1,520 research outputs found

    2011 GREAT Day Program

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    SUNY Geneseo’s Fifth Annual GREAT Day.https://knightscholar.geneseo.edu/program-2007/1005/thumbnail.jp

    Online collaborative Padlet-mediated learning in health management studies

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    IntroductionThe Padlet interactive platform constitutes a virtual online board on which users can post various types of multimedia content, such as documents, questions, comments, images, video clips, and audio clips. This platform has gained popularity in higher education yet remains ancillary in the fields of medical education and medical management.MethodsThis case study sought to initially design an intervention program that employs online collaborative learning enabled by Padlet and to assess how Health Management students perceived the activity and its ramifications for their learning. 85 students’ reflective journals were content analyzed.Resultsfive main categories stood out: (1) user experience of the platform; (2) visuality and visibility of the platform; (3) collaborative learning and OCL; (4) active online learning and student engagement; and (5) cognitive flexibility.DiscussionThis study emphasizes the importance of incorporating digital tools in education, particularly the use of the Padlet platform to facilitate collaborative learning and improve the quality of teaching and learning. It demonstrates that Padlet-mediated online collaborative learning can be an effective digital learning tool because of its ease of use and ability to accommodate both pedagogical and technological challenges

    PROCEEDINGS 5th PLATE Conference

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    The 5th international PLATE conference (Product Lifetimes and the Environment) addressed product lifetimes in the context of sustainability. The PLATE conference, which has been running since 2015, has successfully been able to establish a solid network of researchers around its core theme. The topic has come to the forefront of current (political, scientific & societal) debates due to its interconnectedness with a number of recent prominent movements, such as the circular economy, eco-design and collaborative consumption. For the 2023 edition of the conference, we encouraged researchers to propose how to extend, widen or critically re-construct thematic sessions for the PLATE conference, and the paper call was constructed based on these proposals. In this 5th PLATE conference, we had 171 paper presentations and 238 participants from 14 different countries. Beside of paper sessions we organized workshops and REPAIR exhibitions

    Uncovering the Electronic Structure of Systems Vital to Nuclear Energy, Life, and Space Exploration via Anion Photoelectron Spectroscopy

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    Photoelectron spectroscopy provides a window into the complicated world of electronic structure and interactions on a molecular level. More specifically, anion photoelectron spectroscopy (aPES) allows one to obtain information regarding an anionic atom, molecule, or cluster as well as its neutral counterpart, with the additional advantages of improved resolution and species selection through the direct manipulation of the ion beam. A combination of mass spectrometry, anion photoelectron spectroscopy (aPES) and theory were used harmoniously in this work to study the electronic structure of several atomic and clusters anions, from atoms to large heterogeneous metal clusters. Studies of biological molecules are presented in Chapter 2, including the correlation-bound anion p-chloroaniline and several antioxidants. Chapter 3 (as well as Appendix A) focus on uranium and thorium species, including the experimentally measured electron affinity of the uranium atom: a fundamental property of the element. Chapter 4 focuses on systems related to propulsion applications, including systematic studies of Al3Hn− (n=1–9) clusters and of Ir n− with hydroxylamine, offering a wealth of information regarding reactions leading to combustion and ignition in jet engines

    Automatic generation of software interfaces for supporting decisionmaking processes. An application of domain engineering & machine learning

