Learning Innovations

MENTAL MODELS AND NETWORK PEDAGOGY

Philip Barker
University of Teesside, UK
philip.barker@tees.ac.uk

ABSTRACT

Mental models provide a powerful mechanism for storing knowledge within the human mind. Because of the ways in which they can influence behaviour, such structures have a significant impact on virtually all forms of human activity. This is particularly so in the areas of teaching, learning and expert behaviour. Because of their importance, this paper discusses the significance of mental models in the context of designing interactive, web-based, learning environments. In doing this, particular attention is paid to the basic principles advocated by constructivist theory.

1. INTRODUCTION

Increasingly, the world in which we live is becoming more and more complex. In order to handle complexity, powerful intellectual tools are needed. One such tool is general systems theory (GST). A very important aspect of GST is its ability to classify systems into generic categories according to their properties and the kinds of behaviour that they exhibit. One important class of systems is that involving human activity - that is, systems in which an individual or a group of people work together in order to achieve some particular goal. This might involve writing a report, learning a new programming language, building some artefact or conducting a scientific experiment.

As the above list of illustrates, human beings can become involved in a diverse range of activities. They can therefore exhibit many different types of behaviour. In order to understand and explain this behaviour, it is necessary to consider what happens when individuals (or groups of people) are confronted with one or more 'stimuli'. We regard a stimulus is being an event, object or process that can be perceived by one or more individuals and which may cause at least one of them to take some form of action. This action may be overt or covert; it may also be voluntary or involuntary; and it may take place in either a conscious or a subconscious fashion. The various stimuli to which an individual is exposed may be internal to that person (such as a pain, a bio-signal or a thought); they may therefore be embedded 'deep' within his/her cognitive and/or physical anatomy. Alternatively, the stimuli may arise from some outside source that is external to the individual concerned - for example, another person, a book, a television, a telephone, a personal organiser or the screen of a computer system.

Because of their importance with respect to influencing human behaviour, it is necessary to understand what happens when an individual is confronted with a stimulus of some sort. Naturally, as far as this paper is concerned, our primary interest will be in considering this issue within the context of teaching and learning behaviour since these are of vital importance to all individuals, organisations and societies.

As a basis for understanding what happens when someone is exposed to a stimulus, the basic model depicted in figure 1 will be used as a starting point.

Figure 1 Knowledge acquisition and behaviour in a task domain

This model proposes that as a consequence of the external stimuli that are embedded in teaching and learning experiences, people commit appropriate 'things' to their memory systems (the 'put' operation in figure 1). Subsequently, at some later time, in other different situations in which similar stimuli appear, people recall from memory material that is relevant to the situations in which they find themselves (the 'fetch' operation in figure 1). Naturally, a fundamental issue that we now need to consider is the mechanisms by which learning experiences are held in a person's memory system. The psychological literature suggests that accumulated experiences (or 'knowledge') that we hold in our heads can take two basic forms: declarative and procedural. Various types of cognitive structure are used to store this knowledge - such as lists, associations, plans, scripts, schemata and mental models. In this paper we are concerned only with mental models.

For our present purposes we shall regard a set of mental models (in any given domain of study) as being a powerful representation 'in the head' of previous experiences relating to that domain. Background material relating to studies of mental models can be found in the book by Rogers, Rutherford and Bibby (1992). Descriptions of more recent research work are presented in Staggers and Norcio (1993), Fuchs-Frohnhofen et al (1996), Corritore and Wiedenbeck (1999) and in our own research publications (Barker, van Schaik and Hudson, 1998; Barker et al, 1998; Barker and van Schaik, 1999).

Bearing in mind what has been said above, the remainder of this paper will attempt to identify the important relationship between mental models and task performance within a given task domain - as advocated in the mental model hypothesis (Barker et al, 1998). It will also discuss some of the important implications of mental models for the design of computer-based learning resources that are delivered via network strategies involving intranets and/or the Internet. In order to realise these objectives, the following section of the paper is intended to outline some of the 'theoretical foundations' that form the basis for the design of computer-based learning environments. This is followed by a section that describes the ways in which mental models can be studied. Finally, some of the implications of these models for the design of network-based learning resources will be discussed.

2. THEORETICAL ISSUES

This section of the paper is organised into four basic parts. The first of these outlines the important relationship between mental models and the various types of learning environment that we create. The second part then explores how educational technology can be used to support teaching and learning activities and te creation of learning environments. The two subsequent sections then discuss: the use of computer networks for the realisation of pedagogical goals; and the important role played by end-user interfaces (to software packages) in promoting the development of mental models; respectively.

