Learning with Computers

Analysing Productive Interactions

Paul Light, Karen Littleton

• Publisher: Routledge
• Year: 2002
• Topic: Psychology
• eBook ISBN:
  9781134764716
• Subtopic: History & Theory in Psychology
• Index: Psychology

Contrary to the belief that computers isolate users, Karen Littleton and Paul Light demonstrate that learning with computers is often a collaborative and social activity. Learning with Computers brings together a significant body of research that shows how working with others at the computer can be beneficial to learners of all ages, from the early school years to the highest levels of education. It also investigates factors such as gender that explain why some interactions are not as productive as others.

1 Introduction

Getting IT together

Paul Light and Karen Littleton

Computers and children's learning

In one guise or another, computers have become almost ubiquitous over the last quarter of the twentieth century, and one of the things that is clear about the twenty-first century is that computers will play an increasingly significant role in both our leisure environments and our working lives. Consequently, learning to live and work with computers must figure amongst the more obvious ‘attainment targets’ of any contemporary educational curriculum. In parallel with this (and potentially independent of it) there is the issue of what the computer has to offer as a technology for supporting education more generally. What, if anything, can computers offer as adjuncts to (or even substitutes for) classroom education?

One vision of the place of computers in education (perhaps the predominant one in the early days) saw the computer as a perfect vehicle for carefully tailored contingent instruction, whereby each student could be taught at his or her own level and pace. Psychologists and educationalists who favoured an associationist model of learning saw the possibility that the computer might succeed where the teaching machines of the 1950s had failed (Light, 1997). Meanwhile critics of the new educational technology bewailed the impending ‘dehumanisation’ of the teaching/learning process.

A great deal of software developed for school use has indeed adopted essentially this approach; breaking desired learning goals into small steps and relying on reward, repetition and contingent incrementation of difficulty levels to impart various skills. Such ‘drill and practice’ software has been especially popular in the area of elementary arithmetic, where rote learning has long held a place. The computer takes the place of the teacher, in asking the questions and giving feedback to the learner. Typically, such software takes little from the learner's response to each question other than whether it is correct or not.

From this starting point the obvious direction of development, as greater computational power becomes available in the classroom, is to emulate more of the human teacher's capabilities. We can see this reflected in the move towards ‘Intelligent Tutoring Systems’ which ‘model’ each learner on the basis of patterns of response, and shape a teaching strategy accordingly. Progress in this direction has been frustratingly slow, and thus far only a few extremely expensive systems with very restrictive domains of application can claim much success.

In practice, though, computers in schools are more often than not used by pairs or small groups of children rather than by individuals (Wegerif and Scrimshaw, 1997). This pattern has doubtless been shaped in part by resource constraints, and perhaps also by children's apprehensiveness about working with new technology on their own. Increasingly, however, there is also a positive belief on the part of teachers that interacting around the computer can be a particularly productive way of learning. Indeed it is widely held that some of the clearest benefits of classroom computer use arise from the fact that they lend themselves so well to collaborative modes of use (Crook, 1994).

There is a good deal of research evidence to support this proposition, as we shall see throughout this volume. In a wide range of situations involving working with computers, pairs or small groups of children not only appear to perform tasks better than individuals, but also to learn more from doing so. This is true even with types of software developed specifically for individual use, such as the drill and practice software (Mevarech et al., 1991) or Intelligent Tutoring Systems (e.g. Woolf, 1988).

What are the bases of this intellectually productive interaction? What features of the computer hardware or software contribute to or influence it? Are there circumstances in which such interactions around the computer are unproductive or even counterproductive? What research methods are available to explore these issues, what assumptions do they make and what problems do they pose? This introduction will offer an overview of some of the broader issues involved, while the contributions which follow will pursue particular approaches in greater depth.

Cognitive approaches: peer facilitation of individual learning

There are clearly lots of possible ways in which working with others might be helpful in approaching a task, and other ways in which the presence of others might prove a hindrance. Some of these can be approached from the standpoint of the cognitive or information-processing resources which partners might bring to the interaction.

Where several people work on a problem together, whatever it is, there is an obvious sense in which there are greater cognitive resources available for its solution than if a single individual is faced with the same problem. Thus, for example, even if the group members have got equally good memories, it is likely that some will spot and remember some items of relevant information and others will remember other items. Likewise one child may have a particular talent for a given aspect of the task, another for another aspect. With a computer task, one child may have more experience of the type of software involved, another may have better keyboard skills and so on.

