Our Flexible Friend: The implications of individual differences for information technology teaching

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Computers & Education xxx (2005) xxx–xxx

Our flexible friend: The implications of individualdifferences for information technology teaching

S.J. Waite a,*, S. Wheeler a, C. Bromfield b

a University of Plymouth, Douglas Avenue, Exmouth, Devon EX8 2AT, UKb University of the West of England, Frenchay Campus, Coldharbour Lane, Bristol, BS16 1QY, UK

Received 2 August 2004; accepted 26 November 2004

Abstract

In this article, we report the observed differential uptake and use of computer programs and activities of

seven boys and girls of high, medium and low attainment in a classroom in the UK where over 40 children

aged 10 and 11 have a networked PC on their desk all day and every day. We observed the detail of what

happened in the small space between the pupil and the screen over the period of 1 year in the social and

instructional context of the classroom. We found interesting individual differences superseding the expectedvariation based on gender and attainment. We suggest some possible �within child� and external factors

which may contribute to these differences and consider some of the implications for teaching and learning

through ICT and the need for further research to investigate the nature of these differences.

� 2005 Elsevier Ltd. All rights reserved.

Keywords: Elementary education; Human–computer interface; Multimedia/hypermedia systems; Pedagogical issues;

Teaching and learning strategies

1. Introduction

The importance of information and communication (ICT) skills for the future has been asserted(DfES, 2002; DfEE, 1997) and substantial UK government investment has been made to support

0360-1315/$ - see front matter � 2005 Elsevier Ltd. All rights reserved.

doi:10.1016/j.compedu.2005.01.001

* Corresponding author.

2 S.J. Waite et al. / Computers & Education xxx (2005) xxx–xxx

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the development of these skills in schools. Some studies into the impact of ICT in education havebeen large scale and have commented on broad trends (McFarlane et al., 2000; Smeets & Mooij,2001; Selwyn & Bullon, 2000; Robertson, 2002), while others have looked at affective componentsin small scale studies (for example, Cooper & Brna, 2002). There have been studies which havelooked at ICT as the means of presenting learning material (Kemmis, Atkin, & Wright, 1977; Rid-ing & Grimley, 1999) and others that have addressed ICT�s facilitative role for learning (Ander-son, McAteer, Tolmie, & Demissie, 1999; Burley, 1998). In the context of calls for greaterpersonalisation of learning;

Information and communication technology (ICT) is a powerful tool for learning, helping teach-ers explain difficult concepts, giving access to a huge range of examples and resources, andengaging pupils easily. It is also a vital tool for personalisation – giving the opportunity to tailor

tasks to children (DfES, 2004, Chapter 5, para 17)

the examination of individual differences in the use of ICT becomes increasingly important. Somestudies comment on the differential use of ICT by individual students, for example through homecomputer ownership (e.g. Hayward, Alty, Pearson &Martin, 2003) and gender has long been sug-gested as influencing the uptake of ICT (e.g. Joiner, Messer, Littleton, & Light, 1996). The rela-tionship between ICT and attainment appears to be seen mainly in terms of the effect of ICT onattainment (Cox et al., 2003). The converse has rarely been examined; how higher attainment orability levels may affect students� use of ICT. Harrison et al. (2002), for example, found no evi-dence that pupils at any one ability level were advantaged or disadvantaged by high use ofICT. Therefore, in designing our study, although we only observed a small group of pupils in de-tail, we sought to control for gender and attainment to monitor possible effects. This article seeksto explore the individual differences which may shape children�s use of ICT in the light of a lon-gitudinal study of a primary school class of 10 and 11 year olds.

2. Sources of individual differences

Individual differences are self-evident in our daily experience but the source of these differences,their stability over time and their contribution to differences in performance are much more com-plex considerations. Intelligence, cognitive styles, learning approaches and personality types aresome of the psychological constructs that have been associated with the study of individual dif-ferences and their influence upon patterns of behaviour. In addition to these internal constructs,past experience is clearly a source of individual differences and will interact with internal factors toengender different responses.

Cognitive style has been defined as �an individual�s preferred and habitual approach to organ-ising and representing information� (Riding & Rayner, 1998, p. 8). There has been a great dealwritten about learning styles, preferences and cognitive styles (see Cassidy�s review, 2004). Cassidy(2004) distinguishes between traits, which are relatively stable and fixed (cognitive and learningstyles) and states, which are more responsive and fluid (learning strategies). Both may impacton how particular learning contexts work for different individuals, but �states� may be more flex-ible to them. There is considerable debate about the reliability, validity and usefulness of sometests of cognitive and learning style (Coffield, Moseley, Hall, & Ecclestone, 2004; Leutner & Plass,

S.J. Waite et al. / Computers & Education xxx (2005) xxx–xxx 3

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1998; Smith, 2002). Apart from issues of reliability and validity, some tests are inappropriate forchildren under 11, for example where self report requires a level of self awareness of learning pref-erences which many young children do not possess. Gardner�s Theory of Multiple Intelligences(1983), Riding�s Cognitive Styles Analysis approach (1991) and Dunn, Dunn and Price�s LearningStyles Inventory are probably the most commonly used with primary aged learners. They offerpossible frameworks for factors accounting for differential use of ICT by young children. Desmedtand Valcke (2004) argue that citation analysis of learning styles indicates the impact of differentlearning style orientations and Dunn and Riding are both frequently cited. However, Dunn, Dunnand Price have been criticised because of a lack of independent evidence of their test�s effective-ness, both as a reliable psychometric measure and as a useful tool for tailoring pedagogy for indi-viduals (Coffield et al., 2004). Gardner�s Multiple Intelligences (1983) were not easily deducedfrom the activities we observed in our study.

