This empirical research demonstrates the effectiveness of content analysis to map the research literature of the software engineering discipline. The results suggest that certain research themes in software engineering have remained constant, but with changing thrusts. Other themes have arisen, matured, and then faded as major research topics, while still others seem transient or immature. Co‐word analysis is the specific technique used. This methodology identifies associations among publication descriptors (indexing terms) from the ACM Computing Classification System and produces networks of descriptors that reveal these underlying patterns. This methodology is applicable to other domains with a supporting corpus of textual data. While this study utilizes index terms from a fixed taxonomy, that restriction is not inherent; the descriptors can be generated from the corpus. Hence, co‐word analysis and the supporting software tools employed here can provide unique insights into any discipline's evolution.

This empirical research demonstrates the effectiveness of content analysis to map the research literature of the software engineering discipline. The results suggest that certain research themes in software engineering have remained constant, but with changing thrusts. Other themes have arisen, matured, and then faded as major research topics, while still others seem transient or immature. Co-word analysis is the specific technique used. This methodology identifies associations among publication descriptors (indexing terms) from the ACM Computing Classification System and produces networks of descriptors that reveal these underlying patterns. This methodology is applicable to other domains with a supporting corpus of textual data. While this study utilizes index terms from a fixed taxonomy, that restriction is not inherent; the descriptors can be generated from the corpus. Hence, co-word analysis and the supporting software tools employed here can provide unique insights into any discipline's evolution.

There is often a severe problem of lack of communication between teacher and pupils. When two people communicate, what passes between them are the words and gestures they use to attempt to convey meaning, not the meaning itself. So a teacher has some ideas which he or she hopes to convey by putting them into words, diagrams or symbols. The child may take note of the words, and so on, but from these has to build up a meaning for them. There is clearly a strong possibility that this meaning created by the child is not the meaning intended by the teacher. This possibility is very high if the type of language used by the teacher, or workcard, or textbook writer, is not familiar to the child. Then various things may happen, as Barnes (1986) has so clearly pointed out: a) The child may ignore what the teacher is saying. b) The teacher may ignore what the pupil is saying (the teacher “controls” knowledge by using unfamiliar language, consequently children'S ideas are devalued and are only heard when they talk among themselves). c) The teacher may insist that the pupils use the “correct” words and so, sound scientific. (We, like Barnes, have seen children praised for “thinking like a scientist” when it is clear that the children are simply “making noises which sound scientific”).