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End date: 2022 × Start date: 2020 × Start date: 2003 × DDC: 370 × Has files: Yes × Type: Text ×

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Now showing 1 - 10 of 25
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    Translating the Concept of Goal Setting into Practice: What ‘else’ Does It Require than a Goal Setting Tool?
    (Setúbal, Portugal : Science and Technology Publications, Lda, 2020) Kismihók, Gábor; Zhao, Catherine; Schippers, Michaéla; Mol, Stefan; Harrison, Scott; Shehata, Shady; Lane, H. Chad; Zvacek, Susan; Uhomoibhi, James
    This conceptual paper reviews the current status of goal setting in the area of technology enhanced learning and education. Besides a brief literature review, three current projects on goal setting are discussed. The paper shows that the main barriers for goal setting applications in education are not related to the technology, the available data or analytical methods, but rather the human factor. The most important bottlenecks are the lack of students’ goal setting skills and abilities, and the current curriculum design, which, especially in the observed higher education institutions, provides little support for goal setting interventions.
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    Towards Bacteria Counting in DI Water of Several Microliters or Growing Suspension Using Impedance Biochips
    (Basel : MDPI, 2020) Kiani, Mahdi; Tannert, Astrid; Du, Nan; Hübner, Uwe; Skorupa, Ilona; Bürger, Danilo; Zhao, Xianyue; Blaschke, Daniel; Rebohle, Lars; Cherkouk, Charaf; Neugebauer, Ute; Schmidt, Oliver G.; Schmidt, Heidemarie
    We counted bacterial cells of E. coli strain K12 in several-microliter DI water or in several-microliter PBS in the low optical density (OD) range (OD = 0.05–1.08) in contact with the surface of Si-based impedance biochips with ring electrodes by impedance measurements. The multiparameter fit of the impedance data allowed calibration of the impedance data with the concentration cb of the E. coli cells in the range of cb = 0.06 to 1.26 × 109 cells/mL. The results showed that for E. coli in DI water and in PBS, the modelled impedance parameters depend linearly on the concentration of cells in the range of cb = 0.06 to 1.26 × 109 cells/mL, whereas the OD, which was independently measured with a spectrophotometer, was only linearly dependent on the concentration of the E. coli cells in the range of cb = 0.06 to 0.50 × 109 cells/mL.
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    The Concept of Identifiability in ML Models
    (Setúbal : SciTePress - Science and Technology Publications, Lda., 2022) von Maltzan, Stephanie; Bastieri, Denis; Wills, Gary; Kacsuk, Péter; Chang, Victor
    Recent research indicates that the machine learning process can be reversed by adversarial attacks. These attacks can be used to derive personal information from the training. The supposedly anonymising machine learning process represents a process of pseudonymisation and is, therefore, subject to technical and organisational measures. Consequently, the unexamined belief in anonymisation as a guarantor for privacy cannot be easily upheld. It is, therefore, crucial to measure privacy through the lens of adversarial attacks and precisely distinguish what is meant by personal data and non-personal data and above all determine whether ML models represent pseudonyms from the training data.
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    Crowdsourcing Scholarly Discourse Annotations
    (New York, NY : ACM, 2021) Oelen, Allard; Stocker, Markus; Auer, Sören
    The number of scholarly publications grows steadily every year and it becomes harder to find, assess and compare scholarly knowledge effectively. Scholarly knowledge graphs have the potential to address these challenges. However, creating such graphs remains a complex task. We propose a method to crowdsource structured scholarly knowledge from paper authors with a web-based user interface supported by artificial intelligence. The interface enables authors to select key sentences for annotation. It integrates multiple machine learning algorithms to assist authors during the annotation, including class recommendation and key sentence highlighting. We envision that the interface is integrated in paper submission processes for which we define three main task requirements: The task has to be . We evaluated the interface with a user study in which participants were assigned the task to annotate one of their own articles. With the resulting data, we determined whether the participants were successfully able to perform the task. Furthermore, we evaluated the interface’s usability and the participant’s attitude towards the interface with a survey. The results suggest that sentence annotation is a feasible task for researchers and that they do not object to annotate their articles during the submission process.