The field of learning styles and cognitive styles is complex with different labels and conceptsoverlapping (Cassidy, 2004). Some researchers believe them to be correlated with personalitytraits (Jackson & Lawty-Jones, 1996), while others claim that personality has only a moderatingeffect on learning style (Riding & Wigley, 1997). Personality itself may have an impact on the dif-ferential use of ICT (Benyon, 2002). For example, it might be supposed that extravert personal-ities would be drawn by the communicative and multimedia possibilities that offer highstimulation. Conversely, ICT�s potential for reduction of classroom noise by electronic communi-cation and for independent study might be more attractive to introverts. High levels of anxietymay also impede children�s capacity to remember and hence their ability to process information(Elliman, Green, Rogers, & Finch, 1997).

Deep and surface approaches to learning (Marton, Hounsell, & Entwistle, 1997) offer anotherway to consider the individual differences which impinge on students� use of ICT. Those studentsmotivated to understand the material they are learning will tend to adopt a deeper approach tolearning and look beyond the surface features required to satisfactorily complete tasks. Anemphasis on presentational features of ICT may suggest a more surface approach. However, Valleet al. (2003) argue that in practice many students have multiple goals including learning and per-formance goals (akin to deep and surface approaches) which offer more flexibility to adapt in dif-ferent learning situations. They distinguish between approach–avoidance tendencies to eitherpromote favourable judgments of competence or avoid negative assessment of competence. Ananxiety about perceived competence may encourage surface approaches and a narrower focuson requirements for task completion. Whether because of anxiety about competence or a lackof understanding of broader learning opportunities within tasks, lower levels of ability may influ-ence students� tendency to adopt surface learning approaches.

What is clear is that individual differences are likely to impinge on observable actions in termsof children�s learning in a complex and interrelated way that makes reliance on one measure aloneinadequate as a source of guidance in how to personalise learning.

3. Our research

Our study aimed to investigate the impact of ICT on learning in a primary school class-room over several years. We took baseline measures in Year 5 (children aged 9 and 10) in


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a classroom with three PCs. We then examined a Year 6 (children aged 10 and 11) contextwhere every child had access to his/her own personal networked computer all day and everyday, and considered the implications of this for teaching and learning from both teacher andpupil perspectives. Individuals were tracked through from Year 5 to Year 8 (secondaryschool), to study the impact of ICT in differing educational environments by interviewingthem in Year 5, 6, 7 and 8. The headteacher, class teacher and teaching assistants were alsointerviewed.

We looked at the detail of what happened in the small operating space between the child, thecomputer and its immediate surroundings. We looked at the teacher�s interventions, the presenceof different staff and the social interaction of the children. We noted their individual activity anduse of computer programs. We tried to understand how these interacted to create unique learningexperiences for the children in our study. We listened to the ideas of the children and staff aboutwhat they thought had been happening in their classroom.

Our study adopted an ecological approach, as proposed by Kemmis et al. (1977, p. 321) recogn-ising the importance of context and the environment within which learning takes place. We foundthat the computers were only actually used 49% of the time; maths took up about 25% of the ob-served time, using handwritten work books (13.6%) and that 28% of observed time was taken upby organisational issues and teacher talking. We observed very little music in class; this seemed totake place with a teaching assistant on a PC or singing by groups of pupils in their free time in thehall. We did not see any art lessons;

We were supposed to do it every Thursday . . .but that didn�t quite work out.

I think the whole year we only drew one thing, it was our shoes!(Pupils, follow up interview, Year 7, secondary school).

The curriculum in year 6, the year of observations, was principally composed of literacy, andhumanities mediated by literacy practices, and mathematics, with less emphasis on other aspects,including science.

While this emphasis on the core subjects is probably widespread in primary schools in thewake of standard assessment tests (SATs), the school in which the study takes place is unusualin that it has frequently appeared in the press because of its high level of investment in ICT forits oldest children. It also accepts a higher than usual proportion of children with special edu-cational needs.

The headteacher and class teacher, who is also Deputy Head, are energetic and entrepreneurialwith powerful personalities. The teacher gave the pupils in our study a great deal of freedomabout how and when they did their work. They would have a number of tasks to complete, whichthe teacher usually sent to them via email, having initially introduced each new topic in a wholeclass session.

The two teaching assistants seemed to fulfil two distinct roles; Mr. Pratt is �always on his com-puter�, while Mrs. Marks �comes round and looks at your work and checks your spelling is all rightand that your work makes sense and she helps you in Maths and spelling and that� (pupil, year 6,primary school). The class receives many visitors: teachers, press and ministers, who come to ob-serve their unusually high use of ICT. The children were accustomed to being watched andanswering questions about their use of computers, which made very close observation of their ac-tions easier than it might be in other classrooms.


