Carla Limongelli

Adaptive Learning with the LS-Plan System: A Field Evaluation

LS-Plan is a framework for personalization and adaptation in e-learning. In such framework an Adaptation Engine plays a main role, managing the generation of personalized courses from suitable repositories of learning nodes and ensuring the maintenance of such courses, for continuous adaptation of the learning material proposed to the learner. Adaptation is meant, in this case, with respect to the knowledge possessed by the learner and her learning styles, both evaluated prior to the course and maintained while attending the course. Knowledge and Learning styles are the components of the student model managed by the framework. Both the static, precourse, and dynamic, in-course, generation of personalized learning paths are managed through an adaptation algorithm and performed by a planner, based on Linear Temporal Logic. A first Learning Objects Sequence is produced based on the initial learners Cognitive State and Learning Styles, as assessed through prenavigation tests. During the students navigation, and on the basis of learning assessments, the adaptation algorithm can output a new Learning Objects Sequence to respond to changes in the student model. We report here on an extensive experimental evaluation, performed by integrating LS-Plan in an educational hypermedia, the LecompS web application, and using it to produce and deliver several personalized courses in an educational environment dedicated to Italian Neorealist Cinema. The evaluation is performed by mainly following two standard procedures: the As a Whole and the Layered approaches. The results are encouraging both for the system on the whole and for the adaptive components.

LS-Plan: An Effective Combination of Dynamic Courseware Generation and Learning Styles in Web-Based Education

This paper presents LS-Plan , a system capable of providing Educational Hypermedia with adaptation and personalization. The architecture of LS-Plan is based on three main components: the Adaptation Engine, the Planner and the Teacher Assistant. Dynamic course generation is driven by an adaptation algorithm, based on Learning Styles, as defined by Felder-Silvermans model. The Planner, based on Linear Temporal Logic, produces a first Learning Objects Sequence, starting from the students Cognitive State and Learning Styles, as assessed through pre-navigation tests. During the students navigation, and on the basis of learning assessments, the adaptation algorithm can propose a new Learning Objects Sequence. In particular, the algorithm can suggest different learning materials either trying to fill possible cognitive gaps or by re-planning a newly adapted Learning Objects Sequence. A first experimental evaluation, performed on a prototype version of the system, has shown encouraging results.

Personalized e-learning in Moodle: the Moodle_LS System

Learning Management Systems are among the most popular e-learning tools. Over the last few years, however, scientific research has made considerable progress in developing valuable resources currently unavailable in most Learning Management Systems, including solutions aimed at providing students with personalized support throughout the learning process, which is an essential requirement in continuing education. Observing and modelling the learner, and adapting their learning experience accordingly means opening up new technological and, above all, methodological perspectives in e-learning. The work described in this paper is part of the Open Learning project, in which business-based and university researchers aim to combine the most frequently used e-learning technologies, Learning Management Systems, with the benefits of customized systems so as to develop an innovative learning content delivery system based on the personalization of the learning experience. The proposed system integrates moodle with an engine, LS-Plan, which provides automated sequencing of the learning material based on the learner’s knowledge and learning styles. This paper describes the new system and presents the results of tests conducted in the domain of Italian Neorealist Cinema.

A Teaching-Style Based Social Network for Didactic Building and Sharing

Nowadays, teachers tend to build their own didactic local repository composed by learning objects retrieved from web repositories or, in most cases, by self-made didactic material. In this way they do not share their teaching experience, loosing a precious shortcut to a fast professional update and to an improvement of their teaching activity. In this paper we address the problem of helping teachers to retrieve didac- tic material from a repository through a didactic social network where teachers with similar Teaching Styles, can help each other in retrieving educational material. To this aim a teaching-styles based social network is built following the Grasha TS paradigm. We present a first evaluation of the network embedded in a web application.

Supporting Teachers to Retrieve and Select Learning Objects for Personalized Courses in the Moodle_LS Environment

In this paper we present a comprehensive framework supporting the tasks of defining, retrieving, and importing Learning Objects (LOs) for personalized courses. It is partially implemented in a Moodle-based personalization system, where the instructional designer is guided through: 1) a theoretical specification of the needed LOs; 2) a retrieval function of actual LOs, by automatically querying standard-compliant repositories; 3) an analysis of such items, to import those selected by him, also adding metadata relevant to the personalization system, at hand. This work overcomes some well known shortcomings of the Moodle system in supporting retrieval of learning material in a personalization context.

