Mike Sharples
email: m.sharples@bham.ac.uk

Socio-cognitive Engineering

Socio-cognitive engineering is a framework for the human-centred design of technologybased systems to enhance human knowledge working, decision making, collaboration and learning. Like user-centred design, it draws on the knowledge of potential users and involves them in the design process. But it extends beyond individual users to analyse the activity systems of people and their interaction with technology, including their social interactions, styles and strategies of working, and language and patterns of communication, to form a composite picture of human knowledge and activity that can inform system design. The framework consists of two main parts: a phase of activity analysis to interpret how people work and interact with their current tools and technologies, and a phase of systems design to build and implement new interactive technology. Socio-cognitive engineering has been refined and tested through a series of projects to develop computer systems for supporting learning and knowledge working.

INTRODUCTION

Socio-cognitive engineering is a framework for the systematic design of socio-technical systems (people and their interaction with technology) based on study and analysis of how people think, learn, perceive, work and interact. The framework has been applied to the design of a broad range of human centred technologies, including a Writer's Assistant [START_REF] Sharples | Developing a Writer s Assistant[END_REF] a training system for neuroradiologists [START_REF] Sharples | Structured Computer-based Training and Decision Support in the Interpretation of Neuroradiological Images[END_REF], and a mobile learning device for children [START_REF] Sharples | The Design and Implementation of a Mobile Learning Resource[END_REF]. It has been adopted by the European MOBIlearn project (www.mobilearn.org) to develop mobile technology for learning. It has also been taught to undergraduate and postgraduate students, to guide their interactive systems projects. An overview of the framework can be found at [START_REF] Sharples | Socio-Cognitive Engineering: A Methodology for the Design of Human-Centred Technology[END_REF].

BACKGROUND

The approach of socio-cognitive engineering is similar to user-centred design [START_REF] Norman | User Centered System Design: New Perspectives on Human-Computer Interaction[END_REF]) in that it builds on studies of potential users of the technology and involves them in the design process. But users are not always reliable informants. They may idealize their methods, describing the ways in which they would like to or have been told to work, rather than their actual practices. Although users may be able to describe their own styles and strategies of working, they may not be aware of how other people can perform a task differently and possibly more effectively. Surveys of user preferences can result in new technology that is simply an accumulation of features, rather than an integrated system. Thus, socio-cognitive engineering is critical of the reliability of user reports. It extends beyond individual users to form a composite picture of the human knowledge and activity including cognitive processes and social interactions, styles and strategies of working, and language and patterns of communication. The term 'actor' rather is used rather than 'user', to indicate that the design may involve people who are stakeholders in the new technology but are not direct users of it.

The framework extends previous work in soft systems [START_REF] Checkland | Soft Systems Methodology in Action[END_REF]) sociotechnical and cooperative design (Greenbaum & Kyng, 1991;[START_REF] Mumford | Effective Systems Design and Requirements Analysis: The ETHICS Approach[END_REF][START_REF] Sachs | Transforming work: collaboration, learning and design[END_REF] and the application of ethnography to system design (see [START_REF] Rogers | Grounding blue-sky research: How can ethnography help? Interactions[END_REF] for a review). It incorporates existing methods of knowledge engineering, task analysis and objectoriented design, but integrates them into a coherent methodology that places equal emphasis on software, task, knowledge and organizational engineering.

The framework also clearly distinguishes studying everyday activity using existing technology from studying how the activity changes with proposed technology. It emphasises the dialectic between people and artefacts: using artefacts changes people's activities, and this in turn leads to new needs and opportunities for design.

FRAMEWORK

Figure 1 gives a picture of the flow and main products of the design process. It is in two main parts: a phase of activity analysis to interpret how people work and interact with their current tools and technologies, and a phase of systems design to build and implement new interactive technology. The bridge between the two is the relationship between the Task Model and the Design Concept. Each phase comprises stages of analysis and design, which are implemented through specific methods. The framework does not prescribe which methods to use: the choice depends on the type and scale of project.

It is important to note that the process is not a simple sequence, but involves a dialogue between the stages. Earlier decisions and outcomes may need to be revised to take account of later findings. When the system is deployed it will enable and support new activities, requiring another cycle of analysis, revision of the Task Model and further opportunities for design.

The elements of socio-cognitive engineering are shown below.

Project. The diagram shows the process of design, implementation and deployment for a single project.

Actors. Different types of people may be involved in or affected by the design and deployment, including (depending on the scale of the project) design, marketing and technical support teams, direct users of the system, and other people affected by it (such as administrative staff).

Roles. The actors take on roles (such as 'team leader'), that may change during the project.

Stage. Each box represents one stage of the project.

Methods. Each stage can be carried out by one or more methods of analysis and design, which need to be specified before starting the stage.

Tools. Each method has associated tools (for activity analysis, software specification, systems design, and evaluation) to carry out the method.

Outcomes. Each stage has outcomes which must be documented, and these are used to inform and validate the system design.

Measures. Each design decision must be validated, by reference to outcomes from one of the stages.

The general sequence for socio-cognitive engineering is as follows:

1. Form a project team. 2. Produce general requirements for the project.

3. Decide which methods and tools will be used for each stage of the project. 4. Decide how the process and outcomes will be documented. 5. Decide how the project will be evaluated. 6. Carry out each stage of the project, ensuring that the requirements match the design. 7. Carry out a continuous process of documentation and evaluation.

The process starts by specifying the General Requirements for the system to be designed. These provide broad yet precise initial requirements and constraints for the proposed system, in language that designers and customers can understand. They are used to guide the design and to provide a reference for validation of the system. The requirements should normally indicate:

the scope of the project; -the main actors involved in designing, deploying, using, maintaining the system; -the market need and business case; -general attributes and constraints of the proposed system (such as whether it aims to support individual or collaborative working).

The requirements will be extended and made more precise as the project progresses.

This leads to two parallel studies: a theory-based study of the underlying cognitive processes and social activities, and an investigation into how everyday activities are performed in their normal contexts. The Theory of Use involves an analysis of relevant literature from cognitive psychology, social sciences and business management, to form a rich picture of the human knowledge and activity. It is essential that this should offer a clear guide to system design. Thus, it must be relevant to the intended use of the system and extend the requirements in a form that can be interpreted by software designers and engineers.

The aim of carrying out Field Studies is to uncover how people interact with current technology in their normal contexts. The role of the fieldworker is both to interpret activity and to assist technology design and organizational change. This addresses the widely recognized problem of ethnographic approaches that, while they can provide an understanding of current work practices, they are not intended to explore the consequences of socio-technical change.

Table 1 shows a multi-level structure for field studies, with level 1 consisting of a survey of the existing organizational structures and schedules, levels 2 and 3 providing an analysis of situated practices and interactions of those for whom the technology is intended, and level 4 offering a synthesis of the findings in terms of designs for new socio-technical systems. The four levels give an overview of activity, leading to more detailed investigation of particular problem areas, with each level illuminating the situated practices, and also providing a set of issues to be addressed for the next level. These piece together into a composite picture of how people interact with technology in their everyday lives, the limitations of existing practices, and ways in which they could be improved by new technology.

Level 1

Activity structures and schedules

Activity: Study work plans, organizational structures, syllabuses, resources.

Purpose:

To discover how the activities are supposed to be conducted.

Outcome: Description of the existing organizational and workplace structures; identification of significant events.

Level 2 Significant events

Activity:

Observe representative formal and informal meetings and forms of communication.

Purpose:

To discover how activities, communication, and social interaction are conducted in practice.

Outcome:

A description and analysis of events that might be important to system design; identification of mismatches between how activity has been scheduled and how it is has been observed to happen.

Level 3 Conceptions and conflicts

Activity: Conduct interviews with participants to discuss areas of activity needing support, breakdowns, issues, differences in conception.

Purpose:

To determine people's differing conceptions of their activity; uncover issues of concern in relation to new technology; explore mismatches between what is perceived to happen and what has been observed.

Outcome:

Issues in everyday life and interactions with existing technology that could be addressed by new technology and working practices.

Level 4 Determining designs

Activity: Elicitation of requirements; design space mapping; formative evaluation of prototypes.

Purpose: To develop new system designs.

Outcome: Prototype technologies and recommendations for deployment.

Table 1. Multi-level structure for field studies

The outcomes of these two studies are synthesized into a Task Model. This is a synthesis of theory and practice related to how people perform relevant activities with their existing technologies. It is the least intuitive aspect of socio-cognitive engineering, and it is tempting to reduce it to a set of bullet-point issues, yet it provides a foundation for the systems design.

