Running Head: IMPROVING EFFECTIVENESS IN DISTANCE EDUCATION 1 Improving Effectiveness in Distance Education through Multi-media Tools William T. Butler, Ph.D.
Running Head: IMPROVING EFFECTIVENESS IN DISTANCE EDUCATION 1
Improving Effectiveness in Distance Education through Multi-media Tools
William T. Butler, Ph.D.
Running Head: IMPROVING EFFECTIVENESS IN DISTANCE EDUCATION 2
Abstract
There is a lack of research establishing delivery methods to learning styles for online courses.
Even more apparent is the reluctance of institutions to use existing technology to accommodate
the growing number of online students with different learning styles. Published scholarly articles
were reviewed and sometimes compared to determine the effectiveness of prior studies in
establishing basic effectiveness measures in distance education. Five research areas identified as
standard measures of effectiveness in distance education emerged. Three of the five areas based
on quantitative measurements are: 1) graded assignments that reflect regurgitation of reading
assignments, 2) measurements of written interactive participation in online discussions, and 3)
demonstrated levels of increasing knowledge through interactive discourse with instructors.
These three are the institutional norm for most online course sessions. With the emergence of
multimedia tools on the web, their introduction as standard training tools into distance education
need to be considered. These two additional areas are: 4) course presentation as a function of
learning styles, and 5) determining course structure using multimedia tools.
Keywords: distance education, multi-media, distance learning
Running Head: IMPROVING EFFECTIVENESS IN DISTANCE EDUCATION 3
Introduction
There is a lack of research establishing delivery methods to learning styles for online
courses. Even more apparent is the reluctance of institutions to use existing technology to
accommodate the growing number of online students with different learning styles. Published
scholarly articles were reviewed and sometimes compared to determine the effectiveness of prior
studies in establishing basic effectiveness measures in distance education. Five research areas
identified as standard measures of effectiveness in distance education emerged. Three of the five
areas based on quantitative measurements are: 1) graded assignments that reflect regurgitation of
reading assignments, 2) measurements of written interactive participation in online discussions,
and 3) demonstrated levels of increasing knowledge through interactive discourse with
instructors. These three are the institutional norm for most online course sessions. With the
emergence of multimedia tools on the web, their introduction as standard training tools into
distance education need to be considered. These two additional areas are: 4) course presentation
as a function of learning styles, and 5) determining course structure using multimedia tools.
The analysis of available research, identified a gap in the research of quantifying
effectiveness by institutions in Distance Education (DE). This research indicates that use of new
technology such as multi-media tools, has been generally overlooked by scholarly research
sources especially when applied to developing post-graduate effective learning methods. In the
past, research involved measuring effectiveness of DE delivered via the internet using text
delivery and limited instructor-student interchange. Modern multi-media tools change the
paradigm of delivered course methodology. This paper reviews the use of multi-media tools and
how these tools affect student learning styles.
Running Head: IMPROVING EFFECTIVENESS IN DISTANCE EDUCATION 4
Definition
This section provides definitions of three key subjects necessary to identify effective
delivery of online courses, distance education (DE), effectiveness measurements, and online
training environments.
Distance Learning
The Distance Education and Training Council (2009) has been identified as an accepted
standard for accrediting DE institutions with the Department of Education. Utilizing their definition
which was refined in 2009 included printed materials, videotapes, audio recordings, facsimiles,
telephone communications, and the internet through e-mail and Web-based delivery systems as
acceptable forms of DE training. In the Distance Education Accreditation Handbook, (DETC,
2009) which was the guideline for accrediting higher educational institutions, the subject of
measuring the effectiveness of the training was never broached. DETC is primarily concerned
with the administration and record keeping that accredited institutions use to maintain accurate
data on the enrollment, progress, and graduation of the students. The closest statement of
measuring the effectiveness of the learning experience is summarized in one statement. “The
institution documents that students complete their studies at rates that compare favorably to those
of courses/programs offered by similar DETC-accredited institutions.” DETC further explains
that “compare favorably” means each program’s graduation rate falls within 15 points of the
mean for courses/programs at similar DETC institutions. Apparently, it is left to the institution
to survey and discover the mean for each course offered. This indicates that there exists a need to
define a measure of effectiveness that can be calculated or derived by institutions offering
distance education. Although DETC is vague as to the DE methods of delivery, it is understood
that traditional DE methods were first introduced in the late 1920's. Videotaped subjects have
been used in distance education at the postgraduate level since the 1980’s (Stephen, 1982).