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One of the dilemmas we faced in this research is a tension between trying to measure and quan-tify the use of ICT by the children for different purposes and to understand the processes under-lying their observed behaviour. This has guided our methodology and directed the mixed methodsof data collection we used, which are explained in more detail below.

4. The methodology

We selected six children as �representatives� to explore the effect of gender and attainment levels.Previous research (for example, Clegg, 2001; Joiner et al., 1996) led us to think that gender mightexplain differential uptake of ICT. Joiner (1998) compared performance on software that wasstructurally identical but either male or female stereotyped and found that girls performed worsethan boys on both versions of the software even taking into account computer experience. Passey,Rogers, Machell, McHugh, and Allaway (2003) have suggested that ICT has a more positive effecton boys extending their interest span. However, Harrison et al. (2002) found that this did nottranslate into an advantage with learning over girls.

We also considered attainment might be a major factor, so we included a male and female ofhigh, medium and low attainment, as assessed by their class teacher, in our observational targetgroup. The head teacher also added a seventh child, representative of high attainment andfemale.

Since characteristics and the attitude of teacher would clearly be influential on their develop-ment during the year and, with two other staff as Teaching Assistants present, it was consideredvital to keep fieldnotes of the overall picture in the classroom. Some background features werealso noted in the observation schedule. These two sources enabled us to take account of someof these background characteristics. However, pilot observation showed that it was impossibleto determine how individuals were working from a single advantage point and the layout ofthe room meant that a group working together and geographically co-located to enable groupobservation was rare (Wheeler, Waite, & Bromfield, 2002). We decided to observe the targetgroup children for periods of 16 min each, noting their actions every minute, and then movingon to another child to repeat the process. The observations included a running record of activity,which was coded under the following categories:

� date,� time,� whether the child was in the main classroom or annexe,� what curriculum area being covered,� what principal software was used,� the nature of the activity the child was engaged in,� whether they were on or off task, quiet or talking,� what sort of contribution the teacher or teaching assistants were making at that point,� what staff were present in the room.

Efforts were made to ensure balance in the number and timing of the observations so that eachchild was observed for approximately the same length of time and at different times of the day


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and week. Over 200 individual records were taken of each child during 22 visits to the schoolthroughout the school year and at different times of the day. While this enabled a spread of dif-ferent activities to be sampled, because only one observer was present for most of the time, con-temporaneous observations were uncommon. As part of our original design, this was notespecially problematic as the observations were going to be grouped for analyses, and the smallestunits of analysis we intended to look at were gender and attainment levels. However, the methodof data collection precludes comment on the different responses of individual children to the same

set of teaching and environmental characteristics. As we continued to collect data and spend timein the classroom, we began to suspect that individual differences might be playing a bigger rolethan the variables we had chosen. A further study in which several researchers observe target chil-dren during the same periods of time would therefore be helpful to examine how whole classinstructions are translated by individuals into activities in that narrow interface between computerscreen and pupil.

We interviewed and observed the target children in the summer term before they joined theYear 6 class to get a baseline measurement for how they worked and an insight into their attitudestowards computers. They were then observed on an almost weekly basis, varying the day of obser-vation, for the whole of their final year in primary school. They were interviewed at the end of thisfinal year, after a term at secondary school and again after a year and a term at secondary school.An examination of their changing views of ICT will be the subject of another article. They alsocompleted the NFER-Nelson Non-Verbal Reasoning Test 10 and 11 (Smith & Hagues, 1993).The school operated a computer based assessment system whereby children were assessed annu-ally by their class teacher as high, medium or low within National Curriculum levels. Learninggain was derived from these assessments. Proficiency with ICT was derived from observationsand self report.

5. Data analysis

The coded observational data was entered in Excel and analysed using SPSS. During the col-lection and analysis of the data, it became clear that individual pupil�s responses to and uses ofthe ICT varied considerably. We became interested in what might be the source of these indi-vidual differences. It did not seem appropriate for us to use Gardner�s multiple intelligencesmodel as we had limited opportunities to observe the children in music or art and so wouldbe unable to infer ability in these areas. These subjects rarely featured as part of the regularschool day in the class studied. Subjects were mostly taught through topic and project workfor the majority of the year, with a period focused on practice papers as SATS preparation.Dunn, Dunn, and Price (1989) have been criticised for the theoretical underpinning of theirmodel (Coffield et al., 2004) so this model was rejected. Riding�s categorisation, on the otherhand, offered a means of exploring learning style as a source of the individual differences ob-served, by inferring from observation and interviews where the individual children lay withinhis schema. It would also be possible to tentatively compare this very small sample with a widerrange of other studies, despite the fact that cognitive style had not been identified as a variableat the outset of our project.


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6. Inferring learning styles

No formal assessment had been made of intelligence, learning preferences, cognitive style orpersonality, as these were not principal foci of our research at the outset. This technique of deter-mining learning styles may not in itself be detrimental to the research. Leutner and Plass (1998)found that their observational tool was more successful in predicting learning outcome than ques-tionnaires about learning preferences. Observation may be particularly important as a tool forassessing learning style when children are unaware of their preferences and where an ethnographicapproach attempts to discover how real learning occurs in a real classroom situation. Using testsin artificial situations is of limited value when our methodology was designed to provide a richcontextual background of other factors operating in this primary school classroom. The mainproblem in the use of the following framework as a tool to organise the data stems from the posthoc nature of the categorisation. Issues of circularity arise in that it is their behaviour which placesthem in a construct defined by those very behaviours rather than as a result of an independent pre-test.

