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1.
The cognitive aspect of interactive learning and teaching in visual arts education
Zlata Tomljenović, 2020, original scientific article

Abstract: The task of contemporary visual arts education is to enable quality interaction among all subjects of the teaching process, through which the students are encouraged to think, imagine, and develop higherorder cognitive activities. The objective of this empirical research study was to verify the differences in the results of students in the control and experimental groups (n=285) regarding their knowledge and understanding of visual arts content. Analysis of the results shows that the students in EG showed significantly better results compared to the students in CG, which means that the interactive model of learning and teaching positively influenced the students' understanding of visual arts content
Keywords: nteractive approach to learning and teaching, visual arts, cognitive abilities, creative thinking, critical thinking
Published in DKUM: 19.06.2025; Views: 0; Downloads: 0
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2.
Learning environment variables and the efficacy of student learning in secondary school in Abak local government, Akwa Ibom State
Abisola Oladeni Sakirudeen, Ekanem Uwe, 2020, original scientific article

Abstract: Four research questions and four null hypotheses were formulated to guide the study. A simple random sampling technique was used in selecting 34 respondents from each 6 schools, with a sample size of 204 was selected from the population of 1,518. The instrument titled LEVSLEQ was used to elicit response from the respondent. The reliability of the research instrument yielded a co-efficient of 0.82. The data was analyzed using dependent t-test and was tested at .05 level of significance. The findings indicated that environmental variable studied influence students' learning effectiveness.
Keywords: learning, environment, learning effectiveness, Students’, variables
Published in DKUM: 19.06.2025; Views: 0; Downloads: 0
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3.
The impact of online learning on student motivation in science and biology classes
Mila Bulić, Ines Blaževič, 2020, original scientific article

Abstract: The research aimed to check for difference in learning motivation between students learning online and students participating in modern classroom instruction. The study participants included students attending grades 5 to 8, divided into experimental (online classes) and control groups based on pre-testing. The results show that there is no statistically significant difference in motivation between the tested sub-samples. Student motivation for learning natural sciences declines with their years of schooling, but this is not statistically significant. It can be concluded that online teaching of Science and Biology as a learning tool can be as motivating as modern teaching using active classroom methods.
Keywords: class motivation, e-learning, Moodle, natural sciences, primary school
Published in DKUM: 19.06.2025; Views: 0; Downloads: 0
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4.
Synergy of blockchain technology and data mining techniques for anomaly detection
Aida Kamišalić Latifić, Renata Kovačević, Iztok Fister, 2021, review article

Abstract: Blockchain and Data Mining are not simply buzzwords, but rather concepts that are playing an important role in the modern Information Technology (IT) revolution. Blockchain has recently been popularized by the rise of cryptocurrencies, while data mining has already been present in IT for many decades. Data stored in a blockchain can also be considered to be big data, whereas data mining methods can be applied to extract knowledge hidden in the blockchain. In a nutshell, this paper presents the interplay of these two research areas. In this paper, we surveyed approaches for the data mining of blockchain data, yet show several real-world applications. Special attention was paid to anomaly detection and fraud detection, which were identified as the most prolific applications of applying data mining methods on blockchain data. The paper concludes with challenges for future investigations of this research area.
Keywords: anomaly detection, blockchain, distributed ledger, data mining, machine learning
Published in DKUM: 16.06.2025; Views: 0; Downloads: 0
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5.
E-learning materials for the Slovene language in elementary schools (6th-9th grade)
Alenka Valh Lopert, Mihaela Koletnik, 2019, original scientific article