Running Head: IMPROVING EFFECTIVENESS IN DISTANCE EDUCATION 5
Audio recordings were first produced for distance education in the 1960’s for the training of
newscasters, sportscasters and music announcers. Facsimile machines were first invented in the
late 1870’s but in the 1990’s facsimiles connected to video conferencing equipment were
predicted to be the wave of the future for distance education (Barron & Orwig, 1997).
Telecommunications has progressed rapidly in the past decade. Virtual learning classrooms
(Weiss, Nolan, Hunsinger, & Trifonas, 2006), interactive online dialogue and online
conversational design (Luppicini, 2008), interactive video and even three dimensional erasable
holographic displays (Savage, 2008) have an effect on how students can learn through distance
education.
Effectiveness Measurements
Educational institutions should try to establish a means of measuring educational successes.
Innovative distance education delivery techniques are being introduced sporadically and with
little dissemination among competing institutions. Although some of the methods are
groundbreaking, there is a lack of documentation on the effectiveness of these methods. Trying
to quantify success rates among educational institutions is tantamount to counting heads. How
many graduates in each subject and how many drop outs in each subject, only serve to mask the
issue of effectiveness. The question should be relegated to whether the student learns the subject
matter presented in each course. The tools needed to measure learning effectiveness, have
historically been written exercises. The tool utilizes the same delivery technique that many
educational researches believe to be a deterrent to visual and auditory learners. There is prior
research and substantial empirical groundwork on learning methods that have not been applied to
distance education (Bangurah, 2004). Specifically, the area of interest selected in this paper is
identifying and measuring effectiveness of media based interactive distance learning utilizing the
Running Head: IMPROVING EFFECTIVENESS IN DISTANCE EDUCATION 6
most common delivery techniques in a stand-alone mode or in combinations. The potential
relevance of choosing this topic is valid due to an abundance of prior qualitative studies but a
dearth of quantitative studies. There are many problems encountered by students (Ransdell and
Gaillard-Kenney, 2009) when they are placed in a self-motivated training environment. There is
a perception that the introduction of the computer into this environment has decreased attrition
rates previously experienced by correspondence courses (Picciano, 2002). The question that is
left unanswered is what role IT has played in changing students perceptions of effective learning
through DE. Most advanced learners are very familiar with interactive tools, instant messaging
(IM), video on demand, audio and video streaming and newer tools incorporated in You Tube,
U-stream, and other interactive online sessions. With the introduction of multimedia tools, and
instantaneous connectivity, the student should be required to be more engaged in their own
learning process. Attrition due to long delay in grading assignments, or lack of contact with the
instructor (Beckstrand, 2003) is no longer the reason provided for dropping out. Instead, the
paradigm has shifted to keeping the content meaningful, current and in some cases entertaining.
This paper does not agree with prior research that correlated effectiveness measures as the
number of visits or posts the student places in a forum (Ransdell & Gaillard-Kenney, 2009).
However, it is believed there are quantitative measures that can be used other than regurgitating
reading gmaterial and replying with social network comments. Exposing students to new
interfaces such as interactive audio, web page animation, streaming, groupware sessions and
gaming can be an overwhelming experience for a DE student but rearding when engaged. With
very little preparation the effectiveness of these tools can prove useful for developing an
effectiveness gradient that can be used by educational institutions to advance their curriculums.
Therefore, the definition of effectiveness measurements will be centered on the student and will
Running Head: IMPROVING EFFECTIVENESS IN DISTANCE EDUCATION 7
be defined as the student's ability to successfully complete a course based on a style of learning
that keeps the student actively engaged through course completion.
Online Training Environment
Product developers such as Cisco and Microsoft recognized the need for interactive
education through online courses over ten years ago and developed certification programs
accessible through distance education. Duffy and Kirkley (2004) performed a case study that
highlighted the reluctance of educational institutions to implement new DE technology. Schrum, L.
