• Title/Summary/Keyword: programming languages education

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A DBMS-Independent Web-based Query Learning System Providing Feedback Information on Student's Exercise (학습자 실습과정 정보를 제공하는 DBMS에 독립적인 웹 기반 질의 학습 시스템)

  • Kim, Taeyoung;Choe, Hyunjong
    • The Journal of Korean Association of Computer Education
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    • v.6 no.2
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    • pp.137-146
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    • 2003
  • The Web programming techniques like CGI and server-sided script languages such as ASP, PHP and JSP have been used for developing on-line Web-based learning systems on SQL. But, the systems developed by using those techniques are dependent on the platforms on which the target DBMS's are located. Therefore, they can be hardly reused and maintained. In addition, it is not easy for them to provide a learner with the feedback information on processing his/her query and to give a teacher an opportunity of monitoring and guiding learner's learning process. In this paper, we propose an SQL learning system on the Web by using Java Applet and JDBC, which is independent on the target DBMS's. Moreover, it gives feedback information on learner's queries so that a teacher can monitor the learning process and teach them efficiently.

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Digital Competencies Required for Information Science Specialists at Saudi Universities

  • Yamani, Hanaa;AlHarthi, Ahmed;Elsigini, Waleed
    • International Journal of Computer Science & Network Security
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    • v.21 no.2
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    • pp.212-220
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    • 2021
  • The objectives of this research were to identify the digital competencies required for information science specialists at Saudi universities and to examine whether there existed conspicuous differences in the standpoint of these specialists due to years of work experience with regard to the importance of these competencies. A descriptive analytical method was used to accomplish these objectives while extracting the required digital competency list and ascertaining its importance. The research sample comprised 24 experts in the field of information science from several universities in the Kingdom of Saudi Arabia. The participants in the sample were asked to complete a questionnaire prepared to acquire the pertinent data in the period between January 5, 2021 and January 20, 2021. The results reveal that the digital competencies required for information science specialists at Saudi universities encompass general features such as the ability to use computer, Internet, Web2, Web3, and smartphone applications, digital learning resource development, data processing (big data) and its sharing via the Internet, system analysis, dealing with multiple electronic indexing applications and learning management systems and its features, using electronic bibliographic control tools, artificial intelligence tools, cybersecurity system maintenance, ability to comprehend and use different programming languages, simulation, and augmented reality applications, and knowledge and skills for 3D printing. Furthermore, no statistically significant differences were observed between the mean ranks of scores of specialists with less than 10 years of practical experience and those with practical experience of 10 years or more with regard to conferring importance to digital competencies.

A Study on the Application of Coding Education through Gamification for Tourism Experience - Focusing on "Computational Thinking" Factor Analysis - (관광경험 증대를 위한 게이미피케이션 코딩교육 활용 방안 - 컴퓨팅 사고력 요소 분석 중심으로 -)

  • Kim, Tae-Gyu;Kim, Kyoung-Bae;Kang, Shin-Young
    • Journal of Digital Convergence
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    • v.18 no.4
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    • pp.403-409
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    • 2020
  • Gamification can be more fun and interesting than boring and it can be used for variety of educational subjects. Through the fun and flow of the learner, the learner understands the meaning and context of the problem to be solved. It will be able to collect, analyze and creatively solve data in a way that computers understand. Training through gamification will be an effective and memorable coding education for the efficient learning of coding education among the newly designated compulsory education. It is considered to be highly useful as a convergence study to increase tourism experience. Currently, in the field of school, coding education is mainly conducted using entry and scratch, which are educational programming languages, and coding education using gamification is not extensively used in the current education field. It is also expected to be used to increase the tourism experience, and it can be used to enhance the learner's computational thinking ability and creativity.