It could indicate:

the main actors and their activity systems; -how the actors employ tools and resources to mediate their interaction and to externalise cognition;

how the actors represent knowledge to themselves and others; -the methods and techniques that the actors employ, including differences in approach and strategy;

the contexts in which the activities occur; -the implicit conventions and constraints that influence the activity; -the actors' conceptions of their work, including sources of difficulty and breakdown in activity and their attitudes towards the introduction of new technology. indicate how limitations from the Task Model will be addressed by new technology.

outline a system image [START_REF] Norman | Cognitive Engineering[END_REF] for the new technology; -show the look and feel of the proposed technology; -indicate the contexts of use of the enhanced activity and technology; -propose any further requirements that have been produced as a result of constructing the design concept. The Design Concept should result in a set of detailed design requirements and options that can be explored through the design space.

The relationship between the Task Model and Design Concept provides the bridge to a cycle of iterative design that includes:

generating a space of possible system designs, systematically exploring design option and justifying design decisions;

specifying the functional and non-functional aspects of the system; -implementing the system; -deploying and maintaining the system. Although these stages are based on a conventional process of interactive systems design (see [START_REF] Preece | Interaction Design: Beyond Human-Computer Interaction[END_REF] for an overview), they give equal emphasis to cognitive and organizational factors as well as task and software specifications. The stages shown in Figure 1 are an aid to project planning, but are not sufficiently detailed to show all the design activities. Nor does the Figure make clear that to construct a successful integrated system requires the designers to integrate software engineering with design for human cognition, social interaction and organisational management. The 'building block' diagram in Table 2 gives a more detailed picture of the systems design process.

The four 'pillars' indicate the main processes of software, task, knowledge and organizational engineering. Each 'brick' in the diagram shows one outcome of a design stage, but it is not necessary to build systematically from the bottom up. A design team may work on one 'pillar', as knowledge engineering, up to the stage of system requirements, or they may develop an early prototype based on a detailed task analysis but without a systematic approach to software engineering. How each activity is carried out depends on the particular application domain, actors and contexts of use.

The design activities are modular, allowing the designer to select one or more methods of conducting the activity, according to the problem and domain. For example, the usability evaluation could include an appropriate selection of general methods for assessing usability, or it could include an evaluation designed for the particular domain.

It should be emphasized is that the blocks are not fixed entities. As each level of the system is developed and deployed is will affect the levels below, (for example, building a prototype system may lead to revising the documentation or re-evaluating the human-computer interaction; deploying the system will create new activities). These changes need to be analysed and supported through a combination of new technology and new work practices. Thus, the building blocks must be revisited both individually to analyse and update the technology in use, and through a larger process of iterative re-design.

Although the Table 1 shows system evaluation as a distinct phase, there will also be a continual process of testing, to verify and validate the design, as shown on Figure 1. Testing is an integral part of the entire design process, and it is important to see it as a lifecycle process [START_REF] Meek | A Lifecycle Approach to the Evaluation of Learning Technology[END_REF], with the results of from testing of early designs and prototypes being passed forwards to provide an understanding of how to deploy and implement the system, and the outcomes of user trials being fed back to assist in fixing bugs and improving the design choices.

The result of the socio-cognitive engineering process is a new socio-technical system, consisting of new technology and its associated documentation and proposed methods of use. When this is deployed, in the workplace, home, or other location it should not only produce bugs and limitations that need to be addressed, but also engender new patterns of work and social and organizational structures which become contexts for further analysis and design.

FUTURE TRENDS

The computer and communications industries are starting to recognise the importance of adopting a human-centred approach to the design of new socio-technical systems. They are merging their existing engineering, business, industrial design and marketing methods into an integrated process, underpinned by rigorous techniques to capture requirements, define goals, predict costs, plan activities, specify designs and evaluate outcomes. IBM, for example, has developed the method of User Engineering to design for the "total user experience". (IBM, 2004). As web-based technology becomes embedded into everyday life, then it is will be increasingly important to understand and design distributed systems for which there are no clear boundaries between people and technology.

CONCLUSION

Socio-cognitive engineering forms part of an historic progression from user-centred design and soft systems analysis towards a comprehensive and rigorous process of socio-technical systems design and evaluation. It has been applied through a broad range of projects for innovative human technology and is still being developed, most recently as part of the European MOBIlearn project.

Figure 1 .

 1 Figure 1. Overview of the flow and main products of the design process.

The

  Design Concept needs to be developed in relation to the Task Model. It should indicate how the activities identified by the Task Model could be transformed or enhanced with the new technology. It should:

Table 2

 2

		Software	Task	Knowledge	Organizational
		Engineering	Engineering	Engineering	Engineering
	Maintain	Installed system	New task	Augmented	New
			structure	knowledge	organizational
					structure
	Evaluate	Debugging	Usability	Conceptual	Organizational
				change, skill	change
				development
	Integrate		Prototype System
	Implement	Prototypes,	Interfaces,	Knowledge	Communications,
		Documentation	Cognitive tools	representation	Network
					resources
	Design	Algorithms and	Human-computer	Domain map,	Socio-technical
		heuristics	interaction	user model	system
	Interpret		Task Model
	Analyze	Requirements	Tasks: goals,	Knowledge:	Workplace:
			objects, methods	concepts, skills	practices,
					interactions
	Survey	Existing systems Conventional task	Domain	Organizational
			structures and	knowledge	structures and
			processes		schedules
	Propose		General Requirements

. A 'building block' framework for socio-cognitive system design.

TERMS AND DEFINITIONS

Activity system. The assembly and interaction of people and artefacts, considered as a holistic system that performs purposeful activities. See http://www.edu.helsinki.fi/activity/pages/chatanddwr/activitysystem/ Human-centred design. The process of designing socio-technical systems (people in interaction with technology) based on analysis of how people think, learn, perceive, work and interact. Socio-technical system. A system comprising people and their interactions with technology, for example the worldwide web.

Soft systems methodology. An approach developed by Peter Checkland to analyse complex problem situations containing social, organisational and political activities.

System image. A term coined by Don Norman [START_REF] Norman | Cognitive Engineering[END_REF] to describe the guiding metaphor or model of the system that a designer presents to users (e.g. the 'desktop metaphor', or the telephone as a 'speaking tube'). The designer should aim to create a system image that is consistent, familiar, where possible, enables the user to make productive analogies.

Task analysis. An analysis of the actions and/or knowledge and thinking that a user performs to achieve a task. See http://www.usabilitynet.org/tools/taskanalysis.htm User-centred design. A well-established process of designing technology that meets users' expectations, or that involves potential users in the design process.

User Engineering. A phrase used by IBM to describe an integrated process of developing products that "satisfy and delight users".


Ingo Kollar
email: i.kollar@iwm-kmrc.de

Frank Fischer

How Internal and External Scripts Guide Argumentative Knowledge Construction in a Web-based Collaborative Inquiry Learning Environment

How internal and external scripts guide argumentative knowledge construction in a web-based collaborative inquiry learning environment

Ingo Kollar, Frank Fischer

Introduction

Over the last years, educational psychology has devoted strong efforts to develop web-based collaborative inquiry learning environments, in which learners can explore scientific phenomena, gather and present data, set up hypotheses etc. (e.g., [START_REF] Schwartz | Towards the development of flexibly adaptive instructional design[END_REF]. [START_REF] Quintana | A scaffolding design framework for software to support science inquiry[END_REF] define "inquiry as the process of posing questions and investigating them with empirical data, either through direct manipulation of variables via experiments or constructing comparisons using existing datasets" (p. 340). Examples for web-based collaborative inquiry learning environments are WISE [START_REF] Slotta | How do students make sense of Internet resources in the science classroom[END_REF], CoLAB (Savelsbergh, van Joolingen, Sins, de Jong & Lazonder, 2004), and BGuILE [START_REF] Reiser | BGuiLE: Strategic and conceptual scaffolds for scientific inquiry in biology classrooms[END_REF]. These environments include a variety of scaffolds, which are supposed to chanel and to focus the learners' attention to relevant concepts and mechanisms of the problem at hand [START_REF] Pea | The social and technological dimensions of scaffolding and related theoretical concepts for learning, education, and human activity[END_REF], thereby stimulating substantial elaborations about the contents of the learning material. For example, in CoLAB, learners can manipulate the amount of water in a tank by changing number values and then run a simulation representing the pressure in the tank and the amount of water flowing out of it when opening a ventile.

However, many of these environments seem to assume that learners generally are able to engage successfully in collaborative learning activities. As a consequence, designers of these environments often do not undertake much effort to structure collaboration and argumentation between the learning partners, even though it is clear that collaborative argumentation is a core activity in collaborative inquiry learning. For example, quite often learners are simply asked to "discuss" at a particular point in a curriculum unit, without getting instructional support concerning how to engage in a fruitful discussion. This is especially regrettable since many studies have demonstrated that students often experience difficulties when supposed to engage in argumentation [START_REF] Kuhn | Effects of dyadic interaction on argumentive reasoning[END_REF][START_REF] Brem | Explanation and evidence in informal argument[END_REF]. In order to address this problem, in theory and research on computer-supported collaborative learning (CSCL) as well as in instructional psychology, collaboration scripts are considered a powerful means to improve processes and outcomes of collaborative learning [START_REF] Pfister | Supporting discourse in a synchronous learning environment: The learning protocol approach[END_REF][START_REF] Rummel | Instructional support for computer-mediated collaboration -results from process analyses[END_REF][START_REF] Kollar | Cooperation Scripts for Computer-Supported Collaborative Learning[END_REF].

