Search

E-learning is becoming the courseware in this global digital era transforming how learning takes place. Regardless of distance and time, e-learning is becoming unstoppable with its synchronous and asynchronous mode of instructional presentation. This study investigated the impact of e-learning on lecturers’ knowledge of quantitative data analysis in SPSS at the Federal College of Education (Special) Oyo State, Nigeria. A descriptive survey research design was adopted in the study. A total number of one hundred and fifty (150) lecturers were selected through simple random sampling techniques for the study. Purposive sampling was used to select the school that was adopted for the study. Three (3) Research questions were generated and answered in this study. Data collected from the sampled population employing a questionnaire were analyzed using simple percentages and mean scores to answer the three research questions. The results of the findings revealed that e-learning is an important platform accessible and utilized by college lecturers. The findings also revealed that lecturers gained knowledge in data analysis in SPSS through an e-learning platform as it serves as a research and leisure tool which provides various opportunities to many people worldwide, particularly college of education lecturers.

When using multi-criteria decision-making methods in applied problems, an important aspect is the determination of the criteria weights. These weights represent the degree of each criterion's importance in a certain group. The process of determining weight coefficients from a dataset is described as an objective weighting method. The dataset considered here contains quantitative data representing measurements of the alternatives being compared, according to a previously determined system of criteria. The purpose of this study is to suggest a new method for determining objective criteria weights and estimating the proximity of the studied criteria to the centres of their groups. It is assumed that the closer a criterion is to the centre of the group, the more accurately it describes the entire group. The accuracy of the description of the entire group's priorities is interpreted as the importance, and the higher the value, the more significant the weight of the criterion. The Centroidous method suggested here evaluates the importance of each criterion in relation to the centre of the entire group of criteria. The stability of the Centroidous method is examined in relation to the measures of Euclidean, Manhattan, and Chebyshev distances. By slightly modifying the data in the original normalised data matrix by 5% and 10% 100 and 10,000 times, stability is examined. A comparative analysis of the proposed Centroidous method obtained from the entropy, CRITIC, standard deviation, mean, and MEREC methods was performed. Three sets of data were generated for the comparative study of the methods, as follows: the mean value for alternatives with weak and strong differences and criteria with linear dependence. Additionally, an actual dataset from mobile phones was also used for the comparison. [ABSTRACT FROM AUTHOR]

School inspections are a common feature of many education systems. These may be informed by quantitative background data about schools. It is recognised that there are pros and cons of using such quantitative information as part of the inspection process, though these have rarely been succinctly set out. This paper seeks to fill this gap by presenting arguments both for and against the use of quantitative data in informing school inspections. We argue that while quantitative data provide objective information about important outcomes, their usefulness is limited somewhat by a range of factors including missing data, small sample sizes, the creation of perverse incentives, and the fact that most readily available measures capture aspects other than school quality. We conclude by discussing how the Office for Standards in Education, Children's Services and Skills (Ofsted) – the school inspectorate in England – currently makes the trade-off between these pros and cons. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic precipitated an abrupt transition to online learning, impacting students with disabilities uniquely. This study examines the experiences of 62 such students in the new educational paradigm, employing a mixed-methods approach. Quantitative data were collected through surveys and questionnaires to assess privacy and security concerns arising from online learning tools. Qualitative insights were gathered via interviews and focus groups, revealing that while students appreciate the flexibility of online learning, they express a critical need for enhanced guidance and support. Neurodiverse students, in particular, emphasized the necessity of a secure online environment. Addressing these challenges, our research integrates blockchain and machine learning technologies to enhance biometric authentication. Specifically, the Highly Secure Blockchain-Based Compressive Sensing (HSBCS) system is proposed, ensuring data integrity and improving accessibility for Personal Records. Preliminary testing of the HSBCS system showed promising results, with an average accuracy rate of 95% in biometric authentication among visually impaired students. Moreover, participants reported a 30% increase in perceived security and ease of access to their Personal Records compared to traditional authentication methods. These findings underscore the potential of integrating advanced technologies to meet the unique educational needs of students with disabilities while enhancing data security and accessibility in online learning environments.

