1,720,989 research outputs found
Ontology-Based Context Modelling for Designing a Context-Aware Calculator
Full text linkThis paper reports on the research conducted by a team from the
France-Quebec research project TEEC, and its advances. This team is responsible
for modelling and designing of a context gap calculator, the MazCalc. The
MazCalc is a computer artifact aimed at measuring the effects of two distinct
context with the same object of study. In a Context-Based Teaching project such
as the one presented in this paper: Context Modelling is essential in identifying
the context parameters needed to include in the design of the context gap
calculator in order to predict context differences; At the same time, measurements
provided by the MazCalc are essential to guide the design of learning scenarios
aiming to produce context effects among learners. The article is divided into three
parts. First, the contextual modelling is presented, then we discuss the design of
the MazCalc, and finally, we address the challenges of this research, namely: (1)
the definition of the didactic context and its modelling, leading to the
identification and the prediction of context deviations; and (2) the articulation of
this modelling with the specifications of the MazCalc artifact. Context modelling
is done using an ontological approach. While the iterative design of the MazCalc
in connection with the realization of design experiments is conducted according
to the Design Based Research method. At the end, we discuss the next steps to
be taken
Context or Culture: What is the Difference?
Full text linkLiterature can sometimes tend to present context and culture almost as synonyms. This creates ambiguity, which can complicate the consideration of contextual and cultural variables in instructional design, learning, and teaching. From an ontological point of view, some clarification of these two concepts is essential as each may influence learning and teaching in different ways. Moreover, since context and culture are interconnected to a certain degree, one may influence the other. It is crucial to make a clear distinction between these two concepts in the knowledge models used in intelligent tutoring systems and distance education systems if we want to facilitate (1) their consideration in pedagogical scenarios, and (2) the accumulation of knowledge about different contexts and cultures. This article offers an interpretation of the difference between these two concepts, presenting context as a substrate of culture. Contextual issues in the learning ecology are also discussed, based on this distinction
Workshop Preface: International Workshop on Context and Culture in Intelligent Tutoring Systems
Full text linkWith the internationalization of education, the need for adaptation and flexibility in
ITS and other learning systems has never been more pressing, extending to many levels
and fields including: the international mobility of learners, teachers and researchers; the
integration of international, intercontextual and intercultural dimensions in instructional
programs (from primary to higher education and continuing professional development),
as well as in the designs, methods, techniques and tools that support them; the
international mobility of education viewed through the lens of today’s new reality of
mass open online courses accessible by a diverse range of learners around the world
facilitated by ubiquitous, mobile and cloud learning systems. In this sense, there is a
need for more research about context and culture in intelligent tutoring systems.
Teachers and researchers need to develop new adaptation skills and embrace diverse
contexts and cultures as well as leverage this diversity to foster the transfers that can
enhance learning. Clearly therefore, it is important to make room for this diversity in
curricula and learning systems and integrate transfer and adaptation concerns into
pedagogical practice.
But how can we do this concretely? How can we best manage this complexity and
leverage this diversity? How can this materialize in the ITS field, and what are the
benefits?
One of the main focuses of current research is to define the boundaries of context and
culture (C&C) as a theoretical concept and what constitutes the best methods, techniques
and tools in order to collect, analyze and model it from an adaptive learning perspective.
Until recently, C&C modelling was considered an intrinsic part of the various classical
ITS architecture models. Aspects of C&C were therefore partially covered under the
domain, learner, pedagogical and communication models. Now, however, the advent of
big data in education and significant innovations in artificial intelligence are opening
new doors for us to analyze and model C&C differently, if we are able to take advantage
of the information available through the learning analytics process. Big data offers an
exciting opportunity for us to look at C&C modelling for ITS through a new lens. Do
we need a fifth model? Should we view it as another layer in the ITS architecture? Let’s
start thinking about it. In today’s era of adaptive learning delivering anything learners
need, anywhere and at any time, the potential for context and culture-aware ITS could
be huge. What would knowledge representation and reasoning mechanisms look like in
ITS? What kinds of limits might C&C represent for ITS? How can we identify or
measure these limits? Can ocular and biometric measurement play an instrumental role?
What are the logical next steps in terms of conducting studies about context and cultureaware
ITS and gathering and analyzing data about context and culture?
This C&C@ITS2018 workshop aims to build the foundations of this research stream by
forming an international research community and providing new avenues and questions
for research. New avenues and questions for research may include the following: Will
integrating context and culture mean changing traditional ITS architecture by proposing
new models? Is there any interest in using AI innovations (big data, deep learning) with
the modelling of context and culture knowledge? Why, knowing that there are many
schools of thought? Where do we begin to combine our efforts? Do other modelling
methods such as ontological engineering represent a better way to achieve this goal? Is
it relevant to use AI techniques for education such as educational data mining or learning
analytics to maintain up-to-date knowledge about contextual and cultural diversity?
How can an lTS accommodate and leverage this new complexity to gain awareness of
contextual and cultural diversity? How can earning analytics support contextual and
cultural adaptation, and how can we combine the two? What is the role of the learner in
contextual and cultural adaptation? How can contextual and cultural diversity make
learning deeper and richer?
In light of the above, submissions are welcomed for this workshop on topics
including, but not limited to, the following: Contextual theory; Ontological and
cognitive modelling of contextual or cultural knowledge/context or culture-aware ITS;
Context-aware collaborative learning; Contextual or cultural knowledge in ubiquitous,
mobile and cloud learning systems and various application areas
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Full text link“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
Full text linkWe 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
Full text linkWe 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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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