Riding (2002, pp. 25–28), describes two cognitive style dimensions:

� wholist (tends to see material as a whole, and have overarching view and appreciate context) toanalytic (tends to see elements of material and be good at comparing and contrasting parts butmay struggle to see bigger picture).

� verbaliser (tends to consider material as words and more externally, socially oriented) to imager(tends to consider material in pictures and more internally oriented).

The interaction of these dimensions may complement and moderate or intensify these features.Using these descriptions and applying them to the �portrait� of the children built up from ourdata, an inference was made about where the target children lay in Riding�s framework withtwo researchers independently categorising the pupils on the basis of questionnaires abouttheir computer use, interviews and observations. These are illustrated by quotations fromthese sources in the following table, although these cannot adequately convey the fuller knowl-edge of the children gained through weekly contact over the period of a school year (seeTable 1).

7. Non-verbal reasoning and learning gain

The children took the NFER-Nelson Non-Verbal Reasoning test 10 and 11 (Smith & Hagues,1993) which measures the ability to recognise similarities and patterns in unfamiliar designs. It isbelieved to be related to the ability to understand and assimilate new ideas and information(Smith & Hagues, 1993) and we thought it might distinguish which of them were more �suited�to a discovery way of learning through exploration that this class used. We used the non-verbaltest as it is assumed to free the assessment from language bias but intuitively one might expectthere to be a link to Riding�s concepts of imager and verbaliser, whereby imagers would performbetter on the non verbal and verbalisers on the verbal test. The test is considered likely to identifythose with strengths in maths, science, design and technology.

Table 1

Inferred personality and cognitive style

Target

child

Inferred

cognitive style

Illustrative quotations

1 AI �You can get Clipart to put in your work and you can change colours�. �I�ve got a pet on

the Internet, a Neo pet, and I go on to download songs and go on Pop Star search. I did a

project on S Club 7 before I went to see them�. �You can get pictures of the car and make

your own pictures of the car and that. And take pictures of your group�2 AI �The Internet, making my web page, looking at pictures�. � I look for golden retrievers and

other kinds of dogs. I look at wrestling pages�. �I�ve written Pokemon dessert and put the

pictures on. I need to still do the writing part�. �If you�ve got to imagine something and

then you go on the Internet they�ll be lots of things like you�ve imagined but it will be in

different kinds of ways�3 WV �The best thing is the technology really and the information you can get from them�. �At

home, I probably spend about 25% on games, 25% on work and another 50% on other

whatever, like email, something like that�. �I can read the documents. . .and then use it for

work, I want to be an individual, so I do my own thing�4 WI �Internet, Pokemon, Godzilla�. �We did do quite a bit of art on my home computer. It�s

just a lot more fun than a book and sitting on a chair and writing in your book�. �I don�tdo a lot of emailing�. �If I get bored I can sometimes put a sound on. . .and then go back to

my work and it can help me keep awake for a lot longer�5 AI � You don�t know which programme does what and you�ve got to find it out, work it out

which programme does what by playing around with things�. �I like writing stories, just to

let your imagination go wild, you can make up anything you want�6 AV �Write work down, go on internet, send emails� �At home for writing invitations and thank

you letters and to play games�7 AB �I�mmaking Internet pages. . .there are special drawing programmes� �I�ve got this painting

thing and you can download popstars, movies and when friends come over we quite enjoy

doing that�. �There�s all sorts of things, like I can make sounds. . .the way you can change

the computer . . .I can design my own background if I wanted to�. �We�ve discussed it in

our groups and I understand it a lot more now. . .writing in your books is boring but if

you do it on the computer on Textease you can. . .just put a few pictures on them and

change the writing, colours and things�


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The usefulness of these �within child� categorisations needs careful thought in educational set-tings rich with other social and contextual influences, and caution is needed as other aspects ofindividual difference were also operating, such as experience of computers outside of the schoolenvironment. The post hoc designation may also have been subject to researcher bias, althoughtwo colleagues had independently categorised the children to mitigate any risk of this kind of bias.

8. Research findings

Our initial analyses showed how gender and attainment organised some of the data. For exam-ple, some gender variation in activity was marked with the girls having nearly twice the number ofsocially interactive activities (asking questions, helping others with work, seeking help, discussion,answering questions, instant messaging) observed in comparison with the boys. Although male

0

10

20

30

40

50

60

Research Reading Writing Interactive Demo Thinking

No

. of

ob

serv

atio

ns

HighMediumLow

Fig. 1. Activities by attainment levels.


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and female were equally represented in the top users of programs, the sorts of programs they fa-voured differed. Typically, boys engaged in Starspell, database, file manipulation, CD roms andInternet; while girls used Media Player, Photoshop, communication software, Publisher, Power-Point and the Intranet to a greater extent. This echoes Clegg� findings (2001) about more socialuses of computers by females. However, in a study by Joiner (1998) which looked at gender ste-reotyped software, he found that while boys preferred gender stereotyped computer based prob-lem solving, girls showed equal preferences for all. The generic nature of the software used mayhave circumvented a gender issue for boys but points up a possible gender difference in the appealof even generic programs.

