Iskanje po katalogu digitalne knjižnice

Opis: The motivation of adult learners in the workplace is an area of research that focuses on understanding the factors that influence adults' desire to engage in learning activities within an organizational context. We studied various internal and external factors that contribute to the motivation of adult employees to acquire new knowledge, skills, and competencies to accelerate their professional development and career advancement. Understanding the motivations of adult learners at work is crucial for organizations that want to design effective learning programs. With other factors, such as intrinsic and extrinsic motivation, perceived relevance, and goal orientation, organizations can develop strategies that promote and sustain employee motivation. This can ultimately lead to improved engagement, performance, and professional growth among employees.
Ključne besede: motivation, adult education, adult learning, motivational factors, lifelong learning
Objavljeno v DKUM: 25.04.2025; Ogledov: 0; Prenosov: 0
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Opis: The world economy and society are in a complex process of transition characterized by a high degree of uncertainty. Therefore, further development and management of the transition will largely depend on the quality of the decisions made and, accordingly, on the decision-making process itself. The main goal of this study is to analyze the reliability of International Energy Security Risk Index as a tool to support the process of energy and economy transition decision making, as closely related and highly interdependent phenomena. The index is composed of 29 aggregated variables (grouped into eight categories), and the research is conducted on a research sample of 25 countries over a period of 36 years. The reliability assessment is performed by using Multiple Regression Analysis. Multicollinearity test, plus Multicollinearity test with Variance Inflation Factors, is used for methodological verification. The test results indicate a high degree of unreliability of the Index, as is concluded based on the observed errors in its methodological settings. These errors primarily relate to a high degree of multicollinearity in all 29 variables, whereby independent variables lose their independence and thus jeopardize reliability of the total Index. Out of the eight groups of variables, the fuel imports group is the only one that does not show big methodological errors. The paper presents a recommendation for the improvement of the observed Index (review of the role of individual variables found to be particularly methodologically indicative), as well as a recommendation for different distribution of weighting coefficients.
Ključne besede: energy and economy transition, decision making, international energy security risk index, multiple regression analysis, multicollinearity test, multicollinearity test with variance inflation factors
Objavljeno v DKUM: 04.02.2025; Ogledov: 0; Prenosov: 6
Celotno besedilo (447,82 KB)
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Opis: The paper aims to investigate the main factors influencing the mathematics achievement of social sciences university students in Slovenia. A conceptual model was derived where three categories of variables were taken into account: attitude towards mathematics and math anxiety, engagement in learning activities, and attitude towards involving technology in learning mathematics. Data were collected for seven consecutive academic years and analysed using Structural Equation Modelling (SEM). The results showed a very high coefficient of determination for mathematics achievement (0.801), indicating that variables “Perceived Level of Math Anxiety”, “Self-Engagement in Mathematics Course at University”, and “Perceived Usefulness of Technology in Learning Mathematics”, together, explain 80.1% of the total variance. Based on our findings, we can conclude that teaching in secondary school is a crucial determinant for success in mathematics at university. It is essential to identify the best methods for secondary school math teachers which will help them give future students better entry-level knowledge for universities. These methods will, hopefully, also improve the level of mathematics self-confidence, as well as lower the level of math anxiety, which all considerably affect the performance of students in university mathematics.
Ključne besede: mathematical education, good practices in mathematics, mathematics achievement, education, influencing factors, university, social sciences, structural equation modelling (SEM)
Objavljeno v DKUM: 14.01.2025; Ogledov: 0; Prenosov: 6
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Opis: This paper aims to present the model of factors which influence the digital transformation in maritime transport sector. The preliminary model is based on a literature review and interviews conducted to identify the relevant factors influencing the digital transformation of stakeholders operating in the maritime transport sector. In order to test the model, the survey was conducted on the sample of Croatian administrative (port authorities, ministry, harbormaster’s offices, etc.) and commercial stakeholders (freight forwarders, agents, terminal operators, etc.) operating in maritime transport sector. The collected data was analyzed using the partial least squares structural equation modeling (PLS-SEM) approach. The research has shown that organizational, technological, and environmental (TOE) factors affect the digitalization of the organizations in the maritime transport sector. As a result of digitalization, changes in business models are visible: organizations in maritime transport sector generate additional revenue from new sources, provide new services, and introduce new sales channels.
Ključne besede: digital transformation, maritime transport sector, seaports, TOE factors, PLS-SEM
Objavljeno v DKUM: 16.12.2024; Ogledov: 0; Prenosov: 4
Celotno besedilo (588,07 KB)
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Opis: Background: Supporting and understanding the health of patients with chronic diseases and cardiovascular disease (CVD) risk is often a major challenge. Health data are often used in providing feedback to patients, and visualization plays an important role in facilitating the interpretation and understanding of data and, thus, influencing patients’ behavior. Visual analytics enable efficient analysis and understanding of large datasets in real time. Digital health technologies can promote healthy lifestyle choices and assist in estimating CVD risk. Objective: This review aims to present the most-used visualization techniques to estimate CVD risk. Methods: In this scoping review, we followed the Joanna Briggs Institute PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. The search strategy involved searching databases, including PubMed, CINAHL Ultimate, MEDLINE, and Web of Science, and gray literature from Google Scholar. This review included English-language articles on digital health, mobile health, mobile apps, images, charts, and decision support systems for estimating CVD risk, as well as empirical studies, excluding irrelevant studies and commentaries, editorials, and systematic reviews. Results: We found 774 articles and screened them against the inclusion and exclusion criteria. The final scoping review included 17 studies that used different methodologies, including descriptive, quantitative, and population-based studies. Some prognostic models, such as the Framingham Risk Profile, World Health Organization and International Society of Hypertension risk prediction charts, Cardiovascular Risk Score, and a simplified Persian atherosclerotic CVD risk stratification, were simpler and did not require laboratory tests, whereas others, including the Joint British Societies recommendations on the prevention of CVD, Systematic Coronary Risk Evaluation, and Framingham-Registre Gironí del COR, were more complex and required laboratory testing–related results. The most frequently used prognostic risk factors were age, sex, and blood pressure (16/17, 94% of the studies); smoking status (14/17, 82%); diabetes status (11/17, 65%); family history (10/17, 59%); high-density lipoprotein and total cholesterol (9/17, 53%); and triglycerides and low-density lipoprotein cholesterol (6/17, 35%). The most frequently used visualization techniques in the studies were visual cues (10/17, 59%), followed by bar charts (5/17, 29%) and graphs (4/17, 24%). Conclusions: On the basis of the scoping review, we found that visualization is very rarely included in the prognostic models themselves even though technology-based interventions improve health care worker performance, knowledge, motivation, and compliance by integrating machine learning and visual analytics into applications to identify and respond to estimation of CVD risk. Visualization aids in understanding risk factors and disease outcomes, improving bioinformatics and biomedicine. However, evidence on mobile health’s effectiveness in improving CVD outcomes is limited.
Ključne besede: cardiovascular disease prevention, risk factors, visual analytics, visualization, mobile phone, PRISMA
Objavljeno v DKUM: 26.11.2024; Ogledov: 0; Prenosov: 8
Celotno besedilo (435,60 KB)