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For the interval 1962-2022 y, during the continuos publication last 60 years, in Metalurgija Journal Authors from 40 countries from Mexico to China (all 5 continent ) have publish. The goal of the Article is give List of Papers published in this interval, 199 issues or 238 numbers, 2721 scientific and technical, and 287 contributions (total 3008 papers ) of Authors whose investigation results and ideas have been examined and found on the pages of this Journal. Thanks for all.

The paper argues that learning analytics as a research field can benefit from a theory-informed shared language to describe sensemaking of learning and teaching data. To make the case for such shared language, first, I critically review prominent sensemaking theories to then demonstrate how studies in learning analytics do not use coherent descriptions of sensemaking, eclectically combining the paradigms that have underlying differences. I then propose a conceptualization of sensemaking that overcomes the differences between these theories and explains how the concepts of "activity system," the "definition of the situation" and "affordances" can be used to capture individual differences in sensemaking. The paper concludes with a preliminary framework and examples demonstrating its utility in raising new theoretical questions, informing design principles and providing shared language for researchers in learning analytics.

This study examines data from the California EMS Information System (CEMSIS) to identify factors that influence prehospital time for EMS events related to motor vehicle collisions (MVCs). While only 19 percent of the United States population resides in rural areas, over half of all traffic fatalities involve rural motor vehicle collisions. Rural and urban MVCs result in similar injury severities, however relative inaccessibility of trauma centers and prehospital EMS time (activation, response, and transport time) likely contribute to the generally higher mortality rate in rural areas. For the present study, 24 CEMSIS data variables were requested, many of which involved missing data, which severely restricted the potential analysis of the impact of EMS response times. However, the findings did show that average overall EMS time (including response, scene and transport time) were approximately twice as long for collisions in rural zip codes compared with urban zip codes. Several limitations influence the interpretation of these results. Data on prehospital EMS times is missing for much of the state—even for zip codes with records of EMS events, data is likely incomplete. In addition, zip code level location data is insufficient for adequate study of the effects of the built environment and road network on prehospital time. Furthermore, according to the National EMS Information System (NEMSIS) User Manual, the national dataset suffers from selection and information bias, which are likely also present in the CEMSIS data. Although the present study cannot analyze the effect of longer prehospital times on patient outcome, other research has found that longer prehospital times may negatively impact patient health. Recommendations for reducing time from injury to appropriate medical care in rural areas include improving cell phone coverage, compliance of rural 911 center with FCC wireless, use of GPS technology, and integration of automatic vehicle location and computer aided navigation technologies into all computer-aided dispatch systems. In addition, CEMSIS should improve the coverage of their dataset and ensure that all EMS activities are recorded. To expand the type of analyses that can be conducted using CEMSIS data, EMS records must include fields that allow them to be linked to hospital and police datasets. When such data becomes available, research must be conducted to determine whether prehospital time is significantly related to patient outcome following motor vehicle collisions.

Examines the characteristics of rejected manuscripts submitted to the "African Journal of Library, Archives and Information Science." Most of the papers were rejected because they contributed nothing new to knowledge (65.5%), used unreliable data (13.1%) and lacked focus (13.1%). There were no remarkable differences with regard to status and affiliations between authors of rejected and accepted papers. (Author/AEF)

This project interrogates the United States' national fixation on the answer to the question: Who are you? In this article, it is posed that identity documentation practices arising out of the Chinese Exclusion Act era cast identity as an empirical and immutable phenomenon, specifically in response to the racialization of American-born Chinese settlers as duplicitous, through the mechanisms that information is collected, the actual information itself, and the cross-references or connections created between cases. Through tracing this lineage, racialized identification data is identified and theorized as part of hegemonic data regimes. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has fast-tracked the development of digital applications and inspired everyone to adapt to the technologies to curb the spread of outbreak. As this crisis intensifies, the rapid usage of digital devices and apps has echoed the serious concerns about civil liberties, privacy, and data protection. Considering the situation, this research aimed to explore the internet using habits of the youths of West Bengal, a state in eastern India, during COVID-19. Besides, the paper explored their experiences of using various digital applications, the fundamental digital literacy and how safely they protect data from breaches. Thus, the paper presents the results by conducting an online survey among the youths in West Bengal. The result, from 215 participants, highlighted that the increased use of these digital applications has not matched the demand for digital privacy literacy among the young generation of the state. While this pandemic has raised their concerns over digital privacy and data protection, yet they do not undertake any strong protection mechanisms to safeguard them digitally. Besides, this paper suggests suitable plans to raise awareness among this generation and form a healthy digital citizenship with a proper regulatory framework as it is the need of the hour.

Employment and training services offered through Extension are part of and continue a long tradition of policy-focused employment and job training. This paper chronicles the successes of UT Extension's work as a third-party partner in the delivery of workforce development programming geared toward individuals receiving Supplemental Nutrition Assistance Program (SNAP) benefits. The paper begins with an overview of the federal program and a discussion of how Tennessee forged a state-level partnership for the delivery of workforce services. Data showing program success including number of participants served, supportive services offered, and economic impact are highlighted. Finally, lessons learned are outlined.

