Running Head: TRAINING
STRATEGIES and e-LEARNING
Training Strategies and e-Learning
Anthony P. Niemann
ELFH 675-50
Training Strategies and e-Learning
There are many new traning strategies involving e-Learning in education today. Perhaps the term e-Learning should be placed in
historical context before we examine strategies. During the 1960s and 1970s this researcher worked in
the computer field maintaining analog computers for the U.S. Air Force. Since the early 1970s computer technology has
changed the face of education. Technicians who worked in the field repairing
computers for companies such as General Electric, Honeywell, Burroughs,
Sperry-Rand (Univac), Raytheon, IBM, and DEC (Digital Electronics Corporation)
were used to making frequent trips to areas of the northeast to attend electronic
schools run by computer industry companies. For every software engineer working
in the field in those days there were ten hardware engineers. Hardware repairs
had to be performed at the component level, not the printed circuit board level.
In the 1980s the situation changed rapidly as personal computers replaced
mainframe computers in businesses throughout the country. The center of the
computer industry moved from the northeast to the west coast. Mnemonics such as
CBT (Computer Based Training), already becoming a well-known term in the
computer industry in the 1980s, soon became recognized by human resource
departments throughout the country.
The evolution of e-Learning
strategies since the 1980s has been dramatic. There are strategic reasons for
employing e-Learning in training efforts. We are told that web-based training
is strategic when it is used to support long-range goals (Driscoll, 2002).
Reasons would include the following: developing a global workforce; responding
to shorter product development cycles; managing flat organizations; adjusting
to needs of employees; enabling a contingent workforce; retaining valued
workers; and increasing productivity and profitability (Driscoll, 2002). International
Data Corporation (IDC), an organization that tracks industry trends, reports
that from October of 2005 until 2008 the e-Learning market should more than
double (Tucker, 2005). They project a 13.5 billion dollar market in the
A LMS gives the employer a method to
track employee training. This can be quite expensive, ranging from $20K to 900K
in 2002 dollars (Driscoll, 2002). Often, an LMS system will be integrated into
the company’s human resource application, such as PeopleSoft or Systems
Applications and Products in Data Processing (SAP) software (Driscoll, 2002). Concerns
about systems integration and costs foretell a battle in the marketplace
between the large integrators that Driscoll mentions and the smaller ones such
as TEDS, Click2Learn, Plateau Systems, and
There are some who feel that the decision to
implement an LMS is overly driven by technology (Dealtry, 2005). Perhaps the
path to become an e-Learning organization should first be prepared by
developing learning organization culture and infrastructure. This involves using
a “holistic stakeholder approach that connects with all the management, resourcing,
and underlying organisational activities which are essential for the creation
of a well managed, cohesive and sustainable strategic learning intervention”
(Dealtry, 2005, p. 467). With the growth of e-Learning associated we see inquiry
to discover what makes it work well. One very recent study found that students who
had high proactive personalities in addition to high learning goals had a much
greater appreciation of the quality of learning that occurred. They also
experienced greater satisfaction with the learning experience (Kickul, G. &
Kickul, J., 2006). The study emphasized the importance of understanding a
student’s personality and learning goals. Yet another research project tracked
instructors and students activities, recording them for analysis. Later, the
data was extracted to discover how and when learning took place, thereby
linking learning to instructor and student activities (Luczaj, 2003).
Decisions made in using e-Learning strategies also
involve choices about how information is presented. Driscoll (2002) dedicates
an entire chapter in discussing ways to implement and evaluate e-Learning.
Implementation and evaluation are the final two stages of the well known ADDIE
model. Choices include types of tools organizations choose to use. One research
tool that a large organization may consider implementing during these stages is
data mining. With the huge investment that is currently taking place in
e-Learning for academics and business, this tool can be very useful. Data
mining can be defined as the process of analyzing data to identify patterns. Data
mining involving e-Learning, also known as web-mining,
consists of three basic types: content, structure, and usage (Hanna, 2004). In
defining the three concepts, Hanna differentiates between targeting and usage by
saying that “Unlike targeting, personalization may be performed on the target
Web page” (Hanna, p. 30). Content mining employs methods designed to improve on
performance of “traditional search engines through such techniques as concept
hierarchies and synonyms, user profiles, and analyzing the links between pages”
(Hanna, p. 30). Hanna believes that e-Learning has yet to tap into the benefits
of data mining techniques.