For example, Weinberger, Reiserer, Ertl, Fischer and Mandl (in press) demonstrated that collaboration scripts embedded in different net-based learning environments were able to improve the learners' recall rates of learned information as well as their ability to apply theory-based knowledge to transfer problems. One main advantage of collaboration scripts is that they can be tailored to support a variety of activities like problem solving, learning from text or learning concrete procedures (see [START_REF] O'donnell | Structuring dyadic interaction through scripted cooperation[END_REF], for an overview). It is plausible then that collaboration scripts could also be designed to provide instructional support for collaborative argumentative knowledge construction. It is hoped that by implementing a collaboration script that specifies learners' collaborative argumentative processes will engage them in specific patterns of argumentative knowledge construction so that they will acquire domain-general knowledge on how to engage in argumentation, which in turn should enable them to elaborate the domain-specific content knowledge of the specific learning unit more deeply, thereby also acquiring more domain-specific knowledge concerning the content of the learning material (e.g., mechanisms that underlie scientific phenomena).

However, it has hardly been subject to research how the provision of externally induced collaboration scripts interact with the learners' personal scripts with respect to how to accomplish the task at hand. It is reasonable to argue that learners bring different internal scripts [START_REF] Schank | Scripts, plans, goals and understanding[END_REF] that guide them in their behaviour to a particular situation and that these scripts interact with the external instructional support that is given. In this paper, we therefore aim to investigate the interaction between external and internal scripts with respect to different dimensions of individual knowledge acquisition in a web-based collaborative inquiry learning environment.

What is argumentative knowledge construction?

Argumentative knowledge construction can be considered as a core activity learners have to engage in during collaborating in a web-based collaborative inquiry learning environment.

For example, learners are required to engage in argumentation when setting up hypotheses, when making sense of evidence they have explored etc. Yet, there is a lack of an agreed upon definition of what argumentation actually is, accompanied by the fact that research on argumentation and argumentative knowledge construction appears to be scattered (see [START_REF] Stein | The origins and nature of arguments: Studies in conflict understanding, emotion, and negotiation[END_REF]. At least two different approaches to argumentative knowledge construction can be found. On the one hand, there is a structural perspective, which seeks to assess the quality of single arguments on the basis of the structural components they include [START_REF] Toulmin | The Uses of Argument[END_REF].

On the other hand, there is a dynamic perspective on argumentation, dealing with how argumentation develops in discourse. Each of the two perspectives are presented in the following sections.

Structural perspective on argumentative knowledge construction

Coming from a philosophical background, [START_REF] Toulmin | The Uses of Argument[END_REF] developed a structural scheme that can be used to judge the completeness of arguments being uttered both in oral or in written discourse. Although often being criticized for being to theoretical, the model had a strong influence on psychological and linguistic research on argumentation (e.g., [START_REF] Cobb | Reasoning with tools and inscriptions[END_REF][START_REF] Stein | The origins and nature of arguments: Studies in conflict understanding, emotion, and negotiation[END_REF][START_REF] Mcneill | Supporting students' construction of scientific explanations using scaffolded curriculum materials and assessments[END_REF]. According to this model, an argument consists of up to six components. Firstly, arguments are based on data representing evidence on which the argument relies on. Such data can be a single observation or multiple observations of regularities (e.g., a steel chair heats up faster than a wood chair) as well as references to authorities (e.g., newspaper articles or researchers). Secondly, arguments usually include a claim by which the speaker expresses his position. Thirdly, arguments can contain a warrant that specifies the relationship between data and claim. For example, such a warrant might be "because a black shirt absorbs more light energy" for the claim "a black shirt feels warmer on your skin than a white shirt when sun is shining on it". Fourthly, in order to highlight the validity of a warrant, arguments can contain a backing. For example, a backing can point to Newton's Second Law to support the warrant that a ball can hit a target because it was thrown with a certain force. Fifthly, arguments can contain a qualifier that sets constraints to the validity of the claim. Quite often, such a qualifier consists of a single word like "maybe" or "assumably". Finally, an argument can contain a rebuttal, by which conditions are specified under that the claim is not valid. For example, a speaker could a sentence like "as long as there is no traffic jam" into his or her argument saying that he or she will be downtown at 6 pm when leaving home at 5 pm.

In a number of studies, Toulmin's argument scheme has been used either to assess written or oral discourse between learners (e.g., [START_REF] Cobb | Reasoning with tools and inscriptions[END_REF][START_REF] Bell | Scientific arguments as learning artifacts: Designing for learning from the web with KIE[END_REF] or as a means to teach learners how to argue effectively (e.g., [START_REF] Carr | Using computer supported argument visualization to teach leagal argumentation[END_REF][START_REF] Mcneill | Supporting students' construction of scientific explanations using scaffolded curriculum materials and assessments[END_REF]. It is generally assumed that giving more complete arguments should lead to a deeper elaboration of learning materials and finally to better learning than giving incomplete arguments. In the study by [START_REF] Mcneill | Supporting students' construction of scientific explanations using scaffolded curriculum materials and assessments[END_REF], it was shown that learners were in deed able to learn and apply Toulmin's argument scheme from a scaffold resulting in giving stronger explanations after the scaffold was removed.

Applying this scheme in oral discussions is not always easy, as is analysis of written or oral discourse by aid of the scheme as well. [START_REF] Stein | The origins and nature of arguments: Studies in conflict understanding, emotion, and negotiation[END_REF] for example state that even experts may experience difficulties in identifying a warrant in an argument because warrants often remain implicit when a speaker assumes that the discourse partner has access to the information that would be uttered in the warrant. Furthermore, it often appears to be difficult to clearly define the difference between warrants and backings as well as between qualifiers and rebuttals. In line with previous research [START_REF] Mcneill | Supporting students' construction of scientific explanations using scaffolded curriculum materials and assessments[END_REF][START_REF] Marttunen | Learning of argumentations skills in networked and face-to-face environments[END_REF], we claim it might be reduce the complexity of Toulmin's model. Therefore, we focus on three essential components of arguments, namely data, claims, and reasons (which comprise both warrants and backings).

Dynamic perspective on argumentative knowledge construction

Toulmin's model was often criticized because it neglects the aspect of how an argumentation between two or more persons develops over time. Rather, the model focuses on single arguments, analyzing them in terms of their completeness. In order to account for the function of an argument in its context, [START_REF] Leitão | The potential of argument in knowledge building[END_REF] proposed a model that includes three basic types of arguments: (a) arguments, (b) counterarguments and (c) replies. In her view, an argument represents an assertion that is preceded or followed by a justification. A counterargument can then be of one of three kinds: The first possibility is that it represents a shift in the topic, so that the argument in its original form remains intact. For example, speaker A might utter an argument like "Car traffic intensifies global warming because statistics say as traffic increases, more emissions are produced harming the ozone layer", and speaker B might response by saying "Emissions of aeroplanes also intensify global warming", thereby shifting attention to another aspect and leaving the validity of the argument untouched. A second possible form of a counterargument is to doubt the validity of the argument, for example by explicitly challenging the claim that was taken in it (e.g., "This is not true because I read it is exactly the other way around"). Finally, a counterargument might also be formulated questioning the relation between the components of the argument. For example, an interlocutor might assert that the evidence his or her partner was citing did not support the claim he or she was making.

Next, according to [START_REF] Leitão | The potential of argument in knowledge building[END_REF], replies on counterarguments can also take on several forms: Firstly, they can represent a dismissal of the counterargument, when the speaker experiences himself as able to reject the claim that was made in the counterargument because it was not true. Secondly, a reply can represent a local agreement in a sense that it agrees with parts of the counterargument but not as strongly that it would fundamentally change the interlocutor's position. Thirdly, speaker A might offer an integrative reply, which connects parts of both the original argument and the counterargument. This sort of reply might be considered as most strongly influencing collaborative knowledge construction since it is collaboratively created by the two interlocutors. Finally, as a fourth form a reply can take on, speaker A might simply abolish his or her original argument. [START_REF] Leitão | The potential of argument in knowledge building[END_REF] then claims that argumentative sequences of the structure "argumentcounterargument -(integrative) reply" might be most fruitful for collaborative knowledge construction, since they require both learners to deeply elaborate content information. This deeper elaboration of content information then should in turn lead to higher content specific knowledge acquisition on an individual level (e.g., [START_REF] Chi | Selfexplanations: How students study and use examples in learning to solve problems[END_REF]. Moreover, by engaging in meaningful sequences of argumentation, learners might internalize these processes and apply them even when they are not explicitly asked to do so, thereby also acquiring domain-general knowledge about argumentation itself.