& Ohler, J. (2005) reviewed a case study to determine the “perceptions, problems and opportunities presented by DE” using
surveys. This qualitative approach revealed an overwhelming desire by the student to understand how DE would
contribute to their educational goals before enrolling in an online course. The Cardean University case
study addressed by Duffy and Kirkley (2004) revealed an overall reluctance to move from the front of
the classroom to the front of a monitor by the instructors not the students. The antagonistic
environment between learners desiring DE training and institutional instructors resenting the new
technology forced a compromise in DE delivery. Thus, the current online environment utilized by most
institutions is a read and write environment. The instruction is broken into unit lessons with reading
assignments, augmented by instructor recommendations and the learner has to respond in writing to
each assignment. In the past ten years, many institutions started implementing course management
systems (CMS). These products help facilitate a more interactive DE environment but they are not
being used to their full potential. These pre-developed CMS software systems are promoted as one
size fits all institutions (Blackboard Inc., 2009). The responsibility of customizing the
presentation of the software to the students is developed by the institution’s IT staff. Therefore,
the online environment varies by institutional involvement in the course design but the important
issue is that the institution has full control of the delivery method and the content of each course.
The institution has the ability to improve the delivery of a subject as well as present the course in
different delivery modes but instiutions have reluctantly experimented with new technology. It is
believed that this situation persists because instructors are still resisting technology. Very few
Running Head: IMPROVING EFFECTIVENESS IN DISTANCE EDUCATION 8
industrial online courses are presided over by an instructor yet corporations and government
agencies are using these new technologies for everything from orientations to technical
certification including job learning simulators.
Review and Analysis
Measuring Effectiveness
According to Poulin (2002) distance learning can overcome the barriers of learning styles
that has been known for the past forty years when first addressed by Knowles (1984). "We now
know that people learn in different ways, and that because some students do not absorb
information well from a lecture style of instruction does not mean they are stupid…. But research
won't change things until its findings are put to use" (Hull, p. 7). The common complaint about
distance learning is that it does not accommodate the learning styles of a large contingent of
students. This complaint could have been made of the lecture method of teaching for decades,
but it still is the dominant form of training on higher education campuses. "Using video, audio,
active learning, simulations, and electronic advances can overcome problems encountered by
learners who do not adapt to just one learning style" (Poulin, 2002). With the academic world
lending credence to the work of Dunn and Dunn (1979), Kolb (1981), and Knowles (1984) it
seems logical that educators would add media to enhance educational delivery, even creative
techniques such as virtual classrooms on a level with Second Life virtual reality.
Quantifying Effectiveness
Quantitative research usually involves the collection and analysis of data. There have
been several surveys on distance education satisfaction but none specifically addressed the
delivery of the subject. Paechter (2010) addressed a survey performed on college students that
consisted of 2196 participants in Austria. Overwhelming response to questions on student
Running Head: IMPROVING EFFECTIVENESS IN DISTANCE EDUCATION 9
satisfaction dominated the answers. "Besides the instructor’s expertise and support, only a few
variables proved to be important for students’ perceptions of learning achievements and course
satisfaction. These variables describe three fields in which instructors need professional
expertise: the structure and coherence of the learning material and the course, the stimulation of
learning motivation, and the facilitation of collaborative learning." (Paechter, 2010) For the
majority of students to chose stimulation of learning motivation as a primary area of importance
demonstrates the need for institutions to re-assess online course delivery techniques. Paechter
(2010) concludes from the survey that students measure effectiveness by determining whether a
course can "contribute to learning achievements or satisfaction: students’ motivation,
opportunities for self-regulated and collaborative learning, and the clarity of the course structure"
are the primary measure of effectiveness.
An effective quantifying measurement tool from an institutional viewpoint would be a
satisfaction survey similar to the survey offered in the Paechter (2010) research. Each student
would participate in an online survey after each online course that would address delivery issues
in the course.
Mena (2007) addressed research that incorporated twenty five additional references the
majority addressing the issue of quality in distance education from a global perspective. This is
important in assessing the effectiveness of distance education because a global perspective would
benefit from a multi-media presentation of course material. Any measurement standards that are
developed should be able to stand up to the scrutiny of a global review in education and global
industry. Mena (2007) reflects that distance education should not be limited to a localized region
but must take into account the diversity of a global learning environment. The only variation in
effectiveness of a distance education model would be the translation from one language to
Running Head: IMPROVING EFFECTIVENESS IN DISTANCE EDUCATION 10
another of the content of the course being offered. The global perspective offered by this paper
directly relates to online DE courses that are accessible to any learner. Although she does not
address any quantitative measures for her opinions, her years of experience do lend some
qualitative significance to her statements. The article relates to the papers subject because it
opened a window of research previously not considered, the fact that my research should address
a global market to be citable.
