Abstract
This chapter introduces the reader to some social research characteristics that are central to the social study of computer science. It introduces research studies that focus on the sociocultural aspects of computing and computer science, explains some of the central characteristics of those studies, and discusses their implications for the computer science discipline. Furthermore, this chapter is aimed at giving the reader a basic understanding of why social studies are important for the discipline of computing, as well as some broad guidelines and pointers towards carrying out such studies in computer science. Our objective … is to state precisely and clearly where and why sociological analysis is necessary in the understanding of scientific knowledge. Our main method is to present historical case studies. We then show how sociological analysis applies in these cases, and how it is an essential complement to even the most insightful interpretations derived from other perspectives.
Our objective … is to state precisely and clearly where and why sociological analysis is necessary in the understanding of scientific knowledge. Our main method is to present historical case studies. We then show how sociological analysis applies in these cases, and how it is an essential complement to even the most insightful interpretations derived from other perspectives.
—Barnes, Bloor, & Henry (1996)
TopIntroduction
Computer science is a relatively new discipline, and it spans across traditional disciplinary boundaries, covering mathematical, engineering-oriented, and scientific traditions (Denning et al., 1989). From the birth of modern (digital, Turing-complete, electronic) automatic computing in the 1940s, those traditions have been essential to the development of the discipline. Modern computer science was born in the 1940s as a result of a number of organizations, a number of top people, many coincidences, a variety of disciplines, an uncommon political situation, a certain culture, unusually liberal funding, and convergence of a number of technical and scientific breakthroughs (Tedre, 2006:passim).
Since the 1940s, modern computer science has been surrounded and shaped by a vastly complex conjunction of affairs. Due to their rich and colorful history, computer science and computer technologies include plenty of phenomena, the form and functioning of which cannot be explained in terms internal to those phenomena. For instance, one cannot explain the design and the (non-)diffusion of any programming language by referring solely to its technical characteristics (Sammet, 1991). Understanding the design and diffusion of any programming language requires understanding its history and the original motivations for its development in the first place (e.g., Denning, 2003; Rosenblatt, 1984). Similar, one cannot explain the development of GNU/Linux in solely technological terms—several non-technological motives, such as economic, political, ideological, and cultural motives, can be attributed to the development of GNU/Linux (cf. Tedre et al., 2006). Technical characteristics of GNU/Linux that stem from non-technological motives are perhaps better explained in other terms, such as in psychological, sociological, or anthropological terms.
So it is implausible that one could understand the current state, a static snapshot, of knowledge in computer science without understanding the history of computer science. Moreover, one cannot understand why knowledge in computer science is what it is without understanding the history of computer science. In addition to history, one must also understand how society and culture today shape computer science. As computer science is a product of an array of sociocultural forces, any portrayal of computer science is a historically, culturally, and societally specific image. Especially computer science as human activity always happens in some philosophical, historical, and sociocultural framework. That is, of course, not to say that computer science that is situated in a historical, cultural, and societal framework could not be objective. Objectivity can be defined in a number of ways that permit comparisons of socially constructed knowledge (e.g., Searle, 1996:p.8). For example, objectivity can refer to how strong consensus there is concerning a specific statement.
Key Terms in this Chapter
Method: The term method refers to a means or a procedure for accomplishing something, like measuring the execution time of a task, interviewing a group of people about an interesting phenomenon, or comparing the execution times and output sizes for a given input with two computer algorithms.
Case Study: The term case study can refer to a method, research strategy, or focus of study. In the latter meaning case studies aim at finding out what can be learned from a single case. Case studies can have quantitative and qualitative aspects, and they aim at giving rich, detailed descriptions of a phenomenon.
Methodology: The term methodology refers both to a specific set of methods and to the study of usage patterns, procedures, principles, and assumptions that underlie such set of methods.
Ethnomethodology: The study of the ways (such as conventions, practices, and codes) through which people make sense as well as create their social reality and which underlie social interactions between people.
Ethnography: The term ethnography is used in various meanings, but as a set of methods, it refers to observational and participatory methods that focus on the life of some particular group of people; their culture, behavior, social interactions, and other aspects of their everyday life.