1. Designing the ideal political identity questionnaire using machine learning and ideology scalesAna Nikolić, Uroš Sergaš, Marko Tkalčič, 2025, objavljeni znanstveni prispevek na konferenci (vabljeno predavanje) Opis: Political ideology shapes beliefs, behavior and attitudes toward society. Many existing questionnaires for measuring ideology are lengthy, repetitive, and misaligned with self-perception. This paper investigates whether a shorter, reliable, two-dimensional political identity questionnaire can be created using machine learning and psychometric methods. Sixty participants completed four ideological instruments (MFQ, SDO, RWA and 8values). Lasso regression and Random Forest with nested cross-validation identified predictive items, while psychometric evaluation included CFA and Cronbach’s alpha. Random Forest outperformed Lasso. Internal reliability was excellent and factor loadings supported a two-factor structure despite moderate model it. Findings show that ideology can be measured efficiently with reduced items, supporting applications in research, digital platforms and political psychology.
Ključne besede: political ideology, questionnaire design, machine learning, psychometrics
Objavljeno v RUP: 30.01.2026; Ogledov: 149; Prenosov: 2
 Celotno besedilo (189,01 KB) |
2. Enhanced precision in axle configuration inference for bridge weigh-in-motion systems using computer vision and deep learningDomen Šoberl, Jan Kalin, Andrej Anžlin, Maja Kreslin, Klen Čopič Pucihar, Matjaž Kljun, Doron Hekič, Aleš Žnidarič, 2025, izvirni znanstveni članek Opis: Heavy goods vehicles (HGVs) have a significant impact on road and bridge infrastructure, with overloaded vehicles accelerating structural deterioration and increasing safety risks. Bridge weigh-in-motion (B-WIM) systems estimate gross vehicle weight (GVW) using strain measurements, but inaccuracies in axle configuration recognition can reduce reliability. This study presents a low-cost computer vision (CV) extension for existing B-WIM installations that verifies strain-inferred axle configurations using traffic camera images and flags GVW estimates as reliable or unreliable. Experiments on a data set of over 30,000 HGV records show that by combining convolutional neural networks with strain-based heuristics, GVW reliability can improve from 96.7% to 99.89%, effectively excluding nearly all erroneous measurements. The approach operates without interrupting ongoing B-WIM operations and can be applied retrospectively to historical data. Limitations include the inability to detect raised axles (RAs), which the method excludes as unreliable. This method provides a practical, high-precision enhancement for structural health monitoring of bridges.
Ključne besede: B-WIM, computer vision, deep learning
Objavljeno v RUP: 16.01.2026; Ogledov: 150; Prenosov: 4
Celotno besedilo (2,01 MB)
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3. Upskilling older employees in the artificial intelligence eraTinkara Žabar, Aleksander Janeš, 2025, izvirni znanstveni članek Opis: Research Question (RQ): What is the effect of new technologies, with an emphasis on artificial intelligence (AI), on the need to upskill older employees (50+ years). Purpose: The purpose of the research was to carry out a systematic literature review of existing research in the field of the effect of AI on the upskilling needs of older employees. Method: We performed a systematic literature review across six academic search engines: ProQuest, Emerald, Sage Journals, Springer, Research Gate, and Google Scholar. Results: Artificial intelligence is significantly transforming the labor market, as it requires constant adaptation to new skills and knowledge. AI has a significant effect on older employees, who are exposed to greater challenges due to a possible lack of digital skills and sensitivity to change. In this context, training and further education are key mechanisms to ensure that skills match the requirements of the work environment and the labor market. Organizations must quickly adapt to changing requirements by creating a culture of lifelong learning that encourages seniors and other employees to improve. Training programs must be based on the specific needs and challenges faced by older employees. Organization: The research emphasizes the importance of training older employees in the age of AI and encourages organizations to create a culture of lifelong learning as part of the organization's strategic directions and goals. Society: The importance of research for society is reflected in the insight into the involvement of all age groups in the possibility of improving knowledge, skills, and attitudes towards the use of modern technologies. Organizations and society itself bear the social responsibility to enable older employees to successfully integrate into the work environment in the AI era. Originality: The research addresses the need to improve the skills of a specific age group in the age of AI, where it simultaneously highlights the importance of fostering a culture of lifelong learning in a rapidly changing world. The research findings provide guidelines for policymaking in the field of training on the national level in the context of an aging workforce and new technologies. Limitations/further research: The literature review was limited to six publicly available databases. In the article, older employees were considered as people in the labor process older than 50 years. We must emphasize that older employees differ from each other in terms of education, economic, social, and other circumstances. Further research should investigate the effect of new technologies regarding the specific circumstances mentioned in this age group.
