1. Exploratory study of digital competence predicting sustainable development beliefs and behavior : evidence for an integrated competence framework among pre-service teachersAndreja Istenič, Marina Volk, 2026, izvirni znanstveni članek Opis: Digital competences are increasingly recognized as important enablers of education for sustainable development (SD), particularly through their capacity to facilitate access to learning resources and knowledge, support their effective and critical use, and foster innovation in teaching and learning. In recent decades, the concept of digital competence has increasingly incorporated ethical and sustainability-related dimensions, reflecting the need to use digital technologies in ways that are responsible, inclusive, and sustainable. Against this background, the present exploratory study examined the structure and interrelationships of digital competences and SD competences among 368 pre-service teachers, with particular attention to the extent to which digital competence dimensions predicted SD beliefs and behavior. The findings indicate that digital competence significantly predicted sustainable society beliefs, although the overall explanatory effect was small. In contrast, digital competence did not significantly predict gender equity beliefs. Regarding energy saving behavior (ESB), responsible problem-solving made a statistically significant positive contribution to the individual predictor level; however, the overall regression model did not significantly predict ESB. Taken together, these findings suggest that digital competence and sustainability competence should not be viewed as entirely separate constructs. Rather, they appear to represent increasingly interconnected dimensions of competence that may contribute to responsible participation in contemporary society. At the same time, the relatively small explanatory effects observed in the present study indicate that digital competence alone is insufficient to account for substantial variation in sustainability-related beliefs and behaviors. This highlights the importance of considering digital competence alongside broader personal, social, educational, and contextual factors in efforts to strengthen education for SD.
Ključne besede: digital competences, sustainable development, pre-service teachers, higher education, predictors, digital literacy, sustainable development literacy
Objavljeno v RUP: 15.10.2026; Ogledov: 67; Prenosov: 2
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2. Combining multiple and boosting regression analyses to identify factors predicting achievements on mathematics national assessmentsDaniel Doz, Bor Bregant, 2026, izvirni znanstveni članek Opis: Numerous factors are related to students’ performance on standardized mathematics tests, including teacher-assigned math grades, gender, socio-economic status (ESCS), origin, geographic location, and school type. Typically, the influence of these factors on students’ outcomes on standardized mathematics tests is analyzed using classical regression analyses, which might not be able to handle complex, high-dimensional datasets and capture non-linear relationships. Boosting regression, a machine learning approach, was employed to overcome these limitations, allowing for more robust estimation of variable importance, detection of interaction effects, and provision of insights that are directly relevant for educational policy and intervention. Therefore, in this paper, we investigate the significance of these factors in predicting students’ achievements on the Italian national assessment of mathematical knowledge, INVALSI, through both multiple regression and boosting regression analyses. Results indicate that school type and teacher-assigned grades emerged as the most influential predictors, contributing approximately 42% and 30% of the relative importance within the predictive model, respectively, followed by macroregion (19%), gender (6%), and ESCS (3%). Students’ origin accounted for less than 1% of relative importance. These values reflect predictive contributions rather than causal effects and should be interpreted as indicators of the strength of association within the model rather than direct proportions of explained variance. This study demonstrates that the combination of multiple regression and boosting regression analyses can offer educators and policymakers clearer insights into the determinants of students’ performance in the national mathematics knowledge assessment.