Advantages accruing to groups as a result of these factors may not depend to any significant extent on any form of productive interaction beyond that required to let each contribute according to his or her strengths. In fact group performance might be optimised by marginalising the less able member(s) of the group and letting the more able member(s) complete the task. Whether learning outcomes at the level of the individual will be enhanced or damaged by this kind of group work is an open question. Benefit is possible, even for the child who has been reduced to the role of observer. Undoubtedly there are circumstances in which it is more instructive to observe a successful solution to a problem than to participate in an unsuccessful one. Equally clearly, there are circumstances in which less actively involved group members may simply ‘switch off’, or ‘free ride’ on the performance of their partners.

Such analyses make minimal assumptions about interactions between the partners working together at the computer, but of course such interactions will take place. They may embody conflicts of various kinds. A computer keyboard does not lend itself particularly well to being shared, and a ‘mouse’ even less so. There may well be conflicts about who does what. There may also be conflicts about the best approach to solving the problems presented by the task itself. The potentially productive role of conflicting perspectives on the task is highlighted in one particular tradition of research in this field, namely the neo-Piagetian approach. Though this work largely antedated the advent of computers, it is an approach that finds echoes in contemporary research involving productive interactions around computers, and has had considerable influence methodologically.

Piaget himself saw children's active construction of their own understanding as fundamental to their cognitive growth, and viewed peer interaction as a peculiarly potent source of progress (Piaget, 1932). According to Piaget, the young child cannot treat adults’ ideas on their own merits, because of the differences of status involved. Disagreements with other children serve much more effectively to highlight alternatives to the child's own point of view. The alternatives can be considered ‘on equal terms’, and since the resulting conflicts of opinion demand resolution, the children involved are effectively prompted towards higher-level solutions which incorporate the partial insights reflected in their varying initial positions.

This model of peer facilitation of children's understanding is linked to Piaget's particular account of the genesis of ‘operational thinking’ in the early school years. However, via the work of Doise and colleagues in Geneva in the 1970s and 80s, it has come to exert a rather wider influence. Doise and Mugny (1984) and Perret-Clermont (1980) set out to demonstrate that individual progress in understanding could be fostered by ‘sociocognitive conflict’; that is, exposure to the conflicting ideas of peers in the context of paired or small-group problem solving.

The typical design adopted in their studies involved individual pre-tests and post-tests, separated by a period of practice on the task undertaken either individually (the ‘control’ condition) or in pairs/groups (the ‘experimental’ condition). The key research question was thus not whether groups would do better on the task than individuals, but whether children who have had a chance to work on the task in groups will make greater individual progress than those who have not.

Where, as was often the case, greater individual gains were apparent in the experimental than in the control group, the explanation offered was couched in terms of sociocognitive conflict. The resolution of this conflict was conceived of in essentially individualistic terms. It might not even happen during the session itself, but perhaps later. Howe et al. (1992) offer evidence that progress made as a result of peer interaction may not be apparent in individual performance until perhaps several months later. Moreover, Doise demonstrated that the other child who supposedly held the conflicting point of view did not need to be physically present at all, as long as the conflicting views were introduced as being those of another child. Here again, then, a social process of sorts is involved, but the role of actual interaction is minimal.

The three-step (individual pre-test/group or individual treatment/individual post-test) design adopted by Doise and colleagues has been widely adopted in research on peer facilitation of computer-based learning, as we shall see in this volume. So too has the use of rather brief and circumscribed (not to say contrived) tasks. These features, especially when taken together with the rather self-contained nature of much computer-based interaction and the convenience of computer-based data collection, offer ideal conditions for experimental methods. The individualistic, cognitive level of analysis has thus come to be associated with the adoption of experimental methods of research in this field. This association is reflected in a variety of ways and degrees in several chapters of the present volume.

We have noted that an emphasis on the productive potential of conflict marks much of the research in this field (Howe and Tolmie, Chapter 3; Scanlon, Issroff and Murphy, Chapter 5). However, the emphasis in much of this research is not so much on the child's exposure to conflicting points of view, but rather on the socially mediated processes of conflict resolution. Concepts such as ‘argumentation’ and ‘negotiation’ move us toward a much more fundamentally social model of productive interaction, to which we turn in the next section.

