Instructional Science 16:215-231 (1987) 215 © Martinus Nijhoff Publishers (ICduwer), Dordrecht - Printed in the Netherlands

Enhancing children's thinking skills: an instructional model for decision-making under certainty

R U T H B E Y T H - M A R O M 1, R U T H N O V I K 2 & M I C H E L E S L O A N 2 1. Everyman's University----The Open University of Israel, 16 Klausner Street, Tel-Aviv, Israel. 2. Israeli Science Teaching Center, Center for Curriculum Research & Development, School of Education, Tel-Aviv University.

Abstract Modem society is characterized by rapid change, an overload of information, an interrelation between once distinct fields (science, technology and society) and a growing rec- ognition of the importance of personal and social values. In such a dynamic society the teach- ing of facts becomes less vital while the teaching of thinking skills turns out to be indispensable. Educators have recognized the need for curricula devoted to thinking skills in general and attempts to attain this goal have already been made. However, almost no attention has been given to teaching children the very important and daily used skill of decision- making under certainty. In the present paper we propose a framework for developing school material which cultivates decision-making skills. This framework is a tripartite model which describes (a) the general strategy an ideal decision maker should adopt, (b) the underlying cog- nitive skills needed for that strategy and (c) the educational objectives for the promotion of each cognitive skill mentioned.

I n t r o d u c t i o n

" G i v e m e a fish and I eat for a day; teach m e to f ish and I eat for a l i fe t ime." (Serf,

1981)

T h e a b o v e quota t ion descr ibes id iomat ica l ly the d i f fe rence b e t w e e n " W h a t " and

" H o w " in educa t ion . T h e p resen t paper descr ibes the first step in d e v e l o p i n g a

schoo l cu r r i cu lum d e v o t e d to the " H o w " facet o f learning. Spec i f ica l ly , w e shall be address ing the ques t ion o f " H o w to m a k e dec i s ions" and, e v e n m o r e speci f i -

ca l ly , h o w to m a k e dec i s ions w h e n no probabi l i s t i c e l e m e n t (no uncer ta in ty) is

involved .

T h e pape r beg ins by a rguing the case for a cu r r i cu lum which p r o m o t e s think-

ing skil ls in general , and dec i s ion-mak ing under cer ta inty in part icular .

Thereaf te r , a f r a m e w o r k for deve lop ing school mater ia l wh ich cul t iva tes deci-

s i o n - m a k i n g ski l ls wi l l be proposed . This f r a m e w o r k is a t r ipart i te m o d e l wh ich

descr ibes (a) the " 'normat ive H o w " - the genera l s l ra tegy an ideal dec i s ion make r

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should adopt, (b) the underlying cognitive skills needed for that strategy and (c) the educational objectives for the promotion of each cognitive skill mentioned.

Finally, an evaluation of the model will be made by analyzing its possible contributions to the process of curricula development and implementation.

The need for training in thinking skills

Modern society is characterized by rapid change (Chen and Novik, 1984), interrela- tions between once distinct fields (Ellul, 1963), a growing recognition of the importance of personal and social values (Thelen, 1983), an overload of informa- tion (Bell, 1978; Carroll, 1971) and an uncertain future. This makes it inexpedient to teach learners only facts. Facts relate to the past and present; they usually do not relate to an uncertain future, especially in a dynamic society. Furthermore, by the time the student has mastered and absorbed a set of facts, new developments may have already occurred and those facts may be outdated.

In addition to supplying students with information, we have to teach them how to "analyze information, synthesize it and apply it in a value-oriented way" (Lewis, 1983). Education for the future must "attempt to assist individuals in developing 'internal anchors' which will permit them to survive and to promote the survival of society regardless of terms of events.., an essential such 'anchor' consists of skills with information and skills in decision-making" (Fletcher and Wooddell, 1981).

