The twenty-first century is arguably the century of computing. In such a world saturated by computing, Computational Thinking is now recognized as a foundational competency for being an informed citizen and being successful in STEM work. Nevertheless, how to effectively import different types of teaching methods in university courses (lecture based learning, project based learning) is subjected to further evaluation. Currently, the arguments in favor of tangible robots including high interaction, great practicality, and specific operation results make themselves to be often used as a teaching medium and tool for teaching activities between teachers and students. Hence, in addition to cultivating students with computational thinking ability, this paper discussed how to integrate tangible robots into project-based learning courses of thinking skills training to improve the learning performance of the computational thinking ability. This study conducted in one semester on the 105 students from three classes. Experimental results show that the project-based learning method integrated with the teaching material of robotic visual programs approach had significantly better effectiveness in improving students' learning achievements than the traditional teaching method integrated with paper practice teaching materials approach. Analysis of the questionnaire results showed that the proposed learning approach did not increase the students' cognitive burden. In sum, the proposed approach helps students' learning achievement and cognitive load.
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http://dx.doi.org/10.3389/fpsyg.2021.828568 | DOI Listing |
Womens Health Rep (New Rochelle)
January 2025
Hospital Nuestra Señora de Fátima, Vithas Vigo, Vigo, Spain.
Objectives: This study aimed to develop an anamnesis checklist for oral contraceptive (OC) choice focused on their safety profile and associated risk factors.
Study Design: This study involved eight health care professionals in Spain, including six gynecologists and two internists, selected for their expertise in contraception counseling. We employed the design-thinking process, structured in five phases: empathizing with patients' needs, defining key areas of impact, devising innovative solutions, prototyping ideas into testable proposals, and validating prototypes.
JMIR Cancer
January 2025
Department of Radiation Oncology, University of California, San Francisco, San Francisco, CA, United States.
Background: Early-stage breast cancer has the complex challenge of carrying a favorable prognosis with multiple treatment options, including breast-conserving surgery (BCS) or mastectomy. Social media is increasingly used as a source of information and as a decision tool for patients, and awareness of these conversations is important for patient counseling.
Objective: The goal of this study was to compare sentiments and associated emotions in social media discussions surrounding BCS and mastectomy using natural language processing (NLP).
Philos Trans A Math Phys Eng Sci
January 2025
ICAR, National Research Council (CNR), Palermo, Italy.
Quantum computing is a branch of computer science derived from the fundamental laws of quantum mechanics, such as state superposition, multi-value logic and destructive measure. An open challenge in itself is to re-think in quantum terms classic problems and solving techniques. Another nature-inspired field is the development of swarm-based robotic applications, where the challenge is catching the fundamental laws governing swarm dynamics, such as pattern formation and target reaching.
View Article and Find Full Text PDFPLoS One
January 2025
Faculty of Computer Science and Information Technology, Universiti Malaya, Kuala Lumpur, Malaysia.
Background: Online malicious attempts such as scamming continue to proliferate across the globe, aided by the ubiquitous nature of technology that makes it increasingly easy to dupe individuals. This study aimed to identify the predictors for online fraud victimization focusing on Personal, Environment and Behavior (PEB).
Methods: Social Cognitive Theory (SCT) was used as a guide in developing the PEB framework.
JMIR Med Inform
January 2025
Department of Systems Design Engineering, Faculty of Engineering, University of Waterloo, Waterloo, ON, Canada.
Background: While expert optometrists tend to rely on a deep understanding of the disease and intuitive pattern recognition, those with less experience may depend more on extensive data, comparisons, and external guidance. Understanding these variations is important for developing artificial intelligence (AI) systems that can effectively support optometrists with varying degrees of experience and minimize decision inconsistencies.
Objective: The main objective of this study is to identify and analyze the variations in diagnostic decision-making approaches between novice and expert optometrists.
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