personalised learning environments (part 2): a conceptual model for construction

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Personalised learning environments (part 2): a conceptual model for construction S.M. Syed-Khuzzan and J.S. Goulding Abstract Purpose – The purpose of this paper is to present a conceptual model for a PLE prototype, specifically incorporating learning styles for the UK construction industry. Design/methodology/approach – The initial research methodology approach adopted for this paper embraced the distillation of core research material gathered from a detailed literature review. The literature review encompassed the needs and importance of developing a PLE prototype, and used as a context learning styles for the UK construction industry. A qualitative approach was used in this research, as this was considered more suitable for studying social and cultural phenomena. This paper explores the relationship between pedagogy and technology in the context of the design and implementation of a PLE. The implementation framework for the PLE adopted the principles of the ‘‘Collaborative System Design’’ approach as identified by the Advanced Distributed Learning (ADL) Initiative Guidelines. Findings – This paper describes the development phases of the PLE prototype incorporating learning styles. This prototype incorporates a learning style inventory – known as the diagnostic questionnaire which was developed based on the amalgamation of three existing models of learning styles defined from a detailed synthesis of the literature – namely the Kolb’s model of learning styles, Honey and Mumford’s model of learning styles and the Felder and Solomon’s model of learning styles. Originality/value – This paper is a very useful source in developing a learning style inventory and a PLE prototype incorporating learning styles. Keywords Learning, Learning styles, Questionnaires Paper type Conceptual paper 1. Introduction This paper introduces a conceptual model for a PLE prototype incorporating learning styles for the UK construction industry. The aim of the research was to develop a PLE prototype that was able to accommodate individual learning styles for learners; tailored to suit to their own preference of learning styles. Learners often have different levels of motivation, different attitudes about teaching and learning, and different responses to specific classroom environments and instructional practices. In this context, the more thoroughly instructors understand these differences, the better chance they have of meeting the diverse needs of their learners (Felder and Brent, 2005). Furthermore, Karagiannidis and Sampson (2004) noted that there was a general shortage of evidence to back up the belief that e-learning provided real advantages – the assumption of which was that the ‘‘traditional’’ mode of instruction (one-to-many lecturing/one-to-one tutoring) could not fully accommodate the different learning styles, strategies and preferences of diverse learners. Following this train of thought, research is now being undertaken on adaptive learning environments that can personalize the learning experience (Vercoustre and McLean, 2005; Karagiannidis and Sampson, 2004). DOI 10.1108/00197850910927769 VOL. 41 NO. 1 2009, pp. 47-56, Q Emerald Group Publishing Limited, ISSN 0019-7858 j INDUSTRIAL AND COMMERCIAL TRAINING j PAGE 47 S.M. Syed-Khuzzan and J.S. Goulding are both based at the University of Salford, Salford, UK.

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Page 1: Personalised learning environments (part 2): a conceptual model for construction

Personalised learning environments (part 2):a conceptual model for construction

S.M. Syed-Khuzzan and J.S. Goulding

Abstract

Purpose – The purpose of this paper is to present a conceptual model for a PLE prototype, specifically

incorporating learning styles for the UK construction industry.

Design/methodology/approach – The initial research methodology approach adopted for this paper

embraced the distillation of core research material gathered from a detailed literature review. The

literature review encompassed the needs and importance of developing a PLE prototype, and used as a

context learning styles for the UK construction industry. A qualitative approach was used in this

research, as this was considered more suitable for studying social and cultural phenomena. This paper

explores the relationship between pedagogy and technology in the context of the design and

implementation of a PLE. The implementation framework for the PLE adopted the principles of the

‘‘Collaborative System Design’’ approach as identified by the Advanced Distributed Learning (ADL)

Initiative Guidelines.

Findings – This paper describes the development phases of the PLE prototype incorporating learning

styles. This prototype incorporates a learning style inventory – known as the diagnostic questionnaire

which was developed based on the amalgamation of three existing models of learning styles defined

from a detailed synthesis of the literature – namely the Kolb’s model of learning styles, Honey and

Mumford’s model of learning styles and the Felder and Solomon’s model of learning styles.