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    OER Recommendations to Support Career Development
    (Piscataway, NJ : IEEE, 2020) Tavakoli, Mohammadreza; Faraji, Ali; Mol, Stefan T.; Kismihók, Gábor
    This Work in Progress Research paper departs from the recent, turbulent changes in global societies, forcing many citizens to re-skill themselves to (re)gain employment. Learners therefore need to be equipped with skills to be autonomous and strategic about their own skill development. Subsequently, high-quality, on-line, personalized educational content and services are also essential to serve this high demand for learning content. Open Educational Resources (OERs) have high potential to contribute to the mitigation of these problems, as they are available in a wide range of learning and occupational contexts globally. However, their applicability has been limited, due to low metadata quality and complex quality control. These issues resulted in a lack of personalised OER functions, like recommendation and search. Therefore, we suggest a novel, personalised OER recommendation method to match skill development targets with open learning content. This is done by: 1) using an OER quality prediction model based on metadata, OER properties, and content; 2) supporting learners to set individual skill targets based on actual labour market information, and 3) building a personalized OER recommender to help learners to master their skill targets. Accordingly, we built a prototype focusing on Data Science related jobs, and evaluated this prototype with 23 data scientists in different expertise levels. Pilot participants used our prototype for at least 30 minutes and commented on each of the recommended OERs. As a result, more than 400 recommendations were generated and 80.9% of the recommendations were reported as useful.
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    Audio Ontologies for Intangible Cultural Heritage
    (Bramhall, Stockport ; EasyChair Ltd., 2022-04-12) Tan, Mary Ann; Posthumus, Etienne; Sack, Harald
    Cultural heritage portals often contain intangible objects digitized as audio files. This paper presents and discusses the adaptation of existing audio ontologies intended for non-cultural heritage applications. The resulting alignment of the German Digital Library-Europeana Data Model (DDB-EDM) with Music Ontology (MO) and Audio Commons Ontology (ACO) is presented.
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    INSPIRE: A European training network to foster research and training in cardiovascular safety pharmacology
    (Amsterdam : Elsevier B.V., 2020) Guns, P.-J.D.; Guth, B.D.; Braam, S.; Kosmidis, G.; Matsa, E.; Delaunois, A.; Gryshkova, V.; Bernasconi, S.; Knot, H.J.; Shemesh, Y.; Chen, A.; Markert, M.; Fernández, M.A.; Lombardi, D.; Grandmont, C.; Cillero-Pastor, B.; Heeren, R.M.A.; Martinet, W.; Woolard, J.; Skinner, M.; Segers, V.F.M.; Franssen, C.; Van Craenenbroeck, E.M.; Volders, P.G.A.; Pauwelyn, T.; Braeken, D.; Yanez, P.; Correll, K.; Yang, X.; Prior, H.; Kismihók, G.; De Meyer, G.R.Y.; Valentin, J.-P.
    Safety pharmacology is an essential part of drug development aiming to identify, evaluate and investigate undesirable pharmacodynamic properties of a drug primarily prior to clinical trials. In particular, cardiovascular adverse drug reactions (ADR) have halted many drug development programs. Safety pharmacology has successfully implemented a screening strategy to detect cardiovascular liabilities, but there is room for further refinement. In this setting, we present the INSPIRE project, a European Training Network in safety pharmacology for Early Stage Researchers (ESRs), funded by the European Commission's H2020-MSCA-ITN programme. INSPIRE has recruited 15 ESR fellows that will conduct an individual PhD-research project for a period of 36 months. INSPIRE aims to be complementary to ongoing research initiatives. With this as a goal, an inventory of collaborative research initiatives in safety pharmacology was created and the ESR projects have been designed to be complementary to this roadmap. Overall, INSPIRE aims to improve cardiovascular safety evaluation, either by investigating technological innovations or by adding mechanistic insight in emerging safety concerns, as observed in the field of cardio-oncology. Finally, in addition to its hands-on research pillar, INSPIRE will organize a number of summer schools and workshops that will be open to the wider community as well. In summary, INSPIRE aims to foster both research and training in safety pharmacology and hopes to inspire the future generation of safety scientists.
