Download doc - Learning Styles in the Future of Online Learning

Learning Styles in the future of online learningWill online learning be shaped by the learner or will it determine learners' learning styles?

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01 INTRODUCTION

When books and blackboards were first introduced into teaching, teachers discovered

that learners develop seemingly innate learning patterns to adapt to these classroom

technologies. Literature refers to these patterns as learning styles. As education evolved, the

roles reversed from teaching materials governing learning styles, to the need of

accommodating learning styles when designing teaching materials.

However, recent widespread applications of computer technology and the Internet

into education appear to have prompted educators back to the drawing board. Burgess (2003)

stated that “faculty and students have to adjust to the pedagogy that uses instructional

technology as an integral component in teaching” which supports the notion that once again

educators are not driving the advancements but are in fact pursuing technology

advancements. Thus, with Internet online learning still in its infancy, it is resourceful to

predict how technology will shape online learning to better equip instructors on designing

courses suitable for learners because “learning can be enhanced when the instructional

process accommodates the various learning styles of students” (Buch and Bartley, 2002, p.5).

The scope of this paper is to analytically predict how flexible online learning will

become with regards to learning styles. Will the learning styles of learners evolve

dramatically because of technology or will technology evolve to accommodate learning

styles? Will certain learning styles be forced upon learners? Attempts in answering these

questions will be supported by analysing the development of online learning at present and

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their effects towards learning styles. It is necessary to note that ‘technology’ and ‘tools’ refer

to the tangible inventions of IT developers while ‘technology trends’ refer to the concepts and

approaches being employed in online learning.

02 LEARNING STYLES

Federico (2000, p.367) stated that “understanding {learning} styles can improve the

planning, producing, and implementing of educational experiences, so they are more

appropriately compatible with students' desires, in order to enhance their learning, retention,

and retrieval”. Such is the importance of learning styles in education that over 80 models

have been extensively researched in literature. For the scope of this paper, two learning style

models will be used, (1) the VAK model and (2) the Myers-Briggs Type Indicator (MBTI).

The VAK model incorporates cognitive learning styles based on stimulus and these

are Visual, Auditory and Kinaesthetic for visual, audio and action stimuli respectively

(Scheurs and Moreau, 2006, p.2-3). Currently, online learning provides ample stimuli for

these areas and interestingly, the big movements in technology today are focusing on stimuli

enhancements. It is therefore natural to refer to the VAK model to analyse the available web-

based technologies and how future developments of them relate to learning styles.

The MBTI model is described by Dewar and Whittington (2000, p.415) as “an

inventory used to determine personality dispositions and preferences based on Carl Jung’s

theory of psychological types”. Carl Jung (cited in Dewar and Whittington, 2000, p.415)

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“postulated that individuals have behavioural patterns which in turn reflect the person’s

preferences for taking in information and making decisions”. The MBTI model is more

detailed (Dewar and Whittington, 2000) than the VAK model and it is therefore used as in-

depth reference for analysing online courses where learners are exposed to multiple

technology and environments.

The model has four psychological dimensions with each having two polar

preferences. However, only the Extravert-Introvert dimension will be referred to because the

scope of this paper is not to list and determine learners’ learning strategies but rather to

determine if learner strategies are accommodated by online learning technology.

Furthermore, the Extravert-Introvert polarity is prevalent in classrooms. If one dimension

sufficiently reveals any disagreement between learner styles and technology trends, it

therefore supports the notion of online learning not being accommodating to certain learning

styles.

To clarify, extravert learners focus on the outer world by interacting with people and

seeking feedback whereas introvert learners focus on the inner world of ideas, feelings and

thoughts. Extraverts have the tendency to act first and reflect later while introverts think first

on what to act and with whom to interact (Dewar and Whittington, 2000, p.416). This

Extravert-Introvert dimension will be referred throughout in both technology trends and

online learning courses because it utilises polar preferences where one learning style is the

opposite of the other (see Appendix 1). Hopefully, this polar structure can elucidate whether

the future of online learning will accommodate both learner types of the same dimension or

favours one from the other. The present technologies involved in online learning will be

juxtaposed against the aforementioned learning styles.

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03 ONLINE LEARNING AT PRESENT

When educators started online learning, there was already a repertoire of technologies

available and educators were not faced with designing courseware but rather, negotiating

learner needs with the technology to produce courseware. From that point onwards, trends

developed through experimentations and, more recently, collaborations with IT companies in

producing online educational tools.

03.1 Technology Components in Online Learning

03.1.1 Software Tools and Platforms

A few prominent web-based education environments such as WebCT and Blackboard

have begun to mark their presence and arguable dominance. Along the periphery of web-

based educational tools are online artefacts increasingly integrated in education such as

Web2.0 Tools, CMC tools, Breeze and SecondLife. Interestingly, both technology

representations are strongly veering towards the socio-communicative direction.

