Opin vísindi
Opin vísindi er varðveislusafn vísindaefnis og doktorsritgerða í opnum aðgangi á vegum íslenskra háskóla og Landsbókasafns Íslands - Háskólabókasafns.
Opinn aðgangur að rannsóknaniðurstöðum er í samræmi við 10. gr. laga nr. 3/2003 um opinberan stuðning við vísindarannsóknir sem og kröfur innlendra og erlendra rannsóknasjóða. Markmiðið með opnum aðgangi er að niðurstöður rannsókna séu aðgengilegar sem flestum óhindrað og án endurgjalds á rafrænu formi. Vistun í varðveislusafninu er varanleg og ætlað að tryggja aðgang að vísindaefni íslenskra háskóla í opnum aðgangi um ókomna tíð. Varðveislusafnið Opin vísindi er tengt við rannsóknagáttina IRIS og rannsóknaniðurstöður í opnum aðgangi sem eru skráðar í IRIS eru um leið vistaðar og gerðar aðgengilegar til framtíðar í varðveislusafninu. Með því að safna þessu efni saman í eitt safn verður aðgangur að því einfaldur og þægilegur fyrir alla sem vilja kynna sér það og geta þannig notið þess öfluga vísindastarfs sem fram fer í háskólum landsins.
Varðveislusafnið er OpenAIRE / OpenAIREplus samhæft og samrýmist kröfum sem gerðar eru um birtingu rannsóknaniðurstaðna úr verkefnum sem styrkt eru úr evrópsku rannsóknaáætlununum FP7 og H2020.
Varðveislusafnið notar opna hugbúnaðinn DSpace.
Opinn aðgangur að rannsóknaniðurstöðum er í samræmi við 10. gr. laga nr. 3/2003 um opinberan stuðning við vísindarannsóknir sem og kröfur innlendra og erlendra rannsóknasjóða. Markmiðið með opnum aðgangi er að niðurstöður rannsókna séu aðgengilegar sem flestum óhindrað og án endurgjalds á rafrænu formi. Vistun í varðveislusafninu er varanleg og ætlað að tryggja aðgang að vísindaefni íslenskra háskóla í opnum aðgangi um ókomna tíð. Varðveislusafnið Opin vísindi er tengt við rannsóknagáttina IRIS og rannsóknaniðurstöður í opnum aðgangi sem eru skráðar í IRIS eru um leið vistaðar og gerðar aðgengilegar til framtíðar í varðveislusafninu. Með því að safna þessu efni saman í eitt safn verður aðgangur að því einfaldur og þægilegur fyrir alla sem vilja kynna sér það og geta þannig notið þess öfluga vísindastarfs sem fram fer í háskólum landsins.
Varðveislusafnið er OpenAIRE / OpenAIREplus samhæft og samrýmist kröfum sem gerðar eru um birtingu rannsóknaniðurstaðna úr verkefnum sem styrkt eru úr evrópsku rannsóknaáætlununum FP7 og H2020.
Varðveislusafnið notar opna hugbúnaðinn DSpace.
Nýlega bætt við
Motivations, materials, and means : Teachers’ attitudes to literature use in Nordic lower secondary schools
(2026-05-18) Nissen, Anna; Hansen, Thomas Illum; Höglund, Heidi; Magnusson, Camilla Gudmundsdatter; Svanbjörnsdóttir, Birna María B.; Faculty of Education
This study aims to reveal how Nordic lower secondary language arts teachers motivate and describe their literature instruction. It investigates what motivations for literature instruction teachers appeal to, what literary materials they use, and by what instructional means and methods they teach literature. An online questionnaire was completed by 701 teachers from a random sample of schools across the Nordic countries. Analyses showed that teachers valued using literature for various reasons, although using literature to develop students’ reading comprehension and linguistic skills were prioritised. Across all five countries, the reading of narrative texts was favoured. However, genre preferences varied by country: contemporary short stories were significantly more frequently read in Norway, Denmark, and Finland than in Sweden and Iceland, while young adult novels were significantly more commonly read in Denmark than in the other four countries. The most common instructional practices included letting students answer text-based questions and discussing literary texts. A key finding of the study is that literature reading in Nordic schools seems to be a matter of reading instruction rather than literature instruction. Thus, while different types of skills are emphasised, less attention is given to literary reading experiences.