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    Combining statistical and machine learning methods to explore German students’ attitudes towards ICT in PISA
    (London : Taylor & Francis, 2021) Lezhnina, Olga; Kismihók, Gábor
    In our age of big data and growing computational power, versatility in data analysis is important. This study presents a flexible way to combine statistics and machine learning for data analysis of a large-scale educational survey. The authors used statistical and machine learning methods to explore German students’ attitudes towards information and communication technology (ICT) in relation to mathematical and scientific literacy measured by the Programme for International Student Assessment (PISA) in 2015 and 2018. Implementations of the random forest (RF) algorithm were applied to impute missing data and to predict students’ proficiency levels in mathematics and science. Hierarchical linear models (HLM) were built to explore relationships between attitudes towards ICT and mathematical and scientific literacy with the focus on the nested structure of the data. ICT autonomy was an important variable in RF models, and associations between this attitude and literacy scores in HLM were significant and positive, while for other ICT attitudes the associations were negative (ICT in social interaction) or non-significant (ICT competence and ICT interest). The need for further research on ICT autonomy is discussed, and benefits of combining statistical and machine learning approaches are outlined.
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    Opening up knowledge systems for better responses to global environmental change
    (Amsterdam [u.a.] : Elsevier, 2013) Cornell, S.; Berkhout, F.; Tuinstra, W.; Tàbara, J.D.; Jäger, J.; Chabay, I.; de Wit, B.; Langlais, R.; Mills, D.; Moll, P.; Otto, I.M.; Petersen, A.; Pohl, C.; van Kerkhoff, L.
    Linking knowledge with action for effective societal responses to persistent problems of unsustainability requires transformed, more open knowledge systems. Drawing on a broad range of academic and practitioner experience, we outline a vision for the coordination and organization of knowledge systems that are better suited to the complex challenges of sustainability than the ones currently in place. This transformation includes inter alia: societal agenda setting, collective problem framing, a plurality of perspectives, integrative research processes, new norms for handling dissent and controversy, better treatment of uncertainty and of diversity of values, extended peer review, broader and more transparent metrics for evaluation, effective dialog processes, and stakeholder participation. We set out institutional and individual roadmaps for achieving this vision, calling for well-designed, properly resourced, longitudinal, international learning programs.
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    Correcting a fundamental error in greenhouse gas accounting related to bioenergy
    (Amsterdam [u.a.] : Elsevier, 2012) Haberl, H.; Sprinz, D.; Bonazountas, M.; Cocco, P.; Desaubies, Y.; Henze, M.; Hertel, O.; Johnson, R.K.; Kastrup, U.; Laconte, P.; Lange, E.; Novak, P.; Paavola, J.; Reenberg, A.; van den Hove, S.; Vermeire, T.; Wadhams, P.; Searchinger, T.
    Many international policies encourage a switch from fossil fuels to bioenergy based on the premise that its use would not result in carbon accumulation in the atmosphere. Frequently cited bioenergy goals would at least double the present global human use of plant material, the production of which already requires the dedication of roughly 75% of vegetated lands and more than 70% of water withdrawals. However, burning biomass for energy provision increases the amount of carbon in the air just like burning coal, oil or gas if harvesting the biomass decreases the amount of carbon stored in plants and soils, or reduces carbon sequestration. Neglecting this fact results in an accounting error that could be corrected by considering that only the use of 'additional biomass' - biomass from additional plant growth or biomass that would decompose rapidly if not used for bioenergy - can reduce carbon emissions. Failure to correct this accounting flaw will likely have substantial adverse consequences. The article presents recommendations for correcting greenhouse gas accounts related to bioenergy.