TL;DR: This article found that lecturers' views on the learnability of various features of explaining were not related to their years of experience of lecturing, and that there were significant differences between arts-based and science lecturers on seventeen of the variables and between least and most experienced lecturers in ten of them concerned with assigned values.
Abstract: A random sample of 93 lecturers responded to a 40-item questionnaire based on researches into explaining. The lecturers' views on the learnability of various features of explaining were not related to their years of experience of lecturing. But there were significant differences between arts-based and science lecturers on seventeen of the variables and between least and most experienced lecturers on ten of the variables concerned with assigned values. It is suggested that a lecturer's views on explaining may arise from the experience of studying a subject as an undergraduate.
TL;DR: Both generalized and specific methodologies for addressing the software engineering characteristics are proposed and the applicability of the methodologies to the MADAM system are presented along with the analysis and evaluation of those methodologies.
Abstract: While there have been numerous research and development efforts directed individually toward information storage and retrieval systems and toward software engineering, relatively little research has addressed a generalized integration of these two areas.
The objective of this research is to define, apply, and evaluate the potential for integrating these areas via a generalized application of software engineering principles to existing information storage and retrieval systems.
Utilizing the results of applying previous evaluation methodologies as well as new evaluation methodologies, each of the following software engineering characteristics are addressed: reliability, correctness, learnability, usability, flexibility, performance, applicability, security/protection, and cost-effectiveness.
Both generalized and specific methodologies for addressing the software engineering characteristics are proposed. The applicability of the methodologies to the MADAM system are presented along with the analysis and evaluation of those methodologies.
TL;DR: Consider eliminating the transformational component of a generative grammar, and the elimination of all movement rules, whether bounded or unbounded, and all rules making reference to identity of indices.
Abstract: Consider eliminating the transformational component of a generative grammar. In particular, consider the elimination of all movement rules, whether bounded or unbounded, and all rules making reference to identity of indices. Suppose, in fact, that the permitted class of generative grammars constituted a subset of those phrase structure grammars capable only of generating context-free languages. Such a move would have two important metatheoretical consequences, one having to do with learnability, the other with processability. In the first place, we would be imposing a rather dramatic restriction on the class of grammars that the language acquisition device needs to consider as candidates for the language being learned. And in the second place, we would have the beginnings of an explanation for the obvious, but largely ignored, fact that humans process the utterances they hear very rapidly.1 Sentences of a context-free language are provably parsable in a time which is proportional to the cube of the length of the sentence or less (Younger (1967), Earley (1970)). But no such restrictive result holds for the recursive or recursively enumerable sets potentially generable by grammars which include a transformational component.