Abstract: In this paper, we shed light on the use of two types of fuzzy genetic algorithms, which 1 stand out from the literature for the innovative ideas behind them. One is the Gendered Fuzzy 2 Genetic Algorithm, where the crossover mechanism is regulated by the gender and the age of the 3 population to generate offspring through proper fuzzy rules. The other one is the Elegant Fuzzy 4 Genetic Algorithm, where the priority of the parent genome is updated based on the child’s fitness. 5 Both algorithms present a significant computational burden. To speed up the computation, we 6 propose to adopt a nearest-neighbour caching strategy. We performed several experiments using 7 first some well-known benchmark functions, trying different types of membership functions and 8 logical connectives. Afterwards, some additional benchmarks were retrieved from the literature for 9 a fair comparison against published results obtained by means of former variants of fuzzy genetic 10 algorithms. A real-world application problem, retrieved from the literature and dealing with rice 11 production, was also tackled. All the numerical results show the potential of the proposed strategy.

Keywords: Nearest neighbour, Caching, Fuzzy rules, Fitness, Priority

DOI: 10.3390/a17120549, Multidisciplinary Digital Publishing Institute

Article BibTeX

Abstract: The topic of persuasion in online conversations has social, political and security implications; as a consequence, the problem of predicting persuasive comments in online discussions is receiving increasing attention in the literature. Following recent advancements in graph neural networks, we analyze the impact of conversation structure in predicting persuasive comments in online discussions. We evaluate the performance of artificial intelligence models receiving as input graphs constructed on the top of online conversations sourced from the “Change My View” Reddit channel. We experiment with different graph architectures and compare the performance on Graph Neural Networks, as structure-based models, and Dense Neural Networks as baseline models. Experiments are conducted on two tasks: 1) Persuasive Comment Detection, aiming to predict which comments are persuasive, and 2) Influence Prediction, aiming to predict which users are persuasive. The experimental results show that the role of the conversation structure in predicting persuasiveness is strongly dependent on its graph representation given as input to the Graph Neural Network. In particular, a graph structure linking only comments belonging to the same speaker in the conversation achieves the best performance in both tasks. This structure outperforms both the baseline model, which does not consider any structural information, and structures linking different speakers’ comments with each other. Specifically, the F1 score of the best performing model is 0.58, which represents an improvement of 5.45% over the baseline model (F1 score of 0.55) and 7.41% over the model linking different speakers’ comments (F1 score of 0.54).

Keywords: Social Media Persuasion, Persuasive Comment Detection, Influence Prediction, Text Data

DOI: 10.1007/s12652-024-04841-8, Springer-Verlag GmbH

Article BibTeX

Abstract: Fake news, which can be defined as intentionally and verifiably false news, has a strong influence on critical aspects of our society. Manual fact-checking is a widely adopted approach used to counteract the negative effects of fake news spreading. However, manual fact-checking is not sufficient when analysing the huge volume of newly created information. Moreover, the number of labeled datasets is limited, humans are not particularly reliable labelers and databases are mostly in English and focused on political news. To solve these issues state-of-the-art machine learning models have been used to automatically identify fake news. However, the high amount of models and the heterogeneity of features used in literature often represents a boundary for researchers trying to improve model performances. For this reason, in this systematic review, a taxonomy of machine learning and deep learning models and features adopted in Content-Based Fake News Detection is proposed and their performance is compared over the analysed works. To our knowledge, our contribution is the first attempt at identifying, on average, the best-performing models and features over multiple datasets/topics tested in all the reviewed works. Finally, challenges and opportunities in this research field are described with the aim of indicating areas where further research is needed.

Keywords: Fake News Detection, Content Based Fake News Detection, Content-Based Features

DOI: 10.1016/j.neucom.2023.02.005, Elsevier Ltd.

BibTeX

Abstract: In the biomedical field, there is an ever-increasing number of large, fragmented, and isolated data sources stored in databases and ontologies that use heterogeneous formats and poorly integrated schemes. Researchers and healthcare professionals find it extremely difficult to master this huge amount of data and extract relevant information. In this work, we propose a linked data approach, based on multilayer networks and semantic Web standards, capable of integrating and harmonizing several biomedical datasets with different schemas and semi-structured data through a multi-model database providing polyglot persistence. The domain chosen concerns the analysis and aggregation of available data on Neuroendocrine Neoplasms (NENs), a relatively rare type of neoplasm. Integrated information includes twelve public datasets available in heterogeneous schemas and formats including RDF, CSV, TSV, SQL, OWL, and OBO. The proposed integrated model consists of six interconnected layers representing, respectively, information on the disease, the related phenotypic alterations, the affected genes, the related biological processes, and molecular functions, the involved human tissues, and on drugs and compounds that show documented interactions with them. The defined scheme extends an existing three-layer model covering a subset of the mentioned aspects. A client-server application was also developed to browse and search for information on the integrated model. The main challenges of this work concern the complexity of the biomedical domain, the syntactic and semantic heterogeneity of the datasets, and the organization of the integrated model. Unlike related works, multilayer networks have been adopted to organize the model in a manageable and stratified structure, without the need to change the original datasets but by transforming their data “on the fly” to respond to user requests.

Keywords: Linked Data, Biomedical Ontologies, Multilayer Network Analysis, Neuroendocrine Neoplasms, Semantic Information Integration, Polyglot Persistence, Multi-Model Database.

DOI: 10.3390/app12189317, Multidisciplinary Digital Publishing Institute

Article BibTeX

Abstract: Nowadays, Artificial Intelligence (AI) is widely applied in every area of human being’s daily life. Despite the AI benefits, its application suffers from the opacity of complex internal mechanisms and doesn’t satisfy by design the principles of Explainable Artificial Intelligence (XAI). The lack of transparency further exacerbates the problem in the field of CyberSecurity because entrusting crucial decisions to a system that cannot explain itself presents obvious dangers. There are several methods in the literature capable of providing explainability of AI results. Anyway, the application of XAI in CyberSecurity can be a double- edged sword. It substantially improves the CyberSecurity practices but simultaneously leaves the system vulnerable to adversary attacks. Therefore, there is a need to analyze the state-of-the-art of XAI methods in CyberSecurity to provide a clear vision for future research. This study presents an in-depth examination of the application of XAI in CyberSecurity. It considers more than 300 papers to comprehensively analyze the main CyberSecurity application fields, like Intrusion Detection Systems, Malware detection, Phishing and Spam detection, BotNets detection, Fraud detection, Zero-Day vulnerabilities, Digital Forensics and Crypto-Jacking. Specifically, this study focuses on the explainability methods adopted or proposed in these fields, pointing out promising works and new challenges.

Keywords: Artificial Intelligence, CyberSecurity, Explainable Artificial Intelligence, Security paradigm, Trust.

DOI: 10.1109/ACCESS.2022.3204171, Institute of Electrical and Electronics Engineers Inc.