In today's data-sharing paradigm, personal data has become a valuable resource that intensifies the risk of unauthorized access and data breach. Increased data mining techniques used to analyze big data have posed significant risks to data security and privacy. Consequently, data breaches are a significant threat to individual privacy. Privacy is a multifaceted concept covering many areas, including the right to access, erasure, and rectify personal data. This paper explores the legal aspects of privacy harm and how they transform into legal action. Privacy harm is the negative impact to an individual as a result of the unauthorized release, gathering, distillation, or expropriation of personal information. Privacy Enhancing Technologies (PETs) emerged as a solution to address data privacy issues and minimize the risk of privacy harm. It is essential to implement privacy enhancement mechanisms to protect Personally Identifiable Information (PII) from unlawful use or access. FIPPs (Fair Information Practice Principles), based on the 1973 Code of Fair Information Practice (CFIP), and the Organization for Economic Cooperation and Development (OECD), are a collection of widely accepted, influential US codes that agencies use when evaluating information systems, processes, programs, and activities affecting individual privacy. Regulatory compliance places a responsibility on organizations to follow best practices to ensure the protection of individual data privacy rights. This paper will focus on FIPPs, relevance to US state privacy laws, their influence on OECD, and reference to the EU General Data Processing Regulation. (GDPR).

Longstanding inequities exist in community colleges across the United States. To address these inequities, California Community Colleges educators have engaged in a variety of practices including the writing of equity plans and participation in equity data inquiry. However, there is an urgent need for greater focus on racial equity and for more faculty involvement in equity work at the classroom level. This paper presents a teacher case study exploring Classroom Equity Data Inquiry (CEDI), a tool for faculty professional learning focused on equitable student outcomes. In CEDI, professors examine their disaggregated classroom data, reflect on their class equity gaps, and pursue relevant professional development. They implement targeted interventions and then assess those interventions. This paper describes the author's sustained CEDI utilizing six years of equity data in her English as a Second Language classes at a small northern California community college. First, it provides a definition and rationale for CEDI. Second, it details the author's CEDI process and challenges. Third, it shares the author's changes in thinking and practice including high impact interventions the author implemented to reduce equity gaps for men of color in her classes. Fourth, the article describes positive qualitative student data and increased success and retention rates for Hispanic and multi-race males following the interventions. The article concludes that CEDI requires training, support, and time, but that the approach merits further research. More research is needed on CEDI methods and their possible impact on racial equity in the classroom.

An increasingly complex and demanding research landscape has seen university libraries rapidly evolve their services. While research data management, bibliometrics, and research impact services have predominantly featured in the literature to date, the full scope of support libraries are currently providing to their institutions is unknown. This paper aims to present an up-to-date view of the scope and extent of research support services by university libraries across Australia and Aotearoa New Zealand. A coding process analyzed content data from university library websites. Eleven research support areas were identified. Service delivery is split between synchronous and asynchronous modes. This paper describes a lived experience of an evidence-based library and information practice approach to improving research support services at two Australian university libraries, and while it highlights continued maturation of research support services, more research is needed to better understand influences on service development.

This paper proposes an online learning platform learner DM method based on the improved fuzzy C clustering (FCM) algorithm, constructs a learner feature database, and combines clustering analysis and SPSS statistical methods to statistically summarize the big data of law, thus improving the deficiencies of static and absolute classification of students in the student model. In the experiment paper, the improved algorithm is implemented and the experimental data is analyzed. The results show that the learner behavior feature extraction model in this paper has fewer errors and higher recall rate. Compared with the traditional CF algorithm, the error rate is reduced by 19.64% and the recall rate is increased by 22.85%. This study provides better targeted teaching programs and case resources for legal case teaching and promotes the innovation of legal case teaching mode.

Purpose: In today's digital world, data-driven digital artefacts pose challenges for education, as many students lack an understanding of data and feel powerless when interacting with them. This paper aims to address these challenges and introduces the data awareness framework. It focuses on understanding data-driven technologies and reflecting on the role of data in everyday life. The paper also presents an empirical study on young school students' data awareness. Design/methodology/approach: The study involves a teaching unit on data awareness framed by a pre- and post-test design using a questionnaire on students' awareness and understanding of and reflection on data practices of data-driven digital artefacts. Findings: The study's findings indicate that the data awareness framework supports students in understanding data practices of data-driven digital artefacts. The findings also suggest that the framework encourages students to reflect on these data practices and think about their daily behaviour. Originality/value: Students learn a model about interactions with data-driven digital artefacts and use it to analyse data-driven applications. This approach appears to enable students to understand these artefacts from everyday life and reflect on these interactions. The work contributes to research on data and artificial intelligence literacies and suggests a way to support students in developing self-determination and agency during interactions with data-driven digital artefacts.

Chinese students studying abroad have been increasing rapidly in the past decades and become a significant financial contribution to receiving countries. Accordingly, understanding their enrollment choice is essential to facilitate college marketing and admission strategies. Though the decision process is believed to be different from domestic students, empirical analysis of Chinese students' enrollment choices is still lacking. This paper fills the void by examining the influential factors of Chinese students' enrollment choice with novel student-level data. We find that in addition to factors domestic students typically consider, such as financial aid and academic quality, Chinese students particularly emphasize college ranking, reputation, and location in their decision process. Furthermore, unlike domestic students who usually prefer colleges with proximity to home, Chinese students' location preference is linked to job prosperity. We also find that the impact of the factors varies for students from different regions of China, which can be attributable to uneven economic development within the country.

Data papers have been defined as scholarly journal publications whose primary purpose is to describe research data. Our survey provides more insights about the environment of data papers, i.e., disciplines, publishers and business models, and about their structure, length, formats, metadata, and licensing. Data papers are a product of the emerging ecosystem of data-driven open science. They contribute to the FAIR principles for research data management. However, the boundaries with other categories of academic publishing are partly blurred. Data papers are (can be) generated automatically and are potentially machine-readable. Data papers are essentially information, i.e., description of data, but also partly contribute to the generation of knowledge and data on its own. Part of the new ecosystem of open and data-driven science, data papers and data journals are an interesting and relevant object for the assessment and understanding of the transition of the former system of academic publishing. [ABSTRACT FROM AUTHOR]