Abstract: The theoretical part of the paper presents the project Slovenščina na dlani (lovene in e al o or and) which is intended for the establishment of an interactive learning environment for the Slovene language (as mother tongue) in elementary and secondary schools. In this paper we limit the research to elementary school. In the empirical section, we focus on freely available e-learning materials for the Slovene language from the 6th to the 9th grade of elementary school and present the results of an analysis of 10,118 tasks according to their types. The findings indicate an unbalanced representation of different types of tasks, with short answer types in the majority, the task type that is least popular among students. By introducing the most advanced linguistic technology into learning processes, we try to overcome the limitations of existing e-resources for learning the Slovene language.
Keywords: Slovene language, language study and teaching, native language, elementary education, learning resources, projects, mother tongue, elementary school, elearning resources
Published in DKUM: 10.06.2025; Views: 0; Downloads: 0
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6.
Informal learning among teenagers through video games : a qualitative analysis of experiences, game modes and didactic benefits
Milan Matijević, Tomislav Topolovčan, 2019, original scientific article

Abstract: The paper analyzes the positive effects of video games on teen development and on teenagers' informal learning. The participants in the research were teenagers. The analysis and interpretation of games and explanations of their pedagogical merit indicate that players recognize their value for informal learning. Latent characteristics of video games include positive elemests such as taking responsibility, teamwork, sense of belonging, creativity, multiculturalism, personal virtues and values, emotion management, learning new information and skills, motor skills development and professional orientation. In that respect, it is possible to conclude that gaming may help in the development of certain abilities important for informal as well as formal learning in today's digital age.
Keywords: digital media, informal learning, teenagers, video games, a qualitative analysis
Published in DKUM: 10.06.2025; Views: 0; Downloads: 0
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7.
High-performance deployment operational Data analytics of pre-trained multi-label classification architectures with differential-evolution-based hyperparameter optimization (AutoDEHypO)
Teo Prica, Aleš Zamuda, 2025, original scientific article

Abstract: This article presents a high-performance-computing differential-evolution-based hyperparameter optimization automated workflow (AutoDEHypO), which is deployed on a petascale supercomputer and utilizes multiple GPUs to execute a specialized fitness function for machine learning (ML). The workflow is designed for operational analytics of energy efficiency. In this differential evolution (DE) optimization use case, we analyze how energy efficiently the DE algorithm performs with different DE strategies and ML models. The workflow analysis considers key factors such as DE strategies and automated use case configurations, such as an ML model architecture and dataset, while monitoring both the achieved accuracy and the utilization of computing resources, such as the elapsed time and consumed energy. While the efficiency of a chosen DE strategy is assessed based on a multi-label supervised ML accuracy, operational data about the consumption of resources of individual completed jobs obtained from a Slurm database are reported. To demonstrate the impact on energy efficiency, using our analysis workflow, we visualize the obtained operational data and aggregate them with statistical tests that compare and group the energy efficiency of the DE strategies applied in the ML models.
Keywords: high-performance computing, operational data analytics, energy efficiency, machine learning, AutoML, differential avolution, optimization
Published in DKUM: 29.05.2025; Views: 0; Downloads: 2
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8.
Artificial intelligence in employee learning process : insights from Generation Z
Branka Zolak Poljašević, Simona Šarotar Žižek, Ana Marija Gričnik, 2024, original scientific article

Abstract: Artificial intelligence, as a field of computer science focused on developing technologies that simulate intelligent behaviours and human cognitive functions, undoubtedly has huge potential to transform all business activities, including the process of employee learning. However, different generations have varying attitudes toward the rapid advancement of technology and the increasing possibilities offered by artificial intelligence. The general purpose of this research is to gain insights into the attitudes of Generation Z regarding the use of AI in the context of the employee learning process. Empirical research was conducted on a sample of 264 respondents from Slovenia and Bosnia and Herzegovina. In addition to descriptive statistics, Cronbach's alpha, Shapiro-Wilk, and Mann-Whitney tests were used to test hypotheses. Generally, the research findings indicate that the upcoming generation of the workforce considers artificial intelligence a significant factor in improving the employee learning process. The study contributes to human resource management literature because it brings new insights into Generation Z attitudes, whose participation in the active workforce will significantly increase in the coming years.
Keywords: learning process, Artificial Intelligence, employees, generation Z, sociodemographic characteristic
Published in DKUM: 27.05.2025; Views: 0; Downloads: 4
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9.
Sprachspiele als Motivationsfaktor im DaF-Unterricht mit jugendlichen und jungen Erwachsenen : Einsatzmöglichkeiten von Sprachelementspielen im Wortschatzerwerb
Brigita Kacjan, 2007, doctoral dissertation