There are growing public discussions about racism in Australia with renewed government commitment to addressing it. Robust evidence and high-quality data are important for informing anti-racism. However, current data have serious limitations that impact our knowledge about the nature, prevalence and impact of racism in Australia. To examine the state and limitations of data on racism in Australia, we conducted a stocktake review of quantitative racism data collected nationally until July 2022. This article reports on 32 survey-based research studies and six ongoing organisational reporting initiatives. We organise and classify existing data based on study designs and participant characteristics, as well as the settings, targets, perpetrators, responses to and effects of racism. We identify data gaps and recommend how they may be bridged. First, we recommend further analysis of existing, under-utilised data, to address outstanding questions about perpetrators' demographics, priority localities, and the health and socio-economic outcomes of racism. Second, we recommend new data collection on emerging settings where racism occurs, under-explored forms, cohorts experiencing racism, and responses to racism. We propose this study as a foundation for a national anti-racism research agenda and data management plan in Australia, and as a template for stocktakes in other countries. [ABSTRACT FROM AUTHOR]

HR analytics is an emerging field attracting substantial practitioner and academic attention. This article introduces the special issue on HR Aanalytics for the HRMJ. Several recent reviews in the area have struggled to find HR analytics research in the published literature and a key aim of this special issue is to show case high quality analytic projects and cutting‐edge analytic techniques to contribute to this emerging subfield of HRM. Before considering the papers in the special issue, we reflect on two key challenges in the area: First, HR analytics is not a recognized keyword, this makes it difficult to categorise and identify HR analytics research in the field. Second, there are a growing number of reviews of a field that has a limited range of recognised examples of empirical papers to draw on. We discuss the difficulties and potential political sensitivities for practitioners seeking to publish 'within firm' HR analytics projects. We also consider the growing recognition that organisations engaging in HR analytics projects have a range of ethical challenges to deal with going forward. [ABSTRACT FROM AUTHOR]

There is a critical need to address the impact of the COVID-19 pandemic on the well-being of students and educators. In this article, we present findings from the second year of implementing the Student Alliance for Flourishing program, a school-wide initiative to promote the flourishing of students and educators. First, we highlight the connection between Ryan and Deci's Self-Determination Theory and the Student Alliance for Flourishing (SAFF) program, emphasizing the importance of autonomy, competence, and relatedness in supporting the psychological needs of educators and students. Then, we describe the SAFF program and present data that highlight the program's impact on advisors and students, particularly as these data relate to participants' flourishing. Finally, we conclude by emphasizing the significance of promoting flourishing in schools and the need for further empirical research in this area. [ABSTRACT FROM AUTHOR]

The goal of this article is to share lessons learned by the author as an organizational ombuds working with data while striving to effectively communicate the value of ombuds work. The article begins with a presentation of how the author transitioned from a faculty researcher to an ombuds working with data with the goal to demystify ombuds work and create opportunities for visitor voices to be heard. This discussion includes both quantitative and qualitative data. The author shares strategies implemented, and decisions made as an ombuds to operationalize data collection, analysis, and reporting. The article ends with final thoughts for organizational ombuds to consider while reflecting on their professional practice with data. [ABSTRACT FROM AUTHOR]