Approach
Matching multi-media to leaning styles
Kolb (1981), Dunn and Dunn (1979), and Honey and Mumford (as cited in Santally and
Alain, 2006) have stated that learning styles are key to defining how an institution can best
service its online DE students. Kolb developed a subdivision of learning styles based on Gregorc
and Butler's (as cited in Santally and Alain, 2006) earlier research on defining learning styles
based on a scale. Kolb is considered the leading authority on defining learning styles in the field
of education. His insight can be translated into an effective approach for improving DE from a
learning viewpoint.
Kolb later defined a research model to match his learning style subdivision of Gregorc
and Butler. The model can be migrated into a DE effectiveness model, which can serve as a
guideline for institutions to use in setting up online DE courses.
Dunn and Dunn (1979) describes the various learning styles utilized by students in
various educational environments. The authors defined five categories that influence learning.
The five styles determine the adaptability of students into different teaching methods. How an
individual is taught is just as important as the tools used to teach. These learning environments
Running Head: IMPROVING EFFECTIVENESS IN DISTANCE EDUCATION 11
affect how well we receive information and retain it. It is important to define the type of multi-
media in the DE course as well as the content of the DE course. Two courses on the same
subject, at the same level can be taught two different ways. Would you teach a sightless person
the same way you would teach someone who can see? The sightless person has to visualize
through audio input what the instructor is trying to relate (audio intensive learning) where the
person with sight needs very little audio input but can see how equations are solved through
visual input (visually intensive learning). Which is more effective? Both are depending on the
learner. This is the learning styles addressed by Kolb (1984).
Santally and Alain (2006) developed an effectiveness model for cognitive learning. They
address previous learning styles and survey methods by Honey and Mumford in particular. Using
Honey and Mumford questionnaire style they surveyed students at the University of Mauritius on
preferences of learning styles divided by visual, auditory, and kinaesthetics. Student preferences
are a learned response over time. This is usually fully developed by adulthood. Most adult
learners which can be categorized as any individual over the age of eighteen, have no idea or
awareness of their learning style.
Evaluating Relevance, Reliability and Validity
In a study by Schrum and Ohler (2005), the authors presented an academic case for their conclusions
and immediately determined that they were going to use qualitative methods to unveil the
perceptions, problems and opportunities presented by distance education. The study subdivided three
groups into levels of experience with distance education and then presented each group with a battery
of questions based on a five point scale. One question presented to faculty inquired as to what role
they would like to play in developing distance education at the university. Half of the instructors not
currently involved in distance education declined to accept any role. This response is indicative of the
traditionalist classroom professor. The response itself provides insight into the difficulty of introducing
Running Head: IMPROVING EFFECTIVENESS IN DISTANCE EDUCATION 12
new technology into academic institutions. The study incorporated 2,300 students and the results
provided yielded 355 valid surveys. From the results of the surveys the highest response to students
feelings toward distance education centered on how well distance education would contribute toward
meeting their educational goals. This emphasizes the need for distance education effectiveness to be
measured in terms of meeting the educational goals of the end user not the desires of the instructor.
The primary purpose of distance education is to provide all learners a method of meeting their
educational goals. Since distance education is an IT function then all research should have started with
a user requirements statement. This is the essential element that was never defined when online
learning was offered. The Schrum and Ohler (2005) article identifies this initial system failure when
the institution involved aligned IT staff with instructors, instructors with the institution, and left the
students out of the equation. The issue should not be whether an instructor likes teaching online DE
course, but how the instructor is involved in online DE courses. This paper recommends a paradigm
shift as part of the method to improving the effectiveness of DE courses using multi-media. The paper
offers nothing revolutionary, but instead requires a different way of thinking about the delivery of
courses utilizing IT tools that are commonplace.