In most previous research, these two accounts to argumentative knowledge construction have been treated separately -studies often focused either on the structural (e.g., [START_REF] Means | Who reasons well? Two studies of informal reasoning among children of different grade, ability, and knowledge levels[END_REF] or on the dynamic perspective of argumentative knowledge construction (e.g., [START_REF] Resnick | Reasoning in conversation[END_REF]. Few studies have considered both perspectives, a research gap that is accounted for in this study.

Scripts for collaborative argumentative knowledge construction in web-based inquiry learning

External Scripts

As mentioned above, one promising way to facilitate students' argumentative knowledge construction is to provide learners with collaboration scripts [START_REF] O'donnell | Scripted Cooperation in student dyads: A method for analyzing and enhancing academic learning and performance[END_REF].

Collaboration scripts are complex instructional entities specifying the processes of collaboration by making use of a whole variety of instructional representations like prompts (e.g., [START_REF] King | Transactive peer tutoring: Distributing cognition and metacognition[END_REF], graphical representations of interaction patterns [START_REF] Stegmann | Scripting argumentative knowledge construction in computer-supported learning environments[END_REF] or special programming of communication interfaces in computersupported collaborative learning environments (e.g., [START_REF] Baker | Promoting reflective interactions in a CSCL environment[END_REF]. Such collaboration scripts typically induce specific activities to be carried out by the (two or more) learning partners, prescribe a specific sequence according to which these activities are supposed to be carried out, and distribute roles among the learning partners (see [START_REF] Kollar | Cooperation Scripts for Computer-Supported Collaborative Learning[END_REF]. What activities are induced by a collaboration script depends on what the actual outcome of collaboration is supposed to be. Of course, a collaboration script should be designed in a way that guarantees a match between the induced activities and the desired learning outcomes. It is clear that the constraints that are inherent in the script instructions should have the function to enable the learners to reach these objectives. Yet, too severe constraints or too strict "chaneling" [START_REF] Pea | The social and technological dimensions of scaffolding and related theoretical concepts for learning, education, and human activity[END_REF] might restrain learners to engage in activities that also might be beneficial with respect to the intended learning outcomes. In a study by [START_REF] Weinberger | Knowledge convergence in computermediated learning environments: Effects of collaboration scripts[END_REF], for example, it could be demonstrated that an epistemic collaboration script, which provided learners with content-specific prompts with respect to the learning material, had positive effects on conceptual learning but simultaneously inhibited transactivity [START_REF] Teasley | Talking about reasoning: How important is the peer in peer collaboration[END_REF] as a (non-intended) negative side-effect. In contrast, a social script that specified that learners should consider the contribution of their learning partners, had positive effects on transactivity but negative effects on conceptual learning. Against the background that collaboration scripts can include very different components with very specific effects, it therefore seems adequate to assess different kinds of learning outcomes in order to get a clearer profile of what particular aspects are influenced by the instructions of an externally induced collaboration script.

Internal Scripts

Despite the rather positive effects of collaboration scripts that have been demonstrated in the literature, it does not seem plausible that externally provided script instructions are the only factor that guides collaborative learning processes. Rather, learners can be viewed as possessing knowledge and strategies about how to proceed in a collaborative learning situation on their own. In cognitive psychology, [START_REF] Schank | Scripts, plans, goals and understanding[END_REF] refer to scripts as a form of culturally shared knowledge about everyday events. For example, most people will hold a "restaurant script" telling them that when they go for dinner, they will sit on a table, wait for the waiter to bring the menu, choose one meal, waiting for the meal being brought to the table, eating the meal, etc. However, in contrast to this culturally highly shared "restaurant script", [START_REF] Schank | Scripts, plans, goals and understanding[END_REF] also speak of "personal scripts" which might not be shared to the same degree but rather be more unique to the individual. For example, it is likely that different individuals will have quite different personal scripts concerning how to write an essay about a political topic. Likewise, we view "argumentation" as one example of an event that does have everyday significance, but about which individuals may hold different scripts that guide their actual behaviour in argumentative discourse. Yet again, differences in the learners' personal scripts might also lead to different profiles of what individuals learn during collaborative argumentative knowledge construction. For example, an individual with a highly developed personal script on argumentative knowledge construction might be more able to elaborate the learning material more deeply, thereby acquiring more domain-specific content knowledge than an individual with less strategic knowledge about how to engage in argumentative knowledge construction. In order to differentiate these personal scripts from the externally induced collaboration scripts we were talking before, we will call these internal knowledge structures internal scripts.

As a consequence, in this paper we focus on both internal (cognitive) and external (instructional) scripts, thereby investigating their each specific effects as well as the effects of their interrelation concerning the acquisition of argumentation-specific knowledge (as an instance of domain-general knowledge) and of different types of domain-specific content knowledge during collaborative learning in a web-based collaborative inquiry learning environment.

Goals of the Study

The main objective of this study is to analyze different cognitive outcomes of students' argumentative knowledge construction during learning in a web-based inquiry learning environment. In order to investigate the relationship between external and internal scripts in facilitating collaborative argumentative knowledge construction, we developed two versions of an external collaboration script (low vs. high structured) and implemented them into a curriculum project of the computer-based collaborative inquiry learning environment WISE.

It was then our aim to investigate how these externally provided collaboration scripts and the learners' internal collaboration scripts interact with respect to both the acquisition of domaingeneral knowledge about argumentation as well as different forms of domain-specific content knowledge in inquiry learning environments. As there is not enough evidence available from prior research, we set up two competing hypotheses, (a) an interactive effects hypothesis and (b) an additive effects hypothesis.

Interactive effects hypothesis: A highly structured externally provided collaboration script will especially facilitate the acquisition of content-specific and argumentation-specific knowledge of learners holding low structured internal scripts, whereas a low structured external script will lead learners holding high structured internal scripts to acquire more domain-general and domain-specific knowledge. This is either because the high structured external script will compensate the deficits low structured internal scripts obtain or because it unnecessarily puts constraints to the learning processes of learners holding high structured internal scripts.

Additive effects hypothesis: A highly structured externally provided collaboration script will support the acquisition of domain-general and domain-specific knowledge of all learners, independently from the nature of their internal collaboration scripts, because even the contents of a high structured internal script will play out only when additional instructional support is provided.

Method

Participants 98 students from grades 8 to 10 from five classes of two German Gymnasiums participated in the study. 46 participants were boys, and 52 participants were girls.

Design

An experimental 2x2-factorial design was established with the internal collaboration script (high vs. low structured) and the external collaboration script (high vs. low structured) as independent variables. Dyads were homogeneous with respect to the learners' internal scripts and gender and were randomly assigned to one of the two external script-conditions.

Reliability of the used scale was sufficient. The design of the study is presented in table 1.

Procedure

The study was conducted in two sessions. In the first session, which took part about two weeks before the actual collaboration phase, learners had to complete several questionnaires on demographic variables, prior domain-specific content knowledge, and collaboration as well as computer experiences. Most importantly, in this first session learners were asked to answer the test assessing their internal scripts. Learners were identified as holding a high or a low structured internal script by assessing their performance in a test, in which they were asked to evaluate a fictitious discourse between two students about a science topic. This discourse included "good" and "bad" arguments and argumentative sequences in the sense of the models proposed by [START_REF] Toulmin | The Uses of Argument[END_REF] and [START_REF] Leitão | The potential of argument in knowledge building[END_REF]. I.e., some utterances contained complete arguments, whereas others did not, and sometimes, argumentative sequences had the "argument -counterargument -integrative argument"-structure proposed by [START_REF] Leitão | The potential of argument in knowledge building[END_REF], whereas in other cases, they had not. The students' task then was to individually identify these "good" and "bad" arguments or argumentative sequences and specify why they were good or bad. On the basis of their answers, students received a test score ranging from 0 to 20. The median score of 3 was used as the criterion according to which learners were classified as holding either a low or a high structured internal script resulting in 48 learners classified as holding a low structured and 50 learners as holding a high structured internal script

For the actual collaboration phase two weeks later, homogenous dyads were established with respect to the degree of structuredness of the learners' individual scripts and gender, i.e.

that there were only dyads consisting of two girls or two boys both holding either a low or a high structured internal script. Each dyad then collaborated on the WISE-project "The Deformed Frogs Mystery", which is described below. Two versions of the "Deformed Frogs"

project were realized, one containing the low structured and the other the high structured external collaboration script (see below). Dyads were randomly assigned to one of these two conditions. Time for collaboration was 120 minutes.

Immediately after collaboration, learners had to complete several questionnaires to assess the domain-specific content knowledge and domain-specific knowledge on argumentation that was acquired during collaboration (see below). Completing these questionnaires required about 40 minutes.

