• Research in Mathematical Education
• /
• v.9 no.4 s.24
• /
• pp.341-350
• /
• 2005

In this increasingly technological world, the creativity development has been highlighted much in many countries. In this paper, two mathematical activities with Chinese characteristics are presented to illustrate how to integrate algorithmic teaching into mathematical activities to develop students' creativity. Case studies show that the learning of algorithm can be transferred into creative learning when students construct their own algorithms in Logo environment rather than being indoctrinated the existing algorithms. Creativity development in different stages of mathematical activities and creativity development in programming are also discussed.

• Communications of Mathematical Education
• /
• v.21 no.2 s.30
• /
• pp.153-176
• /
• 2007

The purpose of this paper is to analyze teaching-learning program which can be applied to mathematically gifted students in primary school, Our program is based on constructivist views on teaching and learning of mathematics. Mainly, we study the algorithmic thinking of mathematically gifted students in primary school in connection with the network problems; Eulerian graph problem, the minimum connector problem, and the shortest path problem, The above 3-subjects are not familiar with primary school mathematics, so that we adapt teaching-learning model based on the social constructivism. To achieve the purpose of this study, seventeen students in primary school participated in the study, and video type(observation) and student's mathematical note were used for collecting data while the students studied. The results of our study were summarized as follows: First, network problems based on teaching-learning model of constructivist views help students learn the algorithmic thinking. Second, the teaching-learning model based on constructivist views gives an opportunity of various mathematical thinking experience. Finally, the teaching-learning model based on constructivist views needs more the ability of teacher's research and the time of teaching for students than an ordinary teaching-learning model.

• Research in Mathematical Education
• /
• v.11 no.1
• /
• pp.65-74
• /
• 2007

The algorithmic idea has been a kind of necessary mathematics quality for modern people in this information society. In China the algorithm was represented fully as one of the new mathematics contents in the secondary level for the first time when The Standards of Mathematics Curriculum for the Senior High School was promulgated in 2003, so the research about the teaching algorithm undoubtedly has its practical implications for mathematics education. In this paper, with the conceptual framework of The Mathematics Task Framework as the research tool, an algorithmic teaching case based on LOGO software was introduced in detail, and data by ways of observations, interviews and worksheets were collected, then the case was analyzed. The results showed that the teaching of algorithm is feasible and effective in the LOGO environment. Some beneficial implications about the instructional design of algorithm were also discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.5 no.10
• /
• pp.1799-1813
• /
• 2011

Many researches indicate that programming learning could help improve problem solving skills through algorithmic thinking. But in general, programming learning has been focused on programming language features and it also gave a heavy cognitive load to learners. Therefore, this paper proposes a programming activity process to improve novice programming learners' algorithmic thinking efficiently. An experiment was performed to measure the effectiveness of the proposed programming activity process. After the experiment, the learners' perception on programming was shown to be changed, to effective activity in improving problem solving.

• International Journal of Computer Science & Network Security
• /
• v.22 no.1
• /
• pp.105-112
• /
• 2022

The development and spread of IT-technologies has raised interest in teaching programming pupils. The article deals with problems related to programming and ways to overcome them. The importance of programming skills is emphasized, as this process promotes the formation of algorithmic thinking of pupils. The authors determined the level of pupils' interest to programing learning depending on the age. The analysis has showed that the natural interest of younger pupils in programming is decreasing over the years and in the most productive period of its study is minimized. It is revealed that senior school pupils are characterized by low level of interest in the study of programming; lack of motivation; the presence of psychological blocks on their own abilities in the context of programming; law level of computer science understanding. To overcome these problems, we conducted the second stage of the experiment, which was based on a change in the approach to programing learning, which involved pupils of non-specialized classes of senior school (experimental group). During the study of programming, special attention was paid to the motivational and psychological component, as well as the use of game technologies and teamwork of pupils. The results of the pedagogical experiment on studying the effectiveness of teaching programming for pupils of nonspecialized classes are presented. Improvement of the results provided the use of social and cognitive motives; application of verbal and non-verbal, external and internal means; communicative attacks; stimulation and psychological setting; game techniques, independent work and reflection, teamwork. The positive effect of the implemented methods is shown by the results verified by the methods of mathematical statistics in the experimental and control groups of pupils.

• Journal of the Korean School Mathematics Society
• /
• v.21 no.2
• /
• pp.113-139
• /
• 2018

There is no doubt about the importance of teacher knowledge for good teaching. Many researches attempted to conceptualize elements and features of teacher knowledge for teaching in a quantitative way. Unlike existing researches, this article suggests an interpretation of preservice teacher knowledge in the field of geometry using the Shulman - Fischbein framework in a qualitative way. Seven female preservice teachers voluntarily participated in this research and they performed a series of written tasks that asked their subject matter knowledge (SMK) and pedagogical content knowledge (PCK). Their responses were analyzed according to mathematical algorithmic -, formal -, and intuitive - SMK and PCK. The interpretation revealed that preservice teachers had overally strong SMK, their deeply rooted SMK did not change, their SMK affected their PCK, they had appropriate PCK with regard to knowledge of student, and they tended to less focus on mathematical intuitive - PCK when they considered instructional strategies. The understanding of preservice teachers' knowledge throughout the analysis using Shulman-Fischbein framework will be able to help design teacher preparation programs.