Thinking skills are necessary tools in a society characterized by rapid change, many alternatives of actions, and numerous individual and collective choices and decisions. "Thinking enables students to continually confront issues and problems with skills that will aid them in developing new ideas, making sound choices, making better decisions and understanding the w~ ,ld around them" (Seif, 1981).

The need to concentrate on thinking skills in school curricula stems both from the above-mentioned overload of information as well as the interrelation between different domains. This interdependence will affect many of our students' choices and decisions in their future roles as responsible citizens. Students need specific training in thinking, in order to reason about major societal decisions and interdis- ciplinary everyday problems.

Among the thinking skills mentioned in the literature are: scientific thinking, creative thinking, decision-making, complex system thinking, ethical value think- ing, probabilistic thinking, logical thinking, etc. (e.g. Seif, 1981; Glaser, 1984).

These skills are neither exclusive nor exhaustive. There exists a great deal of overlap between many of these skills and most of them have not even been clearly defined. Several of them cannot be taught without prerequisite mastery in others. However, all these skills, as well as others which have not been mentioned, are necessary for functioning in modern society.

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The need for the acquisition of thinking skills has become an educational imperative in modern technological society. Recognition of this need is shown by current trends in Education and Psychology, and is expressed in research efforts and theories as well as in applied experiences.

In a review paper, Robert Glaser described the "emerging field of Instructional Psychology in terms of four major components" (Glaser, 1982):

- The nature of the competence to be attained.

- The initial state of the learner.

- The transition processes between these two stages.

Ways of assessing and monitoring performance changes in the acquisition of competence. Instructional Psychology today, with its emphasis on competence and pro-

cesses, has affected the entire approach to teaching. A new approach to teaching has emerged - "Cognitive Process Instruction" - which emphasizes understanding, learning and measuring skills as opposed to rote memorization of factual knowl- edge (Lockhead and Clement, 1979).

Three basic questions face the cognitive process instructor:

What thought processes are actually used by students (the "initial stage")

What thought processes ought to be used by students, i.e., what is a "good habit" of thought (the nature of the competence)

What educational strategies are most likely to help students move from their actual habits to better habits of thought (the transition process). Theoretical developments in Instructional Psychology and their potential

effects on teaching have channelled research efforts in education and psychology towards the following major question: "How do we think?" This general question has been attacked from different angles:

What are some of the early intuitions (before any formal education) children and adults have with regard to: (1) physical concepts such as movement (e.g. McCloskey, Caramazza and Green, 1980), energy (Solomone, 1983), time (Levine, 1982) and density (Strauss et al., 1983); (2) statistical concepts such as the arithmetic average (Strauss et al., in press) or probability (e.g. Kahneman and Tversky, 1973) and (3) biological concepts like natural selec- tion (Brumby, 1984)

How people think under uncertainty (e.g. Kahneman, Slovic and Tversky, 1982) and what is the quality of their deductive reasoning (e.g. Evans, 1982)

When and under what conditions are laymen "good thinkers" or "bad thinkers", relative to a normative model. All these questions and others have been studied. Some of the answers have

already been applied in developing new curricula devoted to thinking skills.

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Nickerson et al. (1985) classified existing curricula which are devoted to the enhancement of thinking skills into five broad categories: (a) Those that focus on the teaching of certain basic cognitive processes or skills that are assumed to be essential to, or components of, intellectual competence (e.g. Feuerstein's Instrumental Enrichment Program, 1980); (b) Those that emphasize certain explicit methods that are presumably applicable to a variety of cognitive tasks, and that teach these methods outside conventional subject matter courses (e.g. Whimbey and Lockhead's Analytical Reasoning Program, 1981); (c) Those for which the objective is to promote formal operational thinking within the context of specific conventional subject matter courses (e.g. the COMPAS course Consortium for Operating and Managing Programs for the Advancement of Skills by Schermerhorn et al., 1982); (d) Those that emphasize symbol manipulation skills (e.g. The LOGO language, Feurzeig et al., 1969); and (e) Those that focus on thinking-about-thinking (e.g. Lipman's Philosophy for Children, 1980).