Article BibTeX

Abstract: Understanding the role played by genetic variations in diseases, exploring genomic variants and discovering disease-associated loci are among the most pressing challenges of genomic medicine. A huge and ever-increasing amount of information is available to researchers to address these challenges. Unfortunately, it is stored in fragmented ontologies and databases, which use heterogeneous formats and poorly integrated schemas. The difficulty in finding the needed information and even in mastering its sources translates into a serious obstacle to research in this field, unnecessarily increasing its time and complexity. To overcome these limitations, we propose a linked data approach, based on the formalism of multilayer networks, able to integrate and harmonize biomedical information from multiple sources into a single dense network covering different aspects on Neuroendocrine Neoplasms (NENs). The problem of information harmonization is particularly felt for this type of rare tumors as the nomenclature associated with them is rather heterogeneous between studies and data sources. The proposed integration schema consists of three interconnected layers representing, respectively, information on the disease, on the affected genes, on the related biological processes and molecular functions. An easy-to-use client-server application was also developed to browse and search for information on the model supporting multilayer network analysis.

Keywords: Linked Data, Biomedical Ontologies, Multilayer Network Analysis, Rare Diseases, Human Genome, Neuroendocrine Neoplasms, Semantic Information Integration.

DOI: 10.4018/IJSWIS.297141, IGI Global

Article BibTeX

Abstract: Massive Open Online Courses (MOOCs) allow students and instructors to discuss through messages posted on a forum. However, the instructors should limit their interaction to the most critical tasks during MOOC delivery so, teacher-led scaffolding activities, such as forum-based support, can be very limited, even impossible in such environments. In addition, students who try to clarify the concepts through such collaborative tools could not receive useful answers, and the lack of interactivity may cause a permanent abandonment of the course. The purpose of this paper is to report the experimental findings obtained evaluating the performance of a text categorization tool capable of detecting the intent, the subject area, the domain topics, the sentiment polarity, and the level of confusion and urgency of a forum post, so that the result may be exploited by instructors to carefully plan their interventions. The proposed approach is based on the application of Attention-based Hierarchical Recurrent Neural Networks, in which both a recurrent network for word encoding and an attention mechanism for word aggregation at sentence and document levels are used before classification. The integration of the developed classifier inside an existing tool for conversational agents, based on the Academically Productive Talk framework, is also presented as well as the accuracy of the proposed method in the classification of forum posts.

Keywords: Massive open online courses, Neural networks, Text mining, Conversational agents.

DOI: 10.1007/s12652-020-02747-9, Springer-Verlag GmbH

Article BibTeX

Abstract: In recent years there has been a significant rethinking of corporate management, which is increasingly based on customer orientation principles. As a matter of fact, customer relationship management processes and systems are ever more popular and crucial to facing today's business challenges. However, the large number of available customer communication stimuli coming from different (direct and indirect) channels, require automatic language processing techniques to help filter and qualify such stimuli, determine priorities, facilitate the routing of requests and reduce the response times. In this scenario, sentiment analysis plays an important role in measuring customer satisfaction, tracking consumer opinion, interacting with consumers and building customer loyalty. The research described in this paper proposes an approach based on Hierarchical Attention Networks for detecting the sentiment polarity of customer communications. Unlike other existing approaches, after initial training, the defined model can improve over time during system operation using the feedback provided by CRM operators thanks to an integrated incremental learning mechanism. The paper also describes the developed prototype as well as the dataset used for training the model which includes over 30.000 annotated items. The results of two experiments aimed at measuring classifier performance and validating the retraining mechanism are also presented and discussed. In particular, the classifier accuracy turned out to be better than that of other algorithms for the supported languages (macro-averaged f1-score of 0.89 and 0.79 for Italian and English respectively) and the retraining mechanism was able to improve the classification accuracy on new samples without degrading the overall system performance.

Keywords: Customer relationship management, Hierarchical attention networks, Machine learning, Natural language processing, Sentiment analysis.

DOI: 10.1007/s10489-020-01984-x, Springer-Verlag GmbH

Article BibTeX

Abstract: Massive Open Online Courses are gaining popularity with millions of students enrolled, thousands of courses available and hundreds of learning institutions involved. Due to the high number of students and the relatively small number of tutors, student assessment, especially for complex tasks, is a typical issue of such courses. Thus, peer assessment is becoming increasingly popular to solve such a problem and several approaches have been proposed so far to improve the reliability of its outcomes. Among the most promising, there is fuzzy ordinal peer assessment (FOPA) that adopts models coming from fuzzy set theory and group decision Making. In this paper we propose an extension of FOPA supporting multi-criteria assessment based on rubrics. Students are asked to rank a small number of peer submissions against specified criteria, then provided rankings are transformed in fuzzy preference relations, expanded to obtain missing values and aggregated to estimate final grades. Results obtained are promising if compared to other peer assessment techniques both in the reconstruction of the correct ranking and on the estimation of students’ grades.

Keywords: Assessment; Group decision making; Technology enhanced learning

DOI: 10.1007/s00500-020-05155-5, Springer-Verlag GmbH

Article BibTeX

Abstract: Adaptive learning refers to technologies that dynamically adjust to the level or type of course content based on an individual's abilities or skill attainment, in ways that accelerate a learner's performance with both automated and instructor interventions. This column explores adaptive learning, its close relationship to artificial intelligence, and points to several results from artificial intelligence that have been used to build effective adaptive learning systems. The pairing of massive open online courses and adaptive learning has revealed new technical and pedagogical challenges that are currently being explored in various research projects.

DOI: 10.1609/aimag.v41i2.5317, AI Access Foundation

Article BibTeX

Abstract: Group Recommender Systems are special kinds of Recommender Systems aimed at suggesting items to groups rather than individuals taking into account, at the same time, the preferences of all (or the majority of) members. Most existing models build recommendations for a group by aggregating the preferences for their members without taking into account social aspects like user personality and interpersonal trust, which are capable of affecting the item selection process during interactions. To consider such important factors, we propose in this paper a novel approach to group recommendations based on fuzzy influence-aware models for Group Decision Making. The proposed model calculates the influence strength between group members from the available information on their interpersonal trust and personality traits (possibly estimated from social networks). The estimated influence network is then used to complete and evolve the preferences of group members, initially calculated with standard recommendation algorithms, toward a shared set of group recommendations, simulating in this way the effects of influence on opinion change during social interactions. The proposed model has been experimented and compared with related works.

Keywords: Group decision making; Recommender systems; Social influence

DOI: 10.1016/j.chb.2018.11.001, Elsevier Ltd.

Article BibTeX

Abstract: This work presents a Smart Learning system based on Knowledge Discovery and Cognitive Computing techniques aimed at citizens, legal students and experts alike, providing them with the possibility of submitting legal cases expressed in natural language and obtaining legal insight and advice in return. Advanced features implemented within the system include the automatic conceptualization and classification of textual legal cases via natural language processing, the generation of learning paths by relying upon legal ontologies, and additional features for managing legal knowledge bases, including editing, versioning, integration and enrichment. The system has been experimented on a diversified user-base and succeeded in obtaining a positive evaluation with respect to the aspects that were subject of the investigation, including effectiveness, efficiency and usability, thus paving the way to make the system a successful cognitive learning platform for future law professionals and knowledgeable citizens.

Keywords: Adaptive learning; Cognitive computing; Knowledge discovery; Natural language processing; Online dispute resolution; Ontology integration

DOI: 10.1016/j.chb.2018.03.034, Elsevier Ltd.