The Influence of Learning App Inventor Programming of LT Collaborative Learning based on Children's Motivation (LT 협동학습 기반의 앱 인벤터 프로그래밍 교육이 초등학생들의 학습 동기에 미치는 영향)

  • Jeon, SeongKyun;Lee, YoungJun
    • The Journal of Korean Association of Computer Education
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    • v.18 no.2
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    • pp.1-9
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    • 2015
  • Excessive cognitive burdens caused by learning grammar should be reduced to cultivate high-level thinking skills in students through programing education. To this end, various educational programing languages have been developed. In recent years, block-based App Inventor that can used in real life have been introduced. This study intends to suggest an educational environment in which programing can be utilized as a leading problem solving tool by designing and producing an app that can be easily used by students in their real life. In particular, given the developmental phase of elementary school students, specific operational activities are important. For this reason, an App Inventor that can be proposed to enable dynamic interactions with the real world based on various smartphone sensors during the process of programing has significance as an educational programing language for elementary school students. In this regard, this study designed App Inventor programing education for elementary school students, which can be used in their daily life. The results of applying the education in fifth graders showed its positive effects on learning programing. LT collaborative learning where the students cooperated with each other, the theme of learning, which enables the utilization of various smartphone sensors in real life, and the app inventor may have generated and sustained the students' interest and attention.

Design and Implementation of IoT based Low cost, Effective Learning Mechanism for Empowering STEM Education in India

  • Simmi Chawla;Parul Tomar;Sapna Gambhir
    • International Journal of Computer Science & Network Security
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    • v.24 no.4
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    • pp.163-169
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    • 2024
  • India is a developing nation and has come with comprehensive way in modernizing its reducing poverty, economy and rising living standards for an outsized fragment of its residents. The STEM (Science, Technology, Engineering, and Mathematics) education plays an important role in it. STEM is an educational curriculum that emphasis on the subjects of "science, technology, engineering, and mathematics". In traditional education scenario, these subjects are taught independently, but according to the educational philosophy of STEM that teaches these subjects together in project-based lessons. STEM helps the students in his holistic development. Youth unemployment is the biggest concern due to lack of adequate skills. There is a huge skill gap behind jobless engineers and the question arises how we can prepare engineers for a better tomorrow? Now a day's Industry 4.0 is a new fourth industrial revolution which is an intelligent networking of machines and processes for industry through ICT. It is based upon the usage of cyber-physical systems and Internet of Things (IoT). Industrial revolution does not influence only production but also educational system as well. IoT in academics is a new revolution to the Internet technology, which introduced "Smartness" in the entire IT infrastructure. To improve socio-economic status of the India students must equipped with 21st century digital skills and Universities, colleges must provide individual learning kits to their students which can help them in enhancing their productivity and learning outcomes. The major goal of this paper is to present a low cost, effective learning mechanism for STEM implementation using Raspberry Pi 3+ model (Single board computer) and Node Red open source visual programming tool which is developed by IBM for wiring hardware devices together. These tools are broadly used to provide hands on experience on IoT fundamentals during teaching and learning. This paper elaborates the appropriateness and the practicality of these concepts via an example by implementing a user interface (UI) and Dashboard in Node-RED where dashboard palette is used for demonstration with switch, slider, gauge and Raspberry pi palette is used to connect with GPIO pins present on Raspberry pi board. An LED light is connected with a GPIO pin as an output pin. In this experiment, it is shown that the Node-Red dashboard is accessing on Raspberry pi and via Smartphone as well. In the final step results are shown in an elaborate manner. Conversely, inadequate Programming skills in students are the biggest challenge because without good programming skills there would be no pioneers in engineering, robotics and other areas. Coding plays an important role to increase the level of knowledge on a wide scale and to encourage the interest of students in coding. Today Python language which is Open source and most demanding languages in the industry in order to know data science and algorithms, understanding computer science would not be possible without science, technology, engineering and math. In this paper a small experiment is also done with an LED light via writing source code in python. These tiny experiments are really helpful to encourage the students and give play way to learn these advance technologies. The cost estimation is presented in tabular form for per learning kit provided to the students for Hands on experiments. Some Popular In addition, some Open source tools for experimenting with IoT Technology are described. Students can enrich their knowledge by doing lots of experiments with these freely available software's and this low cost hardware in labs or learning kits provided to them.

A Study on the Development Trend of Artificial Intelligence Using Text Mining Technique: Focused on Open Source Software Projects on Github (텍스트 마이닝 기법을 활용한 인공지능 기술개발 동향 분석 연구: 깃허브 상의 오픈 소스 소프트웨어 프로젝트를 대상으로)

  • Chong, JiSeon;Kim, Dongsung;Lee, Hong Joo;Kim, Jong Woo
    • Journal of Intelligence and Information Systems
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    • v.25 no.1
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    • pp.1-19
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    • 2019
  • Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.