The 1993 US Supreme Court decision Daubert v. Merrell Dow Pharmaceuticals, Inc. presented new guidance for the judicial assessment of expert witness evidence and testimony in the determination of admissibility. Despite the rarity of admissibility challenges to forensic anthropology evidence, Daubert is frequently cited in published forensic anthropology research. This study undertook a qualitative thematic analysis of forensic anthropology articles published in the Journal of Forensic Sciences to assess why authors continue to cite Daubert and express concerns over potential exclusion. The results show a significant increase in the number of articles that cite legal admissibility standards over time (p < 0.001). Authors frequently cite these standards to contextualize their results within the Daubert framework or to justify the need for their research. Notably, many articles present Daubert as a constraining force, misinterpreting the guidelines as rigid criteria or that they require methods to be strictly quantitative. However, Daubert was intended to be a flexible tool for judges—not a standard or instruction for scientists. While it was reasonable to reflect on the scientific rigor of methods in the wake of the Daubert decision, a new perspective is warranted in which forensic anthropologists shift their focus from trying to "satisfy" admissibility guidelines to adopting quality assurance measures that minimize error and ensure confidence in analytical results, and developing and using methods that are grounded in good science—which is important regardless of whether or not the results are ever the subject of a trial. [ABSTRACT FROM AUTHOR]

Violence against children is a complex social, health, and legal issue in Canada associated with poor physical and mental health (PHAC, 2012; Burczyka, 2017). Eliminating violence against children is a target of multiple Sustainable Development Goals (SDGs) outlined by the United Nations General Assembly in the 2030 Agenda for Sustainable Development (United Nations, 2022). While the SDGs were developed to provide international indicators to assess the progress of signatory nations, insufficient data prevented an evaluation of Canada (UNICEF, n.d. a). Although national, population-based child maltreatment research was underdeveloped in Canada prior to 2012, Statistics Canada, the nation's statistical agency, has been collecting data since the 1960s. However, it may be difficult for researchers to navigate the range of data sources available to study child maltreatment in Canada because they span multiple topics. This paper provides an overview of national survey and administrative data sources capturing child maltreatment housed by Statistics Canada and other government departments. These data may inform future data collection on child maltreatment and assess Canada's progress on SDG indicators related to the protection of children from violence. The paper concludes with a discussion of the benefits of using survey and administrative data, a new methodology to study child maltreatment, gaps in child maltreatment research, and policy implications. [ABSTRACT FROM AUTHOR]

A distinction between quantitative and qualitative data has been regarded as an inviolable separation for a long time, resulting in a significant restriction in setting research designs and methods. In this study, we propose a way to pull this stereotype down and to open more choices for upcoming studies: using Python with 10-K filings via the U.S. Securities and Exchange Commission's application programming interface, we show how to broaden the source of data available for research. In particular, we focus on management's discussion and analysis (MD&A) of 10-K filing. This part has not been fully incorporated due to considerable requirements for an access – substantial time and effort in case of hand collecting. The new perspective approach described in this paper provides significant implications for business practice as well as research in relation to the higher level of utilization of existing data than before. [ABSTRACT FROM AUTHOR]

When using multi-criteria decision-making methods in applied problems, an important aspect is the determination of the criteria weights. These weights represent the degree of each criterion’s importance in a certain group. The process of determining weight coefficients from a dataset is described as an objective weighting method. The dataset considered here contains quantitative data representing measurements of the alternatives being compared, according to a previously determined system of criteria. The purpose of this study is to suggest a new method for determining objective criteria weights and estimating the proximity of the studied criteria to the centres of their groups. It is assumed that the closer a criterion is to the centre of the group, the more accurately it describes the entire group. The accuracy of the description of the entire group’s priorities is interpreted as the importance, and the higher the value, the more significant the weight of the criterion. The Centroidous method suggested here evaluates the importance of each criterion in relation to the centre of the entire group of criteria. The stability of the Centroidous method is examined in relation to the measures of Euclidean, Manhattan, and Chebyshev distances. By slightly modifying the data in the original normalised data matrix by 5% and 10% 100 and 10,000 times, stability is examined. A comparative analysis of the proposed Centroidous method obtained from the entropy, CRITIC, standard deviation, mean, and MEREC methods was performed. Three sets of data were generated for the comparative study of the methods, as follows: the mean value for alternatives with weak and strong differences and criteria with linear dependence. Additionally, an actual dataset from mobile phones was also used for the comparison.