2.1 Designing Learning Environments

It is our belief that all environments and experiences generate sequences of stimuli that can be used either to activate a person's existing mental models or initiate the development of new ones (Barker et al, 1998). The relationship between (learning) environments, experiences, stimuli and mental models is illustrated in figure 2.

Figure 2 Learning activities and their effects on mental models

Within this diagram the importance of learning activities are twofold. First, if a model (for any given situation) does not exist then learning processes provide the mechanisms by which new models can be generated. Second, if a model exists, but it leads to incorrect behaviour then, through reflection, remediation and reconstruction processes the model(s) can be adapted and amended to take into account feedback that is derived from unsuccessful experiences. Modification of mental models therefore takes place in such a way that the next time they are used in a similar situation they will lead to correct behaviour being exhibited.

As can be seen from figure 2, mental models are primarily developed as a consequence of our participation in various types of learning activity; these may be both conscious and sub-conscious. Typical examples of learning activities might include: reading a book; attending a lecture; browsing through a collection of World Wide Web sites; performing an experiment; or using an item of CAL software. In each of these situations, mental models are likely to be created (if they do not already exist) or are enhanced (if they do exist). Similarly, in a 1:1 (or small group) conversational situation (such as a tutor/student or a student/student dialogue), considerable knowledge transfer is likely to occur. As we have illustrated and discussed elsewhere (Barker et al, 1998), the knowledge transfer that takes place is driven by the mental models owned by each of the communicating partners. Of course, the 'quality' and nature of the dialogue that occurs on any given topic will critically depend upon the richness of the mental models that each dialogue partner has. Naturally, during the course of a conversation mental models may be adapted as a result of the acquisition of new knowledge acquired through the dialogue process. In our view, the process of becoming an 'expert' in any particular discipline involves (in part) the development of rich and powerful mental models relating to that subject domain. This issue is discussed in more detail later in the paper.

2.2 Using Technology in Education

A fundamental requirement of the learning environments depicted in figure 2 is the use of appropriate 'educational technology' to facilitate the transfer of knowledge and the development of skills. The importance of technology in education within a university context has been discussed at length by Laurillard (1993). In her book (p. 103), she provides an interesting 'conversational framework' in order to describe the various activities and media involved in a didactic teaching and learning process. In his discussion of Laurillard's work, Bates (1998) shows how her model of teaching and learning can be used to derive most of the commonplace mechanisms of pedagogy. These include:

learning through acquisition (the teacher as 'story-teller');
learning through discussions (teacher and student 'negotiations');
learning through discovery (the student as 'researcher'); and
learning through 'guided discovery' (teacher and learner as 'collaborators').

Although the models proposed by Laurillard are useful, they have some serious shortcomings. First, unlike our own representations, they fail to show the importance of mental models in the conversations that take place. Second, they do not explicitly accommodate the views of constructivist theorists. Third, in our view, there is too much emphasis given to teaching - as opposed to learning. This third point is an important one when computer networks are used for pedagogical purposes. In our view this type of technology should be used to emphasise student-centred learning as opposed to instructor-driven teaching.

2.3 Using Computer Networks

The important roles that computer networks can play within the context of teaching and learning activities have been extensively discussed by numerous researchers - see, for example, Brooks (1997), Eisenstadt and Vincent (1998), and Barker (1999). In the work that we have recently been undertaking we have made the fundamental assumption that future generations of students will all have their own powerful computers which have inbuilt facilities for attachment both to the Internet and to in-house computer networks (intranet facilities). These networks may exist within a university campus, a public library or a home environment. Naturally, technology of this sort can be used to promote both a teacher-centred (instructivist) and a learner-centred (constructivist) philosophy of instruction. As we have argued elsewhere (Barker, van Schaik and Hudson, 1998), the latter approach to knowledge and skill acquisition requires the development of new mindsets (both within teachers and in students) - and the mental models that go with them. The essential feature of our current use of networks to facilitate learning relies upon students building and developing their own personal web structures that reflect their individual interests. They are given (through the use of an intranet facility) a 'core shell' for a particular course and they are then expected to build on this, expanding it in various ways to reflect those parts of the course that they are (individually) most interested in. Over the last few years, we have substantially increased our use of this learning technique while, at the same time, reducing the amount of emphasis given to conventional 'stand and deliver' approaches to instruction.