Justification for Research
Iriberri and Leroy (2009) developed a life-cycle perspective for online community success. The
number of higher education institutions offering distance education is increasing. According to the
Institution of Education Sciences’ National Center for Education Statistics in the academic year 2006–
2007, 66 percent of the 4,160 post-secondary degree granting institutions both 2-year and 4-year
schools offered college level courses through distance education. Overall 97 percent of public 2-year
institutions, and 89 percent of public 4-year institutions, 53 percent of private not-for-profit
institutions, and 70 percent of private for-profit 4-year institutions joined the ranks of those schools
offering remote training. Lagging behind the curve, only 18 percent of the 2 year private for-profit
institutions embraced distance education as a viable form of learning. According to the Department of
Education distance education is defined as a formal education process in which the students and the
instructor are not in the same place. The definition continues to state the type of media the school
may use, with emphasis on the word may. It does not specifically categorize or classify distance
Running Head: IMPROVING EFFECTIVENESS IN DISTANCE EDUCATION 13
education any further. The graduate level e-learning community has determined that a human
instructor needs to be a part of the distance education process in order for distance education to be
effective. Interactive computer learning tools simulating training through trial and error programs
have been used by the military for several decades and no interaction between student and instructor
is present. This statement is relevant because the military has been able to quantitatively demonstrate
inherent benefits derived from an e-learning environment. Iriberri and Leroy (2009) state that there
exists a general acknowledgement that the need for DE is growing. This being agreed upon, then why
would an institution be reluctant to improve the delivery of the DE courses offered. By improving the
course, more students would enroll and the institution would gain more revenue. It might even
emerge as a model institution for instruction. That is the reason this paper is relevant to educational
institutions as well as the individual student.
Ward and Riley (2008) researched and expostulated the idea that e-learning is the cost-
effective way to train in tough economic times. This is timely in the current economy which suffers
from rising fuel costs and diminishing individual incomes. Employee training is still viewed as an area
that has very positive returns to most companies. Therefore Ward and Riley (2008) is credible from an
industry perspective because it addresses the substitution of traditional training for distance education
in the work place. The ideas presented by Ward and Riley (2008) are speculative and not based on
any quantitative measures. The authors address qualitative features realized from their e-learning
experience but they do not explain how the quality of the training was determined other then to
mention employee satisfaction. Since this paper's area of interest is in the effectiveness of distance
education using multi-media, it includes the premise that anytime industry embraces an idea, that
idea will continue to grow until it is fully integrated into the fabric of daily operation.
Method
Learning Style Correlation to Kolb’s Learning Theory
Running Head: IMPROVING EFFECTIVENESS IN DISTANCE EDUCATION 14
Kolb (1984) defined learning styles as falling into one of four quadrants. In effect these
quadrants represent the comfort zones for adult learning. Basically, the quadrants respresent
students that learn most effectively through visual communication, auditory communication,
physical participation and cognitive retrospection. In order to perform a self assessment of the
learning style an individual possesses is through a self examination of Figure 1. Figure 1 displays
the Kolb’s idea of adult learning as influenced by adult learning processes (Chapman, 2005-06).
Within Kolb’s model there are four quadrants of styles, where the individual fits within the
quadrants determines the categorization as established by Kolb’s Theory. It is understood that
adult learners try to adapt to institutional teaching methods, but the level of effective learning is
reduced if the instruction is not correlated to the adult learning style. Learning is either an on or
off process. If an adult turns off the learning process, innovative approaches, novel
presentations, even reward-base processes cannot make the adult learn. There has to be a
willingness to absorb information with the personal goal of retaining that information for
personal improvement. When the ability to absorb the information is not offered then the learner
turns off the learning process and the training is ineffective.
Running Head: IMPROVING EFFECTIVENESS IN DISTANCE EDUCATION 15
Figure 1. Kolb's learning style.
Approach
Matching Learning Styles to IT DE multi-media delivery methods
Kolb's learning styles are most adaptable to an online learning environment. Students
would be classified as either divergers, convergers, assimilators, or accommodators. Courses
could be delivered around these four learning styles. Individual students approach learning from
different backgrounds. Kolb understood that background and environment affect the way
students absorbed knowledge and the different rates of absorption and retention. Understanding
this, he developed the learning styles that encompassed the majority of the population. The range
of absorption relies on multi-sensory inputs to simple logic input. Kolb's delineation lends itself
to a classification system that can be adapted to distance education courses. A normal traditional
Running Head: IMPROVING EFFECTIVENESS IN DISTANCE EDUCATION 16
classroom learning environment cannot begin to offer the many advantages that DE using multi-
media sensory input can offer to accommodate all four learning styles.
