Article
Chemistry, Multidisciplinary
Rika Kobayashi, Theodorus P. M. Goumans, N. Ole Carstensen, Thomas M. Soini, Nicola Marzari, Iurii Timrov, Samuel Ponce, Edward B. Linscott, Christopher J. Sewell, Giovanni Pizzi, Francisco Ramirez, Marnik Bercx, Sebastiaan P. Huber, Carl S. Adorf, Leopold Talirz
Summary: The global pandemic has disrupted chemistry teaching practices by forcing many courses online, particularly impacting the practical component of the chemistry curriculum. As a result, fewer hands-on computational chemistry teaching laboratories are delivered online due to unrecognized differences and issues between in-person and virtual teaching. More adaptation and solutions are needed to address these challenges during this transition.
JOURNAL OF CHEMICAL EDUCATION
(2021)
Article
Surgery
Jacob A. Greenberg, Erin Schwarz, John Paige, Jonathan Dort, Sharon Bachman
Summary: Surgeons faced limited opportunities to learn new techniques and procedures during the COVID19 pandemic, prompting SAGES to create a hands-on course that could be completed at home. The course was successfully delivered through a telementoring platform, providing surgeons with the opportunity to continue their professional development remotely.
SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES
(2021)
Article
Green & Sustainable Science & Technology
Chonnipa Yeerum, Piyanat Issarangkura Na Ayutthaya, Kullapon Kesonkan, Kanokwan Kiwfo, Siripat Suteerapataranon, Piyatida Panitsupakamol, Pathinan Paengnakorn, Dujrudee Chinwong, Surarong Chinwong, Chalermpong Saenjum, Monnapat Vongboot, Kate Grudpan
Summary: Analytical chemistry educators in Thailand have adapted their teaching methods to the new normal brought on by the COVID-19 pandemic, by implementing Lab-at-Home (LAH) experiments. Despite overall satisfaction with the LAH as a tool for new normal experimentation, some students faced poor internet connections during synchronous online classes.
Article
Geochemistry & Geophysics
Lei Han, Yangyang Zhao, Haonan Chen, V. Chandrasekar
Summary: This article introduces a transfer learning framework based on deep learning, which can address the challenge of applying trained models to locations with different precipitation features. The experimental results demonstrate that deep transfer learning models can improve prediction skills.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Walter F. Wiggins, M. Travis Caton, Kirti Magudia, Michael H. Rosenthal, Katherine P. Andriole
Summary: Understanding deep learning in medical imaging is crucial for the next generation of radiologists. However, setting up the technical requirements for deep learning can be a challenge for those with limited computer programming experience and access to GPU-accelerated computing.
JOURNAL OF DIGITAL IMAGING
(2021)
Article
Microbiology
Felix R. Harris, Michael L. Sikes, Michael Bergman, Carlos C. Goller, Andrew O. Hasley, Caroline A. Sjogren, Melissa V. Ramirez, Claire L. Gordy
Summary: Ensuring public understanding of human-microbe interactions, immune responses, and vaccines is crucial during a pandemic. This article presents two Tactile Teaching Tools with Guided Inquiry Learning (TTT-GIL) activities designed to engage diverse learners in exploring molecular interactions within the immune system. These activities utilize physical models and structured activities built on the constructivist framework of Process-Oriented Guided Inquiry Learning (POGIL) to guide learners through the exploration of fundamental immunology concepts.
FRONTIERS IN MICROBIOLOGY
(2022)
Article
Chemistry, Multidisciplinary
Elizabeth W. Kelley
Summary: This article discusses the development of an at-home DIY kit for wet laboratory activities in high school organic chemistry during COVID-19, aiming to provide a practical and relevant hands-on learning experience for students. It includes troubleshooting, tips, handouts, and evidence of learning and engagement, offering instructors the ability to supplement traditional experiments with appropriate alternatives.
