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Knowledge dependencies in fuzzy information systems evaluation
Experience and research within the field of Information Systems Evaluation (ISE), has traditionally centered on providing tools and techniques for investment justification and appraisal, based upon explicit knowledge which encodes financial and other direct situational factors (such as accounting, costing and risk metrics). However, such approaches tend not to include additional causal interdependencies that are based upon tacit knowledge and are inherent within such a decision-making task. The authors show the results of applying a cognitive mapping approach, in the guise of a Fuzzy Cognitive Mapping (FCM) simulation, i.e. Fuzzy Information Systems Evaluation (F-ISE), in order to highlight the usefulness of applying such a technique. The authors highlight those contingent and necessary knowledge dependencies, in an exploratory sense, which relate to the investment appraisal decision-making task, in terms of the interplay between tacit and explicit knowledge, in this regard
Time Aware Knowledge Extraction for Microblog Summarization on Twitter
Microblogging services like Twitter and Facebook collect millions of user
generated content every moment about trending news, occurring events, and so
on. Nevertheless, it is really a nightmare to find information of interest
through the huge amount of available posts that are often noise and redundant.
In general, social media analytics services have caught increasing attention
from both side research and industry. Specifically, the dynamic context of
microblogging requires to manage not only meaning of information but also the
evolution of knowledge over the timeline. This work defines Time Aware
Knowledge Extraction (briefly TAKE) methodology that relies on temporal
extension of Fuzzy Formal Concept Analysis. In particular, a microblog
summarization algorithm has been defined filtering the concepts organized by
TAKE in a time-dependent hierarchy. The algorithm addresses topic-based
summarization on Twitter. Besides considering the timing of the concepts,
another distinguish feature of the proposed microblog summarization framework
is the possibility to have more or less detailed summary, according to the
user's needs, with good levels of quality and completeness as highlighted in
the experimental results.Comment: 33 pages, 10 figure
Alternative model for the administration and analysis of research-based assessments
Research-based assessments represent a valuable tool for both instructors and
researchers interested in improving undergraduate physics education. However,
the historical model for disseminating and propagating conceptual and
attitudinal assessments developed by the physics education research (PER)
community has not resulted in widespread adoption of these assessments within
the broader community of physics instructors. Within this historical model,
assessment developers create high quality, validated assessments, make them
available for a wide range of instructors to use, and provide minimal (if any)
support to assist with administration or analysis of the results. Here, we
present and discuss an alternative model for assessment dissemination, which is
characterized by centralized data collection and analysis. This model provides
a greater degree of support for both researchers and instructors in order to
more explicitly support adoption of research-based assessments. Specifically,
we describe our experiences developing a centralized, automated system for an
attitudinal assessment we previously created to examine students'
epistemologies and expectations about experimental physics. This system
provides a proof-of-concept that we use to discuss the advantages associated
with centralized administration and data collection for research-based
assessments in PER. We also discuss the challenges that we encountered while
developing, maintaining, and automating this system. Ultimately, we argue that
centralized administration and data collection for standardized assessments is
a viable and potentially advantageous alternative to the default model
characterized by decentralized administration and analysis. Moreover, with the
help of online administration and automation, this model can support the
long-term sustainability of centralized assessment systems.Comment: 7 pages, 1 figure, accepted in Phys. Rev. PE
Integrating Authentic Digital Resources in Support of Deep, Meaningful Learning
"Integrating Authentic Digital Resources in Support of Deep, Meaningful Learning," a white paper prepared for the Smithsonian by Interactive Educational Systems Design Inc., describes instructional approaches that apply to successful teaching with the Smithsonian Learning Lab.After defining its use of terms such as deeper learning and authentic resources the authors review the research basis of three broad approaches that support integrating digital resources into the classroom:Project-based learningGuided exploration of concepts and principlesGuided development of academic skillsThese approaches find practical application in the last section of the paper, which includes seven case studies. Examples range from first-grade science, to middle-school English (including ELL strategy) to a high-school American government class. In each example, students study and analyze digital resources, going on to apply their knowledge and deepen their understanding of a range of topics and problems
Computational Sociolinguistics: A Survey
Language is a social phenomenon and variation is inherent to its social
nature. Recently, there has been a surge of interest within the computational
linguistics (CL) community in the social dimension of language. In this article
we present a survey of the emerging field of "Computational Sociolinguistics"
that reflects this increased interest. We aim to provide a comprehensive
overview of CL research on sociolinguistic themes, featuring topics such as the
relation between language and social identity, language use in social
interaction and multilingual communication. Moreover, we demonstrate the
potential for synergy between the research communities involved, by showing how
the large-scale data-driven methods that are widely used in CL can complement
existing sociolinguistic studies, and how sociolinguistics can inform and
challenge the methods and assumptions employed in CL studies. We hope to convey
the possible benefits of a closer collaboration between the two communities and
conclude with a discussion of open challenges.Comment: To appear in Computational Linguistics. Accepted for publication:
18th February, 201
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