This report details the investigation of practices of instructors who use quantitative data to teach undergraduate courses within the Social Sciences. The study was undertaken by employees of the University of California, Santa Barbara (UCSB) Library, who participated in this research project with 19 other colleges and universities across the U.S. under the direction of Ithaka S+R. Ithaka S+R is a New York-based research organization, which, among other goals, seeks to develop strategies, services, and products to meet evolving academic trends to support faculty and students.

This report details the investigation of practices of instructors who use quantitative data to teach undergraduate courses within the Social Sciences. The study was undertaken by employees of the University of California, Santa Barbara (UCSB) Library, who participated in this research project with 19 other colleges and universities across the U.S. under the direction of Ithaka S+R. Ithaka S+R is a New York-based research organization, which, among other goals, seeks to develop strategies, services, and products to meet evolving academic trends to support faculty and students.

Research on performative teaching has expanded in recent decades. This growth has been accompanied by interest in evidence-based practice and evaluation. However, experimentation is complex and classroom-based researchers must carefully and responsibly negotiate many obstacles. Despite challenges inherent in this endeavour, many practitioners are genuinely interested in how and why theatre supports learning. In this article we explore experimentation in the second language classroom and outline a conceptual framework which embeds qualitative data collection within an experimental design. These ideas can be regarded as an extensive case study that combines and furthers the work of teacher artists and scientific practice.

The current paper is aimed at investigating some quantitative and qualitative data, as well as their implications for the space/place/time perspective in terms of fire disaster management in Makana Local Municipality. The working hypothesis of the current article is that fire-fighting under drought conditions will post severe challenges on the disaster risk management system (DRM) in the study area. Methodology of the article includes a combination of document analysis, modelling using the Google-related tools to track and statistically analyse the public interest in fires, the legislation, and financial/practical implications of the drought on fire disaster management in Makana Local Municipality. Results of the study indicate that there has been a constant and increasing trend in terms of the South African public's in fires. That trend is driven by interest in fire-fighting equipment and possible also by the interest of the South African population in fire-fighting as a career. On causality front, the interest in fires is quantitatively driven by number of fires in South Africa between 2004 and 2017, as well as access to the internet by the South African population. [ABSTRACT FROM AUTHOR]

In two studies we aimed at developing the Attitude towards Italian Mafias Scale (AIMS). In study 1 (N = 292) we used an Exploratory Factor Analysis to reduce the number of the items and explore their latent constructs. In study 2 (N = 393) we performed a Confirmatory Factor Analysis on the resulting 18-item questionnaire, whose latent structure was best identified by a general factor Mafia Attitude and three specific factors related to Behaviors, Cognitions and Emotions-Cognitions towards mafias. Moreover, we showed that the AIMS has (i) discriminant validity compared to a measure of attitudes towards crime, (ii) predictive validity of donation behavior to an association against mafias, (iii) internal consistency, and (iv) invariance for people of the five deeprooted mafia regions of Southern Italy and those from the rest of Italy. Finally, we observed a difference between the participants from the five deep-rooted mafia regions (i.e., Apulia, Basilicata, Calabria, Campania, Sicily) and the rest of Italy, with the former having surprisingly more negative attitudes towards mafias compared to the latter. The AIMS might help to reliably survey people's sentiment towards Italian mafias and promote targeted and effective law-related education interventions. [ABSTRACT FROM AUTHOR]

This article discusses the importance of correctly classifying data in research and understanding the different types of data. Categorical data represents characteristics and can be further categorized as nominal or ordinal. Quantitative data represents values that can be counted or measured and can be further categorized as discrete or continuous. The type of data impacts the statistical methods used, with descriptive statistics used for categorical data and inferential statistics used for quantitative data. The article emphasizes the need for accurate and truthful presentation of data in research. [Extracted from the article]

There is a critical need to address the impact of the COVID-19 pandemic on the well-being of students and educators. In this article, we present findings from the second year of implementing the Student Alliance for Flourishing program, a school-wide initiative to promote the flourishing of students and educators. First, we highlight the connection between Ryan and Deci’s Self-Determination Theory and the Student Alliance for Flourishing (SAFF) program, emphasizing the importance of autonomy, competence, and relatedness in supporting the psychological needs of educators and students. Then, we describe the SAFF program and present data that highlight the program’s impact on advisors and students, particularly as these data relate to participants’ flourishing. Finally, we conclude by emphasizing the significance of promoting flourishing in schools and the need for further empirical research in this area.