An Ontology-Driven OLAP System to Help Teachers in the Analysis of Web Learning Object Repositories

The Knowledge Society is increasing the demand for tools to manage the didactic knowledge stored in Learning Objects Repositories, and needed by teachers to generate courseware. In this respect, still there is a lack of automated tools for the analysis and retrieval of learning resources from such repositories. Here we propose the use of the OLAP technique to help teachers to specify a didactic ontology by which performing quantitative and qualitative analysis of Internet-based Learning Objects Repositories. The related system is presented, together with a case study based on real repositories.

A Teacher Model to Speed Up the Process of Building Courses

Building a new course is a complex task for teachers: the entire process requires different steps, starting with the concept map building and ending with the delivery of the learning objects to students through a learning management system. Teachers have to spend a lot of time to build or to retrieve the right learning material from local databases or from specialized repositories on the web. Consequently, having a system supporting this phase is a very important challenge, considering that each teacher expresses her own pedagogy as well. Here we propose a novel Teacher Model that helps teachers to build new courses effectively. The model is based both on a didactic semantic network containing concepts and learning material and on Teaching Styles as proposed in the literature by Grasha. This framework gives teachers the possibility to share their teaching experience as well. A first experimentation of the system gives positive results.

A recommendation module to help teachers build courses through the Moodle Learning Management System

In traditional e-learning, teachers design sets of Learning Objects (LOs) and organize their sequencing; the material implementing the LOs could be either built anew or adopted from elsewhere (e.g. from standard-compliant repositories) and reused. This task is applicable also when the teacher works in a system for personalized e-learning. In this case, the burden actually increases: for instance, the LOs may need adaptation to the system, through additional metadata. This paper presents a module that gives some support to the operations of retrieving, analyzing, and importing LOs from a set of standard Learning Objects Repositories, acting as a recommending system. In particular, it is designed to support the teacher in the phases of (i) retrieval of LOs, through a keyword-based search mechanism applied to the selected repositories; (ii) analysis of the returned LOs, whose information is enriched by a concept of relevance metric, based on both the results of the searching operation and the data related to the previous use of the LOs in the courses managed by the Learning Management System; and (iii) LO importation into the course under construction.

Virtual industrial training: Joining innovative interfaces with plant modeling

Training in industry is one of the most critical and expensive tasks to be faced by the management. Furthermore, in some cases, it is dangerous or even impossible to directly train operators on the real plants where security and safety problems may arise, making it very difficult to start training programs at low cost. For these reasons, the field of training in industry is rapidly developing using software or hardware solutions coming mainly from the following research areas: i) Human-Computer interaction, i.e., the use of complex and interactive human-machine interfaces, ii) plant simulators, i.e., software systems which are delivered with the plant itself to test and to learn complex tasks and processes, iii) Intelligent Training Systems, i.e., the availability of intelligent and personalized training systems where a virtual tutor guides users through a personalized learning path. In this paper we present the overall architecture of a system for industrial training, embedded into an Intelligent Tutoring System that can provide more effective and personalized training and learning in a context where working directly on real plants can be difficult and very expensive. In particular we present a simulator for training operators in using power plants, based on a multimedia and on interactive interface. This system is particularly suitable to be used for training in industrial electric and oil plants. Moreover, the system allows operators for collaborative problem solving. Currently the system is under delivery to an Italian Electric industry.

Exploiting wikipedia for discovering prerequisite relationships among learning objects

Identifying the pre-requisite relationships among learning objects is a crucial step for faculty and instructional designers when they try to adapt them for delivery in their education distance courses. It results in one of the most relevant constraint to check for ensuring that if a learning object references another, the referenced one is also in the course positioned before the former. This paper reports about a project under development aiming at facilitating this step. In particular, a content-based approach supported by semantic analysis techniques identifies pre-requisite relationships between text-based learning objects without effort by the user.