Article BibTeX

Abstract: Although fuzzy preference relations (FPRs) are among the most commonly used preference models in group decision making (GDM), they are not free from drawbacks. First of all, especially when dealing with many alternatives, the definition of FPRs becomes complex and time consuming. Moreover, they allow to focus on only two options at a time. This facilitates the expression of preferences but let experts lose the global perception of the problem with the risk of introducing inconsistencies that impact negatively on the whole decision process. For these reasons, different preference models are often adopted in real GDM settings and, if necessary, transformation functions are applied to obtain equivalent FPRs. In this paper, we propose fuzzy rankings, a new approximate preference model that offers a higher level of user-friendliness with respect to FPRs while trying to maintain an adequate level of expressiveness. Fuzzy rankings allow experts to focus on two alternatives at a time without losing the global picture so reducing inconsistencies. Conversion algorithms from fuzzy rankings to FPRs and backward are defined as well as similarity measures, useful when evaluating the concordance between experts’ opinion. A comparison of the proposed model with related works is reported as well as several explicative examples.

Keywords: Fuzzy preference relations; Fuzzy rankings; Group decision making

DOI: 10.1002/int.21997, John Wiley and Sons Ltd.

Article BibTeX

Abstract: A promising research area in the field of group decision making (GDM) is the study of interpersonal influence and its impact on the evolution of experts' opinions. In conventional GDM models, a group of experts express their individual preferences on a finite set of alternatives, then preferences are aggregated and the best alternative, satisfying the majority of experts, is selected. Nevertheless, in real situations, experts form their opinions in a complex interpersonal environment where preferences are liable to change due to social influence. In order to take into account the effects of social influence during the GDM process, we propose a new influence-guided GDM model based on the following assumptions: experts influence each other and the more an expert trusts in another expert, the more his opinion is influenced by that expert. The effects of social influence are especially relevant to cases when, due to domain complexity, limited expertise or pressure to make a decision, an expert is unable to express preferences on some alternatives, i.e., in presence of incomplete information. The proposed model adopts fuzzy rankings to collect both experts' preferences on available alternatives and trust statements on other experts. Starting from collected information, possibly incomplete, the configuration and the strengths of interpersonal influences are evaluated and represented through a social influence network (SIN). The SIN, in its turn, is used to estimate missing preferences and evolve them by simulating the effects of experts' interpersonal influence before aggregating them for the selection of the best alternative. The proposed model has been experimented with synthetic data to demonstrate the influence driven evolution of opinions and its convergence properties.

Keywords: Fuzzy preference relation; Group decision making; Social influence

DOI: 10.1109/TFUZZ.2017.2744605, Institute of Electrical and Electronics Engineers Inc.

Article BibTeX

Abstract: This research proposes an enhanced approach of decoupling assessment and serious games to support fire evacuation training in smart education. The proposed assessment approach employs an evidence-based dynamic assessment and feedback to guide players through school’s building evacuation. Experimentation results show the applicability of the proposed assessment approach in enhancing fire evacuation training using serious games. Moreover, students were engaged to the proposed learning scenarios and their overall fire evacuation assessment were enhanced using the guided exploratory game-based training.

Keywords: Dynamic assessment; Emergency training; Exploratory learning; Fire evacuation; Serious games

DOI: 10.1007/s12652-016-0436-6, Springer-Verlag GmbH

Article BibTeX

Abstract: Massive Open Online Courses (MOOCs) are becoming an increasingly popular choice for education but, to reach their full extent, they require the resolution of new issues like assessing students at scale. A feasible approach to tackle this problem is peer assessment, in which students also play the role of assessor for assignments submitted by others. Unfortunately, students are unreliable graders so peer assessment often does not deliver accurate results. In order to mitigate this issue, we propose a new model for ordinal peer assessment based on the principles of fuzzy group decision making. In our approach, each student is asked to rank a few random submissions from the best to the worst and to specify, with a set of intuitive labels, at what extent each submission is better than the following one in the ranking. Students' provided rankings are then transformed in fuzzy preference relations, expanded to estimate missing values and aggregated through OWA operators. The aggregated relation is then used to generate a global ranking between the submissions and to estimate their absolute grades. Experimental results are presented and show better performances with respect to other existing ordinal and cardinal peer assessment techniques both in the reconstruction of the correct ranking and on the estimation of students' grades.

Keywords: Fuzzy set theory; Group decision making; Massive open online courses; Peer assessment

DOI: 10.1109/TLT.2016.2565476, Institute of Electrical and Electronics Engineers Inc.

Article BibTeX

Abstract: The paper presents innovative trustworthy services to support secure e-assessment in web-based collaborative learning grids. Although e-Learning has been widely adopted, there exist still drawbacks which limit their potential. Among these limitations, we investigate information security requirements in on-line assessment learning activities, (e-assessment). In previous research, we proposed a trustworthiness model to support secure e-assessment requirements for e-Learning. In this paper, we present effective applications of our approach by integrating flexible and interoperable Web based secure e-learning services based on our trustworthiness model into e-assessment activities in on-line collaborative learning courses. Moreover, we leverage Grid technology to meet further demanding requirements of collaborative learning applications in terms of computation performance and management of large data sets, in order for the trustworthy collaborative learning services to be continuously adapted, adjusted, and personalised to each specific target learning group. Evaluation in a real context is provided while implications of this study are eventually remarked and discussed.

Keywords: Assessment; CSCL; Grid technology; Information security; Online collaborative learning; Prediction; Service-oriented architecture; SOA; Trustworthiness; Web services

DOI: 10.1504/IJWGS.2017.082059, Inderscience Enterprises Ltd.

Article BibTeX

Abstract: Peer grading is a process whereby students are required to grade some of their peers’ assignments as part of their own assignment. Peer grading is capable of improving students’ learning outcomes, metacognition and critical thinking and, at the same time, it can support formative assessment, saving teacher’s time and providing fast feedback, especially for large classes. In this paper we report the results of an experiment where a technology supported peer grading exercise has been assigned to students within a University course on calculus and linear algebra. To improve the reliability of students’ grades, several approaches have been experimented and the obtained results have been compared to grades coming from the teacher. Moreover, we attempted to understand how the peer grading task has contributed to reinforce the development of student’s explanation and argumentation processes.

Keywords: Formative assessment; Fuzzy ordinal peer assessment; Peer grading; Peer rank

ISSN: 18266223, Italian e-Learning Association

Article BibTeX

Abstract: In this paper, we present our results related to the definition of a methodology that combines augmented reality (AR) with semantic techniques for the creation of digital stories associated with museum exhibitions. In contrast to traditional AR approaches, we augment real-world elements by supplementing contents of a museum exhibition with additional inputs that provide new and different meanings. In this way we augment a cultural resource with respect to both its presentation and meaning. The methodology is framed in the cultural re-mediation theory and is grounded on a set of ontologies aimed at modelling a cultural resource and correlating it with external multimedia objects and resources. To provide an easy tool for the creation of museum narratives, the methodology makes use of a set of recognised practices widely adopted by museum curators that have been formalised through inference rules. The defined methodology has been experimented in a scenario related to Flemish paintings to validate the augmentation of cultural objects with two different approaches, the first basing on similarities and the second on dissimilarities.

Keywords: Augmented reality; Cultural re-mediation; Knowledge representation

DOI: 10.1080/0144929X.2016.1208774, Taylor and Francis Ltd.