Ključne besede: knowledge society, upskilling, knowledge management, retraining, older employees, artificial intelligence, lifelong learning
Objavljeno v RUP: 12.01.2026; Ogledov: 136; Prenosov: 4
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4. Predictors of sustainable development outcomes in learning spaces of early childhood : Slovenian teachers' perspectivesJurka Lepičnik-Vodopivec, Adrijana Višnjić-Jevtić, Aleksandra Šindić, 2026, izvirni znanstveni članek Opis: This research examined factors associated with sustainable development outcomes (O-SD) in early childhood learning settings, as perceived by preschool teachers, considering environmental, social, and economic aspects along with contextual elements (child age, eco-program affiliation, teacher experience). Data were gathered through an online survey targeting 114 Slovenian preschool teachers in 2024. The reliability of the instrument was high (α = .942), and principal component analysis confirmed its validity. Correlation and stepwise regression analyses identified the key predictors of O-SD. Education focused on economic sustainability and child age emerged as the primary predictors, accounting for approximately 55% of the variance. While social sustainability was frequently observed in practice, it did not prove to be a significant predictor. The findings highlight the importance of developmentally appropriate and age-sensitive strategies, alongside the intentional inclusion of economic considerations. Limitations include a convenience sample and reliance on self-reported data. Future research should aim to replicate these results in diverse settings and consider mixed-method approaches that incorporate children’s perspectives.
Ključne besede: quality education, early childhood education for sustainability, sustainable development outcomes, early childhood learning settings
Objavljeno v RUP: 07.01.2026; Ogledov: 200; Prenosov: 2
Celotno besedilo (365,89 KB)
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5. Digital Narrative Photography as a Method to Improve Empathy in Health SciencesJuan M. Leyva, 2025, samostojni znanstveni sestavek ali poglavje v monografski publikaciji Opis: This chapter explores narrative photography in health sciences education, highlighting its effectiveness in addressing the often-overlooked psychosocial needs of patients. Traditionally focused on immediate biological outcomes, healthcare has neglected the importance of empathy and reflective practice. Narrative photography, inspired by Photovoice and reflective practice, involves capturing and reflecting on patients’ real-life narratives through visual and written means. Students create self-made photographs or drawings, articulate their interpretations through short reflective narratives, and engage in group discussions to foster deeper empathy and reflection. Originally dependent on face-to-face interaction, narrative photography has been adapted to hybrid formats with digital tools, enhancing accessibility and cost-effectiveness. This chapter examines the origins, methodologies, technological advancements, and real-world applications of narrative photography, along with variations developed by the author. It also provides recommendations for assessing learning outcomes, evidence of effectiveness, and evaluations of student and faculty satisfaction.
Ključne besede: art-based methods, narrative photography, teaching innovation, active learning, hybrid learning
Objavljeno v RUP: 22.12.2025; Ogledov: 164; Prenosov: 2
Celotno besedilo (1,24 MB) |
6. Exploring student perspectives on e-learning in nursing educationMirko Prosen, Sabina Ličen, 2025, samostojni znanstveni sestavek ali poglavje v monografski publikaciji Opis: E-learning has rapidly gained prominence in nursing education, offering flexible alternatives to traditional learning. This study aimed to explore nursing students’ experiences with e-learning, focusing on perceived benefits, challenges, and its impact on skill acquisition. Using a qualitative design, data were collected from four face-to-face focus groups comprising 20 nursing students. Thematic analysis was employed to examine the data, yielding six key themes: Flexibility and accessibility benefits, Impact on student engagement and interaction, Technological and infrastructure challenges, Effect on practical skills and learning outcomes, Diverse preferences in learning approaches, and Self-management and motivation in e-learning. The findings indicate that, while e-learning provides accessibility and flexibility, it poses challenges in practical skill development and engagement. This study emphasises the need for adaptive e-learning models to meet diverse learning requirements effectively.
