David G. Moursund

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5ranked-venue papers

5as first author

0since 2021 · last 1979

—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 3 · 3 first-authorApplied, interdisciplinary, general and emerging computing · 2 · 2 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science

2 papers

Algorithms and data structures · 60% Mathematical optimization · 40%

Topics — the 4 heaviest of 4, each with the papers that count most for it

Topic	Papers	Last	Evidence papers
Algorithms and data structures numerical algorithms	2	1965	Chebyshev Solution of n+1 Linear Equations in n Unknowns · J. ACM 1965 Examination of Multiple Roots and Root Clusters of a Polynomial Using the Bernoulli Procedure · J. ACM 1965
Mathematical optimization › approximation theory chebyshev approximation	1	1965	Chebyshev Solution of n+1 Linear Equations in n Unknowns · J. ACM 1965
Algorithms and data structures › numerical linear algebra linear system solving	1	1965	Chebyshev Solution of n+1 Linear Equations in n Unknowns · J. ACM 1965
Mathematical optimization root finding	1	1965	Examination of Multiple Roots and Root Clusters of a Polynomial Using the Bernoulli Procedure · J. ACM 1965

Methods — techniques the papers use, named apart from their topics

convergence analysis · 0.0chebyshev approximation · 0.0

Year	Publication	Venue	Position
1979	Computers in precollege education (Panel Discussion): What do teachers want or need? abstract What are the major problems involving computers in precollege education?This question will be discussed by a panel of precollege teachers who are seriously interested in instructional uses of computers. They will present their wants and needs. Topics to be covered include software, hardware, courseware, inservice training, administrative support, and loneliness. The panel will discuss both teaching about computers and teaching using computers. There will be time for input from the audience. David G. Moursund	SIGCSE	1
1977	Calculator metaphors, and goals for calculator education in elementary schools David G. Moursund	SIGCSE-1	1
1974	Computers in pre-college education: Oregon moves forward abstract The computers in education field is making rapid progress. We can see this progress in the quality and number of data processing programs at the associates degree and data processing school levels, and in the bachelor's, master's, and doctorate programs at colleges and universities. We can also see large numbers of secondary schools beginning to acquire computing facilities. But we have a long way to go! To put our current progress in perspective we need merely ask: “What percentage of students in the United States made direct instructional use of computers during the past week, how extensive was this usage, and how effectively did it contribute to the student's education?” David G. Moursund	SIGCSE	1
1965	Examination of Multiple Roots and Root Clusters of a Polynomial Using the Bernoulli Procedure abstract The sequence of numbers used in the Bernoulli procedure for finding the dominant root of a polynomial equation is examined.It is shown how to construct from this sequence a new sequence which converges to the order of the dominant root.Certain results on the rate of convergence are obtained.The problem of a cluster of several, nearly equal, dominant roots is discussed.It is shown how the number of roots in the cluster and their approxiraate center of gravity may be determined.A numerical example using a seventh degree polynomial with four nearly equal dominant roots is given. David G. Moursund	J. ACM	1
1965	Chebyshev Solution of n+1 Linear Equations in n Unknowns abstract An algorithm is presented for finding a solution, and the value of a solution, to n + 1 linear equations in n unknowns. The arrangement of the computation makes it convenient for use in computing Chebyshev-type approximations by polynomials. The algorithm is particularly efficient if only the value of a solution is desired. David G. Moursund	J. ACM	1