Originality/value – This paper is a very useful source in developing a learning style inventory and a PLE

prototype incorporating learning styles.

Keywords Learning, Learning styles, Questionnaires

Paper type Conceptual paper

1. Introduction

This paper introduces a conceptual model for a PLE prototype incorporating learning styles

for the UK construction industry. The aim of the research was to develop a PLE prototype that

was able to accommodate individual learning styles for learners; tailored to suit to their own

preference of learning styles.

Learners often have different levels of motivation, different attitudes about teaching and

learning, and different responses to specific classroom environments and instructional

practices. In this context, the more thoroughly instructors understand these differences,

the better chance they have of meeting the diverse needs of their learners (Felder and

Brent, 2005). Furthermore, Karagiannidis and Sampson (2004) noted that there was a

general shortage of evidence to back up the belief that e-learning provided real

advantages – the assumption of which was that the ‘‘traditional’’ mode of instruction

(one-to-many lecturing/one-to-one tutoring) could not fully accommodate the different

learning styles, strategies and preferences of diverse learners. Following this train of

thought, research is now being undertaken on adaptive learning environments that can

personalize the learning experience (Vercoustre and McLean, 2005; Karagiannidis and

Sampson, 2004).

DOI 10.1108/00197850910927769 VOL. 41 NO. 1 2009, pp. 47-56, Q Emerald Group Publishing Limited, ISSN 0019-7858 j INDUSTRIAL AND COMMERCIAL TRAINING j PAGE 47

S.M. Syed-Khuzzan and

J.S. Goulding are both

based at the University of

Salford, Salford, UK.

Page 2: Personalised learning environments (part 2): a conceptual model for construction

According to Felder and Silverman (1988) and McCarthy (1990), accommodating learning

styles in a classroom-based environment has been proven to be effective in previous

research; causing the need to explore the possibilities of incorporating learning styles in

e-learning environments.

2. Research methodology

The initial research methodology approach adopted for this paper embraced the distillation

of core research material gathered from a detailed literature review. The literature review

encompassed the needs and importance of developing a PLE prototype, and used as a

context learning styles for the UK construction industry. A qualitative approach was used in

this research, as this was considered more suitable for studying social and cultural

phenomena (Berger and Luckman, 1966). This paper explores the relationship between

pedagogy and technology in the context of the design and implementation of a PLE. The

implementation framework for the PLE adopted the principles of the ‘‘collaborative system

design’’ approach as identified by the Advanced Distributed Learning (ADL) initiative

guidelines (ADL, 2006).

3. Background research

Primarily, the aim of any e-learning program is to help learners achieve the prescribed

learning objectives (Larocque and Faucon, 1997). In this context, in a traditional classroom

environment, the instructor is present to guide the learners towards the objectives through a

variety of teaching strategies and learning activities; which is the opposite of e-learning. Due

to the independent learning involved in e-learning, learners need to be more self-motivated

and self directed in order to achieve the objectives of the course program; thus, the

responsibility for learning is transferred from the instructor to the learner (Martinez, 2002).

There is no single right way to teach; many instructors naturally confine their teaching to the

method that reflects their own learning style to the exclusion of others (Entwistle, 1981).

Smith and Kolb (1986) argued that students may reject a learning environment that does not

match their learning styles. It has been pointed out in the literature that designing a learning

environment that accommodates learners’ learning style is essential for effective learning.

Hence, since e-learning has influenced a great deal in the field of teaching, training and

development, thus causing a growing number of courses delivered over the web with

increasing numbers of students (Chang, 2001); initiatives to adapt learning styles in

e-Learning are considered essential.

