Do senior CS students capitalize on recursion?

Ginat, David

doi:10.1145/1007996.1008020

Cited by 13 publications

(5 citation statements)

References 8 publications

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“…Other research envisaged involves studying how more senior computer science students cope with recursion in line with the work done by Ginat (2004) who showed that senior students do not always produce recursive solutions even when those would be the most appropriate solutions.…”

Section: Future Workmentioning

confidence: 99%

First year students' understanding of the flow of control in recursive algorithms

Sanders

Scholtz

2012

African Journal of Research in Mathematics, Science and Technol

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Recursion is an important concept for any computer science student to master. Many first year students develop the viable copies mental model of recursion and can successfully trace the execution of a simple recursive function. This article discusses a study focused on determining whether the ability to successfully trace a recursive function means that the student understands recursion or whether they are simply "applying a formula". The research question investigated was thus "To what extent do students with viable trace mental models understand the flow of control of recursive algorithms?" The research followed a phenomenological approach. A group of first year students with viable mental models was identified by classifying the mental models in their answers to test questions. Fifteen of these students were interviewed. The interviews involved the students talking aloud while they tackled various tasks. Each student's understanding of the active flow, the limiting case and the passive flow was assessed. The results show that in most cases even these students have some difficulty with the active flow, are confused about the passive flow and have misconceptions about the limiting case. This implies that more careful thought needs to be given to the examples used in teaching recursion and how the concept is taught.

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Section: Future Workmentioning

confidence: 99%

First year students' understanding of the flow of control in recursive algorithms

Sanders

Scholtz

2012

African Journal of Research in Mathematics, Science and Technol

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“…It is well known that the number of inversions in a permutation can be obtained by a merge sort (Ginat, 2004). We use a similar strategy to compute the d i while performing a merge sort on y 1 , .…”

Section: Fast Computation Of D I Where Dmentioning

confidence: 99%

A fast algorithm for computing distance correlation

Chaudhuri

2019

Computational Statistics & Data Analysis

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Classical dependence measures such as Pearson correlation, Spearman's ρ, and Kendall's τ can detect only monotonic or linear dependence. To overcome these limitations, Székely et al. (2007) proposed distance covariance as a weighted L2 distance between the joint characteristic function and the product of marginal distributions. The distance covariance is 0 if and only if two random vectors X and Y are independent. This measure has the power to detect the presence of a dependence structure when the sample size is large enough. They further showed that the sample distance covariance can be calculated simply from modified Euclidean distances, which typically requires O(n 2 ) cost. The quadratic computing time greatly limits the application of distance covariance to large data. In this paper, we present a simple exact O(n log(n)) algorithm to calculate the sample distance covariance between two univariate random variables. The proposed method essentially consists of two sorting steps, so it is easy to implement. Empirical results show that the proposed algorithm is significantly faster than state-of-the-art methods. The algorithm's speed will enable researchers to explore complicated dependence structures in large datasets.

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“…Wherever programming is featured in introductory courses, recursion is usually avoided, even though it is present in mathematics courses, usually in the guise of numerical progressions, Euclid's algorithm, Newton-Raphson approximation method, and proofs by mathematical induction (Buck, 1963). Therefore, because university students often experience significant difficulties in grasping recursive programming (Sooriamurthi, 2001, Ginat, 2004, some educators have insisted on a better articulation between secondary and post-secondary curriculums. For instance, some researchers have been promoting a greater presence of discrete mathematics and proof techniques in secondary schools (Abramovich and Pieper, 1996, da Rosa, 2002, Rosenstein et al, 1997, Kaiser, 2004a, as well as the creation of computing clubs with activities about recursion (Gunion et al, 2009a).…”

Section: Curricular Approachesmentioning

confidence: 99%

A Survey on Teaching and Learning Recursive Programming

Rinderknecht¹

2014

Informatics in Education

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We survey the literature about the teaching and learning of recursive programming. After a short history of the advent of recursion in programming languages and its adoption by programmers, we present curricular approaches to recursion, including a review of textbooks and some programming methodology, as well as the functional and imperative paradigms and the distinction between control flow vs. data flow. We follow the researchers in stating the problem with base cases, noting the similarity with induction in mathematics, making concrete analogies for recursion, using games, visualizations, animations, multimedia environments, intelligent tutoring systems and visual programming. We cover the usage in schools of the Logo programming language and the associated theoretical didactics, including a brief overview of the constructivist and constructionist theories of learning; we also sketch the learners' mental models which have been identified so far, and non-classical remedial strategies, such as kinesthesis and syntonicity. We append an extensive and carefully collated bibliography, which we hope will facilitate new research.

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Do senior CS students capitalize on recursion?

Cited by 13 publications

References 8 publications

First year students' understanding of the flow of control in recursive algorithms

First year students' understanding of the flow of control in recursive algorithms

A fast algorithm for computing distance correlation

A Survey on Teaching and Learning Recursive Programming

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