Article BibTeX

Abstract: Peer grading is an approach increasingly adopted for assessing students in massive on-line courses, especially for complex assignments where automatic assessment is impossible and the ability of tutors to evaluate and provide feedback at scale is limited. Unfortunately, as students may have different expertise, peer grading often does not deliver accurate results compared to human tutors. In this paper, we describe and compare different methods, based on graph mining techniques, aimed at mitigating this issue by combining peer grades on the basis of the detected expertise of the assessor students. The possibility to improve these results through optimized techniques for assessors' assignment is also discussed. Experimental results with both synthetic and real data are presented and show better performance of our methods in comparison to other existing approaches.

Keywords: Assessment; e-Learning; Graph mining; MOOCs; Peer grading

DOI: 10.3991/ijet.v11i07.5878, Kassel University Press GmbH

Article BibTeX

Abstract: The need of a common environment where to share information and knowledge is of particular interest in the field of special education not only to support the access to a large amount of available information (along with the ability to derive value from this information) but also to foster synergistic actions involving different special education operators. In this paper we present the results of a research aimed at defining a Web-based environment for special education providing, to operators of the field, personalized information and digital assets covering both their expressed and latent information needs. Offered personalization features are based on the definition and the implementation of a hybrid recommender system based on a mix of cognitive and collaborative approaches, the first based on the similarities among digital objects, the latter leveraging on similarities among user profiles. By combining these two approaches the system is able to provide meaningful but not obvious recommendations with a fair level of serendipity. The encouraging results of an experimentation with real users are also reported.

Keywords: Adaptive learning; Digital repositories; Recommender systems; Special education

DOI: 10.3991/ijet.v10i7.4608, Kassel University Press GmbH

Article BibTeX

Abstract: Emergency preparedness is a promising application field for digital serious games enabling the simulation of real emergency scenarios and allowing a high learning transfer thanks to engagement and focus on specific tasks. Games can also play a role in the assessment that may happen without interrupting the learner, observing and evaluating what she is doing. Based on these premises we defined a serious game for evacuation training targeted to primary and secondary school students. The student is immersed in a virtual environment representing her school during an emergency with the aim of evacuating the building and adopting the correct behaviour. Any performed action is evaluated by the system, feedback is provided immediately and also when the game ends. Recovery micro-learning resources are then arranged and provided to the students to explain any errors they made and to help them reach better performances. The system is based on the application of a theoretical framework for evidence-based assessment where knowledge-based structures have been used to represent emergency skills and to relate them to possible actions within the game. An experiment with students coming from four Italian schools has been also performed to validate the models and the prototype.

Keywords: Adaptive learning systems; Emergency training; Evidence centred design; Knowledge representation; Serious games

ISSN: 18266223, Italian e-Learning Association

Article BibTeX

Abstract: In every context where the objective is matching needs of the users with fitting answers, the high-level performance becomes a requirement able to allow systems being useful and effective. The personalization may affect different moments of computer-humans interaction routing the users to the best answers to their needs. The most part of this complex elaboration is strictly related with the needs themselves and the residual is independent from it. It is what we may face by getting personality traits of the users. In this paper, we describe an approach that is able to get the personality of the users by inferring it from the social activities they do in order to drive them to the interactive processes they should prefer. This may happens in a wide set of situations, when they are deepened in a collaborative learning experience, in an information retrieval problem, in an e-commerce process or in a general searching activity. We defined a complete model to realize an adaptive system that may interoperate with information systems and that is able to instantiate for all the users the processes and the interfaces able to give them the best feeling and to the system the highest possible performance.

Keywords: Adaptive system; Collaborative learning; Interaction processes; Neural networks; Personality; Social networks

DOI: 10.1016/j.chb.2014.10.058, Elsevier Ltd.

Article BibTeX

Abstract: The use of the emotional language of stories and the amplification of the empathic driver thanks to the identification with story characters, makes the storytelling a valuable educational approach, especially for children. In accordance with embodied and situated cognition theories, manipulative storytelling proposes interactive environments where it is also possible for learners to manipulate the story through objects and tangible interfaces. In line with this vision, we propose in this paper a new model enabling the design and the execution of educational stories for children aged from 3 to 6. Stories are seen as sequences of missions: game experiences where children can interact to reach the educational objective. A re-mediation strategy, able to adapt the story on three different axis (immediacy-hypermediation, similarity-dissimilarity and aggregation-disaggregation) on the basis of assessment results, is also presented. A proof of concept based on the popular Brother Grimm's Hansel and Gretel tale is then discussed to demonstrate the capabilities of the model in the construction and deconstruction of the building blocks of a story.

Keywords: Augmented narrative; Digital storytelling; Embodied and situated cognition; Re-mediation

DOI: 10.3991/ijet.v10i7.4623, Kassel University Press GmbH

Article BibTeX

Abstract: This paper presents a methodology for helping citizens obtain guidance and training when submitting a natural language description of a legal case they are interested in. This is done via an automatic mechanism, which firstly extracts relevant legal concepts from the given textual description, by relying upon an underlying legal ontology built for such a purpose and an enrichment process based on common-sense knowledge. Then, it proceeds to generate a training path meant to provide citizens with a better understanding of the legal issues arising from the given case, with corresponding links to relevant laws and jurisprudence retrieved from an external legal repository. This work describes the creation of the underlying legal ontology from existing sources and the ontology integration algorithm used for its production; besides, it details the generation of the training paths and reports the results of the preliminary experimentation that has been carried out so far. This methodology has been implemented in an Online Dispute Resolution (ODR) system that is part of an Italian initiative for assisted legal mediation.

Keywords: Adaptive learning systems; Knowledge representation; Online dispute resolution; Ontology engineering; Ontology integration; Semantic search; Text analysis

DOI: 10.3991/ijet.v10i7.4609, Kassel University Press GmbH

Article BibTeX

Abstract: Context-aware e-learning is an educational model that foresees the selection of learning resources to make the e-learning content more relevant and suitable for the learner in his/her situation. The purpose of this paper is to demonstrate that an ontological approach can be used to define leaning contexts and to allow contextualizing learning experiences finding out relevant topics for each context. To do that, we defined a context model able to formally describe a learning context, an ontology-based model enabling the representation of a teaching domain (including context information) and a methodology to generate personalized and context-aware learning experiences starting from them. Based on these theoretical components we improved an existing system for personalized e-learning with contextualisation features and experimented it with real users in two University courses. The results obtained from this experimentation have been compared with those achieved by similar systems.

Keywords: Knowledge representation; Learning context; Learning design; Terms-adaptive learning systems

DOI: 10.3991/ijet.v9i7.3666, Kassel University Press GmbH

Article BibTeX

Abstract: Getting citizens prepared to emergencies, and especially children, is an essential issue which requires special attention in the educational process. Many evidences show that misconceptions about natural disaster and incorrect beliefs are often the basis for misguided actions that can lead to inefficient behaviours in case of dangerous events. Then school has a major role in the development of 'disaster-aware' citizens, since it is asked to design appropriate resources and select suitable methods able to guarantee retention and progression of the learning process. Teaching emergency preparedness involves studying several complex topics and more than some studies have shown that storytelling can be an effective method for teaching subjects that are intricate in nature. The educational technology considers research on construction of digital storytelling as an educational challenge. Digital narratives even gain noticeable importance when users' emotions are taken into account. Basing on these considerations, we propose in this work an adaptive, dynamic and narrative-based digital artefact in which emotions are used to rebalance the learners' status. We experimented this learning resource to teach earthquake preparedness in Italian secondary schools.

