6533b85efe1ef96bd12c059e

RESEARCH PRODUCT

Scientific and Design Stances

subject

description

Human technology interaction is a strange field of expertise, because both academics and industry are interested in it. And yet, every now and then, it becomes apparent that academics and industry do not always see eye to eye (Carroll, 1997). They seem to think in different manner. While scientists look for how things are, industry mostly seeks out how things should be. Indeed, sometimes two very different stances behind the basic thinking of the two important human–technology interaction (HTI) communities surface. Scientists primarily are interested in general laws and principles, even eternal truths with no exceptions. They want to identify general laws and use them to explain individual phenomena. As an analogy, they are not satisfied with the simple assessment that a car is not working, but would prefer rather to say that the carburetor of a car broke because freezing water expands as it changes its state (Hempel, 1965). Scientists equally are concerned about finding deterministic or stochastic laws, which are valid in all circumstances (Bunge, 1967) Thus, much of scientific thinking is built upon the idea that the function of science is to produce generalizations. This way of thinking can be termed in this editorial as scientific stance. In solving HTI problems, general principles regarding the human mind are very valuable. Consider the notion of limited capacity (Broadbent, 1958; Miller, 1956). When interaction problems are to be solved, the ergonomic and human factor dimensions are evident. Every cognitive ergonomist knows that it is essential to decrease mental workload and organize matters so that people can use chunking, for example. Programming paradigms provide a good example. We have no other reason for constructing computer languages and paradigms such as structures programming or object oriented programming except to decrease mental workload by chunking. The problem is not the machine but the mind. A somewhat polemical person may point out that the complexity of the code for a machine is precisely the number of the symbols in a program; any other measure is always constructed from human perspective. The number of functions, or meaningful reserved words, for example, makes sense only to people. They have no meanings to the machines because machines do not have any meanings. Nevertheless, the importance of functions and meanings can be explained on the grounds of human’s limited working memory capacity and its laws (Miller, 1956).