• Title/Summary/Keyword: Learning Tools

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Differences between Pre-service Elementary Teachers' Perceptions and Designs on Smart Tools in Developing Smart-based Lesson Materials (스마트 지원 수업 설계에서 초등 예비교사들이 보이는 스마트 도구에 대한 인식과 활용의 차이)

  • Kang, Eunhee
    • Journal of Korean Elementary Science Education
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    • v.37 no.1
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    • pp.66-79
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    • 2018
  • The purpose of this study is to explore how pre-service elementary teachers perceive and use smart learning environments. For this purpose, 23 pre-service elementary teachers who took theory and practice in a science education course were asked to develop lesson materials using smart tools and make a self-report questionnaire. These data were categorized in an instructional, exploratory, and interactive approach, depending on how they guided students to access knowledge and information. As a result of the study, pre-service teachers perceived the smart tools as the exploratory and interactive learning tools to be used for students to actively search for and interact with data and knowledge. But in developing lesson materials, they usually used the smart tools for resource sharing and communication in the instructional manner. In conclusion, the gap between their perception of smart tools and lesson materials, and the educational implications will be discussed.

A Study on Project-based Smart Learning Tool Model (프로젝트 기반 스마트 학습 도구 모델에 관한 연구)

  • Lee, Keun-Ho
    • Journal of Internet of Things and Convergence
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    • v.8 no.5
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    • pp.93-98
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    • 2022
  • With the development of new digital technologies, research on various learning tools is being actively conducted. These learning tools are also being developed so that they can be applied to various environments by applying the technology of artificial intelligence or using smart functions to which big data technology is applied. These smart learning tools are contributing a lot to increasing educational effectiveness and learning efficiency. Recently, various learning tools have been applied in universities, and solutions for smart learning from smart attendance are introduced to improve student learning efficiency. This study intends to propose a design for a smart learning tool that can increase the efficiency of project progress and increase the scalability of the results when conducting a company's customized project through such a university's smart learning tool. The proposed smart learning tool is expected to have the advantage of being able to easily adapt to the practical business project as the company-customized projects that can improve practical skills are smoothly used as a learning tool. The proposed project-based smart learning tool model is later built as a related LMS and applied to actual project progress to check its utility, and to revise and supplement the proposed smart learning tool model to provide a project-based smart learning function want to strengthen.

Effects of the use of a conversational artificial intelligence chatbot on medical students' patient-centered communication skill development in a metaverse environment

  • Hyeonmi Hong;Sunghee Shin
    • Journal of Medicine and Life Science
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    • v.21 no.3
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    • pp.92-101
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    • 2024
  • This study investigated how the use of a conversational artificial intelligence (AI) chatbot improved medical students' patient-centered communication (PCC) skills and how it affected their motivation to learn using innovative interactive tools such as AI chatbots throughout their careers. This study adopted a one-group post-test-only design to investigate the impact of AI chatbot-based learning on medical students' PCC skills, their learning motivation with AI chatbots, and their perception towards the use of AI chatbots in their learning. After a series of classroom activities, including metaverse exploration, AI chatbot-based learning activities, and classroom discussions, 43 medical students completed three surveys that measured their motivation to learn using AI tools for medical education, their perception towards the use of AI chatbots in their learning, and their self-assessment of their PCC skills. Our findings revealed significant correlations among learning motivation, PCC scores, and perception variables. Notably, the perception towards AI chatbot-based learning and AI chatbot learning motivation showed a very strong positive correlation (r=0.72), indicating that motivated students were more likely to perceive chatbots as beneficial educational tools. Additionally, a moderate correlation between motivation and self-assessed PCC skills (r=0.54) indicated that students motivated to use AI chatbots tended to rate their PCC skills more favorably. Similarly, a positive relationship (r=0.68) between students' perceptions of chatbot usage and their self-assessed PCC skills indicated that enhancing students' perceptions of AI tools could lead to better educational outcomes.

A comparative analysis on concept mapping tools for computer-supported collaborative learning (컴퓨터기반 협력학습을 위한 개념도작성도구의 비교 분석 및 고찰)

  • Lee, Hyojin;Jeong, Seunghee;Yang, Sunyoung;Eun, Jihye;Kim, Kyungjin;Kim, Dongsik
    • The Journal of Korean Association of Computer Education
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    • v.18 no.3
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    • pp.37-47
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    • 2015
  • The purpose of this study is to review the concept mapping tools and provide implications for designing tools that support collaborative learning activities. For this purpose, representative concept mapping tools - Convince Me, Knowledge Forum, Cmaptools, Mindmeister, Belvedere - was analyzed by using the 3C(Communication, Coordination, Cooperation) framework. We have applied three research methods; 1) literature review on design principles of tools, 2) heuristic evaluation, 3) focus group interview. As a result, most of comcept mapping tools supported communication functions but partialy supported coordication and cooperation features.

Cyber Learners' Use and Perceptions of Online Machine Translation Tools

  • Moon, Dosik
    • International journal of advanced smart convergence
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    • v.10 no.4
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    • pp.165-171
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    • 2021
  • The current study investigated cyber learners' use and perceptions of online machine translation (MT) tools. The results show that learners use several MT tools frequently and extensively for various second language learning (L2) purposes according to their needs. The learners' overall perceptions of using MT for English learning were generally positive. The learners reported several advantages of machine translation: ease of use, helpful feedback, effective revision, and facilitation of self-directed learning. At the same time, a considerable number of learners were aware of MT's drawbacks, such as awkward sentences, inaccurate grammar, and inappropriate words, and thus held a negative or skeptical view on the quality and accuracy of MT. These findings have important pedagogical implications for using MT in the context of a cyber university. For successful integration of MT in English classes, teachers need to provide appropriate guidelines and training that will help learners use MT effectively.