Keywords: Adaptive instruction; Digital storytelling; Engaged learning; Personalised learning experience; Risk education; Role taking

DOI: 10.1504/IJCEELL.2014.060161, Inderscience Enterprises Ltd.

Article BibTeX

Abstract: The aim of a recommender system is to estimate the relevance of a set of objects belonging to a given domain, starting from the information available about users and objects. Adaptive e-learning systems are able to automatically generate personalized learning experiences starting from a learner profile and a set of target learning goals. Starting form research results of these fields we defined a methodology and developed a software prototype able to recommend learning goals and to generate learning experiences for learners using an adaptive e-learning system. The prototype has been integrated within IWT: an existing commercial solution for personalized e-learning and experimented in a graduate computer science course.

Keywords: Adaptive learning; Intelligent tutoring systems; Recommender systems

DOI: 10.1016/j.chb.2013.07.036, Elsevier Ltd.

Article BibTeX

Abstract: If on the one hand the individualised teaching approaches try to find the best sequence of learning resources capable of satisfying individual goals, preferences and contexts, the intuitive guided learning approaches, on the other hand, envisages a non-linear learning experience where each learner can chose a personal path across the material according to his/her interests and preferences. In this paper we present a model, a methodology and a software prototype that is able to combine the advantages of both approaches by introducing the concept of 'compound learning resource': complex didactic artefacts where content is organised in pages and navigation among pages is user-driven. The pages are linked through semantic connections that have a two-fold function: they guide the learners' navigation, and allow the dynamic adaptation of the resource according to learners' needs and preferences (individualisation). Experimental results with real users in a university context are also presented as well as a comparison with similar systems.

Keywords: Individualised teaching; Intuitive guided learning; Semantic link networks; Typed links

DOI: 10.1504/IJCEELL.2014.060153, Inderscience Enterprises Ltd.

Article BibTeX

Abstract: Over the past years the concept of role in distance education has become a promising construct for analysing and facilitating collaborative processes and outcomes. Designing effective collaborative learning processes is a complex task that can be supported by existing good practices formulated as pedagogical patterns or scripts. Over the past years, the research on technology enhanced learning has shown that collaborative scripts for learning act as mediating artefacts not only designing educational scenarios but also structuring and prescribing roles and activities. Conversely, existing learning systems are not able to provide dynamic role management in the definition and execution of collaborative scripts. This work proposes the application of Social Network Analysis in order to evaluate the expertise level of a learner when he/she is acting, with an assigned role, within the execution of a collaborative script. Semantic extensions to both IMS Learning Design and Information Packaging specifications are also proposed to support roles management.

Keywords: e-Learning; Learner profile; Learning design; Role management; Social network analysis

DOI: 10.3991/ijet.v9i7.3719, Kassel University Press GmbH

Article BibTeX

Abstract: In March 2011 the Italian Government introduced mandatory pre-trial mediation of civil and commercial cases. The Italian mediation model is capable of sensibly speed-up the settlement of disputes but, on the other end, citizens need to be sensitized to the benefits of mediation and must be trained on how mediation works and how to access it. The purpose of this paper is to describe a learning model based on Storytelling and its application in the context of training for civil mediation helping to build challenging training resources that explain, to common citizens with little or no background about legal topics, concepts related to legal mediation in general and in specific areas like e-commerce and civil liability. The defined model has been contextualized with respect to relevant literature and implemented through the development of two software components that have been integrated in an existing e-learning environment.

Keywords: Storytelling, Narrative Based Learning, Adaptive Learning, Legal Education, Legal Mediation

ISSN: 16457641, International Association for the Development of the Information Society

Article BibTeX

Abstract: Over the last decade, the interest in disaster education has grown rapidly. Several studies demonstrate that effective results can be obtained in this field only with instructional methods able to motivate the learner and to support them in practicing skills by means of narrative situations. The narrative is a privileged method that can help developing cognitive skills, organize knowledge and support the construction of meaning. In this paper we present a novel adaptive storytelling model defined in the context of ALICE project and its contextualization in the field of disaster education. The defined model aims at maximizing learner's understanding and development of concepts fostering the "learning in action" and problem solving skills in natural disaster contexts by combining direct experience, observation, discovery and action. In particular the model arises motivation in the story and creatively engage learners in finding solutions to a problem and building personal responsibility. The experimentation results are encouraging and confirm that the storytelling offers higher engagement than the traditional practicing methods.

Keywords: Affective learning; Cognitive process; Digital storytelling; Emergency in education; Empirical evidences

ISSN: 18266223, Italian e-Learning Association

Article BibTeX

Abstract: Searching through the limitless amount of information and resources available on the web poses a serious problem of information overload. Knowledge and semantic technologies may offer a solution in this regard. This paper illustrates a methodology for user modeling that describes user profiles and backgrounds in the use of a semantic repository for Special Education called Knowledge Hub (KH). The main functionalities and resource categories of KH are described.knowledge by accessing, sharing and collaborating with others in knowledge development.

Keywords: Homebound education, Semantic repository, ICF (International Classification for Functioning), User modelling, Web research

ISSN: 1970061X, Istituto per le Tecnologie Didattiche

Article BibTeX

Abstract: The Computer Supported Collaborative Learning (CSCL) is a research domain whose methodological instances are vaguely recognized and even more rarely modeled. The purpose of this paper is to present a new approach for the construction of dynamic collaborative learning experiences and their devolution inside an Intelligent Tutoring System. The presented approach is based on the concept of "pedagogical templates," instructional artifact based on the CSCL scripting used to design learning experiences by applying principles of participatory learning and social media. In order to experiment this approach, a tool purposed to design and execute dynamic collaborative learning experiences has been developed and experimented in formal e-learning settings.

Keywords: Adaptive learning; Computer Supported Collaborative Learning (CSCL) scripts; Learning design; Learning experiences; Learning methods; Pedagogical templates

DOI: 10.4018/jec.2013010103, IGI Global

Article BibTeX

Abstract: In the knowledge society the ultimate goal of education is not only to make learners learn but mostly to grow a correct learning behaviour that creates the best conditions for them to reach learning goals in a controlled and directed way. In many cases, a lack of self-regulatory skills is the main obstacle to adequate regulation and a new class of learning tools, named metacognitive tools, is needed. In this work we present a novel solution for self-regulated learning that tries to solve this issue by recommending feasible learning goals covering explicit and implicit learning needs and by generating individualized learning experiences based on recommended goals.

