Oliver clearly points out that for online teaching to be mainstream, it is necessary for institutions to ensure that their teachers have appropriate skills and expertise not only in the delivery of online courses and programs, but also their design and development. Oliver further states that a substantial proportion of the literature describing online learning provides evidence of a lack of teacher readiness for large-scale moves to online learning. Online teaching requires the teacher to possess a highly different skill set to that of conventional face-to-face teaching. Goodyear, et al. (2001) argue a need for professional development to focus on the various new roles of the online teacher including researcher, assessor, advisor, technologist, designer and manager.

e-Learning programmes are designed or supposed to be designed to be student-centered. In this case, it is important to look at the students’ readiness to be a part of this learning wave. From Oliver (2001), a number of studies in recent years have highlighted critical aspects of learner readiness that need to be addressed. Some of these include:

                  Technology skills

                  Access to Technology

                  Technology Literacy and

                  Self-regulated learning

While it may be relatively easy to achieve points 1 to 3 above, perhaps one of the most critical for Gulf institutions to fully embrace e-learning is the ability of students to be able to determine and manage their own learning process. The issue of maturity is one that cannot be neglected for e-learning to thrive in the Gulf world. While language, which was once a critical barrier in effective teaching and learning, is being gradually managed, the other important psychological factor relating to students’ readiness for self-paced and directed learning remains unresolved.

Technology Infrastructure necessary for e-learning include, according to Oliver (2001) Courseware delivery systems, Technology Infrastructure and Service Provision. Jonassem and Reeves (1996) strongly believe the need for infrastructure to be tied to the professional development of staff so that decisions are led by pedagogical and educational considerations rather than the technology itself.

According to IEEE (2001), a Learning Object is any entity, be it digital or non-digital, that may be used for education and training.  Due to the heavy expense involved in the design and production of e-learning courses, it is important that materials used in the development of these course – graphics, video and audio material etc – be stored for future re-use. Oliver (2001) states that apart from providing cost-effective measures, Learning objects, support quality instructional design. The same importance of the re-usability of learning objects holds true for the design of the courses as well.

Against this backdrop, one may ask where Gulf institutions stand with regard to the development of e-learning courses capable of managing knowledge. From the above, it seems prudent for Gulf institutions to build e-learning courses that will manage knowledge based on Denning’s six laws of KM (Denning, 2000) and Oliver’s requirements for successful e-learning (Oliver, 2001).

Measuring KM in e-Learning

Measuring KM is not an easy task. Albeit, in order to manage how much knowledge is being managed in an e-learning course – as a perquisite or guide in the development of quality e-learning courses – it is imperative to devise methodologies for measuring knowledge.  Determining KM's pervasiveness and impact is analogous to measuring the contribution of marketing, employee development, or any other management or organizational competency (APQC, 2001).

During its 2000 consortium-learning forum entitled Successfully Implementing Knowledge Management, APQC focused on how some of the most advanced early KM adopters implement a knowledge management initiative, mobilize resources, create a business case, and measure and evolve their KM programs. This multiclient benchmarking project helped APQC and project participants identify measurement approaches, specific measures in use, and how measures impact and are impacted by the evolution of KM. Some of the very important measurement points from the APQC study include the following:

                  Measure for progress

                  Measure the gap

                  Measure against a Benchmark

                  Measure your cultural readiness

                  Measure the business value

                  Measure the retention of knowledge

                  Measure the cultural impact

                  Measure the effectiveness of sharing communities

                  Measure the ownership of capital and compilation

                  Measure project management effectiveness and intended results

While it is not the intent of this paper to go into the complex abstract details of the theories or proposed models for the measurement of knowledge, it is worth mentioning that there are ongoing researches in this area. Peter Pirolli and Mark Wilson (1998) discuss explicitly two approaches to the measurement of knowledge: first is a theoretical view of cognition called the Newett-Denett framework which is seen as favourable to the development of measurement approaches; and a second based on a model by Rasch (1960) favourable to the development of cognitive theories. While it may be extremely complex in determining the amount of knowledge managed in an e-learning course, it is still a critical success factor that e-learning courses be designed to fit the needs of a particular audience.

Conclusion

This paper has attempted to review the critical success factors for the development of e-learning courses that actively manage knowledge. Realizing that emphasis on e-learning is the ability to learn anywhere, anytime and at one’s pace and also that KM focuses more on the content, communication, retention and application of knowledge learnt in an e-learning course, this paper proposes that a good mix of the these two sub-disciplines will eventually lead to the development of quality and measurable knowledge-centric e-learning programmes not only for Gulf institutions, but other institutions willing to embrace this new wave of learning called e-learning.

References

APQC (2001), American Productivity and Quality Center, APQC: The Leading Edge of Knowing

Barron T. (2001), A Smarter Frankenstein: The Merging Of e-Learning And Knowledge Management, In ASTD Online.

Bohn D. (1994), Thought As A System, New York, Routledge

Denning S. (2000), The Springboard: How Storytelling Ignites Action In Knowledge-Era Organizations, Boston, Butterworth Heinemann

Drucker P. (1993), Post Capitalist Society, New York, Harper Business

Flemming T. (1996), Coping With A Revolution: Will The Internet Change Learning? Lincoln University, Canterbury, New Zealand

Gaede O. (2002), e-Learning – What Is It? How Did We Get Here? Where Are We Going? College Of Information Technology Symposium, United Arab Emirates University

GodBout A. (1999), Filtering Knowledge: Changing Information Into Knowledge Assets, Journal of Knowledge Management Practice, Vol 1, 1998-1999, http://www.tlainc.com/jkmpv1.htm

Goodyear P., Salmon G., Steeples C. and Tickners, S. (2001), Competencies For Online Teaching: A Special Report, Educational Technology Research And Development, Vol.49; No.1; pp 65-72

Harris D. (1996), Creating A Knowledge-Centric Information Technology Environment. In Knowledge Environment, http://www.dbharris.com/ckc.htm

Jonassen D. and Reeves T. (1996), Learning with Computers: Computers As Cognitive Tools, in D. Jonassen (Ed), Handbook Of Research For Educational Communications And Technology (pp.693-719), Macmillan Library Reference, New York

Oliver R. (2001), Assuring The Quality Of Online Learning In Australian Higher Education. Paper presented at the "Moving Online Conference II" 2-4 September, Southern Cross University, Gold Coast, Australia, http://www.scu.edu.au/schools/sawd/moconf/MOC2_papers.html

Pirolli P., Wilson M. (1998), Theory Of Measurement Of Knowledge Content, Access And Learning. Psychological Review, Vol. 105, No. 1; pp. 58-82

Rasch G. (1960), Probabilistic Models For Some Intelligence And Attainment Tests, Danmarks Pdagogiske Institut, Copenhagen; Expanded Edition, 1980, University of Chicago Press, Chicago



Contact The Author:

Andy Igonor is a Lecturer in Management Information Systems at the United Arab Emirates University. Previously he was employed as a Senior Consultant for an International e-Learning company in Singapore; lectured Management Information Systems at a University in South Africa; and was a Consultant in Database Management with the United Nations Childrens Fund (UNICEF).

To contact the author: Andy Igonor, MIS Division, College of Business and Economics, UAE University, P.O. Box 15551, Al-Ain, United Arab Emirates