In the list of curricula devoted to the different thinking skills, Nickerson et al. do not mention even one which is solely aimed at the improvement of decision- making skills. These skills are, however, mentioned as a small fragment of a gen- eral program in "Project Intelligence", a program to teach thinking skills in the Venezuelan secondary school system (Adams et al., 1982), and in two courses for college students: "A Practicum in Thinking" (Wheeler and Dember, 1979) and "The Complete Problem Solver" (Hayes, 1981).

Why decision-making?

Despite the importance of decision-making as a cenlxal and essential function in human behavior and the frequency of its use, there is little research aimed at teach- ing students how to decide. In other words, students undergo almost no instruction which promotes their ability to choose from among several possible courses of alternative actions, even when they have full information about each choice (deci- sion-making under certainty).

Modern technological society is characterized by problems which incorporate variables related to science, technology and society. These problems cause much public conlroversy since pure scientific considerations often tend to favor a certain alternative of action, while pure societal considerations often favor different ones.

Thus, reaching a consensus with regard to such multidimensional issues neces- sitates the acquisition and application of decision-making skills. In an age where every citizen is confronted with such multidimensional controversial issues, deci- sion-making cannot be allocated to a select elite of technocrats, scientists or engi- neers. Decision-making skills must be regarded as an essential component of every man's literacy and must be equated with coping skills.

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What are these decision-making skills? In the process of developing a Decision-Making Instructional Model, it becomes apparent that good decision- making is a system comprised of various cognitive skills. Some of these skills have been treated separately and have been viewed as serving different purposes in the past. Efficient decision-making requires skills such as value clarification, oper- ational thinking and classification, to mention but a few. One has to master a number of cognitive abilities before gaining mastery in decision-making. Moreover, these underlying cognitive abilities are important tools in their own right. Some of them (e.g. classification, value clarification, the ability to relate to two variables simultaneously) are frequently applied in situations which are not necessarily related to any decision-making activity.

Let us illustrate this point with two examples. A child wants to organize his library so that he will be able to find any book he needs in a short space of time. The child will achieve this more efficiently if he is acquainted with some of the principles underlying good classification (exhaustiveness, exclusiveness, etc.) than if he is completely ignorant of them. Any evaluation, whether of a book, movie, project, or even a friend, requires both the simultaneous consideration of several variables and some elements of value clarification.

Although several recent research programs have offered suggestions for moving school curricula in a direction which would promote decision-making skills (Berman, 1979; Horowitz, 1971; Peterson, 1979; Pulmey, 1970; Roderick, Moyer and Spodak, 1971), none have presented a systematic model which can be examined, evaluated and implemented in modem curricula.

Berman (1979) has enumerated a number of broad suggestions for the promo- tion of decision-making skills, such as:

Breaking away from the "right-wrong syndrome" which rewards quick solutions and limits the child's willingness to search for alternative solutions to problems.

Encouraging the ability to recognize and state the unknown together with the known.

Encouraging the ability to pose questions which would lead to new information and alternative solutions. Horowitz (1971), Poulmey (1970), and Roderick, Moyer and Spodak (1971)

have found consistently that the influence of the peer-group is highly significant in promoting children's decision-making behavior.

Peterson (1979) established an activity center where groups of students work independently on original problems, solving tasks such as: Make a filtration sys- tem for sand from muddy water. How clear can you make the water? Make up intelligence tests for a snail, a mouse and a rabbit (without hurting them).

These research programs are helpful in providing broad practical suggestions for directing curricula programs toward the promotion of decision-making skills.

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However, they neither analyze the cognitive abilities underlying decision-making behavior, nor do they provide systematic analyses of these processes in terms of educational objectives. It seems to us that the latter is the strategy we must adopt if we are to develop a systematic and complete instructional program for the pro- motion of decision-making skills.

