Iskanje po katalogu digitalne knjižnice

Opis: This study investigates artificial intelligence (AI) literacy among university students from Slovenia, Croatia, and India, focusing on variations in their understanding of AI concepts and applications across different educational systems. The sample comprised 471 students from the business studies programmes in Slovenia, Croatia and India. Data were collected through a structured online questionnaire, and statistical analyses utilized descriptive statistics and independent samples proportions to identify significant differences in AI literacy levels across the three countries. The findings reveal substantial disparities in AI literacy. Croatian students demonstrated foundational and practical knowledge of AI, reflecting well-developed educational frameworks. Indian students excelled in interdisciplinary and applied aspects of AI, though their understanding of theoretical concepts revealed notable gaps. Slovenian students showed the greatest need for improvement, particularly in foundational knowledge, practical applications, and ethical considerations. The results also highlight universal challenges, such as gaps in understanding AI’s ethical and legal implications, underscoring the need for all educational systems to incorporate discussions on accountability and societal impacts into their curricula. These findings offer actionable recommendations for educational policy and curriculum design to enhance AI literacy globally and prepare students for the challenges and opportunities of an AI-driven world. This study contributes to the literature by enhancing the understanding of how AI literacy manifests across diverse educational systems, providing comparative insights to support globally relevant curriculum development and digital skills advancement.
Ključne besede: AI literacy, students, higher education, artificial intelligence
Objavljeno v DKUM: 05.11.2025; Ogledov: 0; Prenosov: 0
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Ključne besede: univerze
Objavljeno v DKUM: 22.09.2025; Ogledov: 0; Prenosov: 8
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Opis: To provide a more holistic understanding of how digital tools shape the educational environment, this paper includes a comprehensive analysis that explores several dimensions of technology use in higher education: use of artificial intelligence in education, online collaboration, use of an E-Board for learning, and excessive use of technology. With the aim of measuring students’ use of digital technology to support their studies, this research meets the goals of developing the measurement process, building a multi-criteria model, and applying it to a real-life example of determining the degree of students’ use of digital technology in relation to the demonstrated quality of academic performance. The analysis is based on a survey conducted among students at the University of Maribor’s Faculty of Economics and Business. Using factor analysis and multi-criteria evaluation, the findings reveal that students who demonstrate very-high-quality achievements also report the highest level of technology use to support their studies. They are followed by students with outstanding achievements, who excel in using an E-Board for learning and in demonstrating responsibility regarding excessive technology use. Students who achieve acceptable-quality results with certain defects stand out in online collaboration and the use of AI in the study process. The lowest level of technology use was reported by students demonstrating moderate-quality achievements. Theoretically, this research contributes to a better understanding of the multidimensional use of digital technology in higher education, while, practically, it provides useful guidelines for optimizing digital learning tools and enhancing the overall quality of the academic process
Ključne besede: digital technology in education, artificial intelligence in education, students, academic performance, multi-criteria analysis
Objavljeno v DKUM: 20.08.2025; Ogledov: 0; Prenosov: 10
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Opis: Background/Purpose: This paper aims to analyse the nexus between selected growth determinants and the finan- cial performance of high-growth companies (HGCs) in relation to their ownership. In line with principal-agent theory, we try to determine if the differences exist between managers who are also (co)owners and those managers who are not (co)owners. Also, we analysed if additional equity-based compensation, through different growth determinants, could increase HGC’s financial performance. Methods: The study was conducted on a sample of 119 HGCs from the Republic of Slovenia and was carried out in 2022. The empirical analysis was performed using regression analysis based on exploratory factor analysis (EFA). Analysis was performed using IBM SPSS Statistics 27 software. Results: Results showed that considering the importance of organisational networking capability for HGC’s finan- cial performance, there are statistically significant differences between owner-managers and managers, implying that ownership (and equity-based compensations) could positively shape HGC’s financial performance. In addition, results show that when analysing the owners-managers group of HGCs, risk-taking and organisational networking capability positively and statistically significantly impact HGC’s financial performance. Conclusion: Our paper highlights the importance of organisational networking capability as a growth determinant through which equity-based manager compensations can positively influence HGCs’ financial performance. The study contributes to diverse literature related to HGCs and contributes to relevancy for the policymakers aiming at enabling better financial performance of HGCs.
Ključne besede: high-growth company, entrepreneurial orientation, network capability, financial performance, principal-agent theory, equity-based compensation
Objavljeno v DKUM: 09.07.2025; Ogledov: 0; Prenosov: 9
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Opis: Background: Our research delved into exploring various selected facets of AI-driven employee engagement, from the gender perspective, among Slovenian entrepreneurs. Methods: This research is based on a random sample of 326 large enterprises and SMEs in Slovenia, with an entrepreneur completing a questionnaire in each enterprise. Results: Findings suggest that there are no significant differences between male and female entrepreneurs in Slovenia regarding various aspects of AI-supported entrepreneurial management practice including the following: AI-supported entrepreneurial culture, AI-enhanced leadership, adopting AI to reduce employee workload, and incorporating AI tools into work processes. The widespread integration of AI into entrepreneurship marks a transition to a business landscape that values inclusivity and equity, measuring success through creativity, strategic technology deployment, and leadership qualities, rather than relying on gender-based advantages or limitations. Our research also focused on the identification of gender differences in path coefficients regarding the impact of the four previously mentioned aspects of AI on employee engagement. While both genders see the value in using AI to alleviate employee workload, the path coefficients indicate that female entrepreneurs report higher effectiveness in this area, suggesting differences in the implementation of AI-integrated strategies or tool selection. Male entrepreneurs, on the other hand, appear to integrate AI tools into their work processes more extensively, particularly in areas requiring predictive analytics and project scheduling. This suggests a more technical application of AI in their enterprises. Conclusions: These findings contribute to understanding gender-specific approaches to AI in enterprises and their subsequent effects on employee engagement.
Ključne besede: entrepreneurship, artificial intelligence, AI-supported entrepreneurial culture, AI-enhanced leadership, adopting AI to reduce employee workload, incorporating AI tools into work processes, employee engagement
Objavljeno v DKUM: 01.07.2025; Ogledov: 0; Prenosov: 7
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