Setting and learning environment

Dyads worked on a German version of the WISE project "The Deformed Frogs Mystery" (see figure 1). In this project, learners were introduced to the phenomenon that many frogs with massive deformities on legs and eyes had been found in the late 90's. However, among biologists it is not yet clear what the underlying mechanism for these deformities is.

Therefore, the project provides learners with two competing hypotheses. The Parasite Hypothesis states that a small parasite called "trematode" burrows into the tadpole near where the legs will develop, and the Environmental-Chemical Hypothesis implies that a hormonelike substance in the water of the dumps frogs live in causes legs and eyes to develop strangely. In order to discuss the pro's and con's of these two hypotheses, the web-based learning environment contains different kinds of background information, e.g. journal articles, maps about the distribution of the deformities, or photographs of the deformed frogs.

Discussion should then focus on evaluating the two hypotheses on the basis of this background information. The curriculum project was segmented into five content-specific units, e.g. "What's the problem?", "Where are the deformed frogs?", or "What's in the water?". The two learning partners of each dyad worked together in front of one computer screen and could talk face-to-face. There were always between three and five dyads located in the same room, but they were separated from each other to achieve rather controlled experimental conditions. A teacher was not present.

External collaboration script

The two versions of the external collaboration script were implemented in the "Deformed

Frogs" project. At the end of each content-specific curriculum unit, all learners were asked to discuss the two hypotheses on the basis of the information they had just viewed and to type their arguments. However, the two conditions differed in the way how this typing and discussion phase was structured. In the low structured version of the external script, learning partners did not get further support beyond being asked to discuss the two hypotheses on the basis of the information of the particular unit.

In the high structured (see figure 2) version of the external script, however, learners received additional guidance in how to discuss the two hypotheses, based on the models of [START_REF] Toulmin | The Uses of Argument[END_REF] and [START_REF] Leitão | The potential of argument in knowledge building[END_REF]. The first time learners had to discuss the two hypotheses, learning partner A was assigned to defend the parasite hypothesis. In order to do that, he or she was asked to give an argument containing of data, a claim and a reason. To achieve that, the learner was supposed to type each component (data, claim, reason) in a separate text field including adequate cues (e.g., "It was found that…" for data). Next, his or her learning partner was asked to type a counterargument into the respective text boxes, again containing the three argument components and the respective cues. Finally, both learners were asked to formulate an integrative argument, which again had to consist of data, a claim, and a reason. After that, for the environmental-chemical hypothesis, roles were switched. During the course of collaboration, which learner had to advocate which hypothesis was varied. Moreover, script instructions were continuosly faded out to avoid the problem of "over-scripting" [START_REF] Dillenbourg | Over-scripting CSCL: The risks of blending collaborative learning with instructional design[END_REF]. For example, at the end of the second unit, the high structured external script did not contain any sentence starters anymore, and the textboxes were reduced to one for each argument, i.e. the interface did not force the learners anymore to split their arguments into data, claim, and reason. Anyway, learners still were reminded of those three components. [START_REF] Pea | The social and technological dimensions of scaffolding and related theoretical concepts for learning, education, and human activity[END_REF] strongly suggests that scaffolds should be faded out as learners internalize more and more of the target activities. A recent study by [START_REF] Mcneill | Supporting students' construction of scientific explanations using scaffolded curriculum materials and assessments[END_REF] has demonstrated that fading might even contribute to higher learning gains than leaving instructions unfaded over time.

Instruments and dependent measures

Dependent measures were the individual students' performance in subsequent knowledge tests. One knowledge test aimed to assess the learners' domain-general knowledge on argumentation, and the other one was designed to measure different dimensions of domainspecific content knowledge.

Domain-general knowledge test about argumentation

In this test, learners were supposed to name the three components of a complete argument as well as the three components of an argumentative sequence. Moreover, they were asked to give examples for a complete argument and a complete argumentative sequence concerning the topic "smoking cigarettes". Learners received points for each correctly named component of a single argument and an argumentative sequence as well as for each of these components that was included in their examples. That way, 12 points could be reached in this test.

Reliability of this scale was .72 (Cronbach's Alpha).

Domain-specific content knowledge test

The domain-specific knowledge test contained five open-ended questions. In the first four questions, learners were asked to reproduce the mechanisms that according to the contents of the learning environment might cause the frog deformities (parasite and environmentalchemical). Learners received one point for a partial correct reproduction of a mechanisms (e.g., "The parasite burrows into the tadpole"), two points for a completely correct explanation of a mechanism, and additionally one point for citing relevant data and one more point for making meaningful connections between data and mechanisms, i.e. specifying why a particular set of data counted as evidence for or against one of the mechanisms. The resulting subscale was termed knowledge about mechanisms. After reliability check, one item was deleted yielding a 5-items-scale. Overall, six points could be achieved on this measure. In the fifth question of the domain-specific knowledge test, learners were asked to reason about what could be done to definitely find out the reason for why the frogs are deformed. Learners received credits according to the following scheme: one point was given for uttering that experiments should be conducted, one point for mentioning specific variables that should be examined, one point for mentioning that variables should be systematically varied, and one point for proposing to evaluate the effects of a variation of variables. The resulting scale was termed knowledge about scientific methods. However, we also computed an overall test score for domain-specific content knowledge, in which we added all items of the domain-specific content knowledge test, establishing one overall domain-specific content knowledge measure.

The same content-specific knowledge test was also used to assess the learners' prior knowledge. However, for knowledge about mechanisms the used scale failed to reach sufficient reliability. Therefore, the pretest measure of knowledge about scientific methods was not included in our analyses. Reliabilities of the other measures ranged between .53 (Cronbach's Alpha for knowledge about mechanisms) and .66 (Cronbach's Alpha for knowledge about scientific methods).

Statistical analyses

Concerning both domain-specific content knowledge and domain-general knowledge on argumentation, we computed ANCOVA's with internal and external scripts as fixed factors and the scores in the specific outcome measures as dependent variables to test the two hypotheses. For determining the effects of internal and external scripts on domain-specific content knowledge, the each specific content-specific prior knowledge measures were included as a covariate (except for knowledge about mechanisms because of its low reliability), although learners in the four conditions did not differ significantly concerning their content-specific prior knowledge (F(1,95) < 1.06; n.s.). As a covariate for domaingeneral knowledge on argumentation, the actual point score in the test for assessing their internal scripts was used. For all analyses, the alpha-level was set to 5 %.

Results

Learning prerequisites

Before testing our hypotheses, we controlled for differences in the pretest measures.

Concerning the domain-specific prior knowledge measures, we found no statistical significant differences between the four experimental conditions (F(1,94) < 1.06; n.s.).

Domain-general knowledge on argumentation

Domain-specific content knowledge

Table 2 presents the mean scores and standard deviations in the three content-specific knowledge measures for the four experimental conditions (both for pre-and post-tests). On the overall measure of domain-specific content knowledge, learners holding high structured internal scripts received higher scores than learners with low structured internal scripts. There were only marginal differences between learners having collaborated on the basis of the high structured and the low structured external script. An ANCOVA (with the overall domain-specific content knowledge as dependent variable and the overall prior knowledge as control variable) revealed a significant main effect for the internal script (F(1,93) = 10.33; p < .05).

The same pattern of results could be observed for knowledge about mechanisms. Again, learners holding high structured internal collaboration scripts reached higher scores than learners with low structured internal scripts. Again, there were no differences between learners who had collaborated by aid of the high structured external script and those who followed the instructions of the low structured external script. Consequently, an ANOVA yielded a significant main effect for the internal script indicating that learners holding high structured internal scripts received significantly higher scores than learners with low structured internal scripts (F(1,93) = 4.24; p < .05).

For knowledge about scientific methods, a different and rather surprising pattern occurred. There, learners holding high structured internal scripts who had collaborated on the basis of the low structured external script reached the highest scores, followed by learners with low structured internal scripts who were provided with the low structured external script.

Learners who collaborated on the basis of the high structured external script reached lower scores, especially when they held low structured internal scripts. An ANCOVA revealed a marginally significant main effect for the external script (F(1,93) = 3.18; p = .08) indicating that learners having worked with the low structured external script reached higher scores than learners having been supported by the high structured external script. Post hoc comparisons revealed that learners holding high structured internal scripts who had collaborated on the basis of the low structured external script were significantly better than learners with low structured internal scripts who had learned with the high structured external script (t(46) = -2.23; p < .05).