In two studies we aimed at developing the Attitude towards Italian Mafias Scale (AIMS). In study 1 (N = 292) we used an Exploratory Factor Analysis to reduce the number of the items and explore their latent constructs. In study 2 (N = 393) we performed a Confirmatory Factor Analysis on the resulting 18-item questionnaire, whose latent structure was best identified by a general factor Mafia Attitude and three specific factors related to Behaviors, Cognitions and Emotions-Cognitions towards mafias. Moreover, we showed that the AIMS has (i) discriminant validity compared to a measure of attitudes towards crime, (ii) predictive validity of donation behavior to an association against mafias, (iii) internal consistency, and (iv) invariance for people of the five deep-rooted mafia regions of Southern Italy and those from the rest of Italy. Finally, we observed a difference between the participants from the five deep-rooted mafia regions (i.e., Apulia, Basilicata, Calabria, Campania, Sicily) and the rest of Italy, with the former having surprisingly more negative attitudes towards mafias compared to the latter. The AIMS might help to reliably survey people’s sentiment towards Italian mafias and promote targeted and effective law-related education interventions.

This article covers the key findings from a set of qualitative and quantitative research investigating the relationship between public and professional perceptions of contemporary collecting. Areas of congruence and disconnect were studied using a survey, distributed to public and professional respondents, and a series of interviews with curatorial and directorial staff at two case study science museums: the Science Museum in London and the Rijksmuseum Boerhaave in Leiden. This research demonstrated that while there were certain areas of disconnect and hesitancy, both groups supported the acquisition of twenty-first century material in science, technology and medical museums, acknowledging the importance of such collecting strategies. The data also highlights the importance of contemporary material for audience engagement and development of science capital, enabling visitors to deepen their understanding of the past, present and future through discussions of current science, technology and medicine and its role within society. [ABSTRACT FROM AUTHOR]

A synoptic review of plant disease epidemics and outbreaks was made using two complementary approaches. The first approach involved reviewing scientific literature published in 2021. in which quantitative data related to new plant disease epidemics or outbreaks were obtained via surveys or similar methodologies. The second approach involved retrieving new records added in 2021 to the CABI Distribution Database. which contains over a million global geographic records of organisms from over 50,000 species. The literature review retrieved 186 articles. describing studies in 62 categories (pathogen species/species complexes) across more than 40 host species on six continents. Pathogen species with more than five articles were Bursaphelenchus xylophilus, 'Candidatus Liberibacter asiaticus', cassava mosaic viruses, citrus tristeza viruses, Erwinia amylovora, Fusarium spp. complexes. F oxysporum f. sp. cubense. Magnaporthe oryzae. maize lethal necrosis co-infecting viruses, Meloidogyne spp. complexes, Pseudomonas Syringae pvs., Puccinia striiformis f. sp. tritici. Xylella fastidiosa, and Zymoseptoria tritici. Automated searches of the CABI Distribution Database identified 617 distribution records new in 2021 of 283 plant pathogens. A further manual review of these records confirmed 15 pathogens reported in new locations: apple haminerhead viroid, apple rubbery wood viruses, Aphelenchoides besseyi. Biscognictuxia mediterranea, ' Ca. Liberibacter asiaticus', citrus tristeza virus, Colletotrichum siamense, cucurbit chlorotic yellows virus, Erwinia rhapontici, Erysiphe corylacearum, F. oxysporum f. sp. cubense Tropical race 4, Globodera roslochiensis. Nothophonia quercina, potato spindle tuber viroid, and tomato brown rugose fruit virus. Of these, four pathogens had at least 25% of all records reported in 2021. We assessed two of these pathogens-tomato brown rugose fruit virus and cucurbit chlorotic yellows virus-to be actively emerging in/spreading to new locations. Although three important pathogens-'Ca. Liberibacter asiaticus', citrus tristeza virus, and E oxysporum f. sp. cubense-were represented in the results of both our literature review and our interrogation of the CABI Distribution Database, in general. our dual approaches reveajed distinct sets of plant disease outbreaks and new records, with little overlap. [ABSTRACT FROM AUTHOR]

