1,721,034 research outputs found
The Lecomps5 framework for personalized web-based learning: A teacher's satisfaction perspective
No full textAdaptive web-based educational systems provide learners with personalized courses, where learning material is delivered to learners taking into account their personal learning needs, learning styles and learning progresses. In this paper we show the Lecomps5 system, a didactic framework, supporting the automated production and adaptation of personalized courses, implemented in the Lecomps5 system. In particular, this framework was designed in order to address the teacher's satisfaction issue, arising in many systems that are quite demanding in terms of the teacher's work and range of activities. Lecomps5 allows the teacher, through a simple and intuitive didactic tool, to define learning material, specify its characteristics pertaining to personalization and define, to some extent, the didactic strategies to be applied. In order to support both the management of learning material and the automated construction of personalized courses, the system embeds a planner, based on Linear Temporal Logic. The selection of learning material, its sequencing, and the delivery of courses, is performed according to both learners' initial and run-time knowledge and learning styles. The teacher can focus more on her didactic tasks and preferences rather than on the available authoring tools, and spend less time to generate courses. Finally we show encouraging results from experimentation we conducted to test the system from a teacher's point of view. (C) 2010 Elsevier Ltd. All rights reserved
Definition and Analysis of a System for the Automated Comparison of Curriculum Sequencing Algorithms in Adaptive Distance Learning
No full textLS-Lab provides automatic support to comparison/evaluation of the Learning Object Sequences produced by different Curriculum Sequencing Algorithms. Through this framework a teacher can verify the correspondence between the behaviour of different sequencing algorithms and her pedagogical preferences. In fact the teacher can compare algorithms outcomes over sample individual cases, represented by input student models. Such comparison can be accomplished through subjective observation of the sequences, and by evaluating the metrics computed and presented by the system. LS-Lab architecture allows extending the framework with both additional algorithms and metrics. According to the different algorithms needs, suitably varied data structures for the student models are managed. We show also the result of an experimental analysis, conducted to unveil LS-Lab usefulness, as perceived by teachers. Teacher's appreciation, acceptance of the system, and expected advantages, were analyzed through an experimental application involving 30 teachers, with 3 student models, and 3 different sequencing algorithms
Formal Verification: further Complexity Issues and Applications
No full textProf. Giacomo Cioffi (Università di Roma "La Sapienza"), Prof. Fabio Panzieri (Università di Bologna), Dott.ssa Carla Limongelli (Università di Roma Tre)
Lecomps5: a Framework for the Automatic Building of Personalized Learning Sequences
No full textAbstract. In the context of distance learning, Adaptive Web-based Educational System focus on personalization and adaptation, that is on “learner’s satisfac- tion”. In this paper we address the other side of the coin, that is the "teacher’s satisfaction" problem, which is quite seldom taken into account in educational systems. We present a new version of the Lecomps5 Web-based Educational System, a system capable of providing personalization and adaptation on the basis of learner’s knowledge, learning styles and learning progresses. In this new version, a framework provides the teacher with an easy and flexible tool for managing learning material, expressing different didactic strategies and se- quencing personalized courses by means of an embedded planner. Such func- tionalities are supported by the system basing on evaluations of learner’s knowledge, learning styles, and learning progresses. We report on a first con- trolled experiment, we made to evaluate the “teacher’s satisfaction”
Automated and flexible comparison of course sequencing algorithms in the LS-Lab framework
No full textCurriculum Sequencing is one of the most interesting challenges in learning environments, such as Intelligent Tutoring Systems and e-learning. The goal is to automatically produce personalized sequences of didactic materials or activities, on the basis of each individual student's model. In this paper we present the extension of the LS-Lab framework, supporting an automated and flexible comparison of the outputs coming from a variety of Curriculum Sequencing algorithms over the same student models. The main aim of LS-Lab is to provide researchers or teachers with a ready-to-use and possibly extensible environment, supporting a reasonably low-cost experimentation of several sequencing algorithms. The system accepts a student model as input, together with the selection of the algorithms to be used and a given learning material; then the algorithms are applied, the resulting courses are shown to the user, and some metrics computed over the selected characteristics are presented, for the user's appraisal. © 2010 Springer-Verlag
Student and Teacher Perspectives Testing a System for Adaptive e-Learning
No full textPersonalization is becoming a mandatory requirement in Web-based Education and long distance learning in general, representing a flexible way of learning the exact amount of knowledge to reach a given learning goal. This approach saves time and money and it is particularly suited for life-long learning. The drawback is that the teacher has to produce some effort to prepare didactic material and while research in this field proposes several intelligent systems providing personalization with advanced didactic strategies, teacher’s point of view is less considered. In this chapter we extend our previous work that aimed to build an adaptive system for education called LS-Plan, taking into account both teacher’s and student’s needs. In particular we carried out a comprehensive evaluation of the system embedded into an Adaptive Educational Hypermedia called Lecomps5, in order to experiment and prove the added value of the system
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
The use of e-learning methodologies and technologies for generating personalised tours in cultural heritage environments
No full textThis work addresses the issue of personalised tours in cultural heritage domains, by exploiting methods and techniques developed for e-learning, in particular those that regard personalised e-learning courses. The main idea of our work is that a tour in a museum or in an archaeological site, either fully virtual or blended, may be managed through an e-learning environment. We propose the use of the LECOMPS5, an e-learning environment, to provide museums or other cultural sites with the capability of automatically planning personalised tours, according to visitors' needs and interests. We also show an example of an application of this system to an ancient archaeological site called Lucus Feroniae, showing how an e-learning platform can be successfully used for guiding visitors
Configuration of Personalized e-Learning Courses in Moodle
No full textOur work carries on the idea of configuring
personalized courses by means of automated planning techniques,
preserving coherence with present standards for elearning,
in particular with SCORM properties.
Starting from a previous prototype based on suitably
defined learning objects, learning components, we intend to
make it available in a wider contest. To this aim we design
a mapping between our learning component specification
and the definition of a SCO, a SCORM 1.2 compliant
learning object. In this way we can extend conservatively
the usual SCO by enriching it with those elements that are
relevant for the process of automated configuration: while
the original SCORM properties stay unchanged, we can
then make course configuration with a SCORM compliant
learning object. In order to obtain such a mapping, the
ScormUni tag format has been devised, which is an
extension of SCORM meta data. We show here how the
above mentioned prototype has evolved into UniTag , a
software module that extends Moodle (Version 1.6)
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