As in other forms of instructional design, the e-Learning
audience should be considered. There is a difference between a LMS and a LCMS,
or Learning Content Management System. The first (LMS) has to do with administration
of the students, courses and integration with the core of the company
activities, while the second (LCMS) has to do with content of those classes. Examples
of LCMSs were presented by Bryan Chapman (2003) when he wrote about four companies
that created products for presenting content specifically for Palm devices and
Pocket PCs. Matching the tool to the audience the content targets is critical.
Another tool that that many e-Learning designers have
turned to is simulation software.
Many younger students grew up with video games created for the computer and the
web. According to Clark Aldrich, co-founder of SimuLearn, simulations designed
for e-Learning tends to be “good for reluctant learners and places with high
turnover” (as cited in Weinstein, 2006, p. 34) and “really bad for high
potential, or highly creative people” (as cited in Weinstein, p. 35).
Simulation software can be very expensive, so you might look for an
off-the-shelf product that can be modified to fit the target audience. Many experts feel that the cost of simulation
software is reasonable if you ensure the software is scalable and reusable. Pricing
for simulation software can vary widely, but here are some costs offered in Weinstein’s
article:
·
Out of the box –
per user $100-$200
·
Custom job $200,000-$300,000
·
Interactive
spreadsheet model -per user/daily $500
·
Virtual labs $100,000-$300,000
·
Electronic
version of games –per user
(Trivial
Pursuit) $25-$30
Tony Burns (2005) writes about the
effectiveness of including games and humor in corporate training programs targeting
quality improvement. Among the benefits are costs and time, but to be effective
e-Learning must be user friendly and have “fun motivational content” (Burns, p.
50). If both conditions are satisfied the training will work.
Research targeting strategies for
use with e-Learning audiences has been enlightening. Students’ perceptions
about e-Learning were examined in an undergraduate accounting class (Flynn,
Concannon, & Bheachain, 2005). Their research may have significance for
targeted audiences in university settings that use a blended approach where
traditional classes are combined with current e-Learning strategies. This study
found that e-Learning required considerable more resources than traditional
face-to-face classes. Access of peer to tutor interaction, help, and support
were big factors in success of e-Learning portions of the class. Additional research
(Bambara, Lambert, Andrews, & Harbour, 2006) has indicated that a suitable
framework for student – instructor interactions in e-Learning courses has not
been suitably established. Suitable frameworks require a significant effort on
the part of instructors to assist students taking courses.
In university settings at locations in Hong Kong
where e-Learning has become a priority, a consequence of the government’s push
to establish a knowledge-based economy, there have been significant problems
noted. Among the problems are high student drop-out rates and low student
satisfaction with the learning process (Leung & Li, 2006). In other studies
of virtual synchronous classrooms (VSC) a gap was found in current
instructional design theory and the use of e-Learning technology, and this gap
greatly affected learners who are outside the university setting. VSC is not available to many non-university
students (Thompson, 2003).
Corporate education using a blended, instructor-led
approach coupled with e-Learning techniques has grown exponentially in the past
several years. Minaya (2005) completed an impressive study of the blended
approach and reported seven findings in his research. Of the following seven
findings, note that four involve the instructor:
·
Blended learning
is here to stay
·
Efforts are
being made to increase scale and reduce costs
·
Instructors are
fearful as to what will happen to their jobs
·
There is little
training to help instructors transition to blended learning
·
Instructors who
do not make the transition will lose their jobs
·
Corporate
universities that do not make the transition to blended universities will cease
to exist as a result of costs and value factors
·
Corporate
leadership wants proof for the effectiveness of instructors and the training
that they provide
Training strategies involving e-Learning would not be
complete without discussing guidelines for the best ways to use text, graphics,
and audio on a web page. For guidance in this area we take a brief glance at
six principles highlighted in a book by Ruth Clark and Richard Mayer (2003):
1. Use words and graphics rather than words alone. The
authors cite cognitive theory and research evidence to corroborate this
principle.
2. Place corresponding words and graphics near each
other. The authors tell us that people learn better because they can easily
make sense of the association, instead of using cognitive resources (mental
association) to link two items that are physically separated from each other. Research
sources are cited as evidence for conclusions.
3. Present words as audio narration rather than onscreen
text. If you employ principle “1” above, then the authors feel that spoken words
are preferable to written words. Cognitive overload is cited as the reasoning
for this principle, i.e., the reader would have to look at the words AND look at the figures.