Concerning the increase in the number of trips and tourists after the COVID-19 pandemic, TSPs (Transport Service Providers) and transport organizations are trying to improve their operability to answer the needs and expectations of passengers. This paper presents a methodology to assess and evaluate to what extent innovative technologies meet the needs of tourists and TSPs involved in the digital ecosystem for door-to-door trips in Europe, making railways and public transport more attractive and consequently encouraging people to use more intermodal solutions in public transport. In this study, two kinds of quantitative data are used: operational KPIs (Key Performance Indicators) and USI (User Satisfaction Index) surveys. The Effectiveness concept, as a metric of the capacity to meet these needs and expectations by the innovative technology, is calculated by merging both types of quantitative data. The method considers tourists' socio-demographic profiles, allowing comparisons among TSPs and profiles for a specific technology, and it is extended to figure out correlations among variables through regression and Bayesian Networks analysis. In addition, specific socio-demographic data relevant to the needs and expectations were studied through the ANOVA test. This work belongs to the methodological framework of the IP4MaaS (Innovation Program 4 Mobility as a Service) project, which sets six demo sites on which this assessment method will be applied in a further stage. The concept of Effectiveness is applied in all the above-mentioned demo sites for the final assessment. Some IT innovations such as Location-Based Experience and Journey Planning have shown high Effectiveness. This work could be interesting for TSPs and IT (Information Technology) developers, researchers, policymakers, and organizations in the transport sector. [ABSTRACT FROM AUTHOR]

The purpose of this study is to examine the impact of in-service education designed to improve early childhood teachers’ environmental awareness, knowledge, attitudes and their skills on integrating environmental issues in their teaching. Thirty early childhood teachers in the treatment group and Thirty in the control group participated the study. Teachers in the control group did not attain in-service education. Teachers responded to the Environmental Problems Attitude Scale (EPAS) before and after the in-service education. After the education process, teachers in the treatment group provided qualitative data about the impact of this education. For the treatment group the Mann-Whitney U test revealed a significant increase from pretest to posttest. Mann-Whitney U did not indicate a significant increase for the control group. Three major themes derived from qualitative data. These are an increase in environmental awareness, an increase in individual responsibility and taking action, as well as increased motivation and being better equippedfor environmental education.

Statistical analysis is an integral part of medical research. It helps transform raw data into meaningful insights, supports hypothesis testing, optimises study design, assesses risk and prognosis, and facilitates evidence-based decision-making. The statistical analysis increases research findings' reliability, validity and generalisability, ultimately advancing medical knowledge and improving patient care. Without it, meaningful analysis of the data collected would be impossible. The conclusions drawn would be unsubstantiated and misleading. Many health professionals are unfamiliar with statistical analysis and its basic concepts. The analysis of clinical data is an integral part of medical research. Identifying the data type (continuous, quasi-continuous or discrete) and detecting outliers are the first and most important steps. When analysing the data distribution for normality, graphical and numerical methods are recommended. Depending on the type of data distribution, appropriate non-parametric or parametric tests can be used for further analysis. Data that are not normally distributed can be normalised using various mathematical methods (e.g., square root or logarithm) and analysed using parametric tests in the next steps. This review provides essential explanations of these concepts without using complex mathematical or statistical equations but with several graphical examples of various statistical terms. [ABSTRACT FROM AUTHOR]

