21,647 research outputs found

    Data Science: A Study from the Scientometric, Curricular, and Altmetric Perspectives

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    This research explores the emerging field of data science from the scientometric, curricular, and altmetric perspectives and addresses the following six research questions: 1. What are the scientometric features of the data science field? 2. What are the contributing fields to the establishment of data science? 3. What are the major research areas of the data science discipline? 4. What are the salient topics taught in the data science curriculum? 5. What topics appear in the Twitter-sphere regarding data science? 6. What can be learned about data science from the scientometric, curricular, and altmetric analyses of the data collected? Using bibliometric data from the Scopus database for 1983 – 2021, the current study addresses the first three research questions. The fourth research question is answered with curricular data collected from U.S. educational institutions that offer data science programs. Altmetric data was gathered from Twitter for over 20 days to answer the fifth research question. All three sets of data are analyzed quantitatively and qualitatively. The scientometric portion of this study revealed a growing field, expanding beyond the borders of the United States and the United Kingdom into a more global undertaking. Computer Science and Statistics are foundational contributing fields with a host of additional fields contributing data sets for new data scientists to act, including, for example, the Biomedical and Information Science fields. When it comes to the question of salient topics across all three aspects of this research, it was revealed that a large degree of coherence between the three resulted in highlighting thirteen core topics of data science. However, it can be noted that Artificial Intelligence stood out among all the other groups with leading topics such as Machine Learning, Neural Networks, and Natural Language Processing. The findings of this study not only identify the major parameters of the data science field (e.g., leading researchers, the composition of the discipline) but also reveal its underlying intellectual structure and research fronts. They can help researchers to ascertain emerging topics and research fronts in the field. Educational programs in data science can learn from this study about how to update their curriculums and better prepare students for the rapidly growing field. Practitioners and other stakeholders of data science can also benefit from the present research to stay tuned and current in the field. Furthermore, the triple-pronged approach of this research provides a panoramic view of the data science field that no prior study has ever examined and will have a lasting impact on related investigations of an emerging discipline

    Associated Patterns in Open-Ended Concept Maps within E-Learning

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    A concept map is a diagram that visualizes the structure of individual cognitive knowledge. An approach to creating a concept map structure that allows users to contribute concepts and linkages that express their understanding freely is known as an "open-ended concept map." It has been demonstrated that an open-ended concept map accurately depicts student knowledge structures and reveals student differences. However, manually analyzing an open-ended map is difficult, time-consuming, and includes many propositions, especially in a big classroom. Educational data mining could be used to further process and analyze a collection of concept maps. However, many works attempted to employ data mining in order to produce concept maps structure from text documents rather than examining the knowledge representation. This study aimed to identify hidden students' knowledge representation combination patterns using association rules analysis. The dataset used in this study consisted of 27 open-concept maps created by university students. This study found interesting patterns that reveal students' knowledge in understanding the material given by the teacher

    An Analysis of Major Acquisition Reforms through Text Mining and Grounded Theory Design

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    Cost growth is an established phenomenon within Defense Acquisition that the US Government has attempted to abolish for decades through seemingly endless cycles of reform. Dozens of experts and senior leaders within the acquisition community have published their notions on the reasons for cost growth, nevertheless, legislation has yet to eradicate this presumed conundrum. For this reason, this research is aimed at identifying existing trends within past major Defense Acquisition Reform legislation, as well as in a compendium of views from leaders within the Defense Acquisition community on the efficacy of acquisition reform, to determine the possible disconnect. To accomplish this goal, this research takes a qualitative approach, utilizing various Text Mining methodologies (word frequency, word relationships, term frequency-inverse document frequency, sentiment analysis, and topic modeling), along with Grounded Theory Design, to analyze the major reforms and expert views. The results of this research corroborate the current literature’s claim that past Defense Acquisition reforms have not been able to sufficiently address the root causes of cost growth, and identifies six potential root causes of cost growth: Strategy, the Industrial Base, Risk Management, the Requirements and Research, Development, Test, and Evaluation (RDT&E) Processes, the Workforce, and Cost Estimates and the Planning, Programming, Budget, and Execution (PPBE) Process

    Moral Turbulence and the Infusion of Multimodal Character Education Strategies in American Elementary Schools

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    Pockets of American society are marked by increase in violent crime with concurrent decline in moral character. This phenomenon is infiltrating the nation’s school system as evidenced by growing numbers of aggressive incidents in the classroom. As a result, there is an increasingly accepted need for effective character education programs in the schools as a means to help change the décolleté trajectory of the behavior of the nation’s school children. While more money and growing numbers of legislation have been put forth to support such an endeavor, research is still lacking as to what activities, skills, goals, and approaches would be best incorporated for optimal outcomes. This article makes a case for assessing the effectiveness of a multimodal approach incorporating cognitive, social, and sociocultural learning elements is than a single approach using cognitive elements alone, and considers the complexity of a Christian perspective on character education in schools

    Digital technologies in architecture, engineering, and construction

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    Digitalization in the architecture, engineering, and construction (AEC) sector is slow due to significant challenges in technology adoption. The study aims to promote technology adoption by advancing the understanding of digital technologies in the AEC sector. This article presents the findings from a quantitative scoping review, encompassing 3950 technology-related abstracts retrieved from the Scopus database, providing a preliminary assessment of literature size, geographic innovation hotspots, research gaps, and key concepts in the AEC field. The results show that Building Information Modelling (1852 studies) dominates the literature, while topics like 3D Printing (311) and Internet of Things (227) are gaining traction. China (687 publications) and the United States (566) produce most research articles. Despite the increasing interest in emerging technologies, their implementation often necessitates acquiring specific skill sets. Academia needs to put a stronger focus on these technologies in education and tighter collaboration with the industry is needed.publishedVersio

    Artificial intelligence in the cyber domain: Offense and defense

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    Artificial intelligence techniques have grown rapidly in recent years, and their applications in practice can be seen in many fields, ranging from facial recognition to image analysis. In the cybersecurity domain, AI-based techniques can provide better cyber defense tools and help adversaries improve methods of attack. However, malicious actors are aware of the new prospects too and will probably attempt to use them for nefarious purposes. This survey paper aims at providing an overview of how artificial intelligence can be used in the context of cybersecurity in both offense and defense.Web of Science123art. no. 41

    A System Dynamics Model Investigating the Efficacy of Non-Kinetic Policy Strategies on the Diffusion of Democratic Ideologies in China

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    Shaping the next century of global politics and power, United States-China relations comprise one of the most significant bilateral relationships in the world. A new era of unrestricted warfare is one example of how aggression from China could be very costly for the United States. The growth of democratic ideals within China decreases the risk of detrimental impacts according to democratic peace theory. This thesis explores a multifaceted system of relationships that regulate the diffusion of democratic ideology within China, as defined by a proxy-measure characterized as human rights by Freedom House. Relative deprivation theory coupled with an adapted Bass diffusion model are leveraged as constructs leading to the emergence of a social movement influencing Chinas system of government. Non-kinetic policy strategies directed towards reforming government are assessed utilizing system dynamics. Subsets within system dynamics theory, goal dynamics incorporating soft variables, are investigated and implemented within the model as a means to evaluate interactions between actors while accounting for competing objectives. The resulting model provides a pilot operational assessment of driving factors, marrying both policy and strategic influence objectives with mathematically structured analysis as applied to this realm of research. Results suggest areas of study for future development that potentially further United States objectives within China. Thus, this research illustrates the value of applying a system dynamics approach to connect quantitative and qualitative factors in a way that provides a more thorough understanding of complex geopolitical interactions
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