Analyzing the four categories it becomes evident that Kolb's analysis is simple and
complex. An individual with a learning style adaptable to the standard classroom would be
classified by Kolb as assimilating. A student that learns through hands on replication would be
classified as accommodating. This learning style would discover an interactive holographic
learning experience as the most effective learning process. An individual that absorbs through
visual would be categorized as reflective but how they learn could be divided between feeling an
experience, which could be accommodated by online role playing. The visual learner that
absorbs through reflection is well suited to the standard read and respond online training that is
current prevalent method.
There are various combinations of learning styles but all the styles can be accommodated
through online delivery. The solution is provide training with the end user being the beneficiary
of the CMS system not the institution offering the training. Luppicini (2008) defined the role of
conversation in instruction, especially in the design and development of technologically advanced
educational environments. Conversation poses serious challenges for online course designers and
instructors. Luppicini's approach added another online tool to defining and developing effective
techniques for distance education courses. Luppicini(2008) borders on reaching the same conclusion
addressed in this paper. Online DE courses needs more then written input to be effective for learning.
Courses can be conversational or experiential to influence a learner's memory. Conversational learning
can occur in multiple ways. Vocal delivery and response is the most common and would accommodate
another learning style that of the accommodator that has have an emotional response to learning and
need that classroom emotional feedback and assurance in order to feel accomplished. Individual
retention can occur in two ways, experiential (swimming for example), and absorption (reading).
Some combination of experiential and conversational is needed to make an online learning experience
effective.
Running Head: IMPROVING EFFECTIVENESS IN DISTANCE EDUCATION 17
Conclusion
Widening the scope of research into student learning styles in an IT multi-media rich DE
environment is a relatively new area. As the demand for DE courses increases, so does the
expectations of the learner. In the majority of articles researched for this paper, the overriding
view by institutions is one of letting the learner adjust to the multi-media online style of the
institution. If the learner wants to learn, then the learner will adjust to the institution style. This is
outdated thinking. It is the wrong attitude in a competitive environment, where the learner has a
growing list of institutions from which to choose. It would be helpful for every learner to
understood what type of learning environment produces the best results for their learning style.
In the past, institutions of higher learning defined effectiveness in terms of attrition. Students that
drop out just did not have enough motivation to succeed. From multiple research studies, we now
know that this idea is false. Students, once they reach adulthood cannot change their learning
style regardless of their motivation. In most cases, students do not know what type of learning
style they possess, however institutions know that different learning styles exist because of thirty
years of proven academic research. This paper presents the issues involved in learning accepted
by higher education institutions from forty years of accepted research. The author has also
offered the solution of treating the student as the user of the system not the institution. A new
paradigm requires new applications. These applications already exist but now they need to be
implemented.
References
Bangurah, F. M. (2004). A study of completion and passing rates between traditional and web-based instruction at a two-year public community college in northeast Tennessee. East Tennessee State University. Retrieved January 27, 2010, from http://proquest.umi.com/pqdweb?did=765274731&Fmt=7&clientId=62763&RQT=309&VName=PQD
Running Head: IMPROVING EFFECTIVENESS IN DISTANCE EDUCATION 18
Barron, A.E. & Orwig, G.W. (1997). New technologies for education: A beginner’s guide.
Englewood, CO: Libraries Unlimited. (3rd ed.).
Beckstrand, S. (2003). Reduction of attrition and fail grades in an online module using student screening and supplemental instruction lectures. In D.Lassner & C. McNaught (Eds.), Proceedings of World Conference on Educational Multimedia, Hypermedia and Telecommunications (pp. 361-362). Chesapeake, VA.
Blackboard Inc. (2009). Engaging learners, for engaging learning. Retrieved July 31, 2009, from http://www.blackboard.com/Teaching-Learning/Learn-Platform.aspx
Chapman, A. (2005-06) Kolb Learning Style. Retrieved from http://www.businessballs.com /kolblearningstyles.htm
Distance Education and Training Council (2009). DETC Accreditation Handbook – 2009: Accreditation standards, 41 Washington, DC: Author.