Sociocognitive approaches: the joint construction of understanding

The approaches which we want to introduce in this section have in common a concern with the negotiation of meaning in collaborative problem solving. The focus is upon the ways in which the presence of partners influences the child's perception of the task and of the situation. More specifically, attention is given to the processes whereby learners can jointly construct an understanding of a task in such a way as to facilitate its solution.

To the hard-nosed cognitive psychologist, a task is a task is a task. It might involve solving the Towers of Hanoi, or a quadratic equation, or transposing a piece of music, but it can be defined essentially from the outside. Its meaning is determinate. To the social psychologist, life is typically more complex. Tasks, whether on the computer or off it, are usually susceptible of a variety of ‘readings’. Areas of indeterminacy might include whether we are supposed to be doing the task as fast as possible or as carefully as possible, whether we are going to look stupid if we get it wrong, whether it is a ‘fun game’ or ‘boring school stuff’, and so on. All of these meanings are potentially negotiable. The very fact of having a partner may make some of these readings of the task more or less likely (e.g. a task may be more likely to be construed as a test if each child works separately than if they work together). Moreover, the presence of a partner affords the opportunity to negotiate an agreed attitude to the task and the situation.

At another level, the solution of the task may in turn involve building some kind of mental representation of ‘what the problem is’. Developmental and educational psychologists influenced by Vygotsky have tended to focus upon the processes whereby the problem is interpreted and a strategy for solution is adopted. Vygotsky (1978) saw these processes as highly susceptible of social influence, though unlike Piaget he focused mainly upon interactions between partners who differed markedly in their levels of ability.

Using the concept of a ‘zone of proximal development’, Vygotsky offered a sketch of the ways in which a more experienced partner could extend at the margins the competences of a less experienced child. Newman et al. (1989) use the more attractive term ‘construction zone’ to refer to that area of potential development just beyond what the child can achieve unassisted.

This ‘social constructivist’ approach has been adapted by a number of contemporary researchers to encompass the situation of children of more or less the same level of ability working on a task collaboratively (e.g. Forman and McPhail, 1993, cited in Forman and Larreamendy-Joerns, 1995). Mercer and Wegerif(Chapter 6) offer an analysis largely in this vein, though they see it as going well beyond Vygotsky. Whereas Vygotsky saw social processes as constitutive of individual knowledge, Mercer and Wegerif argue that classroom knowledge needs to be construed as intrinsically social. In the present context, their emphasis is on talk, and its role in building ‘common knowledge’ amongst children sitting together at the computer. In contrast to studies in the neo-Piagetian tradition, the emphasis is upon the interaction per se, and the evidence it offers for group productivity, rather than simply on individual pre- and post-tests.

Videotaping, computer logs and transcripts have been the principal resources for this kind of analysis, and the challenge has been to find the analytic approaches which best illuminate ‘what it is that really matters’ in effective interactions. Thus, for example, Howe and Tolmie (Chapter 3) have explored a variety of aspects of discourse amongst students working on computer-supported collaborative science tasks in an essentially quantitative fashion, using coding schemes and correlations with learning gains as their principal investigative tools. By contrast, Mercer and Wegerif (Chapter 6) adopt a more qualitative approach, and are less directly concerned with individual learning outcomes. From analysis of primary school children's talk in the context of collaborative computer work they distinguish three different types of talk (‘disputational’, ‘cumulative’ and ‘exploratory’) and address the potentials for learning inherent in each of these.

The social constructivist approach has tended to be mainly concerned with the role of overt, observable processes of interpersonal interaction in shaping the child's response to cognitive tasks. The emphasis tends to fall very heavily on talk. This suffers the limitation tha...

Table of contents

• Front Cover
• Learning with Computers
• Title Page
• Copyright
• Contents
• List of illustrations
• Notes on contributors
• Acknowledgements
• 1 Introduction: getting IT together
• 2 Task effects on co-operative and collaborative learning with computers
• 3 Productive interaction in the context of computer-supported collaborative learning in science
• 4 Time-based analysis of students studying the Periodic Table
• 5 Collaborations in a primary classroom: mediating science activities through new technology
• 6 Is ‘exploratory talk’ productive talk?
• 7 Computers in the community of classrooms
• 8 Sociocognitive interactions in a computerised industrial task: are they productive for learning?
• 9 Learning as the use of tools: a sociocultural perspective on the human–technology link
• 10 Analysing asynchronous learning interactions: computer-mediated communication in a conventional undergraduate setting
• 11 Productivity through interaction: an overview
• Index