Ponedeljkov seminar računalništva in informatike - Arhiv
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četrtek, 26. marec 2026 Karolina TRAJKOVSKA in Michelle FERNANDO: Beyond Rote Memorisation: The Impact of AI-Generated Visuals and Personalised Mnemonics on Vocabulary Retention
V ponedeljek, 30. marca 2026, bo ob 16:00 uri izvedeno
predavanje v okviru PONEDELJKOVEGA SEMINARJA RAČUNALNIŠTVA IN INFORMATIKE
Oddelkov za Informacijske znanosti in tehnologije UP FAMNIT in UP IAM.
ČAS/PROSTOR: 30. marec 2026 ob 16.00 v FAMNIT-VP3.
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PREDAVATELJICI: Karolina TRAJKOVSKA in Michelle FERNANDO
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Karolina Trajkovska is a PhD student and researcher at UP FAMNIT. She is a young researcher in HCI/UX, contributing to research on how people interact with digital systems, especially using modern techniques like eye-tracking and augmented reality.
Michelle Fernando is a PhD student and teaching assistant at UP FAMNIT, where she works with the HICUP Lab. She received the B.Sc. (Hons) degree in computer science from the University of Colombo, Sri Lanka. Her research focuses on human-computer interaction, extended reality, and human motion analysis in the context of sports training and skill acquisition.
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NASLOV: Beyond Rote Memorisation: The Impact of AI-Generated Visuals and Personalised Mnemonics on Vocabulary Retention
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POVZETEK:
Mnemonics, such as the keyword method, are effective for vocabulary learning, where learners form a mental image cues linking a foreign word to a phonetically similar word in a familiar language. However, many avoid mnemonics because generating these cues is cognitively demanding. The first aim of this study is to examine whether non-personalised (pre-generated) cues can decrease cognitive effort while maintaining performance compared with personalised (self-generated) cues. The second aim is to compare externalised cues in image and video formats, using novel text-to-images/video generation. We built an interactive tool and ran a mixed-design study with 32 participants, manipulating PERSONALISATION (personalised vs non-personalised mnemonic cues) and MODALITY (images vs videos). The analysis is presented in two parts:
Part I (presented by Karolina Trajkovska):
Performance & Efficiency. Personalised cues produced significantly better immediate and delayed recall but took more time and increased perceived workload, whereas non-personalised cues were more efficient in recall per unit time. Despite this, participants preferred personalised cues, suggesting subjective benefits beyond performance. Finally, modality showed no significant differences, though images had a modest advantage.
Part II (presented by Michelle Fernando):
Biometric data collection & Emotional Engagement. We detail the collection and analysis of biometric data to evaluate physiological correlates of the "personalisation effect." This explores how self-generation influences emotional arousal and cognitive investment compared to passive consumption of cues. The statistical analysis shows a significant main effect of PERSONALISATION on emotional engagement.
Seminar bo potekal v angleškem jeziku v predavalnici FAMNIT-VP3 s pričetkom ob 16:00 uri.
Vabljeni!
ponedeljek, 23. marec 2026 Karolina TRAJKOVSKA: Can Immersion Protect us From Distraction? The Impact of Real-World Distractions on Learning in Augmented Reality
V ponedeljek, 23. marca 2026, bo ob 16:00 uri izvedeno
predavanje v okviru PONEDELJKOVEGA SEMINARJA RAČUNALNIŠTVA IN INFORMATIKE
Oddelkov za Informacijske znanosti in tehnologije UP FAMNIT in UP IAM.
ČAS/PROSTOR: 23. marec 2026 ob 16.00 v FAMNIT-VP3.
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PREDAVATELJICA: Karolina TRAJKOVSKA
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Karolina Trajkovska is a PhD student and researcher at UP FAMNIT. She is a young researcher in HCI/UX, contributing to research on how people interact with digital systems, especially using modern techniques like eye-tracking and augmented reality.
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NASLOV: Can Immersion Protect us From Distraction? The Impact of Real-World Distractions on Learning in Augmented Reality
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POVZETEK:
While many digital distractions can be managed, real-world interruptions, such as phone calls, notifications, and office noise, are harder to control and can harm productivity, well-being, and learning. Mixed reality systems like Augmented Reality (AR) are often described as immersive—a property which might protect users from such disruptions. We tested this assumption by comparing a head-mounted AR interface that overlays digital annotations on physical objects with a traditional flat screen during vocabulary learning under common office distractions. In a user study (n = 32), AR users reported feeling less distracted and recalled less task-irrelevant information, but their learning performance did not improve. Instead, distraction-related performance decline was greater in AR. Physiological and self-report measures showed no reduction in effort or workload, and participants with higher auditory distractibility did not benefit. Overall, AR annotation alone may not sufficiently shield learners from real-world distractions, motivating new design approaches.
Seminar bo potekal v angleškem jeziku v predavalnici FAMNIT-VP3 s pričetkom ob 16:00 uri.
Vabljeni!
ponedeljek, 16. marec 2026 Daniil Baldouski: Towards a closed-loop wood value chain: multi-objective optimization and real-world benchmarking
V ponedeljek, 16. marca 2026, bo ob 16:00 uri izvedeno
predavanje v okviru PONEDELJKOVEGA SEMINARJA RAČUNALNIŠTVA IN INFORMATIKE
Oddelkov za Informacijske znanosti in tehnologije UP FAMNIT in UP IAM.
ČAS/PROSTOR: 16. marec 2026 ob 16.00 v FAMNIT-VP3.
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PREDAVATELJ: Daniil BALDOUSKI
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Daniil Baldouski is a fourth-year PhD student of Computer Science at UP FAMNIT.
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NASLOV: Towards a closed-loop wood value chain: multi-objective optimization and real-world benchmarking
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POVZETEK:
This work addresses the problem of designing closed-loop supply chain (CLSC) networks where production residuals and end-of-life products are reintegrated into the production cycle. A multi-objective mixed-integer linear programming (MILP) model is proposed that simultaneously minimizes economic costs and environmental impact. The model supports multiple echelons, multiple resource commodities, and resource transformation through pre-defined recipes, enabling the reuse of production residuals within the network wherever possible. A systematic benchmark generation methodology for CLSC optimization models is also introduced. The methodology supports controlled variation of network spatial structure through multiple location sampling methods and supply chain topology through alternative recipe scenarios. Real-world data from the Slovenian wood value chain is used to generate a benchmark dataset across different scales and configurations. Computational experiments show that small and medium instances are solved to optimality within reasonable time limits, while large instances present computational challenges depending on spatial configuration and supply chain complexity. The results also reveal an asymmetric trade-off between cost and environmental impact under different carbon pricing scenarios, where modest cost increases can lead to significant environmental benefits.
Seminar bo potekal v angleškem jeziku v predavalnici FAMNIT-VP3 s pričetkom ob 16:00 uri.
Vabljeni!