Keywords: Intelligent tutoring systems; Recommender systems; Self regulated e-learning

ISSN: 0949149X, Tempus Publications

Article BibTeX

Abstract: The Semantic Web seems to offer great opportunities for educational systems aiming to accomplish the AAAL: Anytime, Anywhere, Anybody Learning. In this scenario, two different research projects are here introduced: CADDIE (Content Automated Design & Development Integrated Editor), developed at the DIST of the University of Genoa, and IWT (Intelligent Web Teacher), developed at the DIIMA of the University of Salerno, each of them characterized by the use of ontologies and semantic technologies in order to support instructional design and personalized learning processes. The former aims to develop a learning resources and instructional paths authoring tool based on a logical and abstract annotation model, created with the goal of guaranteeing the flexibility and personalization of instructional design, the reusability of teaching materials and of the related whole knowledge structures. The latter represents an innovative e-learning solution able to support teachers and instructional designers to model educational domains knowledge, users' competences and preferences by a semantic approach in order to create personalized and contextualized learning activities and to allow users to communicate, to cooperate, to dynamically create new content to deliver and information to share as well as enabling platform for e-learning 2.0.

ISSN: 18266223, Italian e-Learning Association

Article BibTeX

Abstract: Il Web Semantico appare offrire interessanti opportunità nell’ambito dei sistemi educativi per soddisfare il principio dell’ “apprendimento per tutti, in qualunque momento e in ogni luogo”. In linea con questo principio, in questo lavoro vengono discussi due progetti di ricerca: CADDIE (Content Automated Design & Development Integrated Editor), sviluppato presso il DIST dell’Università di Genova, e IWT (Intelligent Web Teacher), sviluppato presso il DIIMA dell’Università di Salerno, entrambi caratterizzati dall’uso di ontologie e tecnologie semantiche per supportare la progettazione didattica e processi di apprendimento personalizzati. Il primo mira allo sviluppo di un sistema autore per la progettazione di risorse per l’apprendimento e percorsi didattici basato su un modello di anno􏰂a􏰃ione logico e as􏰂ra􏰂􏰂o, crea􏰂o con l􏰄obie􏰂􏰂i􏰅o di garan􏰂ire la 􏰆essibili􏰂􏰇 e la personalizzazione dei processi di progettazione didattica, la riusabilità dei materiali educativi e delle relative strutture di conoscenza. Il secondo rappresenta una soluzione innovativa per l’e-learning in grado di supportare la modellazione di domini di conoscenza, delle competenze e delle preferenze degli 􏰀􏰂en􏰂i, 􏰂rami􏰂e 􏰀n approccio seman􏰂ico al 􏰁ne di creare a􏰂􏰂i􏰅i􏰂􏰇 di apprendimen􏰂o personali􏰃􏰃a􏰂e e contestualizzate, e in grado di consentire agli utenti di comunicare, cooperare, e creare dinamicamente nuovi contenuti da distribuire e condividere.

ISSN: 18266223, Italian e-Learning Association

Article BibTeX

Abstract: Intelligent e-learning systems have revolutionized online education by providing individualized and personalized instruction for each learner. Nevertheless, until now very few systems were able to leave academic laboratories and be integrated into real commercial products. One of these few exceptions is the Learning Intelligent Advisor (LIA) described in this article, built on results coming from several research projects and currently integrated in a complete e-learning solution named Intelligent Web Teacher (IWT). The purpose of this article is to describe how LIA works and cooperates with IWT in the provisioning of individualized e-learning experiences. Defined algorithms and underlying models are described as well as architectural aspects related to the integration in IWT. Results of experimentations with real users are discussed to demonstrate the benefits of LIA as an add-on in online learning.

Keywords: Course sequencing; Knowledge representation; Learner modelling

DOI: 10.1080/10494820902924912, Taylor & Francis Ltd.

Article BibTeX

Abstract: This paper outlines an original approach to e-learning systems which integrates the most recent results in the field of human-computer interaction. Notably it will show the applicability of multimodal, attentive, affective and perceptual user interfaces to monitor the students' behavior during their interaction with an e-learning system, in order to measure their attention level and involvement and promptly provide the necessary support to carry out an effective learning process.

Keywords: Affective user interface; Attentive use interface; E-learning; Multimodal; Perceptual user interface

ISSN: 18266223, Italian e-Learning Association

Article BibTeX

Abstract: In questo articolo si delinea un approccio originale all’interazione con i sistemi di e-learning che integra i più recenti risultati della human-computer interaction. In particolare si mostra l’applicabilità delle multimodal, attentive, affective e perceptual user interface per monitorare i comportamenti dello studente durante l’interazione con un sistema di e-learning con l’obiettivo di misurarne il livello di attenzione e coinvolgimento e di fornirgli tempestivamente il necessario supporto per attuare un processo di apprendimento efficace.

Keywords: Affective user interface; Attentive use interface; E-learning; Multimodal; Perceptual user interface

ISSN: 18266223, Italian e-Learning Association

Article BibTeX

Abstract: In the context of the European Commission Project BEinGRID (FP6), the authors have defined a set of design patterns to develop software components based on service-oriented grid technologies. Some of these patterns have been used to improve the software components of a service-oriented grid middleware named GRid-based Application Service Provision (GRASP) that the authors have defined, designed and implemented in the frame of a former homonymous European Commission Project (FP5). The main improvement of GRASP due to the application of the BEinGRID design patterns is the support for the creation and life cycle management of Virtual Organisations (VOs). This paper presents the authors’ experience and lessons learnt in adopting the GRASP middleware to set up a Business-to-Business (B2B) federated environment supporting collaboration among enterprises. The concrete case study relates to online gaming applications and the adoption of the software as a service business model to provide gaming applications. In addition, a set of lessons learnt during the analysis of several Business Experiments (BEs) of the BEinGRID project are reported.

Keywords: B2B; business-to-business; grid; service-oriented architecture; SOA; virtual organisation

DOI: 10.1504/IJKL.2009.027897, Inderscience Enterprises Ltd.

Article BibTeX

Abstract: This paper presents an approach to automatic course generation and student modeling. The method has been developed during the European funded projects Diogene and Intraserv, focused on the construction of an adaptive e-learning platform. The aim of the platform is the automatic generation and personalization of courses, taking into account pedagogical knowledge on the didactic domain as well as statistic information on both the student's knowledge degree and learning preferences. Pedagogical information is described by means of an innovative methodology suitable for effective and efficient course generation and personalization. Moreover, statistic information can be collected and exploited by the system in order to better describe the student's preferences and learning performances. Learning material is chosen by the system matching the student's learning preferences with the learning material type, following a pedagogical approach suggested by Felder and Silverman. The paper discusses how automatic learning material personalization makes it possible to facilitate distance learning access to both able-bodied and disabled people. Results from the Diogene and Intraserv evaluation are reported and discussed.

Keywords: Automatic course generation and personalization; E-learning; Human-Computer interaction; Learning Styles

DOI: 10.1007/s10209-007-0101-0, Springer-Verlag GmbH

Article BibTeX

Abstract: Purpose - The purpose of this paper is to propose an innovative approach for providing an answer to the emerging trends on how to integrate e-learning efficiently in the business value chain in medium and large enterprises. Design/methodology/approach - The proposed approach defines methodologies and technologies for integrating technology-enhanced learning with knowledge and human resources management based on a synergistic use of knowledge models, methods, technologies and approaches covering different steps of the knowledge life-cycle. Findings - The proposed approach makes explicit and supports, from the methodological, technological and organizational points of view, mutual dependencies between the enterprise's organizational learning and the business processes, considering also their integration in order to allow the optimization of employees' learning plans with respect to business processes and taking into account competencies, skills, performances and knowledge available inside the organization. Practical implications - This mutual dependency, bridging individual and organizational learning, enables an improvement loop to become a key aspect for successful business process improvement (BPI) and business process reengineering (BPR), enabling closure of, at the same time, the learning and knowledge loops at individual, group and organization levels. Originality/value - The proposed improvements are relevant with respect to the state of the art and respond to a real need felt by enterprises and further commercial solutions and research projects on the theme.

