1,721,153 research outputs found

    In conversation: Bannert, Molenaar, & Winne - Multiple perspectives on researching and supporting self-regulated learning via analytics

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    Item does not contain fulltextUnderstanding processes in self-regulated learning (SRL) and tailoring appropriate instructional support to help students become more productive self-regulated learners has been on the agenda of SRL researchers for decades. New data modalities and analytic methods are becoming increasingly available to augment existing methodologies, enhance SRL measurement, test theoretical assumptions about SRL and inform future instructional support. Though promising, this research direction is yet to be fully explored. To learn more about how multimodal learner data and analytic methods can be used to improve research and support for SRL, we invited for a conversation Professors Maria Bannert, Inge Molenaar, and Phil Winne, three prominent scholars who have been extensively researching SRL over the past few decades. The conversation included two parts (1) Studying SRL via Analytics and (2) Supporting SRL via Analytics. The discussion identified several major areas for future research, including integrating multiple data channels in a meaningful way to improve theoretical understanding of SRL, and supporting learners by offering them options on what to do next, rather than by saying that they missed an opportunity to engage in a particular SRL process. Following the polyphonic research methodology, the lead authors and the interviewed SRL scholars co-authored this chapter. A podcast of the conversation is available at https://spotifyanchor-web.app.link/e/NwvHdDh3MMb

    Formalizing interactive staged feature model configuration

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    Feature modeling an attractive technique for capturing commonality as well as variability within an application domain for generative programming and software product line engineering. Feature models symbolize an overarching representation of the possible application configuration space, and can hence be customized based on specific domain requirements and stakeholder goals. Most interactive or semiautomated feature model customization processes neglect the need to have a holistic approach towards the integration and satisfaction of the stakeholder's soft and hard constraints, and the application-domain integrity constraints. In this paper, we will show how the structure and constraints of a feature model can be modeled uniformly through Propositional Logic extended with concrete domains, called P(N). Furthermore, we formalize the representation of soft constraints in fuzzy P(N) and explain how semiautomated feature model customization is performed in this setting. The model configuration derivation process that we propose respects the soundness and completeness properties. © 2011 John Wiley & Sons, Ltd

    Configuring software product line feature models based on stakeholders' soft and hard requirements

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    Feature modeling is a technique for capturing commonality and variability. Feature models symbolize a representation of the possible application configuration space, and can be customized based on specific domain requirements and stakeholder goals. Most feature model configuration processes neglect the need to have a holistic approach towards the integration and satisfaction of the stakeholder's soft and hard constraints, and the application-domain integrity constraints. In this paper, we will show how the structure and constraints of a feature model can be modeled uniformly through Propositional Logic extended with concrete domains, called . Furthermore, we formalize the representation of soft constraints in fuzzy and explain how semi-automated feature model configuration is performed. The model configuration derivation process that we propose respects the soundness and completeness properties. © 2010 Springer-Verlag Berlin Heidelberg

    Improving business process models using observed behavior

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    Process-aware information systems (PAISs) can be configured using a reference process model, which is typically obtained via expert interviews. Over time, however, contextual factors and system requirements may cause the operational process to start deviating from this reference model. While a reference model should ideally be updated to remain aligned with such changes, this is a costly and often neglected activity. We present a new process mining technique that automatically improves the reference model on the basis of the observed behavior as recorded in the event logs of a PAIS. We discuss how to balance the four basic quality dimensions for process mining (fitness, precision, simplicity and generalization) and a new dimension, namely the structural similarity between the reference model and the discovered model. We demonstrate the applicability of this technique using a real-life scenario from a Dutch municipality

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis

    Dispelling the Myths Behind First-author Citation Counts

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    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods

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