Already these technologies being used in teaching have shown support for the

extravert learner who “chooses to work with others, communicates well and greets people

easily” while perhaps blocking out the introvert learner who “chooses to work alone, and

likes quiet space to work” (Dewar and Whittington, 2000, pp.418-419). The socio-

communicative direction may be attributed to the need of replicating classrooms and its

outcome is advocated by supporters of the socio-constructivist approach.

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The classroom is a wonderful technology on its own because it adapts to both

preferences of the same dimension. Extraverts and introverts can coexist. In contrast, the

technologies mentioned work mainly in collaborative instances. Breeze, for example, requires

learners to interact via video and audio, and for introverts this process may be disconcerting

because introverts are “quiet and shy” and “perform better in written work than oral

presentations” (Dewar and Whittington, 2000, pp.418-419). It can be argued that introverts

can be ‘lurkers’ but, unlike the classroom where the teacher can monitor an introvert even

without that learner participating, ‘lurking’ introverts in online environments are difficult to

monitor or facilitate without focusing direct attention only to that learner.

With regards to the VAK model, the technologies aforementioned do comply albeit in

differing ranges - from the text-based WebCT that might not support stimuli based learning,

to the 3D-virtual reality SecondLife that accommodates visual and auditory stimuli that

mimic reality in addition to ‘pseudo-kinaesthetic’ stimuli. There are technologies for both

ends of the VAK spectrum but with improvements in bandwidth, sound and video quality,

technologies are veering towards VAK stimulation.

03.1.2 Technology Trends in Teaching

Online learning has developed several trends based on the technologies available and

their affordances for learning. Two noteworthy concepts include the ‘Virtual Learning

Environment’ (VLE) and ‘Synchronous/Asynchronous Computer Mediated Communication’.

WebCT is a widely utilised VLE and, with the Blackboard take-over, it has lived up

to its claim as the top commercial VLE. However, such monopolization of the mainstream

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online learning domain implicates that the learning styles accommodated by WebCT are

forced upon learners. WebCT is extensively text-based and VAK learners are not easily

stimulated by text-based discussions.

Synchronous and asynchronous CMCs are, at present, the only two ways of

interaction in online learning. Online chat tools such as Skype, forum-boards and Breeze

allow communication in varying nuances. Forum-boards are asynchronous whereby

communication is not in immediate successions, while messengers such as Skype are

synchronous because communication occurs in real-time. Extraverts work well with

synchronous communication because they have “a short attention span, eagerly attend to

interruptions and readily offer opinions and share experiences” (Dewar and Whittington,

2000, pp.418-419).

Introverts, on the other hand, work better with asynchronous communication because

they prioritise reflection by “spending time in thought, before and after action” and have the

tendency to “pause before answering, and shows discomfort with spontaneous questioning”

(Dewar and Whittington, 2000, pp.418-419). With regards to video and audio CMCs,

introverts would again shy away from them but these tools would befit visual and auditory

learners.

03.1.3 Hardware

Hardware is actually quite involved in the issue of learning styles. A decade ago the

second Windows operating system was introduced, and until now it has engraved its interface

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in many technologies from cell-phones to videogames to interactive television. Concurrently,

the first home Internet modems were released. Both technologies have opened the realm of

personal online learning. Learning styles have evolved alongside hardware developments

from the moment when limited bandwidth and processing speed interface favoured the

solitary introvert, to the present where web-cameras and podcasts favour the extravert and

PDAs and interactive gadgetries indulge the kinaesthetic learner.

03.2 Findings

From the observations elaborated above, one can deduce that technology still governs

decisions and designs of online learning and indirectly learning styles. Technology is moving

towards the same direction that was predicted of them a decade ago (Downes, 1998) and

these are interpreted as follows:

Technology evolving into stimulating interfaces (visual, audio, kinaesthetic).

Communalistic objective. The desire to connect people.

Replicating reality if not recreating reality.

Educators tend to decide on which technologies to incorporate and blend in their online

learning courses based on course objectives and learner needs. Nonetheless, educators do not

currently decide how technology will evolve, and as technologies tend to evolve, the online

learning that is dependent on them evolves as well.

Learners are also shaped by technology irrespective of them participating in any

online learning. Everyday items such as cell-phones and interactive gadgets are recreating

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reality and embedding themselves into everyday life. Unbeknownst to learners, they bring

their preferences on being comfortable with or despising interface such as interactive buttons

into their online learning. Since technology is ingraining itself in society, preferences of

everyday life affect a learner’s performance in online learning. The future is pro-technology.