Keywords: Human resource management; Learning; Project management

DOI: 10.1108/13673270810913621, Emerald Publishing Ltd.

Article BibTeX

Abstract: Quella del Project Manager è una professione emergente nel campo dell’Information Technology e sempre più aziende scelgono di affidarsi a professionisti certificati capaci di applicare approcci e processi standard alla gestione dei progetti. Dopo una breve introduzione al Project Management, l’articolo descriverà i principali standard del settore ed i relativi sistemi di certificazione mettendone a confronto pregi e difetti.

ISSN: 11238526, Gruppo Editoriale Infomedia

Article BibTeX

Abstract: Le ontologie sono uno strumento sempre più diffuso tra gli sviluppatori Web per i vantaggi che offrono nella condivisione delle informazioni. In questo mini-corso di tre lezioni cercheremo, attraverso un approccio pragmatico basato su esempi, di introdurre il lettore alla realizzazione di ontologie ed al loro utilizzo nell’ambito di applicazioni Java. In questa prima puntata mostreremo in particolare come definire una semplice ontologia OWL, introducendo anche concetti elementari di modellazione della conoscenza

ISSN: 11238526, Gruppo Editoriale Infomedia

Article BibTeX

Abstract: Prosegue la trattazione delle ontologie e delle loro applicazioni informatiche. Vedremo varie tipologie di proprietà supportate da OWL e ulteriori metodi di definizione delle classi, e molto altro ancora.

ISSN: 11238526, Gruppo Editoriale Infomedia

Article BibTeX

Abstract: Questo terzo articolo conclude la breve trattazione sulle ontologie e sulle loro applicazioni informatiche. Utilizzando un taglio più pragmatico rispetto ai precedenti, si vedrà come realizzare applicazioni ontology-based utilizzando il framework open source Jena di HP Labs.

ISSN: 11238526, Gruppo Editoriale Infomedia

Article BibTeX

Abstract: L’e-learning sta acquisendo importanza sempre maggiore negli ambienti didattico/formativi moderni grazie ai suoi innegabili vantaggi rispetto alla tradizionale formazione in aula. Purtroppo le piattaforme di elearning attualmente esistenti sulla scena tendono a sfruttare la tecnologia solo come veicolo dell’esperienza formativa piuttosto che come regista della stessa. Il presente articolo descrive IWT, una piattaforma di e-learning che si propone di superare questo limite mirando a personalizzare l’apprendimento sulle reali esigenze e preferenze dell’utente ed a garantire estensibilità e flessibilità non solo al livello dei contenuti ma anche nelle funzionalità e soprattutto, a livello più alto, nelle strategie e nei modelli. Dopo un’introduzione sui limiti degli attuali sistemi di e-learning (sezione 1) verrà data una panoramica di IWT (sezione 2) e verranno di seguito descritte le caratteristiche “intelligenti” ed i modelli che hanno permesso la loro implementazione (sezioni 3, 4 e 5). Infine si concluderà facendo il punto sullo stato attuale della ricerca su IWT ed ipotizzando possibili scenari futuri (sezione 6).

Associazione Italiana per l'Intelligenza Artificiale

Article BibTeX

Abstract: Astronomical wide-field imaging performed with new large-format CCD detectors poses data reduction problems of unprecedented scale, which are difficult to deal with using traditional interactive tools. We present here NEXT (Neural Extractor), a new neural network (NN) based package capable of detecting objects and performing both deblending and star/ galaxy classification in an automatic way. Traditionally, in astronomical images, objects are first distinguished from the noisy background by searching for sets of connected pixels having brightnesses above a given threshold; they are then classified as stars or as galaxies through diagnostic diagrams having variables chosen according to the astronomer's taste and experience. In the extraction step, assuming that images are well sampled, NEXT requires only the simplest a priori definition of 'what an object is' (i.e. it keeps all structures composed of more than one pixel) and performs the detection via an unsupervised NN, approaching detection as a clustering problem that has been thoroughly studied in the artificial intelligence literature. The first part of the NEXT procedure consists of an optimal compression of the redundant information contained in the pixels via a mapping from pixel intensities to a subspace individualized through principal component analysis. At magnitudes fainter than the completeness limit, stars are usually almost indistinguishable from galaxies, and therefore the parameters characterizing the two classes do not lie in disconnected subspaces, thus preventing the use of unsupervised methods. We therefore adopted a supervised NN (i.e. a NN that first finds the rules to classify objects from examples and then applies them to the whole data set). In practice, each object is classified depending on its membership of the regions mapping the input feature space in the training set. In order to obtain an objective and reliable classification, instead of using an arbitrarily defined set of features we use a NN to select the most significant features among the large number of measured ones, and then we use these selected features to perform the classification task. In order to optimize the performance of the system, we implemented and tested several different models of NN. The comparison of the NEXT performance with that of the best detection and classification package known to the authors (SEXTRACTOR) shows that NEXT is at least as effective as the best traditional packages.

Keywords: Catalogues; Methods: data analysis; Techniques: image processing

DOI: 10.1046/j.1365-8711.2000.03700.x, Blackwell Publishing Ltd.

Article BibTeX

Abstract: In this paper a hybrid system and a hierarchical neural-net approaches are proposed to solve the automatic labeling problem for unsupervised clustering. The first method consists in the application of nonneural clustering algorithms directly to the output of a neural net; the second one is based on a multilayer organization of neural units. Both methods are a substantial improvement with respect to the most important unsupervised neural algorithms existing in literature. Experimental results are shown to illustrate clustering performance of the systems.

Keywords: Automated labeling; Clustering; Hierarchical neural networks; Hybrid neural networks

DOI: 10.1109/72.737509, Institute of Electrical and Electronics Engineers Inc.

Article BibTeX

Abstract: The rapid expansion of the Internet of Things (IoT) has brought significant security challenges, primarily due to vulnerabilities in the firmware of IoT and network devices, which is predominantly written in low-level programming languages such as C and C++. Traditional vulnerability detection techniques, including static and dynamic analysis, rely on manual rules and face limitations with modern software complexity. Machine learning and deep learning offer promising alternatives by identifying vulnerability patterns from data but require extensive labeled datasets and may struggle to generalize to new code patterns, particularly in the diverse and evolving IoT landscape. This work evaluates open-source Large Language Models (LLMs) for zero-shot vulnerability detection in C and C++ using prompt engineering, benchmarking their performance against traditional static analysis tools and deep learning methods. Leveraging a newly introduced real-world test set, our experimental results confirm the inherent complexity of the vulnerability detection task and highlight the importance of further research aimed at enhancing the effectiveness of existing approaches in realistic contexts.