Ključne besede: boosting regression, factors, mathematics, multiple regression, national assessment
Objavljeno v RUP: 13.10.2026; Ogledov: 127; Prenosov: 5
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3. Predictive role of demographics, maths anxiety, andenjoyment in pupils’ standardised maths achievement : a machine learning approachDaniel Doz, 2026, izvirni znanstveni članek Opis: This study seeks to determine the factors affecting the achievements of Grade 5 primary school pupils in the Italian national assessment, INVALSI, using Machine Learning (ML) regression algorithms. Four ML algorithms were applied to data from 25,827 Grade 5 Italian primary school pupils who participated in the 2017–2018 INVALSI mathematics test. The Boosting model achieved the highest explanatory power (R2 = .152), with mathematics anxiety (relative importance 40.2), ESCS (37.0), and enjoyment (17.0) emerging as the dominant predictors. Random Forest (R2 = .142) and Decision Tree (R2 = .097) models confirmed this pattern, consistently ranking anxiety (46.1%), ESCS (33.5%), and enjoyment (14.0%) as the three most important factors. Regularised Linear Regression (R2 = .127) revealed directional effects: ESCS (β = .213) and enjoyment (β = .130) positively predicted achievement, while anxiety (β = −.180) was negatively associated. Across all four algorithms, gender and macroregion demonstrated minimal predictive importance (≤ 6.4% and ≤ 2.3%, respectively).
Ključne besede: assessment, factors, machine learning
Objavljeno v RUP: 13.10.2026; Ogledov: 125; Prenosov: 8
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4. Psychometric properties of the Slovenian version of the mindfulness in teaching scalePetra Dolenc, Blaž Simčič, 2027, izvirni znanstveni članek Opis: Given the growing importance of mindfulness in educational research and practice, the use of measurement instruments with robust psychometric properties and cultural relevance is essential. The present study aimed to adapt and validate the Slovenian version of the Mindfulness in Teaching Scale (MTS‑SL). The scale was administered to a sample of Slovenian teachers (n = 425; aged 24–64 years), together with self‑report measures of dispositional mindfulness, teacher self‑efficacy, perceived stress, and work engagement. Confirmatory factor analysis supported the two‑related‑factor structure of the MTS‑SL (χ²/df = 1.48, CFI = 0.99, TLI = 0.99, RMSEA = 0.03, SRMR = 0.06), distinguishing Teacher Intrapersonal Mindfulness and Teacher Interpersonal Mindfulness. Multi-group CFA demonstrated configural, metric, and scalar invariance across educational levels taught and years of teaching experience (ΔCFI ≤ .01; ΔRMSEA ≤ .02). The internal consistency for the intrapersonal subscale was good (α = 0.86, ω = 0.86), and for the interpersonal subscale was acceptable (α = 0.70, ω = 0.67). Intrapersonal and interpersonal mindfulness were significantly positively correlated with dispositional mindfulness, teacher self‑efficacy, and work engagement (p < 0.01), and significantly negatively correlated with perceived stress (p < 0.01), providing evidence for convergent and divergent validity. Overall, the findings provide preliminary support for the reliability and validity of the MTS-SL and its use in research involving Slovenian teachers. Further studies are needed to establish its applicability across diverse educational settings and to support its broader practical use.
Ključne besede: mindfulness in teaching scale, intrapersonal and interpersonal mindfulness, psychometric validation, teachers
Objavljeno v RUP: 05.10.2026; Ogledov: 196; Prenosov: 11
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5. Exploring cultural competence among healthcare professionals in Slovenia : a cross-sectional studyEsmina Softić, Mirko Prosen, 2026, izvirni znanstveni članek Opis: Aim: The aim of this study was to examine the cultural competence of healthcare professionals, with the aim of developing educational content on cultural competence in healthcare. Design: A quantitative descriptive approach with a cross-sectional design. Methods: The Slovenian version of the Cultural Competence Assessment Tool (CCATool) was administered to 404 participants representing various healthcare professions. Results: The results showed that most participants (96.2%) demonstrated cultural awareness, with significantly above-average scores across all domains (p < 0.001), while only 2.3% achieved full cultural competence and 1.5% were classified as culturally incompetent, with none achieving cultural safety. Conclusion: Incorporating cultural competency training into educational programs can significantly improve the quality of health services, help reduce health disparities, strengthen awareness of cultural diversity, and promote effective functioning in multicultural environments.
