• Title/Summary/Keyword: Learning Tool

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Increase in dental hygienists' competency and self-directed capacity after capstone design course on community dental hygiene (캡스톤 디자인 지역사회치위생학 수업이 치과위생사 역량 및 자기 주도력 증가에 미치는 효과)

  • Seon-Ju Sim;Sun-Mi Lee
    • Journal of Korean society of Dental Hygiene
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    • v.24 no.2
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    • pp.99-108
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    • 2024
  • Objectives: This study aimed to verify the effect on students' competency and self-directed capacity after a capstone design teaching method with community dental hygiene class. Methods: The study participants were 34 dental hygiene students taking a 4-year community dental hygiene course at a university located in City C. The research tool consisted of 52 questions on major competency and 20 questions on self-directed capacity. Results: After the capstone design class, overall dental hygienists' competency increased (p<0.05), and competencies of clinical dental hygiene and community health promotion showed a high increase (p<0.001). As a result of analyzing the increase in dental hygienists' competency according to self-directed learning ability, the group with low self-directed capacity showed high improvement in clinical dental hygiene competency and community oral health promotion competency. Conclusions: This study confirmed that the capstone design course in community dental hygiene improved students' competency and self-directed capacity, and suggests that it is an excellent teaching method for training competencies required for future society.

The Effect of Virtual Reality-Based Complex Cognitive Training Program on Cognitive Function, Depression, Digital Divide Reduction in the Elderly: An exploratory study (가상현실(Virtual Reality) 기반 복합인지중재 프로그램이 노인의 인지기능, 우울, 디지털 격차 해소에 미치는 영향: 탐색적 연구)

  • Bit-Na Cho;Pumsoo Kim;Dong-Gi Hong;Min-Jung Kwak
    • Journal of The Korean Society of Integrative Medicine
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    • v.12 no.1
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    • pp.109-124
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    • 2024
  • Purpose : The purpose of this study was to examine the effects of a virtual reality-based complex cognitive training program for depression, cognitive function, and digital divide reduction in the elderly who have not been diagnosed with dementia or MCI. Methods : We enrolled 16 participants who were over 65 years old and not been diagnosed with dementia or MCI. We randomly divided into three groups (A, B, C). Participants underwent an 8-week virtual reality-based complex cognitive training program (60 minutes each session, twice per week). At a baseline, all participants completed questionnaires on general features, depression and cognitive function. After four weeks, all participants completed questionnaires on depression and cognitive function. After the end of the last program, participants conducted questionnaires on depression, cognitive function, and usability evaluation. Results : At the 8-week follow-up, 16 participants completed the program. Compared to the baseline, the average score of cognitive function was increased (from 26.5 to 28.5), although it was not statistically significant (p<.061). There were no significant differences between baseline and post-training evaluations on depression scores. The average score of usability evaluation was 75.56, which corresponds to good. Conclusion : Even though the results showed no statistically significant findings in cognitive function and depression after the virtual reality-based complex cognitive training intervention, this pilot study proposed the possibility of utilizing the virtual reality program as a tool that provides active learning opportunities for the elderly and helps improve their cognitive function through multi-sensory components. Also, the findings of this study suggested a positive reevaluation of the elderly's digital access capabilities while reducing the digital divide. A virtual reality-based complex cognitive training program improved the social network of the elderly. We expect that it will expand in size and help with their social participation of the elderly.