In the present paper, an attempt will be made to extrapolate from the norma- tive model to (1) a systematic representation of the cognitive processes involved in decision-making, and (2) to the educational objectives involved in decision- making instruction. Thus, the present paper represents an outline of a model of decision-making instruction.

A decis ion-making instructional model

The development of any educational curriculum requires answers to two primary questions: (a) What are the educational goals? Co) How are these goals to be achieved? In a curriculum devoted to the enhancement of decision-making skills these two generalized questions take the following form: (a) What are the cogni- tive abilities involved in the process of decision-making? Co) What educational objectives are necessary for the acquisition and promotion of these cognitive abilities?

An answer to the f~rst question would be dictated by a normative model which describes the steps one should take in a decision situation. Thus, the following model (presented in Table 1) is comprised of three parts. The first part deals with the normative domain, namely describing five steps one should take when making a decision. In the second section, the cognitive abilities underlying each step (1- 13) have been extrapolated. Finally, the third section represents an attempt to identify the educational objectives toward the promotion of these cognitive abilities.

The normative model

Decisions are not all of one type. Normative procedures for making one decision (e.g. Which car should I buy?) may be inappropriate for making another decision (e.g. What should we do this coming week-end?). Thus, the literature on decision- making in general offers a number of normative models and these attempt to address the specific needs of the various prototypes of decision questions and the decision situations underpinning them.

In the literature, an important distinction exists between decisions under cer- tainty and decisions under uncertainty, risk or conflict. Decision situations under certainty are those in which the task of the decision maker is to determine which

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of the alternatives of action is preferred, knowing in advance all the major out- comes of each alternative. After one alternative has been chosen, its outcomes are always the ones predicted by the decision maker: there is no element of surprise. However, under situations of uncertainty, risk or conflict, the outcomes of the alternatives considered, and the one Finally chosen, are uncertain (probabilistic). The outcomes of the choice made may surprise the decision maker, since these outcomes were not predicted with certainty but with only some measure of confidence.

Although these two states of certainty and uncertainty may seem completely different, they have much in common. In both states the decision maker has to define the problem, list the alternatives of action and compare them on different dimensions (e.g. cost, benefit, effort, etc.). The main difference between the two states is in the probability factor. The process of decision-making under uncer- tainty, risk or conflict requires the consideration of the probability elements involvecL These elements must be detected, estimated and combined with all other relevant considerations.

Although most of our everyday decisions (private as well as public) contain uncertain elements which require probability considerations, in the present paper we have chosen a model suitable for decisions under certain situations. The ratio- nale for this choice lies in the many common characteristics the two models share, as well as the difficulties inherent in the probability factor.

In the last twenty years, psychologists have gathered evidence showing the dif- ficulties people have in assessing probabilities and incorporating them in the deci- sion-making process (e.g. Kahneman, Slovic and Tversky, 1982). Nonetheless, efforts have been made both to assert the importance of teaching probability assessment as well as to teach students these skills (Beyth-Marom et al., 1985). However acquisition of skills in probability assessment, in the context of deci- sion-making, can be taught only after the learner has acquired some of the primary and prerequisite cognitive abilities involved in the model of decision-making under certainty, as presented in this paper. Just as knowledge of addition is a prerequisite for the acquisition of multiplication skills (accompanied by understanding of those skills), so too knowledge about decision-making under certainty is a prerequisite for the acquisition of skills (accompanied by understanding) associated with deci- sion-malting under uncertainty.

Even for decision-making under certainty, several models are suggested in the literature. Most of the stages recommended are similar (defmition of the problem, listing of alternatives, search for relevant dimensions within which the alterna- fives should be compared, etc.), but they differ in their final stage, namely, in the criterion adopted for determining which alternative should be chosen. Thus, the normative models for decision-making under certainty do not differ in the type of data gathered and its organization but, rather in the form in which the data are weighted and combined in order to reach a decision. These differences between the

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normative models (in their final stage) do not limit the development of an instruc- tional model which is guided by the common aspects of all normative models regarding most steps in the decision process.