Ključne besede: cultural awareness, culturally responsive care, educational needs, nursing education, transcultural nursing
Objavljeno v RUP: 14.09.2026; Ogledov: 346; Prenosov: 14
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6. Dystopian children’s literature in socialist and postsocialist contexts : the case of Auto-Moto AntsBarbara Zorman, 2026, izvirni znanstveni članek Opis: Young adult and children’s dystopias enable young readers to engage with social structures and their contradictions; as these are culturally specific, dystopia may be understood as culturally contingent, which suggests the need to expand critical discussions that have largely centred on the anglophone production of this genre. This article focuses on dystopia within socialist and post-socialist contexts. During the Cold War, children’s literature, particularly fantasy narratives, provided Eastern European authors with a medium for articulating veiled political critiques. Jože Snoj's Auto-Moto Ants (1975) provides an interesting illustration of Hunt’s (2009) claim that the best children’s literature preserves traditional structures while subtly undermining them, since it hyperbolically subverts socialist ideology in the dystopian world and contrasts it with a nostalgic patriarchal family idyll in the primary world. The representation of technology further intensifies this subversive-conservative ambivalence, functioning both as an instrument of control over the auto-moto ant collective and as a means of empowerment and liberation for the child protagonists. The 2023 adaptation preserves the original’s core narrative, but the strategy of indirect critique shaped by the need to evade censorship is replaced by a predominantly visual allegory that is no longer intended to conceal meaning. The cross-over appeal of the original is maintained, enticing novice readers with its immersive dystopian atmosphere, while inviting informed readers to recognise layered references. The juxtaposition of socialist-era monuments, contemporary technological motifs, and global political imagery produces a collage-like narrative space in which multiple temporal layers intersect.
Ključne besede: Auto-Moto Ants, children’s dystopia, totalitarianism, Yugoslavia, graphic novel adaptation
Objavljeno v RUP: 11.09.2026; Ogledov: 461; Prenosov: 12
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7. Latent class analysis of student attitudes and performance in online mathematics assessments : a Technology Acceptance Model approachDaniel Doz, Motognon Wastalas d’Assise Dogbalou, Zevick Otieno Juma, Danilo Lewanski, 2026, izvirni znanstveni članek Opis: In recent years, many institutions have transitioned from traditional pen-and-paper mathematics examinations to online assessments. One such system gaining popularity is STACK, which provides students with immediate feedback and supports teaching, learning, and assessment. Although literature suggests students generally have positive attitudes towards STACK, the relationship between these attitudes and final examination performance remains underexplored. This study analysed responses from 115 Italian biotechnology undergraduates about their beliefs regarding STACK, collected before and after their mathematics examination. Using Latent Class Analysis, two distinct student groups emerged based on their attitudes. Class 1, which held more positive attitudes both before and after the exam, achieved higher final scores than Class 2. The Technology Acceptance Model helped interpret the findings, showing that perceived usefulness and ease of use influence attitudes. A significant sex effect was observed: males were predominantly in Class 1 and showed more positive attitudes, while females were more evenly distributed between both classes. Thus, while males showed more positive attitudes on average, this was due to their higher representation in the positive-attitude group rather than a direct comparison. These findings support the potential of STACK and highlight the importance of wider institutional adoption to familiarise students with online assessments.
