Social problem solving (D’Zurilla & Chang, 2004)

25 October 2010

Life is complex and dynamic, filled with many enriching experiences. These experiences are what make life meaningful. When some experiences become bothersome and troubling, a person may feel uncertain about how to deal with them, or a person may try to cope but nothing seems to work. That is when experiences become problems. But experiencing problems and finding ways to deal with them effectively also serve to make life meaningful and promote growth and development. Even in extreme cases involving clinical dysfunction, some have argued that such individuals are experiencing “problems in living” with which they are unable to cope effectively. In that regard, social problem solving represents a broad and complex theory of how we go about solving problems in our day-to-day lives, from problems that are simple and benign to those that are complex and involve multiple causes and consequences. Social problem solving also represents a key form of intervention within contemporary psychotherapy and education, a way to better manage the demands of everyday living in a world that is often complex and unpredictable and sometimes irrational.

(D’Zurilla & Chang, 2004, p. xv)


The situations of practice are not problems to be solved, but problematic situations characterized by uncertainty, disorder and indeterminacy (Schön, 1995)

25 October 2010

The situations of practice are not problems to be solved but problematic situations characterized by uncertainty, disorder and indeterminacy. Russell Ackoff, one of the founders of the field of operations research, has recently announced to his colleagues that “the future of operations research is past” because:

Managers are not confronted with problems that are independent of each other, but with dynamic situations that consists of complex systems of changing problems that interact with each other. I call such situations messes. Problems are abstractions extracted from messes by analysis; they are to messes as atoms are to tables and charts … Managers do not solve problems, they manage messes.

Ackoff argues that operations research has allowed itself to become identified with techniques, mathematical models, and algorithms, rather than with “the ability to formulate management problems, solve them, and implement and maintain their solutions in turbulent environments.” Problems are interconnected, environments are turbulent, and the future is indeterminate just in so far as managers can shape it by their actions. What is called for, under these conditions, is not only the analytic techniques which have been traditional in operations research, but the active, synthetic skill of “designing a desirable future and inventing ways of bringing it about.”

The situations of practice are characterized by unique events. Erik Erikson, the psychiatrist, has described each patient as “a universe of one,” and an eminent physician has claimed that “85 percent of the problems a doctor sees in his office are not in the book.” Engineers encounter unique problems of design and are called upon to analyze failures of structures or materials under conditions which make it impossible to apply standard tests and measurements. The unique case calls for an art of practice which might be taught, if it were constant and known, but it is not constant.

Practitioners are frequently embroiled in conflicts of values, goals, purposes, and interests. Teachers are faced with pressures for increased efficiency in the context of contracting budgets, demands that they rigorously “teach the basics,” exhortations to encourage creativity, build citizenship, help students to examine their values. Workers in the fields of social welfare are also torn between a professional code which advocates attention to persons and bureaucratic pressure for increased efficiency in processing cases. School superintendents, industrial managers, and public administrators are asked to respond to the conflicting demands of the many different groups which hold a stake in their enterprises. Professionals engaged in research and development are not infrequently torn between a “professional” concern for technological elegance, consumer safety, or social well-being, and an institutional demand for short-term return on investment.

In some professions, awareness of uncertainty, complexity, instability, uniqueness, and value conflict has led to the emergence of professional pluralism. Competing views of professional practice – competing images of the professional role, the central values of the profession, the relevant knowledge and skills – have come into good currency. Leston Havens has written about the “babble of voices” which confuses practitioners in the field of psychotherapy. Social workers have produced multiple, shifting images of the nature of their practice, as have architects and town planners. Each view of professional practice represents a way of functioning in situations of indeterminacy and value conflict, but the multiplicity of conflicting views poses a predicament for the practitioner who must choose among multiple approaches to practice or devise his own way of combining them.

(Schön, 1995, p. 16f.)

Problem setting as an art (Schön, 1995)

25 October 2010

When leading professionals write or speak about their own crisis of confidence, they tend to focus on the mismatch of traditional patterns of practice and knowledge to features of the practice situation – complexity, uncertainty, instability , uniqueness, and value conflict – of whose importance they are becoming increasingly aware.

Surely this is a laudable exercise in self-criticism. Nevertheless, there is something puzzling about the translation of wavering confidence in professional expertise into these particular accounts of the troubles of the professions. If it is true, for example, that social reality has shifted out from under the nineteenth-century division of labor, creating new zones of complexity and uncertainty, it is also true that practitioners in such fields as management and industrial technology do sometimes find ways to make sense of complexity and reduce uncertainty to manageable risk.