4. Presenting words in both text and audio narration can
hurt learning. Reasoning includes the fact that this may overload the visual
channel. The authors cite empirical evidence for stating this principle.
5. Adding interesting material can hurt learning.
“Material” includes sounds, graphics, and words. The theory behind this
principle relates mainly to the possibility that the learner may become
distracted.
6. Use conversational style and virtual coaches. The
authors, once again, base their conclusions on cognitive theory and empirical
evidence.
In the six principles highlighted above, the authors
tell us that their recommendations may not apply in all cases. For example, if
the personalization principle highlighted in item “6” above was used
excessively, then distraction could occur. The authors present psychological
reasons for the six principles, as well as explain them in much greater detail
than has been presented here.
As you can see, e-Learning is changing the way we
present information to students. Many principles of instructional design remain
the same, but what has changed is we now must take a new look at the
instructor, learner, and environment. We can’t simple take a face-to-face
course and put it online for the
learner. We must not only ensure that we have the technical capability of
putting the course online, but we must also ensure that the learner has the
prerequisite knowledge and capability to comprehend the knowledge we are
presenting via the internet. This includes availability of hardware and software
necessary to distribute content. We must, as instructors, have capabilities of
presenting the material in ways that can best be learned by audiences.
We started this paper by taking a look back into
history and examined how e-Learning has changed the face of education. Perhaps
it might be interesting to now look forward and consider the effects of
continued advancements in e-Learning. How will effective e-Learning strategies
change the face of education in the future? If technology and network
infrastructure capabilities continue to advance, education may change more in
the next twenty years than it has in the past forty years. Teacher education
may include mandatory technology certifications. Many “bricks and mortar”
institutions at the primary, secondary, and college levels may become “online”
institutions. One-room schools may completely vanish. Parents who fear for the
safety of their children in violent prone primary, secondary, and inner city
schools may choose to educate their children with content available for a
reasonable fee on the Internet. The one thing we can all be sure of is that
e-Learning strategies will continue to change education.
References
Bambara,
C., Lambert, D., Andrews, S., & Harbour, C. (2006). A Classroom research
study concerning the application of a framework for
planning and sequencing e-
learning student interactions. International Journal on ELearning, 5(3), 339-352.
Burns,
T. (2005). E-learning: The future of quality training. Quality progress, 38(2), 50
56.
Clark,
R. C. & Mayer, R. E. (2003). e-Learning
and the science of instruction: Proven
guidelines
for consumers and designers of multimedia learning.
Pfeiffer.
Chapman,
B. (2003). Ask
Dealtry,
R. (2005). Configuring the structure and administration of learning
management. Journal
of Workplace Learning, 17(7/8), 467-477.
Driscoll,
M. (2002). Web-based training (2nd
ed.).
Flynn,
A., Concannon, F., & Bheachain, C. N. (2005). Undergraduate students’
perceptions of technology-supported learning: The
case of an accounting class.
International
Journal on ELearning, 4(4), 427-444.
Hanna,
M. (2004). Data mining in the e-learning domain. Campus – Wide Information
Systems, 21(1),
29-34.
Kickul,
G. & Kickul, J. (2006). Closing the gap: Impact of student proactivity and
learning
goal orientation on e-learning outcomes. International Journal on ELearning, 5(3),
361-372.
and collaborative e-learning. ProQuest Information and Learning Company. (UMI Microform 3192420).
Leung,
E. W. C. & Li, Q. (2006). Distance learning in Honk Kong. International Journal
of Distance
Education, 4(3), 1-5.
Luczaj,
J. E. (2003). A framework for e-learning technology. ProQuest Information and
Learning
Company. (UMI Microform 3093378).
Minaya,
G. A. (2005). Who moved my classroom: Enabling instructor performance for
the 2010s. ProQuest
Information and Learning Company. (UMI Microform
3168036).
Thompson,
T. L. (2003). Even a virtual synchronous classroom has walls: There’s more
to collective meaning making than the technology. National Library of
612-79376-1).
Tucker,
M. A. (2005). E-learning evolves. HRMagazine,
50(10), 74-78.
Schettler,
J. (2005). David & Goliath. Training,
40(5), 18-25.
Weinstein,
M. (2006). Even better than the real thing? Training,
43(6), 33-39.