The new frontier: utilizing ChatGPT to expand craniofacial research

  • Andi Zhang;Ethan Dimock;Rohun Gupta;Kevin Chen
    • Archives of Craniofacial Surgery
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    • v.25 no.3
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    • pp.116-122
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    • 2024
  • Background: Due to the importance of evidence-based research in plastic surgery, the authors of this study aimed to assess the accuracy of ChatGPT in generating novel systematic review ideas within the field of craniofacial surgery. Methods: ChatGPT was prompted to generate 20 novel systematic review ideas for 10 different subcategories within the field of craniofacial surgery. For each topic, the chatbot was told to give 10 "general" and 10 "specific" ideas that were related to the concept. In order to determine the accuracy of ChatGPT, a literature review was conducted using PubMed, CINAHL, Embase, and Cochrane. Results: In total, 200 total systematic review research ideas were generated by ChatGPT. We found that the algorithm had an overall 57.5% accuracy at identifying novel systematic review ideas. ChatGPT was found to be 39% accurate for general topics and 76% accurate for specific topics. Conclusion: Craniofacial surgeons should use ChatGPT as a tool. We found that ChatGPT provided more precise answers with specific research questions than with general questions and helped narrow down the search scope, leading to a more relevant and accurate response. Beyond research purposes, ChatGPT can augment patient consultations, improve healthcare equity, and assist in clinical decision-making. With rapid advancements in artificial intelligence (AI), it is important for plastic surgeons to consider using AI in their clinical practice to improve patient-centered outcomes.

Development and Validation of Distributed Cognition Theory Based Instructional Strategy in Science Class Using Technology (테크놀로지 활용 과학 수업에서 분산인지 이론 기반 수업 전략의 개발 및 타당화)

  • Ja-Heon Noh;Jun-Ho Son;Jong-Hee Kim
    • Journal of the Korean Society of Earth Science Education
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    • v.17 no.1
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    • pp.1-19
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    • 2024
  • This study is a design and development study that developed instructional strategies based on distributed cognitive theory for science classes using technology according to procedures that ensured reliability and validity. To develop instructional strategies, development study and validation study were conducted according to design and development research methodology procedures. In the development study, an initial instructional strategy was developed through prior literature review and prior expert review. In the validation study, the instructional strategy was validated using internal validation (expert validation, usability evaluation) and external validation (field application evaluation) methods, and the final instructional strategy was developed. The final instructional strategy consisted of 3 instructional principles, 9 instructional strategies, and 38 detailed guidelines. Through this study, the researcher suggested the suitability of instructional strategies for science classes using technology, the usefulness of blocks and teaching and learning processes, the possibility of using technology as a cognitive tool, the need for teachers' efforts to cultivate teaching capabilities using technology, and the needs lesson plan that takes into account conditions affecting the application of instructional strategies.

Analysis of Ammunition Inspection Record Data and Development of Ammunition Condition Code Classification Model (탄약검사기록 데이터 분석 및 탄약상태기호 분류 모델 개발)

  • Young-Jin Jung;Ji-Soo Hong;Sol-Ip Kim;Sung-Woo Kang
    • Journal of the Korea Safety Management & Science
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    • v.26 no.2
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    • pp.23-31
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    • 2024
  • In the military, ammunition and explosives stored and managed can cause serious damage if mishandled, thus securing safety through the utilization of ammunition reliability data is necessary. In this study, exploratory data analysis of ammunition inspection records data is conducted to extract reliability information of stored ammunition and to predict the ammunition condition code, which represents the lifespan information of the ammunition. This study consists of three stages: ammunition inspection record data collection and preprocessing, exploratory data analysis, and classification of ammunition condition codes. For the classification of ammunition condition codes, five models based on boosting algorithms are employed (AdaBoost, GBM, XGBoost, LightGBM, CatBoost). The most superior model is selected based on the performance metrics of the model, including Accuracy, Precision, Recall, and F1-score. The ammunition in this study was primarily produced from the 1980s to the 1990s, with a trend of increased inspection volume in the early stages of production and around 30 years after production. Pre-issue inspections (PII) were predominantly conducted, and there was a tendency for the grade of ammunition condition codes to decrease as the storage period increased. The classification of ammunition condition codes showed that the CatBoost model exhibited the most superior performance, with an Accuracy of 93% and an F1-score of 93%. This study emphasizes the safety and reliability of ammunition and proposes a model for classifying ammunition condition codes by analyzing ammunition inspection record data. This model can serve as a tool to assist ammunition inspectors and is expected to enhance not only the safety of ammunition but also the efficiency of ammunition storage management.

