The magic of algorithm design and analysis

ACM SIGCSE Bulletin, 2000

In this paper we outline a method of teaching algorithmic, based on problem-solving and stating the necessary stages to be considered when writing an algorithm which solves a given problem.

This paper presents a new approach to teaching algorithms, in which an algorithm is explained using a hierarchy of abstractions. Each abstraction is designed to focus on a single operation , which is used directly or indirectly in the representation of the algorithm. An abstraction consists of three elements: an Abstract Data Type, an associated visualization, and a representation of using the Abstract Data Type. All abstractions form a tree, rooted at the abstraction representing the algorithm. Primitive operations that do not have the representations in any abstraction are associated with an abstract implementation. The latter implementation can be used to represent primitive operations in various programming languages. This approach makes it possible to teach students not only how and why algorithms work, but also to provide them with generic implementations to teach them how to implement algorithms. The application of this approach is demonstrated on the selection sort.

ACM SIGCSE Bulletin, 2005

How do we know if our students are beginning to think like computer scientists? In this study we have defined four levels of abstraction in the thinking of computer science students about the concept of algorithm. We constructed a list of questions about algorithms to measure the answering level as an indication for the thinking level. This list was presented to various groups of Bachelor Computer Science students. The mean answering level increased between successive year groups as well as within year groups during the year, mainly from the second to the third level. Little relation was found between answering levels and test results on algorithm oriented courses. The study was inspired by the tradition of mathematics education research.

1997

This paper describes our experiences in devising a lightweight, informal methodology for problem solving in introductory, university level, computer science. We first describe the original context of the experiment and the background to the methodology. We then give the details of the steps of the Problem Solving Cycle-Understanding, Designing, Writing and Reviewing-and the lessons we learned about our teaching from devising the material.

25th International Conference on Software Engineering, 2003. Proceedings., 2003

Problems and Programmers is an educational card game that we have developed to help teach software engineering. It is based on the observation that students, in a typical software engineering course, gain little practical experience in issues regarding the software process. The underlying problem is time: any course faces the practical constraint of only being able to involve students in at most a few small software development projects. Problems and Programmers overcomes this limitation by providing a simulation of the software process. In playing the game, students become aware of not only general lessons, such as the fact that they must continuously make tradeoffs among multiple potential next steps, but also specific issues such as the fact that inspections improve the quality of code but delay its delivery time. We describe game play of Problems and Programmers, discuss its underlying design, and report on the results of a small experiment in which twenty-eight students played the game.

Australian Educational Computing, 2019

In this paper, the researchers have tried to solve one of the didactic tasks of an educational institution-the formation of a student's thinking, the development of their algorithmic style of thinking and intelligence. Since an important component of human intellectual development is precisely algorithmic thinking, learning to solve standard algorithmic problems is the primary goal of school education at various levels of computer science. Creating game moments that can be applied when solving problems from the "Basics of Algorithmization and Programming" section is aimed at motivating and increasing the efficiency of work in computer science lessons, as well as improving the quality of students' skills based on their cognitive interest. The use of ready-made and developed game moments when solving problems on the use of a structured array data type allows for a detailed analysis of algorithms in steps explaining the work of teams by the students themselves. Continued use of properly designed algorithms contributes to making students work focused and motivated.

Nicotine & Tobacco Research, 2020

In Computing Science, Algorithms and Data Structures (ADS) are fundamental as they give learners a solid foundation in programming. ADS require abstract thinking and problem-solving abilities from students instead of memorisation – of formula or procedures, for example - without a clear understanding of the concepts. This paper reveals how master’s students (n = 35) perceived and experienced the different activities used to teach ADS in traditional lecture and flipped classroom environments. Results showed that the individual activities that scored higher were problem-solving and peer discussion in the flipped classroom. Regardless of the teaching approach, many students did not access the prior preparation teaching material mainly due to the lack of time. Findings also highlight the importance of communicating the intentions and pedagogical goals better. Findings have wider implication for practitioners facing the same challenges. It is hoped that the experiences reported in this p...

Maple Transactions

Teaching analysis of algorithms to students in Computer Science degrees, using the approach popularized by Knuth in his series of books ``The Art of Computer Programming" and later by Sedgewick and Flajolet in the book ``An Introduction to the Analysis of Algorithms", is not a simple task since, in general, these students are more interested in the implementation of an algorithm than in the corresponding theoretical aspects. This approach concentrates on precisely characterizing the performance of algorithms by determining their best, worst and average case performance using a methodology based on symbolic tools such as recurrence relations and generating functions.The most difficult aspect is to understand the average case since this corresponds to studying the algorithm as its possible inputs vary: this represents the most important goal since generally students have no difficulty in understanding the best and worst cases, corresponding to particular input configurations...

Education and Information …, 2004

This paper is based on rich experience gained in the area of computer science education and it could serve as an inspirational material directed to all educators developing students' programming skills. The area of software development has undergone a rapid expansion and this trend is so far continuing. Each developer has to learn constantly and master new technology. However, the foundation a developer gains at the beginning of his/her career plays a crucial role. An essential part of studies at faculties preparing students in the area of computer science is the development of student's ability to think algorithmically. Students must be able to create various algorithms solving given problems starting with easy ones and consecutively increase their algorithmic knowledge and shifts during studies till the level where they deeply understand much more complex algorithms. The aim of this paper is to introduce our approach that has proven to be successful in the optimization of teaching and learning a subject developing algorithmic thinking of beginners. This is followed by a discussion of the benefits of puzzles, solved within subjects, dealing with graph algorithms and enabling development of students' logical thinking and imagination, i.e. skills needed for deeper understanding more complex algorithms.