04 THE FUTURE OF ONLINE LEARNING

A survey carried out by Kim and Bonk (2006, p.26) revealed that a majority of people

believed online learning will improve in quality in the future with predictions of it being

more superior than traditional learning by 2013, and online learners getting better education

than those in traditional learning by 2013. Online learning is indeed maturing and

technologies within it would eventually become part of everyone’s habitual reality. Below are

two predictions of future technologies in online learning:

Course management systems (CMSs) would increase most drastically in the next five years

(Kim and Bonk, 2006, p.25)

Since CMSs like WebCT tend to be an elaborate amalgamation of tools with

capabilities for each tool to evolve individually, it is difficult to predict how learner styles

will be accommodated. Nevertheless, the importance of accommodating flexible means of

learning is highlighted by Carmen and Haefner (2002, cited in Kim and Bonk, 2006, p.27)

when they stated that CMSs should “foster student choice among various activities,

reflection, apprenticeship, synthesis, real-world problem solving, and rich, timely feedback”.

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Fortunately, recent CMSs are taking heed of this importance and Dewar and

Whittington (2000, p.415) revealed that “introverts and extraverts participate somewhat

equally in [online learning environments], although they do experience it differently” but

they attributed this to providing “the option of using the tools as opposed to mandating its

use”.

It is hoped that future CMSs would allow flexibility in order to accommodate both the

extravert and the introvert or any learner styles preferred by learners.

Preference to Certain Pedagogical Techniques (Kim and Bonk, 2006, p.27)

(1) Online collaboration, (2) case-based learning and (3) problem-based learning are

predicted to be the prevalent online instructional methods in the next decade. The introverts

might shy away from the collaboration of pedagogy (1) and from the trial-and-error tasks of

(2) and (3).

It seems that already a pattern is developing against the introverts. At this juncture, it

is best to mention that “extraverts are more likely to use the Internet” (Dewar and

Whittington, 2000, p.47) and, with technologies and techniques further hindering introverts to

practise their learning style, the introverts are being neglected.

Looking at two future scenarios is enough to suggest that the introvert learning style is

being weeded out and highly unfavoured. Although the Internet is an alcove for introverts

who shy away from community, when online learning brings communalistic objectives into

play, the introverts are left hoping for courses that might offer one-to-one consultation-type

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learning. The extraverts, on the other hand, rejoice at their learning traits being attended to

and possibly several of the learners are converted introverts.

The paper has attempted to expose how online learning does govern learning styles

and at times force learners to evolve their styles, as is the case of the introverts. Unless the

educators have full control of the evolving technology and trends, learning styles will most

likely evolve because of technology. Perhaps in the future, the extraverts will be subjected to

the same predicament. Therefore, it is appropriate to end with a few suggestions on how to

keep online learning for everyone and to err on the side of caution when prioritising

technology in online learning for its dominance or novelty instead of practicality.

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05 SUGGESTIONS AND CONCLUSION

As highlighted earlier, online learning should be flexible to accommodate all learning

styles. This is determined by the course instructor and the chosen technologies. With the

rapid improvements in technology it is hoped that the future will witness online learning that

recognises learner styles and adjust to their preferences. The author believes advancements in

Artificial Intelligence or its similar might be the answer to this quagmire, whereby

technology observes a learner’s learning patterns and regulate the tools needed. A form of

A.I. is being utilised within the Internet where websites observe a user’s preferences for

products, favourite websites and activities and regulate these information to provide the user

with preferred content. Hopefully, online learning will adopt a similar intelligent interface.

Technology should also be given support, via learners agreeing to adapt to technology

and not vice versa. After all, technology is not only intruding into education, but also into

everyday reality. Since patterns of living have changed with technology, learning styles might

as well be revised and readjusted to technology. The author personally believes that in the

distant future, the recessive learning styles of today will be phased out and the dominant

styles of now in addition to potentially new learning styles will converge to become future

‘learning style models’. Such process is reminiscent of the development of learning styles

when the classroom was first used as a technology with its blackboard, notice-boards, reading

corner, projectors and teacher’s desk as its tools.

(2,434 words)

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REFERENCES

Buch, K., Bartley, S. (2002). Learning style and training delivery mode preference. Journal

of Workplace Learning. 14 (1), pp.5-10.

Burgess, L. A. (2003). WebCT as an E-learning tool: A study of technology students’

perception. Journal of Technology Education. 15 (1).

Carmean, C. and Haefner, J. (2002). Mind over Matter: Transforming Course Management

Systems into Effective Learning Environments. EDUCAUSE Review. 37 (6), pp. 27–34.

Dewar, T. and Whittington, D. (2000). Online learners and their learning strategies. Journal

of Educational Computing Research. 23 (4), pp.425-433.

Downes, S. (1998). The future of online learning. Online Journal of Distance Learning

Administration. 1 (3).

Federico, P. (2000). Learning styles and student attitudes toward various aspects of network-

based instruction. Computers in Human Behavior. 16. pp.359-379.

Kim, K. and Bonk, C. J. (2006). The future of online learning and teaching in higher

education: The survey says... . Educause Quarterly. (4). pp.22-30.

Schreurs, J. and Moreau, R. (2006) Learning objects aligning different learning styles. In

Remenyi, D. (ed.) Proceedings of the International Conference on e-learning (ICEL2006).

pp. 415-422.

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