The top users of programs were predominantly (53%) from the high attainment group. The pro-grams they were seen to use to a greater extent tended to be directed towards an end product, suchas Word, PowerPoint, Photoshop and databases. The medium attainment group were observedusing process programs, such as the Intranet and file manipulation to a greater extent. The lowattainment group favoured CD roms, communication software and Media Player. This pro-cess/product divide is reinforced by the sorts of activities engaged in; writing was more commonin the high attainment group and socially interactive activities in the lower attainment groups (seeFig. 1).

However, Fig. 2 groups the pupils into low, medium and high attainment groups as individualsand shows the variation between the individuals clearly. The variation is smoothed and masked byanalysis at attainment level. Analysis at this level only might inhibit our ability to understand howICT use and individual differences may interact.

A further effect was seen in the way individuals engaged in learning. Fig. 3 shows the socialbehaviour of individuals, categorised within on and off task behaviour into �quiet�, �talking topeers�, and �talking to adults�. Some individuals had very low levels of interaction with adultsin the class, for example, target child 6 and target child 2 especially, regardless of whether theywere on or off task.

The observations showed that target child 6 (a high attainer) was the quietest, least off task andhad least interaction with adults. Target child 4 (a low attainer) was the most off task and talked alot to peers. Although target child 7 spoke the most to peers, a high proportion of the talk was

0

20

40

60

80

1 4 2 5 3 6 7Students

No

. of

ob

serv

atio

ns Research

Reading

Writing

Interactive

Demo

Thinking

Fig. 2. Individual activity profiles of students.

020406080

100120140

1 4 2 5 3 6 7Students

No

. of

ob

serv

atio

ns

OT quiet

OT peers

OT adult

OFT quiet

OFT peers

OFT adult

Fig. 3. On and off task behaviour.


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task related. Target child 1 was the least quiet but spoke least to peers and most to adults. Thesesocial observations helped to fill out the pictures of how the children tended to approach learningand provide insight into how independent in their learning the pupils are and the extent to whichthey seek peer or adult support. Frank, Reich, and Humphreys (2003) reported how students ofthis age seek personal contact, although we found that, for some students, the distancing of elec-tronic communication removed inter-personal conflict and thereby supported group learning(Bromfield, Waite, & Wheeler, 2003). Riding (2002) suggests that in addition to being more relianton text for learning, verbalisers tend to use talk more in their learning (p. 29) and that wholistsprefer to learn in groups (Riding & Read, 1996). This, however, illustrates a difficulty of circular-ity in post hoc categorisation of pupils, whose behaviour places them in a construct defined by thebehaviour they have exhibited. Personality characteristics such as introversion might also explainthis difference.

The use of programs also varied between individuals, as different programs might be more com-patible with their preferred way of learning (Riding & Grimley, 1999). Those who sought moresocial contact took up the communication opportunities of email and instant messaging (amal-gamated under �Outlook� in Fig. 4).

The advantage of this was that, whether the child was on or off task, communication was lessdisruptive to others working independently around them. However, it was also more difficult forthe staff to detect if the communication was off task. This lack of awareness of individual response

0

10

20

30

40

50

1 4 2 5 3 6 7Students

No

. of

ob

serv

atio

ns Internet

Intranet

Cdrom

Word

Publisher

Powerpoint

Outlook

Photoshop

Media player

File manip

Database

Starspell

Fig. 4. Individual variation in use of programme types.


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was a disadvantage to facilitating teaching and learning through common open access to pro-grams as support for their learning. As differentiation was by outcome, the potential to find suit-able learning activities and to stretch children was in each child�s own hands rather thancontrolled by the teacher and this suited some but not all students. Sometimes pupils had to stayin at break if they did not achieve certain amounts of work within sessions due to a perceived lackof effort.

Drill and practice software like Starspell was supposed to be used by all at the start of the after-noon but some pupils preferred to go on the Internet or listen to music. Their participation andsuccess in this spelling practice was self-monitored and was not related to attainment level. Thisblanket use of drill and practice software for the whole class is in contrast to the findings of aquestionnaire about computers and literacy sent to West Country schools (Waite, 2004). In this,teaching staff described drill and practice as more likely to be used for children with special edu-cational needs.

One of the interesting individual differences in activity was in �file manipulation�, where the pu-pil was moving between programs. Although this could be interpreted as familiarity with the pro-grams and a facility for ICT, in practice, it often appeared to the observer to be a newtechnological equivalent of unnecessary sharpening of pencils, a time wasting activity, perhapsto afford �down time� from work and indicating an uncertainty about how to approach a task.From observation of target children 2 and 4, they seemed to find difficulty in settling to tasks; theyboth have high rates of file manipulation.

There were also marked differences in the amount of time the pupils used their computers asshown in Fig. 5.

Four of the children used the computer for around 40% of the time but target child 5 used thecomputer much less than this (21.8%) and target children 1 and 3 used it much more (68.3% and75%). This would seem to indicate that for target child 5, the class reliance on the computer astheir main tool for learning may have had detrimental effects on her learning. Her use of the com-puter was largely as a result of direct instruction rather than choice.