Abstract: Ausgehend von einem interdisziplinären Studium eng miteinander verwobener wissenschaftlicher Disziplinen wird in der vorliegenden Dissertation theoretisch untersucht und belegt, wie der Wortschatzerwerb bzw. das Wortschatzlemen bei Jugendlichen und jungen Erwachsenen verläuft und wie Sprachelementspiele sinnvoll in diesen Prozess integriert werden können. Die so eruierten Paradigmen bilden die Grundlage fUr die Entwicklung einer Sprachspieltypologie, die sich speziell mit dem institutionellen Wortschatzerwerb hei Jugendlichen und jungen Erwachsenen beschäftigt, Anhand einer empirischen Fallstudie wird die Effizienz einiger ausgewählter Sprachelementspiele in der Praxis mit jugendlichen Deutschlernem überprüft. Vor dem Hintergrund der theoretischen und empirischen Erkenntnisse werden die aufgestellten Hypothesen im Bezug auf den motivationalen Charakter von Sprachspielen bzw. Sprachelementspielen auf ihre Gilltigkeit überprüft. Schließlich werden noch ein Fragenkatalog und die entwickelte Sprachspieltypologie als Werkzeuge angeboten, die es einer DaF-Lehrkraft ermöglichen, Sprachelementspiele sinnvoll und zielgerichtet in ihrem DaF-Unterricht mit Jugendlichen und jungen Erwachsenen einzusetzen. Dies alles wird durch die genau beschriebene, erklärte und begründete Schrittabfolge des Wortschatzerwerbs, den ausgearbeiteten Fragenkatalog und die entwickelte Sprachspieltypologie ermöglicht.
Keywords: German, foreign languages, didactics, vocabulary, language games, motivation, cognition, learning, adolescents, dissertations
Published in DKUM: 27.05.2025; Views: 0; Downloads: 2
.pdf Full text (9,70 MB)

10.
Weakly-supervised multilingual medical NER for symptom extraction for low-resource languages
Rigon Sallauka, Umut Arioz, Matej Rojc, Izidor Mlakar, 2025, original scientific article

Abstract: Patient-reported health data, especially patient-reported outcomes measures, are vital for improving clinical care but are often limited by memory bias, cognitive load, and inflexible questionnaires. Patients prefer conversational symptom reporting, highlighting the need for robust methods in symptom extraction and conversational intelligence. This study presents a weakly-supervised pipeline for training and evaluating medical Named Entity Recognition (NER) models across eight languages, with a focus on low-resource settings. A merged English medical corpus, annotated using the Stanza i2b2 model, was translated into German, Greek, Spanish, Italian, Portuguese, Polish, and Slovenian, preserving the entity annotations medical problems, diagnostic tests, and treatments. Data augmentation addressed the class imbalance, and the fine-tuned BERT-based models outperformed baselines consistently. The English model achieved the highest F1 score (80.07%), followed by German (78.70%), Spanish (77.61%), Portuguese (77.21%), Slovenian (75.72%), Italian (75.60%), Polish (75.56%), and Greek (69.10%). Compared to the existing baselines, our models demonstrated notable performance gains, particularly in English, Spanish, and Italian. This research underscores the feasibility and effectiveness of weakly-supervised multilingual approaches for medical entity extraction, contributing to improved information access in clinical narratives—especially in under-resourced languages.
Keywords: low-resource languages, machine translation, medical entity extraction, NER, NLP, patient-reported outcomes, weakly-supervised learning
Published in DKUM: 19.05.2025; Views: 0; Downloads: 2
.pdf Full text (338,94 KB)

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