3.1 Importance of incorporating learning style into a PLE

There is no single way to describe learning styles, as a number of definitions appear in the

literature (Sampson and Karagiannidis, 2002). For example, Conner (2005) defines learning

styles as ‘‘. . . the ways you prefer to approach new information’’. Kolb (1976) saw learning

styles as ‘‘the unique learning method presented by the learner during the learning process

and situation’’ while Dunn (1990) described learning styles as ‘‘. . . the way each learner

begins to concentrate, process and retain new and difficult information’’. In addition, Honey

andMumford (1992) define learning styles as ‘‘. . . a description of the attitudes and behavior

which determine an individual’s preferred way of learning’’. Moreover, Felder (1996)

describes learning styles as ‘‘a person’s characteristic strengths and preferences in the

ways they take in and process information’’.

Learning seems to be seen as an integral part of everyday life at work. The skill of knowing

how to learn is considered a must for every worker. It opens doors to all other learning and

facilitates the acquisition of other skills (Blackmoore, 1996). Student learning is a complex

multivariate phenomenon. Some individuals are heavily dominated by one learning style, or

are just particularly weak in one style; so, some learning activities are dominated by explicit

or implicit assumptions about learning styles (Honey and Mumford, 1992). The activity may

be geared to a particular style of learning as to cause a mismatch with any other learners

whose own major styles are different. Furthermore, there are learners whose learning styles

are wide spread, so there are learning activities which contain opportunities to learn in

different ways (Sims, 1990). According to Kim and Chris (2001) and Kolb (1984),

PAGE 48 j INDUSTRIAL AND COMMERCIAL TRAININGj VOL. 41 NO. 1 2009

Page 3: Personalised learning environments (part 2): a conceptual model for construction

educational research and practices have demonstrated that learning can be enhanced

when the instructional process accommodates the various learning styles of students.

Learners generally come from different backgrounds and have a great variety of differing

profiles, learning styles, preferences and ‘‘knowledge hooks’’. Learning should be as

personalized as possible (Vincent and Ross, 2001) as a ‘‘one size fits all’’ approach has

been seen to be ineffective (Watson and Hardaker, 2005). However the, incorporation of

learning styles is said to bring an advantage during the development and implementation of

learning environments (Sims, 1990). Thus, the need for both teachers and trainers to take

learning styles into account appears to be greater today than before, due to the increasing

use of technology-aided instruction.

Technology offers a lot of new ‘‘delivery mode’’ options as compared to the traditional

‘‘face-to-face’’ classroom format, including a variety of computer and television-based

delivery mode formats (Buch and Bartley, 2002). The development process based on

individual learning styles and preferences through adaptive technologies has been a

successful approach towards training that enables real-time performance evaluation

through behavioral and attitude measures (Watson and Hardaker, 2005). Furthermore,

O’Conner (1998) noted that technology offers new capabilities to reconstruct learning

environments around specific learning styles. In this context, individuals with specific

learning styles would have a preference for specific training delivery formats (Buch and

Bartley, 2002). Since e-learning has predominantly had a ‘‘one size-fits all’’ approach, the

idea of incorporating learning styles into the learning environment should enable learners to

learn more effectively and also be motivated to learn by building a ‘‘road-map’’ based on

their individual psychological types and learning preferences (Gunasekaren et al., 2002;

Sims, 1990).

Teachers or instructors should therefore:

B know the material well before beginning to teach;

B write objectives and keep them in focus from planning to evaluation;

B let the students know what the objectives are; and

B determine the learning style of students before teaching and educating students

according to their own learning style showing them how to cope (Vincent and Ross,

2001).

According to Vincent and Ross (2001), learners need to know what their own learning style is

in order to manage their learning more effectively and efficiently. At the same time, trainers

should also be aware of the learning styles of their students so that they can establish

alternate ways of teaching identical information to students. The Dunn and Dunn model of

learning styles prescribes that all individuals have a specific learning style; this differs from

person to person, and each person has learning style strengths or preferences (Pfeiffer et al.,

2005). The model suggests that it is easier to learn through one’s strengths or learning style

preference. The central aim of the model is that the ‘‘closer the congruence between

students’ learning style and their teachers’ teaching styles’’, the higher the level of

achievement (Pfeiffer et al., 2005). Also on this theme, Alsubaie (2006) suggested that

learning styles should be incorporated in a learning environment to achieve a holistic

environment that appeals to a whole raft of learners.