We chose to leave the final stage of the decision-making process to the deci- sion maker 's intuitions with no detailed guidance. Thus, we did not have to com- mit ourselves to any specific normative model. Furthermore, the f'mal stage of the decision-making process - the weighting and combining of the data - is compli- cated in all normative models. In our opinion, the loss associated with the diffi- culties in teaching and learning it will be much greater than the potential gains in

following some normative prescriptions for weighting and combining the data. This opinion is founded on our belief that the gap between the performance of a naive uninstructed decision maker, and that of an expert who is using a normative model is already very wide in the ftrst stages of the decision process. Much can be done to improve the performance of a decision maker in the search for data and its organization and evaluation, thus providing him or her with a better representation of his decision problem, one which reflects all relevant information and his own value system, and enabling him to complete the decision-making process intuitively.

The decision-making instructional model

The instructional decision-making model shown here (Table 1) presents details and elaborations of the steps, cognitive abilities and educational objectives necessary for developing a curriculum aiming at improving decision-making skills. However, since this model exemplifies a long and sometimes complex process needed to reach a sound decision, it is not expected of any person to use that elab- orated model in all the decision situations which are encountered on a daily basis. The utilization of the model depends on a person's subjective judgment as to whether the decision problem is worth the effort of undergoing this detailed process.

Table 1 consists of three columns: the Normative Model, Cognitive Abilities and the Educational Objectives. As seen in the first column, the decision maker 's initial task is to define the problem. In everyday language, concepts and terms whose meanings are often unclear or ambiguous are used. In most cases there is no need for exact definitions of the expressions used. However, for effective group or individual decision-making, all terms in the problem statement should be clearly defined; otherwise irrelevant information may be gathered which might pre- vent the choice of the best alternative.

In our view, the stage of defining the problem involves two main cognitive abilities. First, the decision maker must possess the ability to judge the clarity of the variables (shown as (1) in Table 1), namely, to determine the extent to which there is a need for more precise definitions. In order to achieve this capability, the

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Table 1. The decision-making instructional model

Normative Model Cognitive Abilities Educational Objectives

I) Define the problem

H) List possible alternatives for action

1) Ability to judge clarity of variables

2) Ability to define operationally

3) Ability to identify alternatives

4) Initial filtering of alternatives according to reality

5) Ability to classify alternatives, if necessary

6) Perception of delay in taking a decision as an additional alternative

la) Identification of variables lb) Identification of different meanings of variables

2a) Perception of possibility to define variables in many ways 2b) General ability to distinguish between operational and non- perational definitions 2c) Construction of operational definitions which adequately describe a procedure, concept or property of an object in context used 2d) Se]ection of most relevant and appropriate definition from amongst several

3a) Identification of as many different ahemat ives as possible.

4a) Perception of feasibility of alternatives

5a) Identification and naming of relevant criteria usable for classifying ahemat ives 5b) Identification of similarities and differences between alternatives 5c) Perception of the possibility to construct several classification schemes based on different properties and serving different purposes 5d) Construction of one or more different classification schemes 5e) Construction of classification schemes which are exhaustive, exclusive and operationally defined 5 0 Choice of one classification scheme which is most suitable for a specific problem

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Table 1. The decision-making instructional model (continued)

Normative Model Cognitive Abilities Educational Objectives

IT]') List relevant 7) Ability to identify all 7a) Like 3a dimensions for relevant dimensions assessment of alternatives or classes of altematives

IV) Evaluation of dim- ensions and alternatives (Construction of a matrix of alternatives and dimensions)

V) Weighting and deciding

8) Ability to define operationally relevant dimensions

9) Ability to rank dimensions according to personal preference or importance (list dimensions vertically)

10) Ability to rank all ahematives on each dimension separately, after listing the altemadves horizontally

11) Ability to search for one blatandy most-preferred ahemadve, if it exists. If not, see 12

