Improving Computer Science Education Research Articles

Kemampuan Siswa Kelas V dalam Menyelesaikan Soal Materi Pengelolahan Data di SD Negeri Curug II

This study aims to describe the understanding of grade 5 students in learning data processing and to identify the types of errors that are often made by students. This study originates from the law of the Ministry of Learning of the Republic of Indonesia, No. 57 in 2014 on demonstrating essential skills of mathematics in specialization development, communication and life adjustment. This study used full-time and student checks of 34 students from SD. Data was collected through interviews, questionnaires and tests. Data processing includes making tables, line diagrams and bar diagrams. The results of the study show that students' understanding of data processing still needs to be improved. Common errors are conceptual errors, data usage errors, data interpretation errors, technical and input errors. Errors in the conclusions listed are common errors. Data processing education should be improved by providing a better understanding of basic data processing concepts and teaching students the proper way to use, interpret, and present data. It is also important to choose learning methods that are interactive, relevant and interesting to students. This research helps improve computer science education in grade 5 elementary schools and informs more effective learning efforts to improve students' understanding of mathematics.

Insights to Improve Computer Science Education by Enhancing the Java Language and Tools

Java is the most well-known and widely used object-oriented programming language. It uses “objects” as instances of particular data types, or classes. While many computer science students who take Java programming beginner courses, such as AP Computer Science A and fundamental college Java coding courses, succeed in learning Java fundamentals, some aspects of Java make it less intuitive than other programming languages and more difficult to understand than necessary. The purpose of this study is to present eleven insights on how Java could be made more learner-friendly based on the author’s personal experience learning Java and analyze whether these eleven insights are consistently perceived as useful to current student learners and industry practitioners. A digital survey was conducted with individuals who are learning or have learned the language. Respondents were presented with questions and were instructed to choose the best answer to each question. The results from the survey indicated that four insights were perceived as useful and that there was no inherent preference for the remaining six insights. Further research must be conducted to fully understand the perception differences between new learners and experienced practitioners.

Identification of pupils’ preferences of patterners and dramatists in secondary school computer science education

With the increasing integration of computer science into school curricula, a growing number of pupils are coming into contact with this subject. To get as many pupils as possible interested in computer science, the teaching strategies and methods must meet the heterogeneous prerequisites of the pupils. The purpose of this paper is to find out how to identify two different student behavioral preferences mentioned in the computer science education literature. Considering these preferences, the focus was set on the preferences for socially enriched learning on the one hand and task-oriented learning on the other hand. Even though related research has been found on the preferences of preschoolers and adults, research is missing in the field of computer science education at the secondary school level. Thus, this study focuses on the learning preferences of pupils in secondary school education regarding the two behavioral preferences. As a result, an instrument was developed and piloted that, validated by qualitative methods, measures these different preferences. Preliminary exploratory results from analyses with school classes show that preference clusters can be found in secondary education. Further research aims to use these findings to improve computer science education.

Pathfinding visualizer

Visualizations of algorithms contribute to improving computer science education. The process of teaching and learning of algorithms is sometimes, complex and hard to understand problem. Visualization is a useful technique for learning and analyzing any algorithm easily. Pathfinding refers to computing an optimal route between the specified start and goal nodes. It is an important research topic in the area of Artificial Intelligence with applications in fields such as GPS, Real-Time Strategy Games, Robotics, logistics while implemented in static or dynamic or real-world scenarios. Recent developments in pathfinding lead to more improved, accurate and faster methods and still captivates the researcher's attention for further improvement and developing new methods as more complex problems arise or being developed in AI. A great deal of research work is done in pathfinding for generating new algorithms that are fast and provide optimal path since the publication of the Dijkstra algorithm in 1959.

Pathfinder Visualizer of Shortest Paths Algorithms

Visualizations of algorithms contribute to improving computer science education. The process of teaching and learning of algorithms is often complex and hard to understand problem. Visualization is a useful technique for learning in any computer science course. In this paper an e-learning tool for shortest paths algorithms visualization is described. The developed e-learning tool allows creating, editing and saving graph structure and visualizes the algorithm steps execution. It is intended to be used as a supplement to face-to-face instruction or as a stand-alone application. The conceptual applicability of the described e-learning tool is illustrated by implementation of Dijkstra algorithm. The preliminary test results provide evidence of the usability of the e-learning tool and its potential to support students’ development of efficient mental models regarding shortest paths algorithms. This e- learning tool is intended to integrate different algorithms for shortest path determination.