Discussion

Overall, our results support quite clearly our initial assumption that argumentative knowledge construction is guided by both externally provided instruction and the learners' internal scripts. However, the very structure of these scripts has an impact on what kind of knowledge in fact is acquired. In order to investigate the question how internal and external scripts play together concerning the acquisition of domain-general knowledge on argumentation and domain-specific content knowledge in web-based collaborative inquiry learning, we set up two competing hypotheses, an interactive effects hypothesis and an additive effects hypothesis. The results we found for the acquisition of domain-general knowledge on argumentation clearly support the additivity hypothesis: As predicted, the high structured external collaboration script helped all learners, independently of their internal collaboration scripts. Moreover, the supportive effect of the high structured external script was similar for both learners with high and low structured internal scripts since there was no interaction between external and internal scripts. Therefore, in order to reach the objective to get learners to acquire domain-general knowledge on argumentation, we recommend to provide them with high structured external scripts, which specify in a detailed way how to proceed in collaborative argumentative knowledge construction. Hence, with respect to our main research question, we can say that a web-based collaborative inquiry learning environment can be improved by implementing a high structured external collaboration script, at least considering the acquisition of domain-general knowledge on argumentation, and it can even achieve that all learners regardless of their internal scripts can benefit from it.

However, in contrast to our expectations, the high structured external collaboration script failed to facilitate the acquisition of domain-specific content knowledge. Rather, it appeared that the learners' internal scripts are more influential than external scripts with respect to content-specific knowledge construction. For overall domain-specific content knowledge as well as for knowledge about mechanisms, we found that learners with high structured internal scripts learned more than individuals holding low structured internal scripts, regardless of the structure of the external collaboration script. It seems that since the learners' internal scripts have developed over long periods of time (see [START_REF] Schank | Scripts, plans, goals and understanding[END_REF], they are more easily accessible [START_REF] Perkins | Person-plus: a distributed view of thinking and learning[END_REF] than any freshly induced strategy, so that learners can use their own strategy effortlessly just like a very familiar tool. It is plausible that students will rather rely on strategies they have developed for years and which have been proven functional for them than to adopt an externally induced and probably new strategy as long as they have the opportunity to do so. Since neither the high nor the low structured external script included any hints concerning what specific contents to discuss, learners had a good deal of freedom, thereby having the opportunity to rely more on their internal scripts concerning content-specific aspects of the learning environment. For the high structured external collaboration script to boost the learners' acquisition of domain-specific content knowledge, maybe more content-specific scaffolds like content-related questions rather than the provision of a formal argumentation script might be helpful. However, in the study by [START_REF] Weinberger | Knowledge convergence in computermediated learning environments: Effects of collaboration scripts[END_REF], it appeared that content-specific cues were not able to improve conceptual learning, maybe because they triggered rather automatized than thoughtful reactions. However, stronger effects of the high structured external script used in this study might be observable in studies taking longer time spans into account since it might take time to get learners to internalize the argumentation-specific script instructions, which help them to engage in deep elaborations of the learning material.

In the beginning of this paper, we also had argued that collaboration scripts are complex entities that might have very specific effects on specific learning outcomes and also have negative side-effects, i.e. that benefits concerning some knowledge dimensions can go at the expense of others, even though this might not have been intended when designing the collaboration script [START_REF] Weinberger | Knowledge convergence in computermediated learning environments: Effects of collaboration scripts[END_REF]. Our results provide justification for this view, since we found that individuals tended to acquire more knowledge about scientific methods when they did not receive further support by the high structured external collaboration script.

This result might be attributed to the fact that the high structured external script set constraints for activities, which could have contributed to the acquisition of knowledge about scientific methods, which was not the case for activities that contributed to an acquisition of knowledge about mechanisms. In fact, the high structured external script was more directed towards discussing the two hypotheses and related evidence than towards thinking about what research methods might be able to determine what causes the frog deformities. Thus, our results prove that external collaboration scripts can be tailored to specific outcomes. Designers of collaboration scripts should aim at inducing activities, which contribute to the desired learning outcomes without at the same time restricting further activities that might also be fruitful with respect to these learning outcomes.

In sum, our results are in favour of the additive effects hypothesis and provide counterevidence to the interactive effects hypothesis. The high structured external script supported both learners with high and low structured internal scripts on acquiring domain-general knowledge on argumentation and simultaneously did not impede learning of domain-specific content. However, generalizability of the reported findings might be restricted since learners reached on average rather low scores in the pretest, which assessed their internal scripts. Yet, taking into account the results of international studies like PISA, it could not be expected that students would reach very high scores in this test. We speculate that individuals having been classified as holding high structured internal scripts in this study still did not have enough argumentative skills to fully play them out in a rather unstructured learning environment. It might be that if learners' internal collaboration scripts were structured even higher than were the internal scripts of the learners assigned to this condition in this study, the interactive effects hypothesis might receive stronger support. Subsequent research is needed to address this issue.

With respect to the design of inquiry learning environments to be used in real classroom settings, our results demonstrate that the benefits of such environments can be augmented by adding additional micro-structuring facilities to them. Collaboration scripts can be designed to improve the learners' abilities to argue with hypotheses and evidence that are provided in inquiry learning environments without impeding their content-related learning. Yet, it must be clear that different learners may require different forms of such instructional support in order to reach comparable learning gains. There might be conditions, under which learners with high structured internal scripts can benefit more from a rather open learning environment, whereas in other settings, they might require more external structuring. This points to the need for developing instructional designs that are flexibly adaptable to different types of learners.

Figure 1 :

 1 Figure 1: Welcome screen of "The Deformed Frogs Mystery" project.

Figure 2 :

 2 Figure 2: Screenshots of the high structured external collaboration script (left screen: introductory text; right screen: pre-structured text boxes to be filled in by the participants.

ForFigure 3 :

 3 Figure 3: Mean scores (standard deviations in brackets) in the test on domain-general knowledge on argumentation across the four experimental conditions.

Table 1 :

 1 Design of the empirical study.

			External collaboration script
			Low structured	High structured
	Internal	Low structured	N = 26 (13 dyads)	N = 22 (11 dyads)
	collaboration
	scripts	High structured	N = 26 (13 dyads)	N = 24 (12 dyads)

Table 2 :

 2 Mean scores (standard deviations in brackets) in the domain-specific knowledge tests (pre-and posttests) in the four experimental conditions.

		Low structured internal script	High structured internal script
		Low structured	High structured	Low structured	High structured
		external script	external script	external script	external script
		Pretest Posttest Pretest Posttest Pretest Posttest Pretest Posttest
		M	M	M	M	M	M	M	M
		(SD)	(SD)	(SD)	(SD)	(SD)	(SD)	(SD)	(SD)
	Domain-
	specific content knowledge	2.58 (1.33)	4.69 (2.05)	2.32 (1.32)	4.91 (2.02)	2.50 (1.48)	6.00 (1.65)	2.50 (1.32)	6.12 (2.03)
	(overall)
	Knowledge about mechanisms	0.42 (0.58)	1.77 (1.34)	0.64 (0.73)	2.14 (1.46)	0.58 (0.70)	2.31 (1.62)	0.63 (0.88)	2.83 (1.49)
	Knowledge about research methods	2.15 (1.19)	2.46 (1.07)	1.73 (0.88)	2.18 (1.01)	1.92 (1.09)	2.77 (0.82)	1.92 (0.93)	2.33 (0.76)


Tom Nyvang
email: nyvang@hum.aau.dk

Implementation of ICT in Higher Education as Interacting Activity Systems

Keywords:

Implementation of ICT in higher education is not a trivial process. It is however a process leading to a number of challenges and problems. The paper develops a theoretical model of the implementation of ICT in higher education based on activity theory and on a case study in a Danish university. The model suggest that implementation in itself is an activity system. The implementation activity is composed of three processes: Selection of ICT; adaptation of ICT and change of practice with ICT. Furthermore the model suggests that the implementation activity interacts with and systems development activity and an educational activity. Based on the model and case study the paper suggests a framework of challenges that must be met for an implementation to succeed.

INTRODUCTION

Implementation of networked learning in higher education is a complex task. It affects the way students learn, teachers teach and often the way administrators administrate as well as the way leaders lead the university. It does so by challenging existing organisational, pedagogical and technological practices and the aims normally are to increase quality, efficiency, flexibility and quantity. Research in Computer Supported Collaborative Learning (CSCL), networked learning and related subjects has already stated that ICT influences from a organizational as well as a pedagogical perspective, but a deeper understanding of the implementation seems to lack [START_REF] Collis | Flexible learning in a digital world: Experiences and expectations[END_REF]Dirckinck-Holmfeld & Fibiger, 2002).

Higher education thus needs to explore ways to organize implementation of ICT in learning environments. Bearing in mind the continuous development of ICT it also seems important to recognize that implementation of ICT isn't going to be a one time event. One of the very first steps needed in order to qualify the facilitation of the change processes is to actually understand what implementation of ICT in learning environments is and how it affects practice. Here implementation is defined as the process leading from one practice to a new practice where the new practice is characterized by use of ICT. In addition implementation is understood firstly as a social process and secondly a process in which competent individuals decides to start to use ICT.