Duffy, T.M. & Kirkley, J.R. (2004). Learner-centered theory and practice in distance education: Cases from higher education. Mahwah, NJ: Lawrence Erlbaum Associates Retrieved January 27, 2010, from http://www.questia.com/PM.qst?a=o&d=104720804
Dunn, R. S. & Dunn, K. J. (1979, January). Learning styles/teaching styles: Should they… Can they… Be matched? Educational Leadership 36(4) 234-244, (ERIC Document Reproduction Service No. EJ194046)
Hull, D. (1995). Who Are You Calling Stupid? Waco, TX: Cord.
Iriberri, A. & Leroy, G. (2009, February). A life-cycle perspective on online community success. ACM Computing Surveys, 41 (2), 1-29.
Knowles, M. S. (1984). The adult learner. A neglected species.(3rd ed.). Houston:Gulf.
Kolb, D.A. (1981). Learning styles and disciplinary differences. Retrieved June 26, 2009, from http://www.learningfromexperience.com/images/uploads/Learning-styles-and-disciplinary-difference.pdf
Kolb, D. (1984). Learning styles model and experiential learning theory. Retrieved January 27, 2010, from http://www.businessballs.com/kolblearningstyles.htm
Luppicini, R. (2008). Handbook of conversational design for instructional applications. Idea Group Inc. 2008. Retrieved May 28, 2009, from http://www.igi-global.com/reference/details.asp?id=7280
Mena, M. (2007 April-June). E-Learning quality: A look towards the demands of its good practices. Journal of Cases on Information Technology, 9(2), 1-11. Retrieved May 18, 2009 from http://proquest.umi.com.library.capella.edu
Running Head: IMPROVING EFFECTIVENESS IN DISTANCE EDUCATION 19
Paechter, M., Maier, B., & Macher, D. (2010). Students' expectations of, and experiences in E-
learning: Their relation to learning achievements and course satisfaction. Computers & Education, 54(1), 222-229. Retrieved from http://ezproxy.library.capella.edu/login?url= http://search.ebscohost.com.library.capella.edu/login.aspx?direct=true&db=eric&AN=EJ860890&site=ehost-live&scope=site; http://dx.doi.org.library.capella.edu/ 10.1016/j.compedu.2009.08.005
Picciano, A.G. (2002). Beyond student perceptions: Issues of interaction, presence, and performance in an online course. Journal for Asynchronous Learning Networks. 6(1). Retrieved May 28, 2009, from http://scholar.google.com/scholar
Ransdell, S. & Gaillard-Kenney, S. (2009, January). Blended learning environments, active participation, and student success. The Internet Journal of Allied Health Sciences and Practice. 7(1). Retrieved May 28, 2009, from http://ijahsp.nova.edu /articles/Vol7Num1/pdf/Ransdell.pdf
Poullin, R. (2002). Distance Education in Higher Education. 2nd ed. Ed. James W. Guthrie Vol 2. p 589-593. New York: MacMillan
Santally, M. I., & Alain, S. (2006). Personalisation in web-based learning environments. International Journal of Distance Education Technologies 4(4). Retrieved June 30, 2009, from http://www.eurodl.org/?keyword=e-learning&article=166
Savage, N. (2008, February). The erasable holographic display. IEEE (2008 February). Retrieved May 28, 2009, from http://www.spectrum.ieee.org/feb08/5995
Schrum, L. & Ohler, J. (2005). Distance education at UAS: A case study. Journal of Distance Education, 20(1), 60-83. Retrieved June 2, 2009, from ProQuest Education Journals database. (DOI: 886738981)
Ward, J.L. & Riley, M. (2008, August). E-Learning: The cost-effective way to train in tough economic times. New York: [Electronic version]. Employee Benefit Plan Review, 63(2), 12-14. New York. Retrieved June 25, 2009, from http://www.esiintl.com.sg/site _press.asp?news_id=news20080000028SG
Weiss, J., Nolan, J., Hunsinger, J. & Trifonas, P. (Eds.). (2006). The international handbook of virtual learning environments. Springer Handbooks of Education (vols. 2). Abstract retrieved May 27, 2009, from http://www.springer.com