This study was undertaken to determine the impact of the Rural Financial Institution Building Program (RUFIN) on the productivity of women-owned farms and non-farm enterprises in Northern Nigeria. The study utilized primary data collected through a questionnaire administered to 390 beneficiaries and an equal number of non-beneficiaries selected through a multi-stage sampling procedure. The productivity of women-owned enterprises was determined using Total Factor Productivity (TFP), which was measured as a ratio of the total annual output of the enterprise to the product of capital input, labor input, and total material input. The propensity score matching approach was used to analyze data because of its aptness for overcoming selection bias in an intervention project like RUFIN. Four matching algorithms were tried, which include Nearest Neighbour Matching, Radius Matching, Epanechnikov Kernel Matching, and Stratification methods. Results showed the treatment (RUFIN) had a significant effect on the productivity of women-owned enterprises at 1% probability level, irrespective of the matching method. For the selected stratification matching method, the Average Treatment Effect on the Treated (ATT) was 1.673, indicating participation in RUFIN increases the enterprise productivity of a given beneficiary by 1.673. The study concludes that RUFIN had positive impacts on the productivity of beneficiaries. It is recommended that institutionalized development programs that mirror the design and implementation approach of Rural Financial Institution Building Program (RUFIN) should be promoted across national and sub-national governments of Nigeria as a means of scaling the productivity of rural entrepreneurs and harnessing other benefits that accompany rural financing. [ABSTRACT FROM AUTHOR]

Copyright of EDUKACJA Quarterly is the property of Educational Research Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We presented a novel method to analyze the impact tax management systems have on users (individual impact) in this study. The interrelationship among the three information system (IS) quality constructs is examined. The study is based on the evaluation undertaken in this paper of DeLone and Mclean's (D & M) model. Quantitative data are gathered from a related Ghanaian enterprise. The structural equation modelling of partial least squares was utilized to model the system quality, information quality, and service quality. The result of the study shows that the three quality constructs of the D & M model positively influence the users of a tax management system (individual impact). The results also show that there is a significant positive interrelation among the IS quality constructs. [ABSTRACT FROM AUTHOR]

A rectangular cartogram is a kind of graphical representation that uses a rectangular area to represent the attributes of geographical objects and is widely used in the representation of statistical data such as population, economic statistics, and epidemic distribution. However, there is currently little research on the effectiveness of rectangular cartograms for conveying quantitative data. In this paper, the rectangular cartogram and unclassed choropleth map are compared to evaluate the rectangular cartogram's effectiveness in quantity representation through task-driven eye-tracking cognitive experiments. In addition, the accuracy and efficiency of information communication and the differences in the reading processes of map readers when using the two types of maps for different tasks have been analyzed to provide references for more effective use of rectangular cartograms in the future. The main contributions of this paper are: (1) it has been proven by experiments that when completing the four tasks of locate, compare, find extreme, and estimate, the participants have higher accuracy rates with the rectangular cartogram; (2) the reading process shown by the eye tracking experiment shows that the more complex the task is, the more patient the participants would be with the rectangular cartogram, and the more pronounced the advantages of the rectangular cartogram are. [ABSTRACT FROM AUTHOR]

Statistical analysis is an integral part of medical research. It helps transform raw data into meaningful insights, supports hypothesis testing, optimises study design, assesses risk and prognosis, and facilitates evidence-based decision-making. The statistical analysis increases research findings' reliability, validity and generalisability, ultimately advancing medical knowledge and improving patient care. Without it, meaningful analysis of the data collected would be impossible. The conclusions drawn would be unsubstantiated and misleading. Many health professionals are unfamiliar with statistical analysis and its basic concepts. The analysis of clinical data is an integral part of medical research. Identifying the data type (continuous, quasi-continuous or discrete) and detecting outliers are the first and most important steps. When analysing the data distribution for normality, graphical and numerical methods are recommended. Depending on the type of data distribution, appropriate non-parametric or parametric tests can be used for further analysis. Data that are not normally distributed can be normalised using various mathematical methods (e.g., square root or logarithm) and analysed using parametric tests in the next steps. This review provides essential explanations of these concepts without using complex mathematical or statistical equations but with several graphical examples of various statistical terms.