Utilizing the n-back Task to Investigate Working Memory and Extending Gerontological Educational Tools for Applicability in School-aged Children

  • Chih-Chin Liang;Si-Jie Fu
    • Journal of Information Technology Applications and Management
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    • v.31 no.1
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    • pp.177-188
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    • 2024
  • In this research, a cohort of two children, aged 7-8 years, was selected to participate in a specialized three-week training program aimed at enhancing their working memory. The program consisted of three sessions, each lasting approximately 30 minutes. The primary goal was to investigate the impact and developmental trajectory of working memory in school-aged children. Working memory plays a significant role in young children's learning and daily activities. To address the needs of this demographic, products should offer both educational and enjoyable activities that engage working memory. Digital educational tools, known for their flexibility, are suitable for both older individuals and young children. By updating software or modifying content, these tools can be effectively repurposed for young learners without extensive hardware changes, making them both cost-effective and practical. For example, memory training games initially designed for older adults can be adapted for young children by altering images, music, or storylines. Furthermore, incorporating elements familiar to children, like animals, toys, or fairy tales, can increase their engagement in these activities. Historically, working memory capabilities have been assessed predominantly through traditional intelligence tests. However, recent research questions the adequacy of these behavioral measures in accurately detecting changes in working memory. To bridge this gap, the current study utilized electroencephalography (EEG) as a more sophisticated and precise tool for monitoring potential changes in working memory after the training. The research findings were revealing. Participants showed marked improvement in their performance on n-back tasks, a standard measure for evaluating working memory. This improvement post-training strongly supports the effectiveness of the training program. The results indicate that such targeted and structured training programs can significantly enhance the working memory abilities of children in this age group, providing promising implications for educational strategies and cognitive development interventions.

Comparison of Pattern Design Functions in YUKA and CLO for CAD Education: Focusing on Skirt Patterns (캐드 교육을 위한 YUKA와 CLO의 패턴 제도 기능 비교: 스커트패턴을 중심으로)

  • Younglim Choi
    • Fashion & Textile Research Journal
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    • v.26 no.1
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    • pp.65-77
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    • 2024
  • This study aimed to propose effective ways to integrate CLO into educational settings by conducting a comparative analysis of pattern functions in YUKA and CLO, specifically focusing on skirt prototypes and variations. CLO, being a 3D virtual sample CAD tool, is mainly used in education to facilitate the creation of 3D virtual clothing. In order to explore the applicability of CLO's pattern functions in pattern education, CAD education experts were asked to produce two types of skirt prototypes and two skirt variations. Subsequently, in-depth interviews were conducted. In addition, the skirt pattern creation process was recorded on video and used for comparative analysis of YUKA and CLO pattern functions. The comparison revealed that CLO provides the pattern tools necessary for drafting skirt prototypes. The learning curve for acquiring the skills necessary for drafting and transforming skirt prototypes was found to be relatively shorter for CLO compared to YUKA. In addition, due to CLO's surface-based pattern drawing method, it is difficult to move or copy only specific parts of the outline, and there are some limitations in drawing right angle lines. In the pattern transformation process, CLO's preview function proved to be advantageous, and it was highly rated on user convenience due to the intuitive UI. Thus, CLO shows promise for pattern drafting education and is deemed to have high scalability as it is directly linked to 3D virtual clothing.