Ključne besede: assessment, INVALSI, biotechnology, latent class analysis, mathematics, online, STACK, Technology Acceptance Model
Objavljeno v RUP: 10.09.2026; Ogledov: 443; Prenosov: 12
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8. Leveraging machine learning to predict academic success : a literature review and bibliometric trend analysisBor Bregant, Andreja Istenič, 2026, pregledni znanstveni članek Opis: This study synthesizes research on the use of machine learning (ML) to predict academic success through a three-scope approach. First, a systematic review of 33 review studies from Web of Science (WOS), Scopus, and Taylor & Francis identifies prevailing methods, levels of prediction, and recurrent gaps in the literature. The synthesis of 33 review studies reveals a consolidation around supervised learning approaches and prediction-focused frameworks, with recurring gaps related to real world implementation and pedagogical integration. Second, a qualitative synthesis of the 10 most cited WOS articles provides in-depth insight into influential algorithmic strategies, data sources, and emerging emphases on explainability, human-centered modeling, and early intervention. Third, a bibliometric analysis of 520 WOS articles maps publication trends, country-level productivity, keyword co-occurrence, citation patterns, and international collaboration networks. Results indicate growing publication activity between 2018 and 2025, with research thematically clustering around methodological foundations in educational data mining, model development and prediction strategies, and contextual applications primarily in higher education, with limited chronological differentiation across themes. China leads in publication volume, while major collaboration hubs are concentrated in Australia, India, and Saudi Arabia. Persistent challenges include inconsistent terminology, data heterogeneity, and limited real-world deployment of ML models.
Ključne besede: data mining, machine learning, academic success, education, systematic literature review, bibliometric analysis
Objavljeno v RUP: 08.09.2026; Ogledov: 401; Prenosov: 14
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9. Mobilisation of memory : intergenerational representation of the partisan struggle in Slovenian picturebooksBarbara Zorman, 2026, izvirni znanstveni članek Opis: The paper analyses Slovenian picturebooks intended for children up to ten years of age, representing the partisan movement. The analysis focuses on the construction of cultural memory and identity. Early partisan picturebooks drew on folklore texts by employing anonymous protagonists, the motifs of struggle against overwhelming enemies, as well as symbolic interactions with and assimilation into animals and vegetation. Their struggle symbolically positions the partisans in a liminal space between separation from a fascist-oppressed society and reintegration into a new, more just social order. Two intersecting discourses can be identified: commitment to anti-fascist resistance and pacifism. Children are sometimes depicted as child soldiers legitimising the partisan cause, but more often as witnesses of wartime suffering. In the 1960s, the theme of forgetting emerged, reflecting both the erosion of recognition of war victims and a constructive forgetting that facilitates reintegration into peacetime society.
Ključne besede: Branka Jurca, children's literature, cultural memory, Ela Peroci, mobilisation of memory, representation of war, Vida Brest
Objavljeno v RUP: 07.09.2026; Ogledov: 430; Prenosov: 11
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10. Kodifikacija etike v vzgoji in izobraževanju v SlovenijiKarolina Babič, Tomaž Grušovnik, 2026, izvirni znanstveni članek Opis: Avtorja v prispevku raziskujeta pojavnost in način kodifikacije etike v slovenskem izobraževalnem prostoru. Metodološki pristop temelji na kvalitativni analizi besedil, v okviru katere je bilo analiziranih 84 notranjih aktov, kodeksov etike in nekaterih normativnih predpisov na področju izobraževanja. Raziskava je pokazala, da poleg redkih kodeksov etike, eksplicitno poimenovanih s tem imenom, obstajajo tudi drugačni načini kodificiranja etike v šolskih dokumentih ter da je kodifikacija etike v izobraževanju večinoma oblikovana na način seznamov vrednot, katerih aplikacija je nadalje predpisana s seznamom podrobnejših navodil za ravnanje. Iz kodeksov etike, ki imajo pretežno takšno predpisovalno (preskriptivno) funkcijo, izhajajo določene težave, hkrati pa je takšna predpisovalna oblika kodeksov etike v nasprotju s konceptom avtonomije učitelja in izobraževalne stroke. Prispevek podaja tudi priporočila v smeri bolj procesnega pristopa, kjer je kot akter kodeksov etike prepoznan avtonomni subjekt in kot njegova ključna moč veščina kritičnega etiškega presojanja, kodeks etike pa ne nastopa kot seznam navodil za ravnanje, temveč prej kot vadnica za etiško delo.
Ključne besede: kodeks etike, kodifikacija etike, etika v izobraževanju, avtonomija, etiško presojanje
Objavljeno v RUP: 09.07.2026; Ogledov: 515; Prenosov: 12
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