• The Journal of Korean Association of Computer Education
• /
• v.22 no.6
• /
• pp.11-18
• /
• 2019

Software education is required from elementary schools to prepare students for the fourth industrial revolution, which aims to improve algorithmic thinking. In general, teaching is divided into two stages: using a flowchart to design algorithms and implementing them through programming. However, converting a flowchart into code and checking the results in an educational programming tool is time consuming and requires additional programming activities. This study proposes a tangible coding tool that enables elementary students to convert algorithms designed at the unplugged activity into educational programming tool codes. This tool was developed in order for students to design algorithms at the level of assembling paper blocks and input them into a programming tool by taking a picture. Sixth graders were participated in this activity to evaluate its usability.

• Journal of Convergence for Information Technology
• /
• v.10 no.8
• /
• pp.173-178
• /
• 2020

In the near future, as artificial intelligence and computing network technology develop, collaboration with artificial intelligence (AI) will become important. In an AI society, the ability to communicate and collaborate among people is an important element of talent. To do this, it is necessary to understand how artificial intelligence based on computer science works. An algorithmic education focused on problem solving and learning is efficient for computer science education. In this study, the results of an assessment of computational thinking at the beginning of the semester, a satisfaction survey at the end of the semester, and academic performance were compared and analyzed for 28 students who received algorithmic education focused on problem-solving learning. As a result of diagnosing students' computational thinking and problem-solving learning, teaching methods, lecture satisfaction, and other environmental factors, a correlation was found, and regression analysis confirmed that problem-solving learning had an effect on improving lecture satisfaction and computational thinking ability. For algorithmic education, if you pursue a problem-solving learning technique and a way to improve students' satisfaction, it will help students improve their problem-solving skills.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2012.01a
• /
• pp.119-122
• /
• 2012

정보화시대에 요구하는 인재는 문제를 인식하고 이런 문제를 풀기 위해 다양한 전문가들과 함께 창의적인 사고를 통해 해결책을 제시하는 인물이다. 정보영재교육의 목표 역시 창의적 인재를 기르는 데 있으나, 프로그래밍과 알고리즘 교육은 특정 프로그래밍 언어의 사용법이나 문법 위주의 교육, 정렬 및 탐색과 같은 알고리즘 그 자체에 치중함으로서 이러한 목표에 도달하고 있지 못하다는 지적이 많다. 이에 본 논문에서는 창의적인 알고리즘을 설계하고 개발하는데 필요한 사고력, 즉 사고 과정에 대해 안내하고 생각하는 알고리즘적 사고력을 기르기 위한 방안으로 실생활 주제의 이야기 쓰기를 활용하는 교수 학습 프로그램을 제안하였다. 반성적 사고와 창의성을 기르는 데 효과적인 것으로 알려진 이야기 쓰기 활동에서 출발하여 사건 요소 추출과 시간적 질서 분석하기, 순서도로 알고리즘 표현하기, 동료 학습자와 토의하기 등의 과정을 통해 알고리즘적 사고력을 향상시킬 수 있도록 하였다.

• The Mathematical Education
• /
• v.63 no.2
• /
• pp.233-254
• /
• 2024

This paper delves into the symbiotic integration of coding and mathematics education, aimed at cultivating computational thinking and enriching mathematical problem-solving proficiencies. We have identified a corpus of scholarly articles (n=38) disseminated within the preceding two decades, subsequently culling a portion thereof, ultimately engendering a contemplative analysis of the extant remnants. In a swiftly evolving society driven by the Fourth Industrial Revolution and the ascendancy of Artificial Intelligence (AI), understanding the synergy between these domains has become paramount. Mathematics education stands at the crossroads of this transformation, witnessing a profound influence of AI. This paper explores the evolving landscape of mathematical cognition propelled by AI, accentuating how AI empowers advanced analytical and problem-solving capabilities, particularly in the realm of big data-driven scenarios. Given this shifting paradigm, it becomes imperative to investigate and assess AI's impact on mathematics education, a pivotal endeavor in forging an education system aligned with the future. The symbiosis of AI and human cognition doesn't merely amplify AI-centric thinking but also fosters personalized cognitive processes by facilitating interaction with AI and encouraging critical contemplation of AI's algorithmic underpinnings. This necessitates a broader conception of educational tools, encompassing AI as a catalyst for mathematical cognition, transcending conventional linguistic and symbolic instruments.