This article covers the key findings from a set of qualitative and quantitative research investigating the relationship between public and professional perceptions of contemporary collecting. Areas of congruence and disconnect were studied using a survey, distributed to public and professional respondents, and a series of interviews with curatorial and directorial staff at two case study science museums: the Science Museum in London and the Rijksmuseum Boerhaave in Leiden. This research demonstrated that while there were certain areas of disconnect and hesitancy, both groups supported the acquisition of twenty-first century material in science, technology and medical museums, acknowledging the importance of such collecting strategies. The data also highlights the importance of contemporary material for audience engagement and development of science capital, enabling visitors to deepen their understanding of the past, present and future through discussions of current science, technology and medicine and its role within society.

This article presents the main recent developments in migration trends to and from Belarus. It studies these trends via the migration systems theory lenses, according to which Belarus belongs to the Eurasian migration system. The most significant migration flows are directed towards Russia, due to the existence of the Union State. However, over the last decade, Belarusian statistics have shown a gradual transformation in the direction of these migration flows. After the recession in Russia in 2015, the number of emigrants from Belarus to EU countries increased. The most significant changes have occurred in the migration dynamics between Belarus and Poland and Lithuania. The existence of the Pole’s Card makes it more difficult to measure the number of Belarusian immigrants in Poland, therefore, I provide a comparative analysis of Belarusian and Polish statistics in order to show a more realistic picture of the number and structure of Belarusian emigrants and the problem of underestimation in the sending country. Particular attention is paid to the consequences of the political situation in Belarus after 2020; this has become an additional push factor for emigrants and may also lead to a further reduction of Belarusian migratory links within the Eurasian migration system. Thus, the statistics for 2021 show a significant increase in the number of Belarusian emigrants to the EU, while emigration to Russia has remained at the same level.

Since acrobatic gymnastics is a recent gymnastics discipline, with only a few decades old, with only a few decades old, it is not yet much explored as a scientific research field. Despite its increasing popularity, and while science mapping has become an essential activity for all scientific disciplines, no bibliometric analysis on this topic was available. Therefore, this study aims to provide a static picture of the scientific research development in acrobatic gymnastics by collecting information about the main contributors as well as the main investigation topics, the publication dynamics and cooperative networks. A search conducted in the Web of Science and Scopus databases retrieved 37 journal articles between 2001-2021. Results suggest that the year of 2015 was a milestone for scientific research in acrobatic gymnastics since it marked the beginning of the dominance of authors from Spain, followed by Poland and Portugal. Countries are generally focused on their own territory and there is a limited scientific collaboration between different nations. The Spanish and the Polish research institutions are leading publishing in this sport. As a reference for future studies, our results suggest that although balance was identified as the niche investigation topic, there has been a lack of interest for the pyramids balance, which is a major feature of acrobatic gymnastics.

Mixed methods research is commonly defined as the combination and integration of qualitative and quantitative data. However, defining these two data types has proven difficult. In this article, I argue that qualitative and quantitative data are fundamentally different, and this difference is not about words and numbers but about condensation and structure. As qualitative data are analyzed with qualitative methods and quantitative data with quantitative methods, we cannot analyze one type of data with the other type of method. Quantitative data analysis can reveal new patterns, but these are always related to the existing variables, whereas qualitative data analysis can reveal new aspects that are hidden in the data. To consider data as quantitative or qualitative, we should judge these data as end products, not in terms of the process through which they come into being. Thus, quantitizing qualitative data results in quantitative data and the analysis thereof is quantitative, not mixed, data analysis. For mixed data analysis, both real, non-quantitized qualitative data and quantitative data are needed. As these quantitative data may be quantitized qualitative data, the implication is that, contrary to a common view, mixed methods research does not necessarily involve quantitative data collection. [ABSTRACT FROM AUTHOR]