12) Ability to eliminate least-preferred alternatives

13) Ability to choose most-preferred alternative from amongst those remaining

8a-Sd) Like 2a-2d

9a) Significance of relating to subjective value system 9b) Clarification and application of own value system

10a) Construction and reading of a matrix 10b) Judgment and ranking of alternatives on a specific dimension independent of the other dimensions 10c) Repeat 10b for each dimension

l l a ) Change of focus of attention (expressed in necessity to move from a horizontal to vertical focus in the matrix) 1 lb) Recognition of blatantly most-preferred alternative

12a) Recognition of blatantly least-preferred alternative(s) (if they exist) and elimination from further consideration.

13a) Relating simultaneously to two variables (alternatives and dimensions) 13b) Awareness of the difficulty in comparing remaining alternatives: for each dimension, a different alternative may be preferred 13c) Awareness of personal considerations affecting weighting and choice

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instructional objectives must ensure that the learner can isolate the variables in a problem situation ( la in Table 1) and identify possible different meanings of these variables (lb). Secondly, the learner must be able to construct operational deFini-

tions of the identified variables (2). Operational definitions are a guard against the possibility of attributing several meanings to the variables. This can best be achieved by-creating divergent settings in which the learner can explore and become aware of the possiblity that identified variables may be defined in various ways (2a). Thereafter, it is important that the learner understands the distinctions between operational and non-operational definitions (2b) and be able to construct

appropriate operational definitions which will adequately describe the procedures, concepts, objects or properties of objects which are to be described within the problem situation (2c). It should be possible now to select the most relevant and appropriate definition (2d), from amongst all those found relevant for an identified variable.

The second stage in our model of the decision-making instructional process is

the listing of all possible alternatives for action. For illustration, a hypothetical problem will be examined. Let us assume that a certain amount of money has been allocated for the construction of a new major power plant in Israel. The prob- lem facing the decision makers is "Where should this power plant be built?" After careful and detailed definition of the problem a search for alternative solutions is necessary.

Possible alternatives include all those areas in which the proposed plant will fit in with the existing power plant network and will have basic facilities for the working of the plant. Listing all the possible alternatives necessitates the ability to identify and list as many relevant alternatives as possible (3), while taking into consideration the feasibility of each alternative (4). Unfeasible alternatives must be disqualified from the start, and the remaining ones classified, if necessary, in a coherent useful manner. An attempt was made to analyze and identify the abilities for classification viewed as educational objectives in the classroom (5a - 5f). The above example demonstrates the fact that classification of alternatives is not always a necessary step. Where the number of alternatives is small (e.g. Eilat, Hadera, Tiberias or Rosh Hanikra as possible locations for a power pianO, classi- fication can be avoided. Thus, the necessity for classification depends on the nature of the problem and the number of alternatives.

We have included in the model an ability which is often overlooked in deci- sion-making situations - that of delaying the decision as an additional alternative (6). In many cases, the decision maker concludes that he cannot decide at the present time and chooses to postpone his decision. This delay, however, is often decisive in itself. For example, if the decision maker decides to delay the choice of location for the power plant, the money may be allocated for a different purpose in the new budget, and it will not be available for the power plant at all, thereby eliminating the possibility of constructing the power plant altogether - anywhere.

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The third stage is listing as many relevant dimensions as possible for the assessment of the alternatives or classes of alternatives. Dimensions are all those criteria which the decision maker may use in order to evaluate the different alterna- tives. Again, this involves the ability to identify as many relevant dimensions as possible (7). For example, in the case of the choice of location of the power plant, the decision maker may list the following dimensions: number of consu- mers who will benefit from the plant, availability of fuel supply, proximity to areas in which pollution should be minimized, etc.

Each alternative will later be assessed for each of the dimensions chosen. However, before an actual assessment can take place, it is important for the deci- sion maker to clarify what exactly is meant by each dimension. This necessitates delineating relevant operational definitions for each dimension (8). In our hypo- thetical example, the decision maker may define proximity to populated areas as the distance in kilometers between the suggested location and the outskirts of the nearest settlement containing at least 50 families.

