What’s Motivation Got to Do with It? A Survey of Recursion in the Computing Education Literature

One of the most challenging topics for both computing educators and students is recursion. Pedagogical approaches for teaching recursion have appeared in the computing education literature for over 30 years, and the topic has generated a significant body of work. Given its persistence, relatively little attention has been paid to student motivation. This article summarizes results on teaching and learning recursion explored by the computing education community, noting the relative lack of interest in motivation. It concludes by briefly discussing an approach to teaching recursion is appealing for students interested in web development

An Exploratory Study of Students' Mastery of Iteration in the High School

Although a number of studies report about novices\u2019 diffi-culties with basic flow-control constructs, concerning both the under-standing of the underlying notional machine and the logical connectionswith the application domain, this issues have not yet been extensivelyexplored in the context of high-school education. As part of a projectwhose long-run goal is identifying methodological tools to improve thelearning of iteration, we analyzed how a sample of 164 high-school stu-dents\u2019 approached three small programming tasks involving basic loopingconstructs, as well as two questions on their subjective perception of dif-ficulty. If, on the one hand, most students seem to have developed aviable mental model of the basic workings of the underlying machine,on the other, dealing at a more abstract level with loop conditions andnested flow-control structures appears to be challenging. As to the impli-cations for teachers, the results of the analysis suggest that more effortsshould be addressed to develop a method for testing the conjecturesabout program behavior, as well as to the treatment of loop conditionsin connection with the problem statement

Analisis Perbandingan Kinerja Metode Rekursif dan Metode Iteratif dalam Algoritma Linear Search

Salah satu algoritma pencarian data yang paling populer adalah algoritma linear search.  Dalam proses pencarian data sebuah list menggunakan algoritma linear search dapat diterapkan dengan cara iteratif dan rekursif. Pandangan umum mengenai algoritma linear search adalah bahwa performa metode iteratif memiliki hasil yang sama dengan rekursif. Namun di beberapa penelitian menentang pernyataan tersebut yang mungkin tidak berlaku pada semua kasus. Dari analisis tersebut, penelitian ini berfokus pada perbandingan metode rekursif dan iteratif pada algoritma linear search untuk mengetahui algoritma mana yang paling sesuai, efisien dan efektif. Penelitian dilakukan menggunakan 3 studi kasus dengan masing-masing data sebanyak 1 juta, 10 juta, dan 100 juta. Penelitian berfokus pada hasil penggunaan memori dan waktu akses pada proses pencarian data menggunakan notasi Big-O dan bahasa pemrograman Python. Hasil penelitian menunjukkan bahwa algoritma linear search secara iteratif lebih efektif dan efisien dari pada rekursif. Meskipun kedua metode tersebut memiliki kompleksitas Big-O yang sama, namun hasil dari eksekusi program menunjukkan hasil yang berbeda. Dengan hasil algoritma linear search secara iteratif memiliki hasil waktu eksekusi dan penggunaan memori yang lebih unggul yaitu waktu akses dan penggunaan memori yang lebih sedikit dibanding metode rekursif.The linear search algorithm is one of the most popular data search algorithms. In the process of searching data for a list using a linear search algorithm, it can be applied in an iterative and recursive way. The general view of linear search algorithms is that the iterative methods perform the same as recursive methods. However, some studies contradict this statement which may not apply in all cases. From this analysis, this study focuses on the comparison of recursive and iterative methods on linear search algorithms to find out which algorithm is the most suitable, efficient, and effective. The research was conducted using 3 case studies with data of 1 million, 10 million, and 100 million respectively. The research focuses on the results of memory usage and access time in the data search process using Big-O notation and Python programming language. The results show that the iterative linear search algorithm is more effective and efficient than recursive. Although both methods have the same Big-O complexity, the results of program execution show different results. With the results of an iterative linear search algorithm, the results of the execution time and memory usage are superior, namely, the access time and memory usage are less than the recursive method

Is iteration really easier to learn than recursion for CS1 students?

There is general consensus that recursion is difficult to learn, which may be meant to imply that novice students are more at ease with iteration --- probably a widespread perception of students themselves. However, three years of investigation in a context where recursion is introduced earlier than iteration, as well as control experiments for a standard imperative-first introduction to programming, have provided no evidence that students make more progress with iteration than they do with recursion. More specifically, by means of a pair of questionnaires devised for this purpose, two research questions have been addressed. First, do the students who learned recursion before iteration actually exhibit a stronger ability to deal with the latter? Second, do the students of the imperative-first path master iteration better than those of the recursion-earlier path