If it is true that there is an irreducible element of art in professional practice, it is also true that gifted engineers, teachers, scientists, architects, and managers sometimes display artistry in their day-to-day practice. If the art is not invariant, known, and teachable, it appears nonetheless, at least for some individuals, to be learnable.

If it is true that professional practice has at least as much to do with finding the problem as with solving the problem found, it is also true that problem setting is a recognized professional activity. Some physicians reveal skills in finding the problems of particular patients in ways that go beyond the conventional boundaries of medical diagnosis. Some engineers, policy analysts, and operations researchers have become skilled at reducing “messes” to manageable plans. For some administrators, the need to “find the right problem” has become a conscious principle of action.

And if it is true, finally, that there are conflicting views of professional practice, it is also true that some practitioners do manage to make a thoughtful choice, or even a partial synthesis, from the babble of voices in their professions.

Why, then, should leading professionals and educators find these phenomena so disturbing? Surely they are not unaware of the artful ways in which some practitioners deal competently with the indeterminacies and value conflicts of practice. It seems, rather, that they are disturbed because they have no satisfactory way of describing or accounting for the artful competence which practitioners sometimes reveal in what they do. They find it unsettling to be unable to make sense of these processes in terms of the model of professional knowledge which they have largely taken for granted. Complexity, instability, and uncertainty are not removed or resolved by applying specialized knowledge to well-defined tasks. If anything, the effective use of specialized knowledge depends on a prior restructuring of situations that are complex and uncertain. An artful practice of the unique case appears anomalous when professional competence is modelled in terms of application of established techniques to recurrent events. Problem setting has no place in a body of professional knowledge concerned exclusively with problem solving. The task of choosing among competing paradigms of practice is not amenable to professional expertise.

(Schön, 1995, p. 18f)

Problem setting (Schön, 1995)

24 October 2010

Increasingly we have become aware of the importance to actual practice of phenomena – complexity, uncertainty, instability, uniqueness, and value-conflict – which do not fit the model of Technical Rationality. Now, in the light of the Positivist origins of Technical Rationality, we can more readily see why these phenomena are so troublesome.

From the perspective of Technical Rationality, professional practice is a process of problem solving. Problems of choice or decision are solved through the selection, from available means, of the one best suited to established ends. But with this emphasis on problem solving, we ignore problem setting, the process by which we define the decision to be made, the ends to be achieved, the means which may be chosen. In real-world practice, problems do not present themselves to the practitioner as givens. They must be constructed from the materials of problematic situations which are puzzling, troubling, and uncertain. In order to convert a problematic situation to a problem, a practitioner must do a certain kind of work. He must make sense of an uncertain situation that initially makes no sense.

When professionals consider what road to build, for example, they deal usually with a complex and ill-defined situation in which geographic, topological, financial, economic, and political issues are all mixed up together. Once they have somehow decided what road to build and go on to consider how best to build it, they may have a problem they can solve by the application of available techniques; but when the road they have built leads unexpectedly to the destruction of a neighborhood, they may find themselves again in a situation of uncertainty.

It is this sort of situation that professionals are coming increasingly to see as central to their practice. They are coming to recognize that although problem setting is a necessary condition for technical problem solving, it is not itself a technical problem. When we set the problem, we select what we will treat as the “things” of the situation, we set the boundaries of our attention to it, and we impose upon it a coherence which allows us to say what is wrong and in what directions the situation needs to be changed. Problem setting is a process in which, interactively, we frame the things to which we will attend and frame the context in which we will attend to them.

Even when a problem has been constructed, it may escape the categories of applied science because it presents itself as unique or unstable. In order to solve a problem by the application of existing theory or technique, a practitioner must be able to map those categories onto features of the practice situation. When a nutritionist finds a diet deficient in lysine, for example, dietary supplements known to contain lysine can be recommended. A physician who recognizes a case of measles can map it onto a system of techniques for diagnosis, treatment, and prognosis. But a unique case falls outside the categories of applied theory; an unstable situation slips out from under them. A physician cannot apply standard techniques to a case that is not in the books. And a nutritionist attempting a planned nutritional intervention in a rural Central American community may discover that the intervention fails because the situation has become something other than the one planned for.

Technical Rationality depends on agreement about ends. When ends are fixed and clear, then the decision to act can present itself as an instrumental problem. But when ends are confused and conflicting, there is as yet no “problem” to solve. A conflict of ends cannot be resolved by the use of techniques derived from applied research. It is rather through the nontechnical process of framing the problematic situation that we may organize and clarify both the ends to be achieved and the possible means of achieving them.