‘‘ The skill of knowing how to learn is considered a must forevery worker. ’’

VOL. 41 NO. 1 2009 j INDUSTRIAL AND COMMERCIAL TRAININGj PAGE 49

Page 4: Personalised learning environments (part 2): a conceptual model for construction

4. The PLE prototype incorporating learning styles: a conceptual model

The development of the PLE prototype is divided into two phases: the development of the

diagnostic questionnaire, which is the learning style inventory used to identify the learners’

styles (phase 1); and the development of the prototype itself (phase 2). This is shown in

Figure 1.

Figure 1 shows the relationship of the diagnostic questionnaire to the development of the

PLE. In respect of the development of the PLE, pedagogy will be mapped with technology

using instructional design (ID) theories. ID theory is ‘‘a theory that offers explicit guidance on

how to help people learn and develop’’ (Reigeluth, 1999). This sets out procedural steps to

systematically design and develop instructional materials (Dick and Carey, 1990; Gagne

et al., 1988; Merrill et al., 1996). Learning objects will be used together with e-learning

standards and interoperability between delivery platforms, reusability of e-learning

materials, etc. A learning object is considered as any resource or content object that is

supplied to a learner by a provider with the intention of meeting the learner’s learning

objective(s) (Vercoustre and McLean, 2005). However, the current focus in the e-learning

community has predominantly been centered upon the development of technical

infrastructures that support reusability, interoperability, durability and accessibility of

Figure 1 PLE prototype incorporating learning styles conceptual model

PAGE 50 j INDUSTRIAL AND COMMERCIAL TRAININGj VOL. 41 NO. 1 2009

Page 5: Personalised learning environments (part 2): a conceptual model for construction

learning content (Bannan-Ritland et al., 2002; Hummel et al., 2004). Hence, the key

concepts behind learning objects is that they can be used and reused in different (and

multiple) learning contexts (Dahl and Nygaard, 1966). Put simply, learning objects are

something tangible that is produced by bringing together subject knowledge and

pedagogical expertise (Duncan, 2003). Notwithstanding these issues, the precise

development rubrics applied to PLE’s will be discussed in further works.

4.1 Phase 1 – development of ‘‘diagnostic questionnaire’’

Coffield et al. (2004) noted that it is often difficult to teach students if we do not know what

their learning preferences are. In this context, this questionnaire aimed to identify a learner’s

learning style preference. The questionnaire was formed by amalgamating three models of

learning styles which was determined from the literature; namely Kolb’s model of learning

styles, Honey and Mumford’s model of learning styles, and Felder and Silverman model of

learning styles. It was formed with the basis that a learning style comprises the following

activities:

B perceive and process information (Kolb-LSI) (Kolb, 1984);

B process and organize information (H & M-LSQ) (Honey and Mumford, 2006); and

B process and receive (or remember) information (FS-ILS) (Felder and Silverman, 1988).

For the benefit of the readers, the three-core model of learning styles were identified after a

detailed synthesis of the literature review. These were considered the most suitable for this

research as being the most cited and commonly used in a web-based learning environment;

i.e. INSPIRE (Honey and Mumford model of LS), CS388, LSAS and Tangow (Felder and

Silverman model of LS) (see Stash et al., 2004, for further details). These models have also

been successfully implemented in traditional classroom scenarios.

4.1.1 Process of development of the diagnostic questionnaire for learning styles. Upon

choosing the three models of learning styles, the overall development process of the

Diagnostic Questionnaire was divided into three stages (see Syed-Khuzzan and Goulding,

2008).

Development stage 1: this stage was used to identify and disaggregate the types of learning

styles for all the three models of learning styles, which also involved the ‘‘typical’’

characteristics and traits exhibited by these styles of learning. These characteristics can be

seen in Tables I, II and III; representing Kolb, Honey andMumford, and Felder and Silverman

respectively.

Development stage 2: this development stage was used to identify the similar

characteristics of each learning styles in the three models by amalgamating them

together, in order to tease out four core themes (identified as learning styles A, B, C and D).