2.4 Model Building - The Importance of Human-Computer Interaction

The increased use of computer systems for the promotion of learning activities implies greater use of software systems such as browsers, electronic mail and conferencing tools. In our opinion, the nature of the facilities that are embedded within the end-user interface to a software system (especially, in the context of educational software) are of paramount importance. Indeed, within computer-based systems, the end-user interface is the primary mechanism by which users build mental models of the underlying software. This view has also been echoed by a number of other researchers. Faulkner (1998), for example, states that as a result of interacting with a computer system: 'The user forms a model, known as the user's mental model of how the application works. This model forms the basis of future interactions with the system and enables users to predict ...'.

Bearing in mind what was said above, considerable thought must therefore be given to the way in which an end-user interface is constructed - if it is to project an adequate system image to its users in the most efficient and effective way. It is therefore necessary to carefully select and combine that set of 'interface agents' that will most appropriately fulfil the end-users' requirements in terms of model building and control functionality. Of course, many other factors also have to be considered when designing an interface - such as its ease of use, memorability, forgivingness, look and feel and, of course, its power to motivate. This latter aspect is particularly important in the context of software that is intended to promote learning activities.

3. STUDYING MENTAL MODELS

A variety of different experimental techniques exist for studying mental models. The various methods that have been employed are well-documented in the research literature. In their work, Corritore and Weidenbeck (1999), for example, describe the use of 'sets of comprehension questions' in order to identify the various types of knowledge that computer programmers acquire as a result of programming activity. In our own work (Barker et al, 1998; Barker and van Schaik, 1999) we have employed two basic sets of techniques - one to study declarative knowledge and the other for studying procedural knowledge (although the two sets of methods are not mutually exclusive). The main techniques that we have used to study declarative knowledge are: ratings; sorting; diagramming (using both concept maps and GST hierarchy diagrams); and laddering. For the study of procedural knowledge we have employed the following techniques: action sequences; verbal concurrent protocols (both think aloud and constructive interaction); and teach-back. In order to illustrate how these techniques are used, a short description will be given of one of the studies that we have undertaken relating to the domain of word-processing.

Within educational environments, computer-based text-editing and word-processing systems are important from two major perspectives. First, as systems which are widely used by many people to create electronic documents; and second, from a more academic stand-point (because of their intrinsic interest), as objects of study in their own right. Therefore, because of their importance, we decided to explore the types of mental model that students created as a consequence of their exposure to different kinds of interactive text-editing and word processing systems. In particular, an in-depth study was made of students' use of Microsoft's 'Word for Windows' system - with a view to collecting experimental data that would support (or indeed, refute) the 'mental model hypothesis' (Barker and van Schaik, 1999). Essentially, this states that within any given domain of activity, the richness of a person's mental models directly influences his/her quality of task performance in that domain. In other words, someone (an expert) who has a rich and powerful set of mental models (relating to a given task domain) will show much greater creativity and diversity with respect to problem solving than someone (a novice) that has only weak or non-existent knowledge structures.

Our Word for Windows study was conducted in two phases. First, students' mental models were measured using the techniques described above (ratings, sorting, laddering, teach-back, and so on). Then, their performance 'on task' was measured by giving them a problem to solve - preparing an invoice for an imaginary company. Each student's result was 'marked' and rated in relation to 'expert performance'. A statistical analysis was then conducted in order to look for correlations between each student's task performance and his/her mental model measurements. As we discuss elsewhere (Barker and van Schaik, 1999), the results from our study support the mental model hypothesis.

In addition to studying students' mental models of particular subject domains, we have also conducted various studies that were aimed at exploring their perceptions of the educational system and the mental models that they had of their university courses. We have been particularly interested in exploring students' expectations of the university system and their views about their roles as students. The motivation for this work arose from two sources. First, our interest in wanting to investigate students' views about and attitudes to lifelong learning (Barker, van Schaik and Hudson, 1998); and second our desire to improve the educational experiences of our students through the appropriate use of network technologies. The implications from this latter study are briefly described in the following section.

