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Knowledge Transfer among Programming Languages.

Authors: Wu, Quanfeng; Anderson, John R.;

Knowledge Transfer among Programming Languages.

Abstract

Two experiments were conducted to investigate knowledge transfer from learned programming languages to learning new ones. The first experiment concerned transfer from knowing LISP to learning PROLOG; the results showed that subjects who knew LISP had significant advantages over subjects who did not. Moreover, among the subjects who knew LISP those who knew LISP better seemed to learn PROLOG faster. The second experiment studied transfer from knowing either PASCAL or PROLOG to learning LISP; attention was specifically focused on transfer of knowledge of writing recursive and iterative programs in these languages. The results indicated that PROLOG programmers, who were usually more knowledgeable on recursion, were more ready to learn the recursive part of the LISP language. Some general theoretical discussion about knowledge transfer among programming languages is also presented in the paper.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green