The most efficient way to evaluate available relevant information collected to this point, is by the construction of a two dimensional matrix of alternatives vis-

a-vis dimensions (see Figure 1). This will allow for a cross-evaluation of each alternative on each dimension. The construction of the matrix is dependent upon the ability to rank the dimensions according to personal preference, importance or desirability (9). This ability depends on the decision maker's understanding of the relevance of his own value system to that ranking (9a) and of the importance of clarifying it and applying it properly (9b). (The dimensions are listed vertically in the chosen order. Thereafter, the alternatives are listed horizontally to form a two

dimensional matrix). At this stage, all alternatives must be ranked on each dimension separately

according to the decision maker's preferences and information. (For the first dimension, see Figure 2).

Figure 1. Alternatives vis-a-vis dimensions for a decision regarding the location of a new power plant

A l t e m a t i v e s

Dimensions* Eilat Hadera Tiberias

Number of c o n s u m e r s

w h o will benfit

Fuel supply

Distance from populated areas

*The three listed dimensions are only examples; many more can be listed.

Figure 2. The ranking* of alternatives on the first dimension

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Alternatives

Dimensions* Etlat Hadera Tiberias

Number of consumers 3 1 2 who will benfit

Furl supply

Distance from populated areas

1-most desirable.., n- leas t desirable

The form of expression of the ranks may be numerical, verbal, or a combina- tion of the two. However, for each dimension, a unified form must be kept. The form of expression is determined by the specific problem, the preference of the decision maker and the decision maker 's intellectual level. (See Figure 3 for an example using ranking.)

The last step is the weighting of the different ranks given to every alternative on each dimension in order to reach a final evaluation of that alternative vis-a-vis the other alternatives. This process requires an ability to focus one's attention on the vertical columns in the matrix. The vertical columns represent the decision maker 's evaluation of the alternative across all dimensions.

I f the comparison between the columns shows that there is one blatantly desir- able alternative, the decision-maker can select this alternative and make his choice (11). In our example, Hadera seems to be predominantly desirable (unless fuel

Figure 3. The completed matrix

Alternatives

Dimensions* Eilat Hadera Tiberias

Number of consumers 3 1 2 who will benfit

Fuel supply 1 2 3

Distance from populated areas 2 1 3

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supply is such an important criteria, over and above all others, causing the deci- sion maker to choose Eilat). However, if this is not the case, the decision maker 's strategy must be to eliminate the least desirable alternative(s) (12) and to make his final choice from among the remaining alternatives (13). In order to promote this ability, the decision maker must possess the capability to attend simultaneously to two variables (13a) and to relate to two variables in the form in which they appear in a matrix of this type. This means that the decision maker must be aware of the fact that each dimension may indicate a different alternative as the most desirable one (13b). Despite this, the decision maker must choose one alternative on the basis of his own personal considerations (13c).

E v a l u a t i o n a n d c o n c l u s i o n

Although more and more time and effort have been devoted to the development and teaching of thinking skills in the last few years, this important field still lacks a f'trm theoretical or empirical basis for the development of school curricula. It is thus not surprising that most of the existing programs for the enhancement of thinking skills derive from lists of cognitive abilities and educational objec- fives (e.g. Lipman 's list of skills and dispositions, de Bono 's list of thinking skills). We chose to take a similar course of action with regard to decision-making skills. All the inventories in the literature, as well as our own, are the products of serious analytical processes by which the authors decomposed mental activities into components, thus contributing to the comprehension of the thinking skill involved and to its possible implementation (by way of developing a curriculum) within the educational system.