In the literature inspiration on how to interpret and understand implementation of ICT and networked learning can be found in at least three disciplines: Systems development, organisational learning and theory on diffusion of innovations. Firstly theory on systems development explains to develop ICT in general and seek to ensure that the products meet user demands and needs, but a focus on implementation seem to lack [START_REF] Banks | Networked learning 2004[END_REF][START_REF] Beyer | Contextual design: A customer-centered approach to systems designs[END_REF][START_REF] Dahlbom | Computers in context: The philosophy and practice of systems design[END_REF]. It seems to be an implicit assumption that the implementation process is crucial, but also that one has to look elsewhere for information on how to design or support the process. Secondly theory on organizational learning contains relevant aspects since implementation of ICT is closely linked to organisational changes. However the focus on ICT is traditionally relatively blurred [START_REF] Argyris | On organizational learning[END_REF][START_REF] Krogh | Enabling knowledge creation[END_REF][START_REF] Wenger | Communities of practice -learning, meaning and identity[END_REF][START_REF] Wenger | Cultivating communities of practice -a guide to managing knowledge[END_REF]. Thirdly theory on diffusion of innovations focus on the process of adopting new technologies [START_REF] Rogers | Diffusion of innovations[END_REF]. However it tends to overlook some of the complexity of an adoption. It is as if adoption is either full adoption is none at all [START_REF] Bøving | diffusion and adoption of networked information technologies[END_REF][START_REF] Gallivan | Organizational adoption and assimilation of complex technological innovations: Development and application of a new framework[END_REF].

With the present paper I unfold one possible way to strengthen the theoretical foundation for understanding implementation of ICT in higher education. I do so by drawing on the theoretical framework called activity theory. Activity theory seems relevant because it is already widely used to understand learning and development processes and useful when it comes to tying individual, organisation and technology together in one framework.

ACTIVITY THEORY AS PERSPECTIVE ON IMPLEMENTATION Introduction to Activity Theory

Activity theory derives from Russian psychology where psychologists as Vygotsky [START_REF] Vygotsky | Mind in society: The development of higher psychological processes[END_REF], Luria [START_REF] Luria | Language and cognition[END_REF] and Leontjev (Leont'ev, 1978) developed a cultural historical social psychology during the 20 th century. Over the past 10-15 years activity theory has been subject to growing attention. Yrjö Engeström [START_REF] Engeström | Learning by expanding[END_REF] and others have developed activity theory to use on pedagogical development and design of software and the practice it aims at. Kari Kuuti has also taken part in the development of activity theory and defines it as: "a philosophical and cross-disciplinary framework for studying different forms of human practices as development processes, with both individual and social levels interlinked at the same time." [START_REF] Kuutti | Activity theory as a potential framework for human-computer interaction research[END_REF].

This however also means that activity theory cannot be regarded one complete coherent theory. I thus want to give a brief introduction to the elements of activity theory I draw on bearing in mind that other traditions or foci within activity theory is left out. My point of departure here is the works of Leontjev and Engeström. Leontjev took his point of departure in the works of Vygotsky to continue the development of a cultural historical psychology with focus on the dialectics of human development. Leontjev worked on the key concept mediation. He did originally focus on tool mediation to explain how a tool carries the result of a cultural historical development. A tool thus also mediates the way the user of that tool perceives the task at hand. Leontjev also introduced the distinction between three different levels of an activity. He distinguished between activity, action and operation -three levels that correspond to motive, goal and condition in human behaviour. Motive is the overarching force driving our actions, but it is normally not given conscious attention. Goal is on the other hand a concrete here-and-now in focus goal we pursue as part of a concrete action. Conditions are the out-of-focus, but necessary conditions for an action. What is motive in one activity may be goal in another and so on . Operations may fail and suddenly be brought into attention and thus converted to an action. In all cases the source of development is contradictions because contradictions force us to consider new practices -new practices that can exist until new contradictions become too strong.

Engeström draws on both Vygotsky and Leontjev, but are less psychologically focused. Instead his focus is on what he defines as developmental work. Engeström has developed the triangular model that shows the main components and mediating artefacts of an activity. In the light of the activity theory the working definition of implementation of ICT as the process leading from one practice to a new practice where the new practice is characterized by use of ICT can be elaborated. First of all the old practice can be expected to be part of the new practice since the history is represented either through artefacts, practices, culture, subjects or tools. Activity theory also stresses that implementation of ICT is not only about exchange of two tools. When the new tool offers new possibilities the conditions for practice changes. This may lead to contradictions and thus induce a new practice. It is finally important to notice that new ICT developed in one context and given specific meaning in that context may be given a different meaning in a the use context when it is implemented.

Implementation, Education and Systems Development

It is a central argument of this paper that implementation is something in its own right even though it is closely linked to other processes. In the case of implementation of ICT in higher education at least to neighbouring processes can be identified. These are the process ICT is implemented into, higher education, and the process that produces ICT in the first place, systems development. The main theoretical hypothesis behind this paper is that implementation, education and systems development are driven by different motives and thus represent different activities or activity systems. The hypothesis however also is that these activity systems interact and thus influence each other.

If we look at the research literature on systems development there is different definitions of what software quality is [START_REF] Beyer | Contextual design: A customer-centered approach to systems designs[END_REF][START_REF] Dahlbom | Computers in context: The philosophy and practice of systems design[END_REF][START_REF] Vliet | Software engineering -principles and practice[END_REF]. Some stresses the technical quality while other stresses the needs of future users as a measure of software quality. The literature does however convey the assumption that a prominent motive of systems developers is to create systems of high quality. In the light of activity theory this also implicates that it is feasible to regard systems development an activity. This does not necessarily mean that systems development contradicts implementation of ICT in higher education. It is an important condition to have quality software, but the research on ICT in higher education also stresses that this is not enough.

The general assumption of research in teaching and learning in higher education is that an important motive (but not the only one) for teachers and students is quality education [START_REF] Biggs | Teaching for quality learning at university -second edition[END_REF]. In the present case teachers and students give high priority to student driven activities such as problem based learning or problem oriented project pedagogy (Kolmos et al., 2004). Data from the present case do however also show the teachers and students prioritize time and resource efficient practices.

Finally the assumption is that an implementation is driven by its own motives and thus can be regarded an activity too. This is based on the assumption that a need or wish for change is a prominent driving force behind implementation. The product of the implementation activity is a new educational practice with ICT. If this assumption is correct it is reasonable to conclude that implementation is an activity in itself because it is driven by a motive different from the motives of systems development and higher education. It is however also important once again to stress the three activities are closely linked. Systems development produces tools for higher education and implementation. Systems development also integrates a certain perspective of which practice tool is produced for. When producing a new educational practice the implementation activity also shapes a practice of which the new tool is a part. In short the systems development and implementation activities primarily interact on the ICT component of the implementation. On the other hand the implementation and educational activities primarily interact on the educational component of the new practice.

The analysis will show that it is feasible to understand implementation of ICT in higher education the way suggested here and add more detail based on a case study. The analysis and concluding section of the paper will also look into possible consequences by suggesting how the theoretical model may inform implementation practices in higher education.

CASE STUDY DESIGN AND ANALYSIS BASED ON ACTIVITY THEORY

The analysis of the case study presented later in this paper is based on activity theory. Frameworks that suggest how to base research and analysis on activity theory have been suggested by researchers in the past. [START_REF] Engeström | Learning by expanding[END_REF] suggested an extensive iterative approach that combined investigation and development in an action research like expansive cycle. [START_REF] Kaptelinin | Methods & tools: The activity checklist: A tool for representing the "space" of context[END_REF] Case study of practice.

ICT based infrastructures created and used, log-files.

Table 1. Research design.

The ICT that was the primary focus of iteration 2-4 was Lotus Quickplace. Quickplace is a web-based tool for asynchronous information sharing, communication and collaboration. In this case it was used to distribute administrative information to teachers and students, course information, and to facilitate collaboration between students.

Activity Oriented Analysis

Table one has listed several data sources, but in the analysis the primary data source has been the semi structured interviews [START_REF] Kvale | Interviews. An introduction to qualitative research interviewing[END_REF]. The interview data has been clustered in clusters defined by the central foci of activity theory and the theoretical model of implementation of ICT in higher education suggested earlier:

• Motives, goals and conditions -with special attention to the implementation, educational and systems development activities.

• Subjects (actors) in the activities.

• Mediating artefacts in the activities (tool, culture, division of labour).

• Contradictions internally in one activity or between different activities.

Due to the limited number of pages the following pages are not a full account of the analysis, but an extract of the full analysis reported in Nyvang (2006).

ANALYSIS Implementation activity

Data supports the basic hypothesis of the paper. Patterns in the data material show that study and educational practice with ICT is the central object of an activity whose motive is to develop teaching and learning by implementing ICT and developing a new practice around it. The patterns of the implementation activity that all actors involved return to over and over again are identification of needs for development with ICT, choice of ICT and development of practice with ICT. These patterns equal the goals of the activity.