Students’ Misconceptions and Other Difficulties in Introductory Programming

Efforts to improve computer science education are underway, and teachers of computer science are challenged in introductory programming courses to help learners develop their understanding of programming and computer science. Identifying and addressing students’ misconceptions is a key part of a computer science teacher's competence. However, relevant research on this topic is not as fully developed in the computer science education field as it is in mathematics and science education. In this article, we first review relevant literature on general definitions of misconceptions and studies about students’ misconceptions and other difficulties in introductory programming. Next, we investigate the factors that contribute to the difficulties. Finally, strategies and tools to address difficulties including misconceptions are discussed. Based on the review of literature, we found that students exhibit various misconceptions and other difficulties in syntactic knowledge, conceptual knowledge, and strategic knowledge. These difficulties experienced by students are related to many factors including unfamiliarity of syntax, natural language, math knowledge, inaccurate mental models, lack of strategies, programming environments, and teachers’ knowledge and instruction. However, many sources of students’ difficulties have connections with students’ prior knowledge. To better understand and address students’ misconceptions and other difficulties, various instructional approaches and tools have been developed. Nevertheless, the dissemination of these approaches and tools has been limited. Thus, first, we suggest enhancing the dissemination of existing tools and approaches and investigating their long-term effects. Second, we recommend that computing education research move beyond documenting misconceptions to address the development of students’ (mis)conceptions by integrating conceptual change theories. Third, we believe that developing and enhancing instructors’ pedagogical content knowledge (PCK), including their knowledge of students’ misconceptions and ability to apply effective instructional approaches and tools to address students’ difficulties, is vital to the success of teaching introductory programming.

E-learning Tool for Visualization of Shortest Paths Algorithms

Visualizations of algorithms contribute to improving computer science education. The process of teaching and learning of algorithms is often complex and hard to understand problem. Visualization is a useful technique for learning in any computer science course. In this paper an e-learning tool for shortest paths algorithms visualization is described. The developed e-learning tool allows creating, editing and saving graph structure and visualizes the algorithm steps execution. It is intended to be used as a supplement to face-to-face instruction or as a stand-alone application. The conceptual applicability of the described e-learning tool is illustrated by implementation of Dijkstra algorithm. The preliminary test results provide evidence of the usability of the e-learning tool and its potential to support students’ development of efficient mental models regarding shortest paths algorithms. This e- learning tool is intended to integrate different algorithms for shortest path determination.

How to Implement Rigorous Computer Science Education in K-12 Schools? Some Answers and Many Questions

Aiming to collect various concepts, approaches, and strategies for improving computer science education in K-12 schools, we edited this second special issue of the ACM TOCE journal. Our intention was to collect a set of case studies from different countries that would describe all relevant aspects of specific implementations of Computer Science Education in K-12 schools. By this, we want to deliver well-founded arguments and rich material to the critical discussion about the state and the goals of K-12 computer science education, and also provide visions for the future of this research area. In this editorial, we explain our intention and report some details about the genesis of these special issues. Following, we give a short summary of the Darmstadt Model, which was suggested to serve as a structuring principle of the case studies. The next part of the editorial presents a short description of the five extended case studies from India, Korea, NRW/Germany, Finland, and USA that are selected to be included in this second issue. In order to give some perspectives for the future, we propose a set of open research questions of the field, partly derived from the Darmstadt Model, partly stimulated by a look on large-scale investigations like PISA.

Building a virtual community of practice for K-12 CS teachers

Bringing educators together and focusing their interests toward improving computer science education in high schools.

Dragonfly: strengthening programming skills by building a game engine from scratch

Computer game development has been shown to be an effective hook for motivating students to learn both introductory and advanced computer science topics. While games can be made from scratch, to simplify the programming required game development often uses game engines that handle complicated or frequently used components of the game. These game engines present the opportunity to strengthen programming skills and expose students to a range of fundamental computer science topics. While educational efforts have been effective in using game engines to improve computer science education, there have been no published papers describing and evaluating students building a game engine from scratch as part of their course work. This paper presents the Dragonfly-approach in which students build a fully functional game engine from scratch and make a game using their engine as part of a junior-level course. Details on the programming projects are presented, as well as an evaluation of the results from two offerings that used Dragonfly. Student performance on the projects as well as student assessments demonstrates the efficacy of having students build a game engine from scratch in strengthening their programming skills.

Improving Computer Science Education through CSEdWeek Workshops

Computing is pervasive. It permeates our lives in countless ways on a daily basis. As such, computer science should be an essential component of a wellrounded education. Unfortunately, the state of computer science education is poor and there are indications that it is getting worse. Computer Science Education Week was established in 2009 to raise awareness regarding the importance of computing in today's society and to recognize the need to bolster computer science education at all levels. In support of Computer Science Education Week, the Department of Computer Science and Information Systems at Bradley University has organized and facilitated several activities to help raise awareness and excite young people about computer science. Workshops in programming, Lego robotics, mobile computing, and mathematics were offered to local high school students. Through the successes and failures of our programs, valuable lessons and insights have been gained into improving computer science education outreach activities.

EducationHuman computing skills

Establishing the fundamentals of computational thinking is essential to improving computer science education.

Improving Learning Without Improving Teaching

I have discovered that, by giving my students quizzes at the end of each class, I can noticeably improve their learning without having to improve my teaching. In this paper, I want to discuss how this “discovery” might be used by others, how it might be studied scientifically, and how it might be developed into a well engineered teaching tool. I want to suggest that developing simple, well engineered, educational tools might be a worthwhile goal for those who want to try to improve computer science education.