Fig. 6 shows how the two least off task were target children 3 and 6 and that 1, 2, 5 and 7 hadroughly equal amounts of off task observed, while 4 was off task for about 44% of the time he wasobserved.

Riding (2002) suggests male wholists are most likely to have behavioural problems (p. 63). Infact, in this study, the level of disruptive behaviour in the class as a whole was very low, despitethere being a number of previously excluded pupils in the class. However, the type of off task

1

2

3

4

5

6

7

Fig. 6. Relative time spent off task.

1

2

3

4

5

6

7

Fig. 5. Relative proportion of time spent on computer.


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behaviour more at risk in this setting was quiet, withdrawn passive behaviour, which preventedengagement in the learning tasks but did not interfere with others� learning.

9. Individual differences in ICT use and learning gain

Table 2 illustrates the patterns of ICT behaviour and the children�s rating on a number ofmeasures of individual difference (see Table 2). The overall use of ICT does not seem to ac-

Table 2

Students ranked by learning gaina

Students 7 3 6 4 5 2 1

Gender F F M M F M F

Inferred cognitive style AB WV WV WI AI WI AI

Attainment High High High Low Medium Medium Low

Learning gaina 7 6 5 3 3 3 2

Relative use of programmes 93 155 94 120 56 96 152

Home computer? 1+ 1+ 1 1 1+ 1+ 1

Used for games plus Yes Yes Yes Yes

Used for homework only Yes Yes Yes

Standardised score on NFER NV Test 121 107 118 96 94 78 86

a Learning gain is a numerical representation of the difference between the teacher assessments at Year 5 and Year 6.


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count for the learning gain of the pupils, which is largely in keeping with the attainment levelsthe teacher initially assigned. The higher attaining students seem to be widening the gap be-tween themselves and low attaining students in this ICT-rich and open-ended task environment.Neither does there seem to be an association between particular programs or activities andlearning gain. The children were all fairly skilled in their use of ICT, unsurprisingly in viewof the level of exposure they had to computers in school, but some appeared to have more pro-ficiency and enjoy the use of them more. All of the students had at least one home computerbut there is an interesting difference in the reported sort of use pupils made of the computers inthat using it for more than just homework seemed to be linked to higher learning gain. Thismight indicate that their preference for computers, using them beyond functional necessity,made them more attuned to the opportunities in the ICT-rich classroom. It may also indicatethat their �play� and exploratory approach to learning made them more effective learners in thisparticular classroom, which relied on personal responsibility for learning. Obviously, this is toosmall a study to draw conclusions, but this area may be worth exploration through furtherresearch.

The way in which the computers are used may be qualitatively different depending on the stu-dent�s innate approach and the meaning they attach to tasks. The more narrowly instrumentalpupils are in their use, the less computers may offer a scaffold to learning. It may be that it isunderstanding of computers as a tool amongst others and the matching of this to tasks and learn-ing style that is important, rather than skills in using the capacity of the computer for improvedpresentation.

10. �Within child� individual differences

As previously noted, some caution must be exercised in using labels of learning style, person-ality type or approach to learning as they are merely inferred in this study. It would be necessaryto test for these to see if the inferred types are valid in order to draw any firmer conclusions abouttheir role in using ICT for learning. Furthermore, the usefulness and appropriateness of this cat-egorisation has to be carefully considered. The danger that an externally imposed categorisationplaces on individual differences is one noted by Kemmis et al. (1977).

The recognition of difference depends on the drawing of boundaries, if the boundary is
imposed by the observer he may fail to recognise the boundaries that emerge from the obser-vations, that is, the qualitative differences between the actions of the students themselves(Ibid. p. 234).
Our grounded approach to the consideration of these difficulties circumvents some of this prob-lem but leaves us with another: how can the differential use of ICT be explained?

There are other individual differences which may also contribute to the differential uptake ofICT and the variance in learning outcomes. Applying these theoretical frameworks of individualdifference has helped us in an exploration of what may underpin these individual differences buthas also highlighted their incompleteness. Target children 1 and 5, for example, are both inferredAnalytic Imagers and Extraverts, yet their patterns of computer use are very different. Target chil-dren 7 and 4 have similar patterns of activities but they are polar opposites in terms of Riding�s


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cognitive style and their use of programs and their learning gain are very different. In their studyof students in special schools, Riding and Craig (1999) found that adverse home circumstancesinteracted with cognitive style in contributing to the likelihood of problem behaviours. The �with-in child� differences are thus clearly modified by external factors, such as the practical and socialcontext of learning (Cronbach, 1975).

11. Context for learning

Kemmis et al. (1977) set out three different curriculum paradigms: Instructional (drill andpractice), Revelatory (discovery, playing) and Conjectural (solving problems). He also postu-lated a fourth, Emancipatory, associated with each of the above, which essentially took awaythe tedious elements of work. In the classroom we studied, the children had tasks set by theteacher which fell within these categories. They were expected to begin the afternoon sessionwith Starspell Plus, a drill and practice spelling programme. They also had Eggy day chal-lenges where they designed and built a parachute and a car to convey an egg safely, whichbuilt up their group problem solving skills. They were given a free hand to use and explorethe possibilities of software for research and presentation in a discovery mode. Some of thechildren clearly enjoyed the playing and exploratory nature of their access to ICT; others wereusing it principally as an information source for personal or educational purposes. As for theemancipatory dimension, all the children commented in interview how the computers freedthem from the tedium of writing and rewriting. They also valued the presentational improve-ment in their work, although they did not always seem to be as aware of the re-drafting pos-sibilities. Despite comments such as

�I�m reading it through now, because I never used to read it through. I used to do my work but
I never used to read it through after but now I do. I find I�ve got time to read it now� (Targetchild 1)
sample work taken from first draft through to final version was often still fairly tight to the ori-ginal. Furthermore, in spite of the children�s lauding the computers� spell-checking facilities, spell-ing mistakes often remained.

