110 research outputs found
A Rule-Based System for Test Quality Improvement.
No full textTo correctly evaluate learners’ knowledge, it is important to administer tests composed of good quality question items. By the term “quality” we intend the potential of an item in effectively discriminating between skilled and untrained students and in obtaining tutor’s desired difficulty level. This article presents a rule-based e-testing system which assists tutors in obtaining better question items through subsequent test sessions. After each test session, the system automatically detects items’ quality and provides the tutors with advice about what to do with each of them: good items can be re-used for future tests; among items with lower performances, instead, some should be discarded, while some can be modified and then re-used. The proposed system has been experimented in a course at the University of Salerno.</p
Co-authorship networks and scientific performance. Evidences from a case study by using different bibliographic archives
No full textThe present contribution aims at exploring the effects of collaborative behaviours on scholar scientific performance. Mainly thanks to the availability of international bibliographic archives, seminal studies in various fields have been focused on co-authorship networks as a proxy of scholars' collaborative skills. To this purpose, several data sources are available but they present some drawbacks, especially when a specific discipline or community is under analysis. For instance, international archives might not be able to cover all kinds of scientific production, especially for social sciences where papers can be published in books or in national-oriented journals.
In this scenario, we gathered co-authorship data on the scientific community of Italian academic statisticians as recorded in the Italian Ministry of University and Research database at March 2010. We used three bibliographic archives covering top-international journals as well as thematic and nationally oriented publications: Web of Science (WoS), Current Index to Statistics (CIS), and bibliographic information related to nationally funded research projects (PRIN). Since each data source showed peculiar characteristics influencing both network properties and performance results, we also discussed the main issues and the practical implications on merging data sources (i.e., record linkage and author name disambiguation) improving the bibliographic data quality for reconstruct an unified co-authorship network.
Both network and individual covariates are used to model individual h-index by Generalized Extreme Value (GEV) distribution. Our results provided evidence of our hypotheses on distinct collaboration patterns among statisticians, as well as distinct effects of scientist network positions on scientific performance, by both Statistics subfield and data source.
References
De Stefano, D., Zaccarin, S. (2016). Co-authorship networks and scientific performance: an empirical analysis using the generalized extreme value distribution. Journal of Applied Statistics 43: 262-279.
De Stefano, D., Fuccella, V., Vitale, M. P., Zaccarin, S. (2013) The use of different data sources in the analysis of co-authorship networks and scientific performance. Social Networks 35: 370–381.
Fuccella, V., De Stefano, D., Vitale, M. P., Zaccarin, S. Improving co-authorship network structures by combining multiple data sources: evidence from Italian academic statisticians. Scientometrics (to appear
Fast prototyping of visual languages using local context-based specifications
No full textIn this paper we present a framework for the fast prototyping of visual languages exploiting their local context based specification. In previous research, the local context specification has been used as a weak form of syntactic specification to define when visual sentences are well formed. In this paper we add new features to the local context specification in order to fully specify complex visual languages such as entity-relationships, use case and class diagrams. One of the advantages of this technique is its simplicity of application and, to show this, we present a tool implementing our framework. Moreover, we describe a user study aimed at evaluating the satisfaction and effectiveness of users when prototyping a visual language
Local context-based recognition of sketched diagrams
No full textWe present a new methodology aimed at the design and implementation of a framework for sketch recognition enabling the recognition and interpretation of diagrams. The diagrams may contain different types of sketched graphic elements such as symbols, connectors, text. Once symbols are distinguished from connectors and identified, the recognition proceeds by identifying the local context of each symbol. This is seen as the symbol interface exposed to the rest of the diagram and includes predefined attachment areas on each symbol. We argue that, in many cases, simple constraints on the local context of each symbol are enough to describe diagram languages defined on those symbols. Further refinement and interpretation of the set of acceptable diagrams is then provided through a visual grammar. We also describe the architecture of the framework and provide sample applications for the domains of flowcharts and binary trees
RankFrag: A machine learning-based technique for finding corners in hand-drawn digital curves
No full textWe describe RankFrag: a technique which uses machine learning to detect corner points in hand-drawn digital curves. RankFrag classifies the stroke points by iteratively extracting them from a list of corner candidates. The points extracted in the last iterations are said to have a higher rank and are more likely to be corners. The technique has been tested on three different datasets described in the literature. We observed that, considering both accuracy and efficiency, RankFrag performs better than other state-of-art techniques
KeyScretch on android tablets and smartphones
No full textKeyScretch is a text entry method for mobile devices equipped with touch-screens, based on a menu-augmented soft keyboard. It improves the previously studied menubased methods by enabling the interpretation of compound strokes, corresponding to the input of particularly frequent character sequences. Here we describe the design of an application we developed for the Android system, runnable on tablets and smartphones. section briefly describes the KeyScretch method; Section 3 presents the design of the KeyScretch Android application; finally, Section 4 offers our conclusions and outlines the future work
CyBiS: A Novel Interface for Searching Scientific Documents
No full textAlthough textual interfaces for browsing scientific pa- pers have several drawbacks, they are still the most used in digital libraries. Several visual approaches have been proposed in recent years in order to provide the user with a deeper insight of the search context and to allow him/her to quickly gather a collection of documents judged as useful for his/her research. This paper presents CyBiS, a novel 3D analytical interface for a Bibliographic Visualization Tool with the objective of improving scientific paper search. The design choices are justified on the basis of previous experi- ences described in literature and its effectiveness is shown through the description of an example session
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