THE ROLE OF KNOWLEDGE AND INFORMATION IN DESIGN DECISION-MAKING

Reasoned choices and evaluation are often based on values but, although values are an important basis for making a judgment, the use of relevant conceptual knowledge is needed in order to weigh the advantages and disadvantages of the available options (Perkins and Salomon, 1989; Sadler, 2004). Piaget (1972) theorized that individuals tend to reason at more sophisticated levels in areas in which they have more knowledge. If the nature of designing is related to decision-making on technological issues, as is commonly assumed, then from Piaget‘s theory it follows that those who understand the nature of technology should reason differently on those issues than those who do not.

According to Kimbell (2005), the role of knowledge in design and technology has always been tricky. Polanyi (1962) described the way that people handle various ideas and information around them utilising their ability to operate with ‗tacit‘ knowledge. Which is to say (e.g.) that the way builders choose cross sections of material was not based on explicit, formally constructed mathematics, but by operating on their tacit understanding of what works.

Sadler (2004) concluded that given the fact that technological issues often involve ideas from the frontiers of research, most people must rely on outside sources of information to form positions regarding these issues. He went on and suggested that information of this type is transmitted to decision-makers through a variety of sources including newspapers, magazines, the Internet, politicians, teachers, friends, and family. Research on how people evaluate information pertaining to technological issues suggested that most individuals are ill-prepared for the task (Perkins et al., 1991; Sadler, 2004).

Clemen (1991) argued that in order to improve knowledge information is required and as a result to make good decisions. Not all information, though, is of the same quality or relevance for the decision that needs to be made. Clemen (1991) pointed out that this is an important matter, because many curricula, asking children to make decisions, assume an innate capability to distinguish between useful and irrelevant, or even incorrect, data.

Sadler et al. (2004) suggested that information evaluation needs to be a strong component of scientific and technological issues curricula and instruction. Some studies argued that many children require direct instruction in how to use strategies for evaluating scientific reports as well as experiences in discriminating between scientific evidence and other forms of information (Kolstø, 2001b; Korpan et al., 1997; Perkins and Salomon, 1989; Tytler et al., 2001).

Jimenez-Aleixandre and Pereiro-Munoz ( 2002) suggested that when dealing with problem solving, in order to make a decision, it is important to identify which knowledge is relevant for the problem, and which sources are reliable. The next step would be a synthesis of the different areas or fields of knowledge that are considered both relevant and reliable. Ratcliffe (1996) explored the development of information processing and analysis as one important strand in decision-making, showing the difficulties in increasing the use of an information base and calling for a careful assessment of children‘s abilities before grouping them.

Kolstø (2001a) performed a qualitative study to detect the manner in which children evaluate information and knowledge in socio-scientific decision-making. From his findings, the children based their judgments on two factors: the informational statements themselves or the authorities who provided the information. Children accepted or evaluated the information, or they accepted or evaluated the source of information (Kolstø, 2001a).

Several teaching models for thoughtful decision-making for use in education have been

proposed (Aikenhead, 1985; Geddis, 1991; Kolstø, 2000; Ratcliffe, 1996). Ideally such teaching models should build on knowledge of the strengths and weaknesses in children‘s decision-making. However, only a few studies have explored the kinds of knowledge children draw upon, and how they actually apply this knowledge, when confronted with technologically controversial social issues (i.e. Fleming, 1986a, 1986b; Ratcliffe, 1996).

Gilbert (1991) pointed out that when children face decision-making problems they usually solve the problem by empirical knowledge, which exists apart from scientific knowledge and this sometimes does not produce the best consequences.

Venville, et al. (2004) investigated the sources of information that children employ while working with design activities. The trials performed during class were frequently used as a source of knowledge by children and gave them critical information to make decisions about their designs.

Designs that children had used in previous years were used as an important source of knowledge by some of these children. This process of networking, using other children and people outside the class as sources of information, is similar to Roth (1998) descriptions of learning communities. The teacher was a respected source of information and was well used by children at one time or another in the design project.

The importance of knowledge and understanding in design and technology education had been identified as an area of concern by a number of authors (De Vries and Tamir, 1997;

Herschbach, 1995; Pavlova, 2005a). De Vries and Tamir (1997) argued that ‗‗the epistemology of technology is by no means yet a fully developed area‘‘ (p. 7). Herschbach (1995) also stated that: ‗‗it makes little sense to talk about curricular strategies until the epistemological dimensions of technological knowledge are first determined.‘‘ (p. 32).

From the introduction of design and technology education many researchers have attempted to identify an official and formal body of knowledge for particular areas of design (Norman, 1998).