JOURNAL OF CHEMICAL EDUCATION
(2021)
Article
Education & Educational Research
Valdemar Svabensky, Jan Vykopal, Pavel Celeda, Jan Dovjak
Summary: Computer-supported learning technologies are crucial for hands-on cybersecurity training, providing realistic environments and valuable automated feedback. This study proposes and implements feedback software based on the analysis of trainee data, and conducts field studies and surveys to evaluate its effectiveness. The results demonstrate the importance of feedback in the training process.
EDUCATION AND INFORMATION TECHNOLOGIES
(2023)
Article
Automation & Control Systems
Matthias Feurer, Katharina Eggensperger, Stefan Falkner, Marius Lindauer, Frank Hutter
Summary: This paper introduces the background and development of AutoML, and proposes new approaches. The improvements of the proposed methods are validated through experimental research.
JOURNAL OF MACHINE LEARNING RESEARCH
(2022)
Article
Education & Educational Research
Wei-Sheng Wang, Yu-Ping Cheng, Hsin-Yu Lee, Chia-Ju Lin, Yueh-Min Huang
Summary: This study designs a VR-based learning system for embedded electronic circuits and compares the knowledge, comprehension, and application levels as well as learning performance, anxiety, and confidence levels in different learning environments. The results show that groups receiving VR-mediated training have higher levels of knowledge, comprehension, and application. Learners with higher levels of knowledge and application also exhibit lower anxiety and higher confidence during practical tasks. The VR system described here improves cognitive levels and performance on hands-on tasks, while reducing anxiety and increasing confidence.
JOURNAL OF COMPUTER ASSISTED LEARNING
(2023)
Article
Education & Educational Research
C. R. Narayanaswamy, Vignesh Narayanaswamy
Summary: This article applies R, a free software, and recent stock-price data to illustrate the concept of portfolio diversification. It demonstrates the use of a user-friendly dashboard to enhance student engagement and interest in learning finance concepts.
INTERACTIVE LEARNING ENVIRONMENTS
(2022)
Article
Education & Educational Research
Ding-Chau Wang, Yong-Ming Huang
Summary: This study aims to investigate the factors influencing students' learning performance and identifies the importance of self-efficacy and perceived enjoyment. The results show that students' self-efficacy in technology use is more important than others' assistance in THL contexts, and perceived enjoyment has a more significant impact on learning performance than perceived usefulness.
INTERACTIVE LEARNING ENVIRONMENTS
(2022)
Article
Green & Sustainable Science & Technology
Adrian Suarez, Daniel Garcia-Costa, Joaquin Perez, Emilia Lopez-Inesta, Francisco Grimaldo, Jose Torres
Summary: As the world changes, students need to acquire a diverse set of competencies and skills that focus on sustainability beyond environmental matters. Using educational tools that emulate real-life tasks related to students' future careers can significantly boost their motivation. Adopting teaching techniques that align more closely with the professional work of engineering empowers students and contributes to the advancement of science and technology. This study analyzes the impact of using a mobile robot platform as a teaching approach that merges problem-based learning with hands-on learning. The evaluation shows that students positively perceive the impact of this learning strategy.
Article
Computer Science, Artificial Intelligence
Nuha Alruwais, Marwa Obayya, Fuad Al-Mutiri, Mohammed Assiri, Amani A. Alneil, Abdullah Mohamed
Summary: This study presents a new method for early screening of retinoblastoma, which involves the isolation and categorization of retinal tumor cells. By combining deep learning models and traditional feature extraction methods, the proposed system improves the accuracy, sensitivity, and specificity of the methods. This method provides an effective alternative for early detection and prevention of vision loss in children and adults.
PEERJ COMPUTER SCIENCE
(2023)
Article
Environmental Sciences
Azam Karami, Karoll Quijano, Melba Crawford
Summary: This article explores the use of high-resolution RGB imagery acquired by UAVs and deep learning techniques for monitoring flowering in maize. Results show that different annotation methods impact the accuracy and simplicity of tassel detection, with CenterNet and DetectoRS performing well but with different strengths.