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    [EN] Data analysis is a key process to foster knowledge generation in particular domains or fields of study. With a strong informative foundation derived from the analysis of collected data, decision-makers can make strategic choices with the aim of obtaining valuable benefits in their specific areas of action. However, given the steady growth of data volumes, data analysis needs to rely on powerful tools to enable knowledge extraction. Information dashboards offer a software solution to analyze large volumes of data visually to identify patterns and relations and make decisions according to the presented information. But decision-makers may have different goals and, consequently, different necessities regarding their dashboards. Moreover, the variety of data sources, structures, and domains can hamper the design and implementation of these tools. This Ph.D. Thesis tackles the challenge of improving the development process of information dashboards and data visualizations while enhancing their quality and features in terms of personalization, usability, and flexibility, among others. Several research activities have been carried out to support this thesis. First, a systematic literature mapping and review was performed to analyze different methodologies and solutions related to the automatic generation of tailored information dashboards. The outcomes of the review led to the selection of a modeldriven approach in combination with the software product line paradigm to deal with the automatic generation of information dashboards. In this context, a meta-model was developed following a domain engineering approach. This meta-model represents the skeleton of information dashboards and data visualizations through the abstraction of their components and features and has been the backbone of the subsequent generative pipeline of these tools. The meta-model and generative pipeline have been tested through their integration in different scenarios, both theoretical and practical. Regarding the theoretical dimension of the research, the meta-model has been successfully integrated with other meta-model to support knowledge generation in learning ecosystems, and as a framework to conceptualize and instantiate information dashboards in different domains. In terms of the practical applications, the focus has been put on how to transform the meta-model into an instance adapted to a specific context, and how to finally transform this later model into code, i.e., the final, functional product. These practical scenarios involved the automatic generation of dashboards in the context of a Ph.D. Programme, the application of Artificial Intelligence algorithms in the process, and the development of a graphical instantiation platform that combines the meta-model and the generative pipeline into a visual generation system. Finally, different case studies have been conducted in the employment and employability, health, and education domains. The number of applications of the meta-model in theoretical and practical dimensions and domains is also a result itself. Every outcome associated to this thesis is driven by the dashboard meta-model, which also proves its versatility and flexibility when it comes to conceptualize, generate, and capture knowledge related to dashboards and data visualizations

    Remote Learning During COVID-19 on Internal Medicine Residents\u27 Education: Barriers and Enhancements Through Lived Experiences

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    The COVID-19 pandemic uncovered instructional changes within higher education. Accommodations for continued instruction included a transition to remote learning. However, little research exists regarding the experiences of medical residents during this transition in their education while combating the COVID-19 pandemic. This qualitative study, phenomenological in nature, aimed to explore the lived experiences of internal medicine medical residents at one medical college in Central Florida regarding the transition from face-to-face instruction to remote learning due to the COVID-19 pandemic. Eleven participating medical residents underwent semi-structured interviews via Zoom. Garrison\u27s Community of Inquiry conceptual model and Hall and Hord\u27s Concerns-Based Adoption Model theoretical framework were used. The researcher utilized Colaizzi\u27s phenomenological analysis method to analyze the interview transcripts and Saldaña\u27s coding method to code the data. Dedoose software was used in the analysis process. Participants were found to have shared and non-shared experiences and encountered both benefits and challenges from remote learning. Shared experiences included travel difficulties due to border closures and family challenges. Benefits included the presence of national guest speakers in lectures, attending lectures from the convenience and comfort of home, and the addition of interactive learning methods such as Kahoot and Jeopardy. Challenges experienced during the transition included curricular disorganization, distractions such as watching movies, a lack of interest in attending lectures, and a lack of interaction, with colleagues and by the instructor. Further research recommendations are discussed regarding emergency preparedness in higher education and graduate medical education, in addition to instructor perspectives

    Online Learning Readiness Among International Students

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    The United States holds a commanding 22% of the market share of international students, more than double that of the second leading country (United Kingdom). The number of international students studying at U.S. institutions has had a steady incline for decades and these students now make up approximately 5% of all higher education students in the U.S. Even still, there have been previous examinations of international students’ perceptions of online learning readiness. As online and blended learning elements are an integral part of nearly every degree program, and, indeed, nearly every course, it is imperative that we gain a better understanding of what international students perceive to be important, how confident they view themselves on those same items, if there is a difference between what they perceive as important and their confidence, and the effect of demographic factors on these perceptions. This study examines these questions through the Student Readiness for Online Learning instrument developed by Martin et al. (2020) across four subscales: online student attributes, time management, technological competency, and communication competency. Data were gathered from currently enrolled residential international students at U.S. institutions. There were 117 valid respondents. Descriptive statistics, repeated measures ANOVAs, and correlation matrices were used to address the research questions. Data analysis revealed that the average student viewed all four subscales as being between somewhat to very important and themselves as being somewhat to very confident. Demographic variables did not interact with the dependent variables, though there were correlations for GDP per capita ppp and internet users % per capita. This study shed much needed light on the perceptions of international students online learning readiness. Results indicate the need for further study as well as the development of more comprehensive assessments

    Annual reports of the town of Seabrook, New Hampshire for year ending December 31st, 2021 as compiled by the town officers.

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    This is an annual report containing vital statistics for a town/city in the state of New Hampshire

    Newman v. Google

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