This knowledge aims to develop technological literacy, i.e. what a child needs to be familiar with for the practice of technology. An important part of the definition of this knowledge belongs to the application of concepts and skills in order to solve certain types of technological problems.

According to Kimbell (1994) the term ‗capability‘ was introduced to capture the practical, conceptual and procedural dimensions of technological knowledge (Kimbell et al., 1996).

Vincenti (1984) divided technological knowledge into three types: (a) descriptive, (b)

prescriptive, and (c) tacit. The first two types are varieties of explicit technological knowledge.

Tacit knowledge is implicit in the activity of the person, and it is the outcome of an individual‘s judgement, skill and practice (Polanyi 1962). Tacit knowledge cannot be easily expressed formally. It is personal knowledge; it is subjective knowledge. It is transmitted mainly from one individual to another.

Herschbach (1995) argued about the development of tacit knowledge: ‗‗tacit knowledge is primarily learned by working side by side with an experienced technician or craftsman. Tacit knowledge is embedded in technological activity to a greater extent than is normally recognized.

In addition, tacit knowledge has not disappeared with the use of more sophisticated ways of manufacturing based on the application of science and descriptive technical knowledge‘‘

(Herschbach, 1995, p. 36). Polanyi (1967) suggested that all human action involves some form of tacit knowledge.

Herschbach (1995) claimed that descriptive knowledge ―represents statements of fact which provide the framework within which the informed person works, such as material properties, technical information, and tool characteristics. These facts are often applications of scientific knowledge‘‘ (p. 34). He further argued that descriptive knowledge approaches an approximation of the formal knowledge of a ‗‗discipline‘‘ since it describes things as they are. It can be in the form of rules, abstract concepts and general principles, and it often has a consistent and

generalizable structure. Like all technological knowledge, however, descriptive knowledge finds its meaning in human activity.

McCormick (2004) attempted to define the nature of technological knowledge with an emphasis on two basic types of technological knowledge: procedural and conceptual.

• Procedural knowledge includes such things as: design, problem solving, planning, systems analysis (or systems approach), optimisation, modelling, strategic thinking (heuristics, algorithms and metacognition).

• Conceptual knowledge: for example, systems concepts (McCormick, 2004).

When designing, designers and children apply knowledge from a wide range of areas. The exact form of knowledge needed by designers is currently under debate. Hicks et al. (1982) stated that designers often require information from other disciplines when making decisions.

According to Norman (1998), the information used by designers could be obtained from various sources but only when information is processed in designers‘ minds does it become knowledge.

Technological knowledge could be considered as a component of technology relevant to a particular design area (Norman, 1998). The relation of technological knowledge with scientific knowledge has been identified by many researchers (Hicks et al., 1982; Layton, 1993). Some of them identified technology as being applied science and therefore scientific knowledge being

very important in technology. Hicks et al. (1982) made a connection of technological knowledge with knowledge from other disciplines.

―Designers are continually called upon to make decisions which require information from other disciplines. The form in which this information is needed means that the questions may differ in kind from questions which would arise from a study of those disciplines themselves. For example, although scientific information may be needed when designing, the form in which it is needed requires the generation of new concepts – i.e. technological concepts‖ (Hicks et al., 1982, p 5).

Norman (1998) argued that the above statement about the reformulation of knowledge for practical action could sometimes be misleading, because practical actions can be guided by both tacit knowledge and conceptual knowledge. Norman (1998) pointed out that design

decisions are developed through cognitive modelling, and hence the use of tacit knowledge can be considered likely. According to Archer and Roberts (1979), ―the existence in man of a

distinctive capacity of mind is analogous with the language capacity and the mathematical capacity‖ (p. 55), and this adds to the complexity of understanding design decision-making.

Within the literature there are differing interpretations about the nature of technological knowledge. This causes difficulties in defining technological concepts to be introduced to children. Technology relies on multiple knowledge bases but these can neither be identified nor can technology be reduced to them (Salomon, 1995). A restricted view of technological

knowledge limits children‘s learning in technology by considering only some aspects. According to Perkins and Salomon (1989), it is important that a more coherent picture of technological knowledge is developed. The translation and transfer of knowledge and skills is required in technological practice. Teaching for transfer is difficult but there is some evidence that it is possible (Perkins and Salomon, 1989).

De Vries (2003) explained how many categories of technological knowledge have a normative nature. Hence they are, for example; effective, or ineffective; good, or bad. Pavlova (2005a) argued that knowledge is relative, based on a person‘s experience and directed by human needs and wants and as a result, the use of such knowledge needs the existence of values.

She went on and claimed that is not sufficient to develop a coherent analysis of technological knowledge as it cannot be free from interests, desires and values (Pavlova, 2005a).