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

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.193-198
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• 2023

This paper analyzed the validity of exercise problems for each unit in Python programming education. Practice questions presented for each unit are presented through an online learning system, and each student uploads an answer code and is automatically graded. Data such as students' mid-term exam scores, final exam scores, and practice questions scores for each unit are collected through Python lecture that lasts for one semester. Through the collected data, it is possible to improve the exercise problems for each unit by analyzing the validity of the automatic scoring exercise problems. In this paper, Orange machine learning tool was used to analyze the validity of automatic scoring exercises. The data collected in the Python subject are analyzed and compared comprehensively by total, top, and bottom groups. From the prediction accuracy of the machine learning model that predicts the student's final grade from the Python unit-by-unit practice problem scores, the validity of the automatic scoring exercises for each unit was analyzed.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.613-618
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• 2012

ICT education guidelines revised in 2005 reinforce computer science elements such as algorithm, data structure, and programming covering all schools. And Ministry of Education emphasizes STEAM education. Most important is that "How instruct them". This means necessity of contents. So this paper suggests learning method of Stack and Queue using LEGO MINDSTORMS NXT. The main purpose is that how stack and queue are used, when robot explore realistic maze. Teaching and learning strategies are algorithm, flowchart, and NXT-G programming. Simple maze has path in left or right, but complex maze has three-way intersection. These are developed by authors. Master robot explores maze and push stack, and then return to entrance using stack. Master robot explores maze and transmits path to slave's queue. And then slave robot drives without exploration. Students can naturally learn principles and applications of them. Through these studies, it can improves ability of logical and creative thinking. Furthermore it can apply to ICT and STEAM education.

• Journal of The Korean Association of Information Education
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• v.21 no.1
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• pp.97-104
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• 2017

This paper evaluates the appropriateness of the proposed robot education curriculum to consider conceptual understanding and learning activities model considering the curriculum and achievement criteria in order to make it easier to apply for a course in robot area. The professors of dept. of computer education at national universities of education reviewed the importance of education contents system and appropriateness of education period. Based on the results of the review, the conceptual elements and achievement standards of each sub-area were revised and supplemented, and then evaluated in three stages. Finally, the educational elements of the concept factors and achievement criteria were agreed upon. The proposed robotic computing education information systems and the achievement standards for schools in the area, as well as to match the grade level of the students without distinction variety of robots will be able to take advantage of computing education activities to reorganize the robot computing courses.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.232-237
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• 2020

Given the recent pace of development and expansion of Artificial Intelligence (AI) technology, the influence and ripple effects of AI technology on the whole of our lives will be very large and spread rapidly. The National Artificial Intelligence R&D Strategy, published in 2019, emphasizes the importance of artificial intelligence education for K-12 students. It also mentions STEM education, AI convergence curriculum, and budget for supporting the development of teaching materials and tools. However, it is necessary to create a new type of curriculum at a time when artificial intelligence curriculum has never existed before. With many attempts and discussions going very fast in all countries on almost the same starting line. Also, there is no suitable professor for K-12 students, and it is difficult to make K-12 students understand the concept of AI. In particular, it is difficult to teach elementary school students through professional programming in AI education. It is also difficult to learn tools that can teach AI concepts. In this paper, we propose an educational model for elementary school students to improve their understanding of AI through play or experience. This an experiential education model that combineds exploratory learning and discovery learning using multi-intelligence and the PLAY teaching-learning model to undertand the importance of data training or data required for AI education. This educational model is designed to learn how a computer that knows only binary numbers through UA recognizes images. Through code.org, students were trained to learn AI robots and configured to understand data bias like play. In addition, by learning images directly on a computer through TeachableMachine, a tool capable of supervised learning, to understand the concept of dataset, learning process, and accuracy, and proposed the process of AI inference.

• International journal of advanced smart convergence
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• v.9 no.2
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• pp.28-37
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• 2020

We conducted a comprehensive review on the previous research on r-Learning. By reviewing 843 previous studies about r-Learning published from 2004 to 2015, this study investigated 1) the trend of research on r-Learning over time, 2) the characteristics of targeted students in r-Learning, 3) the educational activities implemented for r-Learning, and 4) the types of educational robots used for r-Learning. The study found that the research on r-Learning has rapidly and steadily increased and the types of educational activities and educational robots has been diversified. Relying on the findings of this review, this study suggests 1) ensuring growth in both the quality and the quantity of research on r-Learning, 2) broadening the target student population of r-Learning beyond the age-limited boundaries, 3) enhancing educational activities of r-Learning, and 4) recognizing the necessity for systematic and clear concepts of types of educational robots.

• The Journal of Korean Association of Computer Education
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• v.10 no.3
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• pp.9-17
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• 2007

This study compared and analysed computer textbooks of the middle school from South Korea and North Korea for preparing the unification of the Korean Peninsula. According to the result of this study, the contents of South Korea textbook were equally selected from all scopes. By contrast, the contents of North Korea mostly consisted of the basic knowledge of computer, word-processing excluding the newest contents as Internet or Multimedia. But with the BASIC programming and algorithm for enhancement of the creative solving ability, prospective IT brains had been trained in North Korea. Moreover, due to differences of language policy and country that delivered IT technology, significant differences were found between South and North Korea in IT terminology. For preparing IT education after unification of the Korean Peninsula, both efforts of people who work in the fields of IT and school system in South and North Korea should be taken in order to relieve these differences.

• Journal of Creative Information Culture
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• v.5 no.1
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• pp.35-43
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• 2019

In this study, we analyzed how information and technology education in elementary and middle school curriculum affects learning achievement of computational thinking courses in university. We conducted a questionnaire survey on students who took computer-related courses for the past year and collected data on what type of computer-related education they received. As a result of analyzing the data, students who received computer-related education in the previous curriculum showed higher overall academic achievement. However, there was a significant difference in learning achievement according to types of contents, and it is necessary to consider the design and improvement of efficient computational thinking education in the future through the results. It is also necessary to continue the analysis of the impact of the new education curriculum.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.225-227
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• 2018

Computational thinking is generally defined as the mental skills that facilitate the design of automated processes. Computational Thinking is being considered as a critical skill for students in the 21st century. It involves many skills, but programming abilities seem to be a core aspect since they foster the development of a new way of thinking that is key to the solution of problems that require a combination of human mental power and computing power capacity. In this paper, we explore how computational thinking conception are changing. We also explore how to identify the psychological and behavioral nature of learners through SW education.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.179-183
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• 2020

The online education platform market is developing rapidly after the coronavirus infection-19 pandemic. As school classes at various levels are converted to non-face-to-face classes, interest in non-face-to-face online education is increasing more than ever. However, the majority of online platforms currently used are limited to the fragmentary functions of simply delivering images, voice and messages, and there are limitations to online hands-on training. Indeed, digital transformation is a traditional business method for increasing coding education and a corporate approach to service operation innovation strategy computing thinking power and platform model. There are many ways to evaluate a computer programmer's ability. Generally, piecemeal evaluation methods are used to evaluate results in time through coding tests. In this study, the purpose of this study is to propose a comprehensive evaluation of not only the results of writing, but also the execution process of the results, etc., and to evaluate the programmer's propensity habits based on the programmer's coding experience to evaluate the programmer's ability and productivity.