Figure 2 shows the amalgamated/synthesized model, the abstract conceptualization of

which shows the four core themes, LS A, LS B, LS C, and LS D.

Development stage 3: the final stage of this development process was used to formulate the

questions within the four core themes. Six questions were formed for each core theme,

adding up to a total of 24 questions. The process of forming the questions was considered

critical as it needed to accurately crystallize the core ‘‘essence’’ of each learning style. In this

respect, the questionnaire was piloted with five domain experts within the field of learning

styles to provide feedback and views concerning:

B questionnaire content;

B questionnaire validity;

B questionnaire construct;

B questionnaire format; and

B type and level of questions used.

VOL. 41 NO. 1 2009 j INDUSTRIAL AND COMMERCIAL TRAININGj PAGE 51

Page 6: Personalised learning environments (part 2): a conceptual model for construction

Subsequently, in measuring the validity and reliability of this questionnaire, it will be tested

with learners alongside with the original models in developing the questionnaire, i.e. Kolb’s

learning style inventory (LSI), Honey and Mumford’s learning style questionnaire (LSQ), and

Felder and Solomon inventory of learning styles (ILS).

4.2 Phase 2 – Development of PLE prototype incorporating learning styles

Upon validation, the diagnostic questionnaire will then be ‘‘mapped’’ into a PLE prototype

(as a strategy to accommodate a combination of different learning styles in an e-Learning

environment) for further research and development work, including the augmentation to

each of the four learning environments (A, B, C and D) (see Figure 1). The precise modus

operandi, development rubrics and technological interdependencies/conformance

requirements will be discussed in further works.

Table I Learning styles characteristics

Model of LS Types of LS Characteristics of each style

Kolb’s model of LS Divergers (concrete experience andreflective observation)

Take experiences and think deeply about themLike to ask ‘‘why?’’Start from detail to constructively work up to the big pictureEnjoy participating and working with otherCalm over conflictsGenerally influenced by other peopleLike to receive constructive feedbacksLike to learn via logical instruction or hands-one exploration withconversation that lead to discovery

Convergers (abstractconceptualisation and activeexperimentation)

Think about thingsTry out ideas to see if it works in practiceLikes to ask ‘‘how?’’Like factsSeek to make things efficient by making small and careful changesPrefer to work by themselvesThink carefully and independentlyLearn through interaction and computer-based learning

Accommodators Most hands-on approachLikes doing rather than thinkingLikes to ask ‘‘what if?’’ and ‘‘why not?’’Do not like routine and repetitionTakes risks to see what happensLikes to explore complexity by direct interactionLearn better by themselvesLikes hands-on or practical learning rather than lectures

Assimilators Have the most cognitive approachPrefer to think rather than actLike to ask ‘‘what is there that I can know?’’Likes organized and structured understandingPrefer lectures for learning (esp. with demonstrations wherepossible)Learn through conversationPrefer logical and thoughtful approachOften have strong control needPrefer clean and simple predictability of internal models to externalmessinessLearns better when lecture starts with high-level concept and workdown to the detailDo not teach by play – they are serious learners

Source: Kolb (1984)

PAGE 52 j INDUSTRIAL AND COMMERCIAL TRAININGj VOL. 41 NO. 1 2009

Page 7: Personalised learning environments (part 2): a conceptual model for construction

5. Conclusion

The advances in technology have increased the demand for new and innovative teaching

approaches, prompting the design and development of cost-effective and high quality

e-Learning environments that can efficiently respond to learners’ needs and requirements.

Over the past decade, research has attempted to address key areas in this field, such as the

automation of the learning process, improving the portability of e-learning materials,

pedagogy, learning objects and e-learning standards. The relationship between pedagogy

and technology also appears to be an important aspect in designing educational systems.

It appears that the developments and strategic alliances in e-learning could produce a

revolution in the way education and training is delivered in the knowledge-based economy,

particularly increasing the delivery of knowledge globally through the Web. It is widely

accepted that learning through the web (e.g. e-learning) can take place anywhere, at any

time, through any computer and without necessarily the presence of a human tutor. However,

research findings have found that the majority of e-learning applications are rather static and

represent a generic approach to tutoring that does not take into account the individual needs

(e.g. learning styles) of each student that is using the educational application.