Dye-Perfused Human Placenta for Simulation in a Microsurgery Laboratory for Plastic Surgeons

  • Laura C. Zambrano-Jerez;Karen D. Diaz-Santamaria;Maria A. Rodriguez-Santos;Diego F. Alarcon-Ariza;Genny L. Melendez-Florez;Monica A. Ramirez-Blanco
    • Archives of Plastic Surgery
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    • v.50 no.6
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    • pp.627-634
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    • 2023
  • In recent decades, a number of simulation models for microsurgical training have been published. The human placenta has received extensive validation in microneurosurgery and is a useful instrument to facilitate learning in microvascular repair techniques as an alternative to using live animals. This study uses a straightforward, step-by-step procedure for instructing the creation of simulators with dynamic flow to characterize the placental vascular tree and assess its relevance for plastic surgery departments. Measurements of the placental vasculature and morphological characterization of 18 placentas were made. After the model was used in a basic microsurgery training laboratory session, a survey was given to nine plastic surgery residents, two microsurgeons, and one hand surgeon. In all divisions, venous diameters were larger than arterial diameters, with minimum diameters of 0.8 and 0.6 mm, respectively. The majority of the participants considered that the model faithfully reproduces a real microsurgical scenario; the consistency of the vessels and their dissection are similar in in vivo tissue. Furthermore, all the participants considered that this model could improve their surgical technique and would propose it for microsurgical training. As some of the model's disadvantages, an abundantly thick adventitia, a thin tunica media, and higher adherence to the underlying tissue were identified. The color-perfused placenta is an excellent tool for microsurgical training in plastic surgery. It can faithfully reproduce a microsurgical scenario, offering an abundance of vasculature with varying sizes similar to tissue in vivo, enhancing technical proficiency, and lowering patient error.

Intention to Continue Using Chat GPT as a learning Tool for College Students: Based on the Technology Acceptance Model (대학생 학습 도구로 Chat GPT 활용에 대한 지속사용 의도: 기술수용 모델을 기반으로)

  • Noh Hyeyoung;Kim Hanju;Ku Yeong-Ae
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.3
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    • pp.933-942
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    • 2024
  • With the development of AI, Chat GPT, an artificial intelligence chatbot that appeared in 2022, is rapidly spreading to a wide range of people and expanding its usefulness. This study was conducted to examine college students' intention to continue using Chat GPT using a technology acceptance model. As a result of the study, all of Chat GPT's features had a positive effect on college students' perceived usefulness and perceived ease of use. However, among the features of Chat GPT, system quality and relative advantages did not directly affect the intention to continue using it. However, it was confirmed that it had an effect when perceived usefulness and perceived ease of use were mediated. The perceived usefulness and perceived ease of Chat GPT were verified to have a positive effect on the intention to continue using it.

Harnessing the Power of Voice: A Deep Neural Network Model for Alzheimer's Disease Detection

  • Chan-Young Park;Minsoo Kim;YongSoo Shim;Nayoung Ryoo;Hyunjoo Choi;Ho Tae Jeong;Gihyun Yun;Hunboc Lee;Hyungryul Kim;SangYun Kim;Young Chul Youn
    • Dementia and Neurocognitive Disorders
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    • v.23 no.1
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    • pp.1-10
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    • 2024
  • Background and Purpose: Voice, reflecting cerebral functions, holds potential for analyzing and understanding brain function, especially in the context of cognitive impairment (CI) and Alzheimer's disease (AD). This study used voice data to distinguish between normal cognition and CI or Alzheimer's disease dementia (ADD). Methods: This study enrolled 3 groups of subjects: 1) 52 subjects with subjective cognitive decline; 2) 110 subjects with mild CI; and 3) 59 subjects with ADD. Voice features were extracted using Mel-frequency cepstral coefficients and Chroma. Results: A deep neural network (DNN) model showed promising performance, with an accuracy of roughly 81% in 10 trials in predicting ADD, which increased to an average value of about 82.0%±1.6% when evaluated against unseen test dataset. Conclusions: Although results did not demonstrate the level of accuracy necessary for a definitive clinical tool, they provided a compelling proof-of-concept for the potential use of voice data in cognitive status assessment. DNN algorithms using voice offer a promising approach to early detection of AD. They could improve the accuracy and accessibility of diagnosis, ultimately leading to better outcomes for patients.