Similarly, when there are conflicting paradigms of professional practice, such as we find in the pluralism of psychiatry, social work, or town planning, there is no clearly established context for the use of technique. There is contention over multiple ways of framing the practice role, each of which entrains a distinctive approach to problem setting and solving. And when practitioners do resolve conflicting role frames, it is through a kind of inquiry which falls outside the model of Technical Rationality. Again, it is the work of naming· and framing that creates the conditions necessary to the exercise of technical expertise.

We can readily understand, therefore, not only why uncertainty, uniqueness, instability, and value conflict are so troublesome to the Positivist epistemology of practice, but also why practitioners bound by this epistemology find themselves caught in a dilemma. Their definition of rigorous professional knowledge excludes phenomena they have learned to see as central to their practice. And artistic ways of coping with these phenomena do not qualify for them as rigorous professional knowledge.

This dilemma of “rigor or relevance” arises more acutely in some areas of practice than in others. In the varied topography of professional practice, there is a high, hard ground where practitioners can make effective use of research-based theory and technique, and there is a swampy lowland where situations are confusing “messes” incapable of technical solution. The difficulty is that the problems of the high ground, however great their technical interest, are often relatively unimportant to clients or to the larger society, while in the swamp are the problems of greatest human concern. […]

There are those who choose the swampy lowlands. They deliberately involve themselves in messy but crucially important problems and, when asked to describe their methods of inquiry, they speak of experience, trial and error, intuition, and muddling through.

Other professionals opt for the high ground. Hungry for technical rigor, devoted to an image of solid professional competence, or fearful of entering a world in which they feel they do not know what they are doing, they choose to confine themselves to a narrowly technical practice.

(Shön, 1995, p. 39ff)

Resistance to innovations (Fisher, 2005)

24 October 2010

Diffusion is the process by which an innovation is communicated through channels over time among members of a social system (Rogers, 2003).

An innovation is an idea, practice, or object that is perceived as new by an individual or other unit of adoption (Rogers, 2003). Knowing of an innovation creates uncertainty in the mind and the potential of a new idea impels an individual to learn more about the innovation. Once information seeking activities reduce uncertainty about expectations to a comfortable level, a decision concerning adoption is made. If adopted, further evaluation about the effects of the innovation is carried out. Thus, the innovation-decision process is essentially an information-seeking and processing activity in which an individual is motivated to reduce uncertainty about relative advantages and disadvantages of an innovation (Rogers, 2003).

The main questions typically asked are: What is the innovation? How does it work? Why does it work? What are its consequences? and, What will be its advantages and disadvantages in my situation? (Rogers, 2003).

According to Rogers (2003), the following perceived characteristics of  innovations help to explain their different rates of adoption:

  • Relative advantage, or the degree to which an innovation is perceived as better than the former idea. This may be measured in economic terms, but social prestige, convenience, and satisfaction are also important factors.
  • Compatibility, or the degree to which an innovation is perceived as being consistent with the existing values, past experiences, and needs of potential adopters. An idea that is incompatible with the values and norms of a social system will not be adopted as rapidly as an innovation that is more compatible.
  • Trialability , or the degree to which an innovation may be experimented with before adoption. New ideas that can be tested in increments will generally be adopted more quickly than those that cannot.
  • Observability, or the degree to which the results of an innovation are visible to others. The easier it is to see the results of an innovation, the more likely it is to be adopted.

Time is a crucial element in three aspects of the diffusion process: 1) the innovation-decision process by which an individual passes from first knowledge of an innovation through to its adoption or rejection; 2) the innovativeness of an individual, that is, the timeliness with which an innovation is adopted compared with other members in the system; and, 3) the rate of adoption of an innovation, usually measured as the number of members of the system who adopt the innovation in a given time period.

In the innovation-decision process, an individual passes from knowledge (first knowledge of an innovation) to persuasion (formation of an attitude toward the innovation) to decision (the decision to adopt or reject) to implementation (actual use of the innovation) and finally to confirmation (commitment to adopt).