The teacher�s aim was for the students to have a choice about how they approached thesubjects. Most of the tasks he set were open-ended for completion over a number of daysor weeks. The children could then work on them as and when they wished. New programswould be demonstrated but the extent to which they were utilised was largely in the handsof the children. The differences observed in the use of programs therefore reflected theirpreferences.

However, there may be significant effects for individuals� learning if they did not find the tasksset easy to understand or structure as this introduced an additional layer to their work. If theyworked more slowly than others did too, this would then mean they were unlikely to achieveall the task within the time frame allowed. Successful working within Revelatory and Conjecturalcurricular paradigms needs to be framed by effective explanations and support. Repeated experi-ence of non-completion of tasks could lead to lower levels of self esteem and incomplete learning.In a follow up interview, two pupils reflected:


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We actually writ everything but never got it finished. No. We would just move on to a different
subject. (pupils, Year 7, secondary school)
The higher attaining pupils seemed to be able to adapt their preferences and turn their hand tomost tasks. They also saw tasks to completion more than the low attainers did. The individualeffect of ICT may therefore have been masked by this overall attainment effect. It is likely thatwhere students are unable to adapt their learning style, they will be disadvantaged, unless the taskis adapted for them. Where students are unable to complete tasks, they can however find alterna-tive activities on the computer that do not interfere with others� learning. A danger exists in asso-ciation with this; because the ICT makes off task behaviour less visible and disruptive, it is lesslikely to be detected and redirected by the teacher.

The home use of computers would appear to be a significant factor. Home computers arerapidly becoming a mainstream household item. 81% of households had access to a computerin the home (BECTA, 2002), up from 78% in the 2001 survey, and 98% of 5–18 year oldsused computers at home, school or elsewhere, with 92% using them at school and 75% usingthem at home. The gap appears to be more in how these computers are used (Facer, 2002). Inour small study we found those children who were using the computer for homework alonemade less learning gains than those who used it for multiple purposes. This may be thatthe children are less confident with the computer, feel less attracted to its use, or merelyuse it as they might use a fountain pen to �copy up in neat� or a book �to find out facts�.For these children, the computer does not appear to be transforming the way they think aboutthings. Cox et al. (2003, p. 13) suggest there is a lack of congruence between children�s homeand school experience of computing which fails to blend out-of-school and within-school useconstructively. However, just bringing the opportunity to �play� into school would not appearto be adequate since the class teacher in our study allowed this at times within school in con-trast to the very focused skills based teaching of ICT in many primary schools. There wouldappear to be some internal factor which predisposes children to be exploratory or not andfurther research is needed to try to identify what this might be. Pragmatically, a more explor-atory approach might be fostered by scaffolded use of ICT, where pathways of exploration aresignposted for children.

12. Implications for teaching and learning

While the use of computers may mediate a �one size fits all� teaching approach to some ex-tent (McDonald & Ingvarson, 1997), we suggest that further progress might be made by amore differentiated use of them. Pittard, Bannister, Dunn, and Riding (2003) in their summaryof large scale studies of the impact of ICT on attainment, motivation and learning point tothe type of ICT use as being important in affecting attainment, where spontaneity and flexi-bility are favoured. They also suggest that �using ICT in the right ways can help personalisepupil learning, develop pupil-centred and collaborative approaches to learning and offer newways of supporting and enhancing pupil�s conceptual learning� (Pittard et al., 2003, p. 14).Attention to the differences in pupils� response to ICT may help to direct how these �rightways� can be addressed practically.


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If the availability of ICT does not directly liberate some pupil�s learning, then some othermeans of making it more appropriate to individual�s learning needs to take place. This mightinvolve creating more structure in open-ended tasks (Hoyles and Noss, 1992, cited in Cox etal., 2003, p. 17), The teacher in our study orally outlined ways to approach tasks such as�Who, What, Where, Why, How� and, on some occasions, this was sent through the interactivewhite screen to each pupil�s computer, but wholists and some low attainers may have benefitedfrom this guidance being available as a permanent writing framework. This would then havefreed them from an initial stage in the task of trying to create a structure for their exploration.They might also have benefited from more paired work where a different approach to ICT usewould allow them to experience beyond their capabilities or inclination. In addition, proficiencyin ICT offered a source of self-esteem for some low academic attaining students and anxiouspersonality types. Choosing partners with either strength in subject knowledge or ICT skillswould enable teachers to combine students to give both partners a zone of proximal develop-ment to encourage their learning and opportunities to build their self-esteem. Collaborationwhich builds on different more responsive and flexible learning strategies rather than stylesmight also help to scaffold learning (Cassidy, 2004).