The implementation activity is also characterized by different prominent mediating artefacts. First and foremost tools already present in the organisation have shaped the implementation in at least two ways. Firstly needs for development have been formulated as a reaction against existing tools. Secondly development of practice has had roots in the existing practice and has thus also had to deal with the infrastructures laid out by existing tools. Tools in focus are tools that the people driving the implementation know based on other professional or private activities they are involved in. Finally the existing pedagogical model is a sort of tool that influenced choice of tool and change of practice.

Culture is another highly influential mediator in the present case. The pedagogical model is also part of the culture of the organization. It is thus expected that new tools and a new practice supports problem oriented project pedagogy or at least doesn't contradict it. The high degree of freedom for teachers and students to choose their own tools and work methods is another highly influential aspect of culture. In the light of this freedom it is not a surprise that the implementation readiness is greater with individuals or smaller groups that implement on their own initiative. In the present case this freedom was challenged by the program wide implementation of Lotus Quickplace.

Figure 2. The implementation activity.

Division of labour mediates the division of labour between management, teachers, students and other actors involved. In the present case development of a new practice by implementation of ICT was used as an opportunity to introduce a new division of labour between teacher and students by some of the teachers. The teachers wanted to move away from traditional lecture based teaching to a learning and learner centered approach. It did on some occasions induce a contradiction between the expectations of teacher and students.

Interaction between Educational Activity and Implementation Activity

In the present case the relation between the educational activity and the implementation activity is obvious.

There is full or partial overlap between subjects, culture and tools. The two activities are actually directed towards the same or part of the same object. The shared part of the object can be defined as educational practice.

Culture, pedagogy

Organization Division of labour

New system

Teachers, students

New practice with ICT

One of the clearest examples of interaction between the two activities was observed when groups of students that were in the midst of the implementation process turned the implementation into a study object. They did so by making it the focus of a semester project. In that way the implementation process had direct impact on not only the form but also the content of their study process. The same group of students suggests that the students are given more opportunities to shape the implementation of ICT as a result of projects like theirs. They do so in recognition of the importance of personal involvement. They stress that the implementation of new ICT is more likely to be a successful part of student practice if the students feel involved, responsible and thus develop personal ownership of a new tool and practice.

It is also possible to trace a tendency to interaction between the two activities among the teachers. One of the teachers explicitly refers to the relation between teaching and implementation because implementation of ICT in his teaching is one of the ways he keeps his knowledge of the technical issues he teaches up to date. The technical challenges he experiences in programming a web interface is thus an integral part of his personal professional development. The same teacher also refers to the interaction between teaching and implementation.

When the same question or problem has come up a significant number of times in his classes he changes the design of his web-based course materials. It is however a very small number of teachers that explicitly expresses links that close between the two activities. Other teachers express the link in a less direct way by asking if the engagement in the implementation project really pays of and can be justified by improvement in teaching and learning.

Figure 3. Implementation and educational practice -interacting activity systems.

Interaction between Systems Development Activity and Implementation Activity

In the present case the relation between the systems development and implementation activity surfaces in at least two ways. Firstly systems development activities have produced the tools already in use as well as the new tools to be implemented. Secondly the relation steps into focus when the negotiation between the affordances of what has been developed and the needs defined by the implementation activity starts. The two activities interact on a shared object that can be defined as ICT for educational practice.

The interaction on the shared object first appears when in-house system developers and their ideas about the specific needs of the organisation are challenged by the new system Lotus Quickplace. There is a debate on the difference between existing systems and the new one. There is also a debate on the actual needs of the organisation. The in-house developers on their part stress the importance of a light weight communication platform that is easily accessible from different clients. The implementation activity however aimed for a tool that was easier to customize into for example course portals by end users such as teachers or students. Case studies during the early iterations of the development project made it clear that both the old and the new solutions had their qualities. It turned out that many users had preferred a new tool that were as light weight and easily accessible as the old communication system and on the other hand had the support for design of new structures and content that the new tool, Lotus Quickplace, offered.

CONCLUSION AND IMPLICATIONS FOR PRACTICE

The paper has a twofold conclusion. First of all the model of implementation of ICT in higher education is a theoretical output. The model supplements earlier research [START_REF] Gallivan | Organizational adoption and assimilation of complex technological innovations: Development and application of a new framework[END_REF][START_REF] Rogers | Diffusion of preventive innovations[END_REF] with its focus on the influence of personal motives and goals. Implementation is thus not only about management driven decisions. It is also a complex negotiation between factors that are often contradicting each other. The theoretical model also contributes with its focus on the domain of higher education.

The model does however still need to be challenged by new cases in new contexts to strengthen its empirical base. It also has to be considered how the relation between the individual in focus here and the overall strategic level of the organisation can be introduced in the model.

The second aim of the paper was to use the theoretical model and case study to extract a list of the major challenges that need to be handled for implementation of ICT in higher education to succeed. In table 2 process has not surprisingly turned out to induce ownership. It is however also quite difficult to develop a new infrastructure for communication and collaboration this way. For such an infrastructure to succeed it obviously needs to be shared between a number of individuals, but often the needs expressed by different individuals contradict each other.

There is also still work to be done of the list of challenges. Firstly it needs test and elaboration against other data too. Secondly it should be developed to suggest strategies or heuristics that prepare implementers to meet the challenges.

Figure 1 .

 1 Figure 1. Triangular model of an activity.

Figure 4 .

 4 Figure 4. Systems development and implementation -interacting activity systems.

Centered Informatics Case Design and Data Collection

  developed a more light weight activity had research in human computer interaction as its primary focus. Here I have selected an approach that draw on both Engeström and Kaptelinin. The present study builds on four cycles of development and data collection in an Engeström inspired manner. The analyses however build on a Kaptelinin inspired check list. In the next two sections I present the case design and analytical strategy. The focus of the research project is implementation of ICT in the program Human Centered Informatics, Aalborg University. Human Centered Informatics is an educational program within the humanities offering both bachelor (3 years) and master level (bachelor + 2 years) education and has approximately 500 students. It combines communication, organisation and ICT studies to provide students with the tools necessary to be critical, but constructive, participants in the evaluation and construction of ICT and new media. The project moved through four iterations involving gradually more students until the full educational program including all teachers, students and administrative staff was involved. The project also used different change and research strategies as shown in table 1.

			Tool
	Culture Subject check list that Human Iteration ICT implementation	Community Involved Goal	Division of labour Object Research method Data Product
	1. Fall	5 th semester of Human	6 teachers,	Document	Pilot study of	Interviews,
	2001	Centered Informatics.	21	existing	existing practice.	ICT used in
		Teachers free to choose	students	implementation		courses
		technology.		procedures.
	2. Fall	3 rd semester of Human	20	Develop, use	Action research.	Interviews,
	2002	Centered Informatics.	teachers,	and document		ICT based
		Teachers have to use the	80	new			infrastructures
		same technology for	students.	implementation		created and
		communication.		procedures.		used, log-files.
	3.	4 th semester of Human	30	Develop, use	Action research.	Interviews,
	Spring	Centered Informatics.	teachers,	and document		ICT based
	2003	Teachers have to use the	160	new			infrastructures
		same technology for	students.	implementation		created and
		communication.		procedures.		used, log-files.
	4. Fall	All semesters and	60	Use
	2003	specializations of of	teachers,	implementation
		Human Centered Informatics. Teachers are	500-600	procedures.
		adviced to use the same	students.
		technology for
		communication.

Table 2 .

 2 the challenges identified are listed. Challenges for implementation of ICT in higher education.Table 2 represents challenges that have been identified in the present case and organises them in a structure extracted from the theoretical model of implementation. The most prominent and most difficult challenge is probably the need for a broad ownership of the implementation and its results. Without broad ownership among the potential participants in the implementation they are likely to ignore implementation of ICT or engage in a competing implementation project. The present case has shown that this challenge is most efficiently met by involving as many actors as possible in the mid-level activities. Personal involvement of the decision and design

		Implementation	Implementation in interaction	Implementation in interaction
			with education	with systems development,
				operation and maintenance
	Motive	What is the overall motive that	How does implementation	How does the new ICT fit
		drives the implementation?	influence education -an	with ICT strategy in terms of
		What steps are taken to secure	opportunity for radical change	for example platform,
		broad ownership of the	or smaller steps? What steps	open/closed source and
		motive?	are taken to secure broad	standards?
			ownership of the motive?
	Goal	How is ICT selected, adapted	How do the new practice and	How does new ICT integrate
		and used to change practice?	ICT fit existing practice with	with systems in use? How
			ICT? How are contradictions	are contradictions resolved?
			resolved?
	Condition How are the future users	Are old course materials and	How are existing user
		trained to use the new ICT?	structures transferred to the	databases transferred to the
			new ICT? If so, how?	new ICT? How are
				challenges handled?