Ključne besede: online learning, blended learning, thematic analysis, skill development, student engagement
Objavljeno v RUP: 22.12.2025; Ogledov: 177; Prenosov: 0
Celotno besedilo (323,42 KB) |
7. Maximizing Nursing Students’ Engagement in Distance Learning: Strategies and InsightsBoris Ilić, Irena Kovačević, Danko Relić, Vesna Švab, Vedrana Vejzović, Seher Yurt, 2025, samostojni znanstveni sestavek ali poglavje v monografski publikaciji Opis: The increase of online nursing education, driven by technology and the demand for flexible learning, has emphasized the importance of student engagement. Participation plays a key role in shaping both academic achievement and the acquisition of crucial nursing skills. This chapter explores the impact of technological factors such as audio and video quality, as well as internet speed, on student engagement. Moreover, it delves into how the ERR framework – a teaching approach that includes Evocation, Realization of Meaning and Reflection, along with other interactive tools can be used in online learning settings to improve nursing students’ participation. This work aims to provide educators with practical insights for improving online nursing education by combining technological considerations with innovative teaching strategies.
Ključne besede: nursing education, distance learning, student engagement, ERR framework, Technological factors
Objavljeno v RUP: 22.12.2025; Ogledov: 184; Prenosov: 1
Celotno besedilo (142,92 KB) |
8. Digital standard for the design of inclusive and effective online courses in higher education : an integrative literature reviewSabina Ličen, Mirko Prosen, 2025, samostojni znanstveni sestavek ali poglavje v monografski publikaciji Opis: This integrative literature review examines models and frameworks for digital education in higher education, synthesizing their key strengths and limitations. By analysing nine existing frameworks covering different aspects of digital education, including pedagogical approaches, technological solutions and assessment mechanisms, the study identifies gaps in the current literature. The findings show that while the individual models provide valuable insights, none of them independently offer a complete approach to the design, implementation and assessment of digital education. Therefore, this study proposes the development of an integrated digital standard that combines theoretical and practical perspectives to promote inclusive and effective online learning. Such a standard could increase the adaptability to students' needs, improve assessment mechanisms and increase the flexibility of digital learning environments. This study contributes to the development of sustainable and adaptable solutions for the future of digital education.
Ključne besede: innovative teaching methods, e-learning, sustainable education, effectiveness of online teaching, digital education
Objavljeno v RUP: 22.12.2025; Ogledov: 168; Prenosov: 2
Celotno besedilo (174,03 KB) |
9. Psychological factors and mechanisms of digital learningMaša Černelič Bizjak, Sabina Ličen, 2025, samostojni znanstveni sestavek ali poglavje v monografski publikaciji Opis: The digital environment is different from natural and social environments. Technologies are evolving to support new methods of collaborative learning and interaction. A key challenge is to ensure that technology-enhanced education is effective and creates a supportive environment for students. This requires considering adaptive motivations, emotions, and psychological factors such as intrinsic motivation, cognitive load and self-regulation, all which influence student engagement and success in digital learning. This chapter provides an overview of literature on psychological processes important in digital learning. Factors such as motivation, cognitive management, and self-regulation shape student performance in these environments. The psychology of digital learning explores the cognitive, emotional, and social dimensions of education in the digital age. Research aims to optimize these environments for better learning outcomes. Understanding these psychological elements is essential for educators to create more effective, engaging, and enjoyable digital learning experiences, though the field is still developing, and many aspects remain to be explored.
Ključne besede: digital learning, intrinsic motivation, cognitive load, self-regulation, technology-enhanced education
Objavljeno v RUP: 19.12.2025; Ogledov: 202; Prenosov: 3
Celotno besedilo (161,71 KB) |
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