Analytics and anxious personality types could have found difficulty in finding their way aroundprograms, being unable to retain the overall picture of how it works. On the other hand, they wereprobably helped by activities such as writing a leaflet about how to use programs, as this allowedthem to sequentially organise the material. Verbalisers and extraverts were also enabled to learnsocially through the extended means of communication and through joint work projects whichoften culminated in a Power Point presentation. A variety of tasks would support this broaderappeal of ICT for different cognitive styles.

A potential disadvantage of �labelling�, as we have done for the purpose of discussion in thispaper, is that in real life situation, it may diminish attention to the complexity of interrelationshipsthrough oversimplification. It is likely that each individual will have several, possibly conflicting,individual differences and that these will tend to dominate and interact in different contexts. Ourstudy suggests that use of a single learning style inventory might yield little of practical value topersonalise teaching. Since it is the interaction of individual characteristics, tasks and programswhich is fundamental to the successful use of the ICT for learning, it is important to becomeaware of individual preferences and differences at an early point so that contexts and tasks canbe adjusted or learning strategies supported. This might mean staff working alongside individualsto observe their approach.

Staff sensitivity to individual learning differences may be usefully enhanced by having a lan-guage with which to conceptualise them (Rosenfeld & Rosenfeld, 2004). Chen and Ford (1997)look forward to adaptive information systems which accommodate to individual differences, butuntil such responsiveness exists, provision of different structure and support by the teacherwould enable the individual use of ICT to be tailored to maximise each child�s engagementand success. Coffield et al. (2004) refer to a �lexicon of learning� (p. 39) which allows teachersto discuss their own and other learning preferences without labelling and praise the practicalvalue of Jackson�s Learning Styles Profiler (2002 cited by Coffield et al., 2004) as a self-devel-opment tool for teachers.


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13. Conclusion

ICT can be a powerful motivator (Bromfield et al., 2003) and an impetus for creative thinking(Wheeler et al., 2002). Movement away from drill and practice software or �copying up� handwrit-ten drafts (Waite, 2004) and the increased use of open-ended tasks, which allow some students tomatch the execution of tasks and selection of programs more to their preferred style introducesmore flexibility. However, some students appear to be unable to direct their use of ICT to the goalof learning without further structure. Moseley et al. (1999, cited in Cox et al., 2003, p. 11) foundthat effective explanations were key to good practice in pedagogy using ICT, where students wereinvolved and examples and counter-examples demonstrated.

There may be a correlation with attainment level. If pupils are very able, they appear to adaptthe ICT to their own purpose more than if they have lower attainment, so that benefits of ICT interms of improved attainment are further reinforced by high attaining students more flexible useof ICT. However, if ICT and tasks are compatible to their learning style, lower achievers may beenabled to improve their performance. Further studies are needed to investigate the inter-relation-ship of types of programs, types of tasks and types of learning style and other mediating factorssuch as pedagogy and motivation.

The development of an exploratory �playful� approach also appears to be an area worthy of fur-ther investigation.

There remains a tension between the ecological study of ICT providing a richness of par-ticular classroom contexts and the rigour of a more experimental design to enable a genera-lisability of results. While naturalistic observation enables real cases to be considered, thecomplexity of learning situations makes it difficult to be sure that effects are due to the appli-cation of ICT. A more experimental approach might be needed to test out hypotheses derivedfrom close ethnographic observation. The learning outcomes for this study, for example, werejudged on the basis of samples of work, teacher assessments and SATs results, integral toschool life, and this presents some difficulties in comparison with more narrowly defined learn-ing outcomes such as Riding and Grimley (1999) identified. Furthermore, we are unable toseparate the distinctive contribution of the ICT from the particular context of this case study.Establishing correlations, let alone causality, is a fundamental problem with educational re-search, given the many variables beyond the control of researchers (Rudd, 2001). Althoughlarge scale studies can provide information about trends, they cannot explain what is happen-ing at a micro level between the child, computer and their context. We hope that the richnessof our data will offer insights into factors influencing children�s learning worthy of furtherinvestigation.

This study only addresses implicitly the usefulness of ICT as a mode of presentation of learn-

ing material, and this is the primary focus for Kemmis et al. (1977) and Riding and Grimley(1999). A distinction also needs to be drawn between this and its usefulness as a flexible tool,among others, for pupil learning and the presentation of those learning outcomes. Somekhand Davies (1991) in their discussion of pedagogical change arising from ICT argue that weneed to move

�from a view of teaching and learning as discrete, complementary activities to an understand-
ing that teaching and learning are independent aspects of a single activity� (p. 156).


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We would go further and suggest that these aspects are not independent within the single activitybut merge in the rich context of an ICT-rich social constructivist learning environment, where stu-dents also learn through teaching others.

Further research is needed to explore whether a link with learning style exists and whether theconcept of learning style offers the best fit as a theoretical framework for the study of individualdifferences and ICT. Despite one pupil�s comment that �we will still need teachers to turn the com-puters on� in the future, implying ICT may absorb more active teaching roles, it appears from ourstudy that increasing use of computers in classrooms needs to take account of individual needs tomaximise pupils� potential and that the teacher�s role is central to facilitate this.

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Our Flexible Friend: The implications of individual differences for information technology teaching

Education

Transcript of Our Flexible Friend: The implications of individual differences for information technology teaching