Artificial Intelligence in Regulated Domains : Lessons from Sleep Medicine
(2026-06-08) Harðarson, Emil; Óskarsdóttir, María; Islind, Anna Sigríður; Arnardóttir, Erna Sif; Department of Computer Science
This thesis investigates how artificial intelligence (AI) and machine learning (ML) can be integrated into the regulated workflow of polysomnography-based sleep architecture analysis while ensuring outcomes are understandable and defensible. Rather than focusing solely on sleep-stage classification accuracy, the thesis argues that different parts of the workflow require different combinations of machine learning, explicit rules, uncertainty representation, and human oversight. Across six papers, the thesis develops AI methods for sleep analysis and, through simulation and empirical studies, examines how their outputs behave within the clinical workflow. These include an LLM-guided neural architecture search framework for autonomously developing multimodal sleep staging models; a rulebased automatic sleep staging system derived from clinical scoring rules, capable of producing auditable justifications in clinical language; simulation and empirical studies of how sleep staging error propagates to downstream sleep metrics (such as total sleep time and time spent in deep sleep); and methods for estimating sleep metrics without performing sleep stage classification. The results show that strong epoch-level agreement does not translate uniformly into reliable downstream sleep metrics and that some sleep metrics vary substantially across expert scorers. They further show that preserving probabilistic uncertainty can improve sleep metric estimation, that direct sleep metric estimation can be competitive with conventional hypnogram-based pipelines, and that parts of the formal scoring workflow can be translated into executable and auditable procedures. Interviews with sleep professionals also show that effective AI decision support requires interactivity, familiar clinical language, and system designs that preserve the human expert’s accountability. These findings are synthesized in the MARBLE framework (Multiple Abstraction-Level Rule-Based Learning Engine), which treats AI decision support in sleep medicine as the coordinated use of rule-based and pattern-based methods across multiple abstraction levels, from raw physiological signals and micro-events to sleep stages, sleep metrics, and higher-level interpretation. The thesis concludes that AI integration in clinical sleep analysis should not be framed as the automation of one prediction task, but as the careful design of decision support across a rule-governed workflow. Although developed in sleep medicine, this may also have implications for AI decision support in other regulated domains.
Exploring the Links Between IT Tools, Management Accounting Practices and SME Performance : Perceptions of CFOs in Ireland
(2022) Cleary, Peter; Quinn, Martin; Rikhardsson, Pall; Batt, Catherine
Notwithstanding its sectoral importance to wealth creation and employment, research on the role of management accounting in small and medium-sized enterprises (SMEs) is limited. This paper first examines the perceptions of chief financial officers (CFOs) on the impact of information technology (IT) tools on management accounting practices (costing, budgeting, and performance management). Secondly, it examines how CFOs perceive these management accounting practices are affecting the performance of their SMEs. The study is based on a survey of CFOs in Irish SMEs. We propose a conceptual model of these relationships. We use partial least squares (PLS) to analyse the data from the 109 participating CFOs. The results show a significant positive relationship between IT tools and all three management accounting practices, along with significant partial support for how CFOs perceive management accounting practices impacting the performance of their SMEs.
COVID-19 -related emotional impact and experiences, Family Income, and Sleep Hygiene of Early Appalachian Adolescents
(2024) Layman, H.; Lilly, CL.; Dino, G.; Jarrett, T.; Richel, C.; Kristjansson, AL.; Department of Psychology
Adolescent Caffeine Use and Problematic School Behavior: A Longitudinal Analyses of Student Survey Data and Teacher Observations
(2024-12) Kristjansson, A.L.; Lilly, C.L.; Mann, M.J.; Smith, M.L.; Kogan, S.M.; Layman, H.M.; James, J.E.; Department of Psychology
Introduction: Caffeine is a psychostimulant possessing arousal, motor activation, and reinforcing properties, which is consumed daily by most adolescents aged 12–19 years. Although current understanding of the implications of adolescent caffeine consumption for school behaviors remains incomplete, studies have shown that in addition to acute effects of the drug, in common with other habit-forming psychoactive substances, regular use leads to physical dependence, evidenced by recurring negative withdrawal symptoms. Methods: Employing two waves of longitudinal data, we tested the prospective association between daily caffeine use and homeroom teacher-observed self-control and problem behavior in a sample of middle-school students in 20 schools in West Virginia in the United States. Caffeine was operationalized with two dichotomized variables, daily consumption of <100 mg, and daily consumption of >100 mg, versus no daily use. Gender, mother's education, family financial status, social support by primary caregiver and adults in school, and school climate, were applied as covariates in linear mixed models. Results: Daily caffeine use of >100 mg was robustly and inversely associated with self-control and positively associated with problem behavior. Conclusions: Caffeine consumption and associated withdrawal symptoms may be an important factor in problematic school behavior among adolescents. Recent advent of highly concentrated caffeine products (e.g., caffeine “shots”) commonly marketed directly at youth, should give rise to concerns including consideration about limiting caffeine consumption among children and youth.
Flokkar í Opnum vísindum
Veldu flokk til að skoða.
- University of Iceland
- University of Akureyri
- Bifröst University
- Hólar University College
- IRIS
- Agricultural University of Iceland
- National and University Library of Iceland
- Iceland University of the Arts