Showing papers by "Marco Ronchetti published in 2006"
TL;DR: This paper analyze two software packages developed by a CMM level 3 software firm and finds the number of methods well correlated with software size, in the sense that the correlation with the final size is high and significant at the level 0.05.
46 citations
TL;DR: The hoarding problem is described and the strategy to solve it is described with the goal of providing an efficient hoarding solution and a solution should be included in every system with a large quantity of data.
Abstract: M-learning is currently a rapidly expanding domain. Provoked by the fast advances of mobile technologies, different applications and systems are developed continuously. Here we address the hoarding problem, which is weakly explored before but is a particularly important issue in the mobile domain, and a solution should be included in every system with a large quantity of data. Hoarding is the process of automatically selecting learning content, which is to be prepared and prefetched on the mobile device's local memory for the following offline session. We describe the hoarding problem and the strategy to solve it with the goal of providing an efficient hoarding solution.
37 citations
05 Jul 2006
TL;DR: The outcomes of the hoarding sub-system of Mobile ELDIT system, developed at the University of Trento, demonstrate that in certain scenarios anytime, anywhere m-learning might be reached even without online access available.
Abstract: The new e-learning trend, called mobile learning opens variety of questions to solve. To allow access to learning content anytime and anyplace a technique called hoarding is sometimes indispensable for covering the periods of disconnection. In this paper we show the outcomes of the hoarding sub-system of Mobile ELDIT system, developed at the University of Trento. Our results demonstrate that in certain scenarios anytime, anywhere m-learning might be reached even without online access available.
21 citations
05 Jul 2006
TL;DR: An approach based on a probabilistic model is presented, which through the automatic classification of learning resources on a given taxonomic organization of the knowledge, allows to associate ontological metadata to the learning resources.
Abstract: Proper reuse of learning objects depends both on the amount and quality of attached semantic metadata such as "learning objective"', "related concept", etc. Manually expressing such metadata is a time consuming and expensive task.. Here we present an approach based on a probabilistic model, which through the automatic classification of learning resources on a given taxonomic organization of the knowledge, allows to associate ontological metadata to the learning resources.
20 citations
01 Jan 2006
TL;DR: In this paper, the authors investigated the university students' readiness to utilize mobile learning and found that the students are mainly positive to the prospective of accessing mobile learning, depending mainly on their previous experience and current habits.
Abstract: Mobile Learning is rather new, but rapidly growing research domain. This paper presents part of a study that we have performed to investigate the university students' readiness to utilize mobile learning. About 600 Italian and 200 Bulgarian students participated in an online questionnaire in June 2005. They were asked about the availability of devices, about their willingness to use m-learning, etc. We studied in depth also similar studies conducted in other countries and confronted the outcomes. The analyses show that the students are mainly positive to the prospective of accessing mobile learning. The attitude differs, depending mainly of their previous experience and current habits. Sometimes gender differences can be noticed and the availability of devices and students' income influence the student's attitude. Things like nationality or studied subject does not seem to influence the future of mobile learning.
20 citations