(Fisher, 2005, p. 118)

Affective Load Theory (ALT), (Fisher, 2005)

24 October 2010

Affective load theory (ALT) is a social-behavioral perspective on the thoughts and feelings of individuals while engaged in information behavior (lB). ALT provides empirical methods for identifying affective states of users that disrupt ongoing cognitive operations (James & Nahl, 1986). Once a disruptive affective state is identified, coping assistance services (CAS) can be provided to encourage users to mitigate disruptive states to achieve task success. ALT identifies underlying habits of thinking and feeling while engaging in information behavior, and clarifies the details of information retrieval from a user perspective. There are three essential ideas in applying social-behavioral psychology to IB:

  1. The mental activity of information users, both cognitive and affective, is defined as behavior (Martin &. Briggs, 1986). For instance, “thinking of a search word” or “feeling motivated to finish a task” are behaviors. Global control of the affective over the cognitive operates at general and specific levels. At the general level of control people possess motivational states such as optimism or pessimism prior to a search. At the specific level of control we experience micro-behaviors that involve search strategy such as inspecting a list, thinking of a synonym, or recalling an item that has been seen before. A search task or session involves hundreds of individual cognitive micro-behaviors, each one connected to an affective state that maintains or interrupts it (Nahl, 1997). Affective states are organized in a top-down hierarchy and can be reliably measured through concurrent self-reports about expectations, satisfactions, and acceptance during continuous cognitive activity.
  2. Affective behavior initiates, maintains, and terminates cognitive behavior (Isen, Daubman & Gorgolione, 1987; Carver & Scheier, 2001). For instance, when searchers lose the motivation to continue a task, they begin thinking about something else. Or, if they unexpectedly find some new information they want, they switch activity midstream. The new affective behavior interrupts and takes over the ongoing activity and continues in a new direction with new cognitive activity. This managerial or directive function of affective behavior over cognitive, makes it desirable in information environments to employ self-monitoring techniques to keep track of the affective behavior of users (Nahl, 1996, 1998).
  3. Affective behavior operates within a binary-value system: on/off or positive/negative. Cognitive behavior operates through a multivalue logic. Therefore, affective behavior is measured with bi-polar scales and cognitive behavior is measured with multiple-choice, matching or fill-in items. Content analysis and protocol analysis of concurrent verbal reports are used to identify affective and cognitive behavior patterns during search tasks (Nahl, 2001).

The behavioral approach to information use is attracting increasing interest among information scientists. However, sufficient attention is not given to the three essential elements outlined above. The focus has been on cognitive behavior and more recently, on how affective behavior is also important to consider. Nahl’s social-behavioral theory of affective load makes explicit the need to create a methodological connection between each cognitive behavior and its affective support or control state. Affective load theory was developed by analyzing concurrent self-reports of searchers and learners in conjunction with quantitative ratings filled out by searchers while engaged in searching and problem-solving. To achieve high reliability, it is critical to obtain concurrent rather than recollected data. Nahl’s ALT theory is emerging from a 20-year research program. One area of application has been to identify affective dimensions like self-efficacy and optimism that help searchers perform better. Currently ALT research focuses on how diverse affective behaviors interact to produce an effective coping style when searchers feel challenged by uncertainty.

ALT proposes that all information behavior involves affective states that provide specific goal-directionality and motivation to support cognitive activity. Affective load ( AL) is operationally defined as uncertainty (U) multiplied by felt time pressure (TP). Uncertainty is defined as the combined degrees of irritation, frustration, anxiety, and rage (Nahl, 2004).

AL = U (irritation + frustration+ anxiety + rage) x TP

Affective load is high when people operate with ineffective cognitive behaviors. For example, cognitive ambiguity, uncertainty, or information overload attract affective behaviors that are negative and counterproductive to the searcher’s goal. For instance, a search that appears to yield no relevant results after some attempts is cognitively disorienting, as represented by such thoughts as, ‘Tm no good at this” or “This is so frustrating! ”

At other times, searchers are able to engage affective coping strategies when faced with cognitive load and uncertainty. For instance, “I’ll just keep going until I find something” or “I’m positive I can find what I need in another database.” These verbal expressions are standard and recurrent within a population of searchers, and because they are learned cultural habits, can be termed “learned affective norms” (LANs). Negative LANs disrupt cognitive strategies, interrupt the search, and often terminate it prematurely, while positive LANs provide persistence and integration to cognitive strategies. In general, negative LANs increase AL and appear in the form of uncertainty, anxiety, frustration, low expectations, pessimism, low self-efficacy, low task completion motivation, low satisfaction, low system acceptance, and other disruptive symptoms that interfere with a positive outcome. On the other hand, positive LANs decrease AL because they provide better coping strategies to manage ambiguity and cognitive load. Support and counseling interventions can be triggered when affective load rises above a specified level. Knowledge about the affective environment of searchers will also be helpful in search instruction. More research is needed on how the affective information environment of searchers impinges on their cognitive activity to strengthen information system services and design.

(Fisher, 2005, p. 39ff)

Goal of problem solving (Ackoff, 1978)

24 October 2010

The solution process is directed at dispelling doubt.

(Ackoff, 1978, p. 12)