The quality of technological delivery and developing effective pedagogies are crucial issues

in shaping the said e-learning future. Hence, this paper briefly introduced the conceptual

model for the development of a PLE (incorporating learning styles) from an educational,

pedagogical, and technological as well as standardization perspective by adopting the

principles of the ‘‘collaborative system design’’ approach, as identified by the Advanced

Distributed Learning (ADL) initiative guidelines (see Alshawi et al., 2006). This conceptual

model has not been tested and the author invites rooms for discussions and comments for

improvement.

Table II Learning styles characteristics

Model of LS Types of LS Characteristics of each style

Honey and Mumford model of LS(Honey and Mumford, 2006)

Activists Like to think independently – like to take direct actionPrefer to have short sessions – like to take direct actionLess interested in the past – interested in the here and nowLikes plenty of varietyLikes to have a go, try things out and participateLikes to be in the center of attention

Reflectors Likes to think in detail before actingPrefer thoughtful approach and thorough preparation (read andread)Likes to research and evaluateGood listeners and prefer to adopt a low profileLikes to make a decision in their own timeLikes to listen and observeWelcome the opportunity to repeat a piece of learning

Theorists Likes to see how things fit into an overall pattern (a global person)Logical (likes logical presentation of ideas) and objective systemspeople – prefer sequential approach to problemsAnalytical – pay attention to details and tend to be perfectionist(likes to feel intellectually stretched)Like structures and clear objectives

Pragmatists Likes to see how things work in practice – to see the relevancy oftheir workPractical – likes to gain practical advantage from learningLikes to solve problems and are down to earthLike credible role modelsLike proven techniquesLike activities to be real

Source: Honey and Mumford (2006)

VOL. 41 NO. 1 2009 j INDUSTRIAL AND COMMERCIAL TRAININGj PAGE 53

Page 8: Personalised learning environments (part 2): a conceptual model for construction

Table III Learning styles characteristics

Model of LS Types of LS Characteristics of each style

Felder andSilverman modelof LS (Felder andSilverman)

How learners perceive:Sensing learners Likes to observe

Gather data through the sensesLikes facts, data and experimentation Likes to solve problems by standardmethods – dislikes surprisesPatient with detail and do not like complicationsGood at memorizing factsCareful but may be slowLikes to do hands-on work

Intuitive learners Likes to speculate, imagine and hunchPrefers principles and theoriesBored by detail and welcome complicationsLikes innovation and dislike repetitionGood at grasping new factsQuick but may be careless

Ways learners receive information:Visual Best remember what they see (pictures, diagrams, flow charts, films,

demonstrations)Auditory Remember much of what they hear andmore of what they hear and say (learn

better by discussion, verbal explanation, and by explaining things)Ways learners process information:Active Feels more comfortable when involved in doing something in the external

world with the information learnedDo not like passive learning environments (i.e. lectures)Work well in groupsTend to be experimentalist – evaluate ideas, design, etc.

Reflective Likes examining and manipulating with the information learnedOccasional pauses for thoughtsPrefers materials that are fundamental understandingTheoreticians (the one who can define the problems and propose possiblesolutions)

Ways learners understand:Sequential Likes presentation of materials to be in a logically ordered progression

Follow linear reasoning processCan work with materials when they understand partially or superficiallyStrong in convergent thinking and analysis

Global Learn in fits and startsMake intuitive leaps; and may be unable to explain how they came up with asolution to a problemSometimes learn better by jumping directly to more complex and difficultmaterialStrong in divergent thinking and synthesis

Source: Felder and Silverman (1988)

Figure 2 Synthesized model: abstract conceptualisation

PAGE 54 j INDUSTRIAL AND COMMERCIAL TRAININGj VOL. 41 NO. 1 2009

Page 9: Personalised learning environments (part 2): a conceptual model for construction

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