Development and Application of Blended Learning Strategy for Collaborative Learning (협력학습을 위한 혼합학습 전략 개발 및 적용)

  • Ku, Jin-Hui;Choi, Won-Sik
    • 대한공업교육학회지
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    • v.34 no.2
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    • pp.267-285
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    • 2009
  • The collaborative learning has been considered as an efficient teaching model and under the recent basic learning environment, even face-to-face classroom circumstance rapidly increases the courses of blended learning which utilize the merits of e-learning environment. Nonetheless, the study on the strategy for systematic blended learning is quite scarce. In this study, the survey was done for developing the blended learning strategy, based on the collaborative learning model at the face-to-face environment and judging the satisfaction on the courses which the model was applied to. The survey consists of demographic questions, satisfaction in the whole courses, satisfaction in the collaborative learning under the blended learning environment and satisfaction in the blended learning strategy and support tools applied to each step of the learning. The result of this study is as follows. First, in response to the question that the blended learning can complement the face-to-face classroom courses, the respondents represented average 4.09 at 5-point Likert scale. And to the question whether the collaborative learning is more efficient under the blended learning environment than the face-to-face classroom, the response corresponds to 4.06 scale on the average. Second, as for the satisfaction in the blended learning strategy and support tools applied to the each step of the blended learning, the satisfaction degree is analyzed as high as over 4.0 on the average toward all the questions. Third, regarding the support tools used for the blended learning strategy, the learners consider the tools as most helpful in order of chatting, team community, mail & note and archive. Lastly, I would like to suggest that the study result should be highly reflected in constructing the collaborative learning module of learning control system in the future.

A Study on the Classification of Variables Affecting Smartphone Addiction in Decision Tree Environment Using Python Program

  • Kim, Seung-Jae
    • International journal of advanced smart convergence
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    • v.11 no.4
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    • pp.68-80
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    • 2022
  • Since the launch of AI, technology development to implement complete and sophisticated AI functions has continued. In efforts to develop technologies for complete automation, Machine Learning techniques and deep learning techniques are mainly used. These techniques deal with supervised learning, unsupervised learning, and reinforcement learning as internal technical elements, and use the Big-data Analysis method again to set the cornerstone for decision-making. In addition, established decision-making is being improved through subsequent repetition and renewal of decision-making standards. In other words, big data analysis, which enables data classification and recognition/recognition, is important enough to be called a key technical element of AI function. Therefore, big data analysis itself is important and requires sophisticated analysis. In this study, among various tools that can analyze big data, we will use a Python program to find out what variables can affect addiction according to smartphone use in a decision tree environment. We the Python program checks whether data classification by decision tree shows the same performance as other tools, and sees if it can give reliability to decision-making about the addictiveness of smartphone use. Through the results of this study, it can be seen that there is no problem in performing big data analysis using any of the various statistical tools such as Python and R when analyzing big data.

The Effectiveness of the Use of Distance-Evaluation Tools and Methods among Students with Learning-Difficulties from the Teachers' Point of View

  • Almaleki, Deyab A.;Khayat, Wejdan W.;Yally, Taghreed F.;Al-hajjaji, Aysha A.
    • International Journal of Computer Science & Network Security
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    • v.21 no.5
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    • pp.243-255
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    • 2021
  • This study aimed to identify the effectiveness of the use of distance-evaluation tools and methods among students with learning difficulties from the teachers' point of view, to achieve this goal. A scale was built, and the psychometric characteristics were validated. It consisted, in its final form, of 17 items distributed on four axes, in addition to three open questions. It was applied to a random sample of (149) teachers of students with learning difficulties in Makkah Region. The results showed that teachers' keenness to encourage students with learning difficulties, so that they would not feel frustrated with the distance learning process. It was also evident that teachers did not use achievement portfolios in the evaluation process. In connection with the appropriate evaluation methods, the majority indicated the use of work sheets and visual evaluation methods that rely on audio and visual skills, such as presenting videos, pictures, audio and games, and applying short objective tests. Among the proposals to improve evaluation methods and tools: Individual evaluation, attention to individual treatment, obligating personal attendance of students to school, splitting the required tasks, and not increasing the skills required to be mastered. As for the obstacles that teachers face: Lack of time, difficulty in communicating with students with distance learning difficulties and problems related to the Internet such as interruption, weakness, or lack of availability.

Teaching a Database Course with Collaborative Team Projects

  • Park, Jae-Hwa
    • The Journal of Information Technology and Database
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    • v.4 no.1
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    • pp.65-77
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    • 1997
  • This paper describes and effective teaching approach to an undergraduate database course. This research draws on practical experience based on the hands-on practice approach which leads students to develop a database application utilizing various tools. Students not only learn concepts, methodologies and tools of database technology in class and through online multimedia learning aids, but also practice how to integrate them through collaborative team projects. The course employs collaborative learning approach and multimedia and internet technologies. Students are encouraged to work collaboratively on assignments and projects and to learn independently through online multimedia learning aids.

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