4. IMPLICATIONS FOR NETWORK PEDAGOGY

It was our intention to use the outcomes from the mental model studies (described in the previous section) as a mechanism for deriving a set of guidelines that would help us to design and create more effective interactive learning environments. In turn, we were hoping that these environments would help us to develop and build new types of university course (in the short term) and, in the future, that they would enable us to create new types of university system (Barker, 1998). At the time of our initial research, the obvious enabling technologies to support these types of development were in-house and global computer network systems (Barker, 1999). We anticipated that these could form a sound basis for the design and development of an approach to network pedagogy that was based on the appropriate use of electronic 'teaching webs'. We thought that such webs could be used to improve the quality of students' learning experiences in five important ways. First, by attaching less importance to instructivist teaching environments - while, at the same time, giving greater emphasis to environments that are based on constructivist approaches to learning. Second, by providing electronic environments that would facilitate the creation of learning communities in which students could organise 'self-help' networks. Third, by providing greater access to academic staff through electronic networking. Fourth, by providing students with access to automated self-assessment and course monitoring mechanisms and, finally, (because all resources would be available in electronic form) ensuring that students could access course materials in more effective ways than they have been able to in the past.

We have built a number of prototype teaching webs that embody the above principles. We are currently involved in developing an operational system to support the teaching of human-computer interaction (HCI) within a modular university degree course. The electronic 'HCI Teaching Web' is based on our departmental intranet and can be accessed by any computer terminal that is attached to the local network. It can also be accessed globally using the Internet (by those who have appropriate access rights). All course materials are then available electronically; apart from the final examination, the 'HCI Teaching Web' represents a totally 'paperless' course. Students are encouraged to download the teaching web to their own machines and then augment and expand it in ways that are appropriate to their own particular interests.

CONCLUSION

Mental models are an important aspect of all human behaviour, especially teaching and learning activities. When designing new courses and new educational systems it is important to consider the nature of the skills and mental models that students are to acquire from the experiences to which they are exposed. This knowledge should then be used to create suitable learning environments based upon the appropriate use of network technologies. Such technologies are important because they can support the development of rich mental models as a result of both individual and collaborative learning experiences that are based on the principles of constructivism.

REFERENCES

Barker, P.G., (1998). The Role of Digital Libraries in Future Educational Systems, 301-310 in Online Information 98 Proceedings, Edited by D. Raitt, Learned Information Europe Ltd, Oxford.

Barker, P.G., (1999). Using Intranets to Support Teaching and Learning, Innovations in Education and Training International, 36(1), 3-10.

Barker, P.G. and van Schaik, P. (1999). Mental Models and Their Implications for the Design of Computer-Based Learning Resources, paper to appear in 'Proceedings of the 4th International Conference on Computer-Based Learning in Science' (CBLIS '99), University of Twente, Enschede, The Netherlands, 1-6 July, 1999.

Barker, P.G., van Schaik, P. and Hudson, S.R.G., (1998). Mental Models and Lifelong Learning, Innovations in Education and Training International, 35(4), 310-318.

Barker, P.G., van Schaik, P., Hudson, S.R.G. and Tan, C.M., (1998). Mental Models and Their Role in Teaching and Learning, 105-110 in Proceedings of ED-MEDIA & ED-TELECOM 98 - 10th World Conference on Educational Multimedia, Hypermedia and Telecommunications, June 20-25, Freiburg, Germany, Edited by T. Ottman and I. Tomek, Association for the Advancement of Computing in Education, Charlottesville, Virginia, USA.

Bates, W., (1998). A Framework for Multimedia Based Virtual Laboratory Experimentation, PhD Thesis, University of Bristol, Bristol, UK.

Brooks, D.W., (1997). Web-Teaching: A Guide to Designing Interactive Teaching for the World Wide Web, Plenum, New York.

Corritore, C.L. and Wiedenbeck, S., (1999). Mental Representations of Expert Procedural and Object-Oriented Programmers in a Software Maintenance Task, International Journal of Human-Computer Studies, 50, 61-83.

Faulkner, C., (1998). The Essence of Human-Computer Interaction, Prentice-Hall, London.

Fuchs-Frohnhofer, P., Hartmann, E.A., Brandt, D. and Weydandt, D., (1996). Designing Human-Machine Interfaces to Match the User's Mental Models, Control Engineering Practice, 4(1) 13-18.

Laurillard, D., (1993). Rethinking University Teaching - A Framework for the Effective Use of Educational Technology, Routledge, London.

Eisenstadt, M. and Vincent, T., (1998). The Knowledge Web: Learning and Collaborating on the Web, Kogan Page, London.

Rogers, Y., Rutherford, A. and Bibby, P.A., (1992). Models in the Mind - Theory, Perspective and Application, Academic Press. London.

Staggers, N. and Norcio, A.F., (1993). Mental Models: Concepts for Human-Computer Interaction Research, International Journal of Man-Machine Studies

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