The most striking fact about the present instructional model is the large num- ber of abilities one has to acquire before decision-making can take place according to the normative model. However, even this list is not exhaustive. There remains a broad range of multifarious mental abilities necessary in every process of infor- mation search and integration which have not been mentioned in the model. Divergent thought, fluency and resistance to closure contribute to the decision- making process when defining the problem ("Is there another meaning I have not thought about?"), in listing alternatives for action ("Did I think about all possible alternatives?") and in listing the relevant dimensions ("Can the alternatives be compared on another dimension?").

In contrast to the divergent thought processes needed for the first stages of gathering and organizing the relevant information, in the final steps of the deci- sion process an ability to focus and to converge on the given evidence is necessary.

Usually the decision maker is overwhelmed with information. The quality and kind of information gathered is not uniform. Some data is observed directly, some is in the form of hearsay, and some may be evidence which is only inferred. Some

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data are relevant, others are not; some are objective, while others subjective. Thus, a decision maker must be able to evaluate the quality of information gath- ered and integrated.

Of the remaining requisite mental abilities, only those perceived as being the essence of a decision-making process as well as best depicting its uniqueness, were included in the model. Thus, no attempt was made to analyze and include all possible mental abilities involved in the various stages of the model.

How, then, should the suggested instructional model be implemented with the school curricula? There are two possible strategies: (a) The development of curri- cula devoted specifically to decision-making; (b) The interweaving of the model into those existing curricula in which decision-making is an important component.

This practical question is closely related to the more theoretical one of general vs. specific cognitive skills, for which there is a lack of consensus in the litera- ture. There is no doubt, however, that learning to solve problems requires domain- specific knowledge and strategies as well as general strategies and cognitive abili- ties. The development of the present model was based on the assumption that decision-making should not be regarded as a by-product of teaching a specific dis- cipline or subject area (like the belief that logic can be taught only by means of Latin and Mathematics). Decision-making has to be taught in its own right, as a separate field of study, which, however, can be integrated into the teaching of dif- ferent content areas.

Decision-making skills are taught as part of a curriculum aimed at improving thinking skills in "Project Intelligence", in "A Practicum in Thinking" and in "The Complete Problem Solver" (all mentioned above). In contrast, the present model was prepared as part of a curriculum project related to Science, Technology and Society 1, aimed at ensuring the scientific and technological literacy of chil- dren. Thus, in our view, decision-making should not be taught out of context but rather in a content area which is broad enough to enable the student to implement decision-making skills. Furthermore, in the context of Science, Technology and Society decision-making is often perceived as the link between the three dimen- sions and thus should be considered as an essential part of that literacy. Whether to apply a new technology to the human environment and the manner in which it is applied exemplify the role of decision-making as an interface between science, technology and society.

People who may be affected by science and technology should at least be able to understand the considerations and the processes behind the decisions regarding the implementation of new technologies. Even more important is the involve- ment of people in the decision process itself, since it is their value system which should be taken into account when decisions regarding their welfare are considered.

The existing programs (or program-components) aimed at improving decision- making skills were designed for secondary school and college students. The curric-

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ulum "Science in a Technological Society" has been developed for elementary and junior high school children. Can the children as such an early age be engaged in decision-making processes? When is the right age to teach them how to decide?

A review of the model reveals that there is no single clear and simple answer to the above question. The model involves many abilities some of which can be taught earlier, some later. Listing or classification may be taught at a relatively early age, but teaching operational definitions, or weighting of all available infor- marion, must be dealt with later on. Thus, decision-making must be taught gradu- ally, beginning with those educational objectives which can be learned by young children. Each of the cognitive abilities involved in the model is important as a general thinking tool, applicable not only in a decision-making context. Each cognitive ability can and should be applied in many areas, decision-making being only one of many. With development and promotion of increasing numbers of basic cognitive abilities, children attain a readiness for the mastery of the more complex abilities inherent in sound decision-making processes.

N o t e

"Science in a Technological Society", a curr iculum developed in the Israeli Science Teach ing Center , Center for Curr iculum Research and Deve lopment , School of Education, Tel-Aviv University.

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