BibTeX

Abstract: In our interconnected world, the dissemination of misinformation has emerged as a crucial and pressing challenge. Social media platforms and technological advancements facilitate the proliferation of false information, thereby leading to significant repercussions on societal, political, and economic fronts. Recent research suggests using Graph Neural Networks (GNNs) to represent relationships among network actors and consequent prediction activities like pinpointing influential nodes and detecting communities. This work exploits a GNN to make link predictions on a graph representing information about misinformation tweets, their authors, and their spread. The objective is to comprehensively investigate the specific attributes of online pathways that compel users to share and amplify inaccurate information. In this sense, starting from an existing dataset of misinformation tweets, the proposed approach first applies an explainability method to each prediction, then, through frequent itemset mining, tries to detect patterns among collected explanations. Results of qualitative and quantitative research questions mainly demonstrate the contribution of interpersonal aspects to misinformation tweets spreading. To the best of our knowledge, this is the first approach exploiting a combination of Explainable Artificial Intelligence (xAI) and Data Mining to GNNs in fake news spreading analysis for prevention and mitigation purposes.

Keywords: Cognitive Security, xAI, GNN, Information Disorder

DOI: 10.1007/978-3-031-64779-6_13, Springer Nature AG

BibTeX

Abstract: Student Performance Prediction (SPP) models and tools are useful for quickly identifying at-risk students in online courses and enable the provi-sion of personalized learning plans and assistance. Additionally, they give educators and course managers the information they need to recognize the programs that require improvement. High accuracy is essential for such tools but understanding the reasons of their predictions is equally im-portant to ensure fairness and build trust in their adoption. Although many SPP models and tools have been proposed so far by different researchers, very few of them take explainability into account. This research proposes an SPP approach that is both effective and explainable. Based on demo-graphic, administrative, engagement, and intra-course outcome data, it ena-bles the prediction of student performance in terms of success/failure and final grade. It supports multiple machine learning models and includes post-hoc techniques for explainability capable of justifying the behavior of the whole system as well as its individual predictions.

Keywords: Learning Analytics, Educational Data Mining, Student Performance Predic-tion, Explainable Artificial Intelligence

DOI: 10.1007/978-3-031-41637-8_52, Springer Nature AG

BibTeX

Abstract: Massive Open Online Courses (MOOCs) are a teaching method that uses Virtual Learning Environments to reach a vast number of students, thus, facilitating access to education by making costs more appealing because of scale economics. Consequently, Tutors' and teachers' interaction is crucial for the successful development of a MOOC. However, due to the size and diversity of the student body in MOOCs, instructors and tutors need help to keep an eye on them carefully and intervene as needed. This work aims to set and validate an architecture for pedagogical interventions in online learning based on how a student feels, using the automatically detected subjective attributes obtained through interactions in the learning management systems. The architecture is based on three layers: (i) the Application layer for managing interaction with the Virtual Learning Environment; (ii) the Knowledge layer for the automatic textual classification, the attributes identification, knowledge representation through ontology and selection of pedagogical intervention actions; and (iii) the Intervention layer carries out pedagogical interventions through an autonomous conversational agent. The proposed architecture can identify the necessary pedagogical intervention, and the conversational agent can make decisions and adopt an approach more suited to the student's needs. The proposed architecture was evaluated using the Stanford MOOC dataset, comprised of 11,042 participants who posted 29,604 messages from eleven courses. The preliminary evaluation results conclude that our approach is able to significantly support the tutor in MOOC environments as 65\% of the student posts were automatically managed by the system while only the 35\% left needed tutor attention.

DOI: 10.1007/978-3-031-29056-5_20, Springer Nature AG

BibTeX

Abstract: Discussion forums are popular tools in Massive Open Online Courses (MOOCs), used by students to express feelings, exchange ideas, and ask for help. Unfortunately, the huge number of enrolled students hinders educational scaffolding activities, including the active participation of instructors in discussion forums. Therefore, students seeking to clarify the concepts learned may not receive the answers they need, reducing engagement and promoting dropout. This work presents a methodology for supporting learners within discussion forums, by analyzing conversations among students and providing them with recommendations in terms of relevant learning resources. The methodology involves several steps: the initial definition of an ontology that details the topics of the course, the real-time analysis of student posts within the discussion forums to extract different attributes including intent of the post, the concepts it is about, the sentiment and the level of urgency and confusion. The extracted information is then used by a rules-based mechanism to assess whether the learner needs a recommendation. If so, the system suggests the most suitable learning resources. The paper also includes an initial evaluation of the proposed methodology.

Keywords: Natural Language Processing, Recommender Systems, Massive Open Online Courses

DOI: 10.1007/978-3-031-21569-8_46, Springer Nature AG

BibTeX

Abstract: Massive Open Online Courses (MOOCs) are a teaching modality that aims to reach a large number of students using Virtual Learning Environments. In these courses, the intervention of tutors and teachers is essential to support students in the teaching-learning process, answer questions about their content, and provide engagement for students. However, as these courses have a vast and diverse audience, tutors and teachers find it difficult to monitor them closely and efficiently with prompt interventions. This work proposes an architecture to favor the construction of knowledge for students, tutors, and teachers through autonomous interference and recommendations of educational resources. The architecture is based on a conversational agent and an educational recommendation system. For the training of predictive models and extraction of semantic information, ontology and logical rules were used, together with inference algorithms and machine learning techniques, which act on a dataset with messages exchanged between course forum participants in the humanities, medicine, and education fields. The messages are classified according to the type (question, answer, and opinion) and parameters about feeling, confusion, and urgency. The architecture can infer the moment in which a student needs help and, through a Conversational Recommendation System, provides the student with the opportunity to revise his or her knowledge on the subject. To help in this task, the architecture can provide educational resources via an autonomous agent, contributing to reducing the degree of confusion and urgency identified in the posts. Initial results indicate that integrating technologies and resources, complementing each other, can support the students and help them succeed in their educational training.

Keywords: Massive Open Online Courses, Recommender System, Conversational Agent

DOI: 10.1007/978-3-030-90677-1_36, Springer Nature AG

Article BibTeX

Abstract: This research presents a comprehensive methodological approach to detect and analyze student engagement within the context of online education. It is supported by e-learning systems, and is based on a combination of semantic analysis, applied to the students’ posts and comments, with a machine learning-based classification, performed upon a range of data derived from the students’ usage of the online courses themselves. This is meant to provide teachers and students with information related to the relevant aspects making up the students’ engagement, such as sentiment, urgency, confusion within a given course as well as the probability for students to keep their involvement in or to drop out from the courses altogether.

DOI: 10.1007/978-3-030-61105-7_21, Springer Nature AG

Article BibTeX

Abstract: Discussion forums are among the most common interaction tools offered by MOOCs. Nevertheless, due to the high number of students enrolled and the relatively small number of tutors, it is virtually impossible for instructors to effectively monitor and moderate them. For this reason, teacher-guided instructional scaffolding activities may be very limited, even impossible in such environments. On the other hand, students who seek to clarify concepts may not get the attention they need, and lack of responsiveness often favors abandonment. In order to mitigate these issues, we propose in this work a multi-attribute text categorization tool able to automatically detect useful information from MOOC forum posts including intents, topics covered, sentiment polarity, level of confusion and urgency. Extracted information may be used directly by instructors for moderating and planning their interventions as well as input for conversational software agents able to engage learners in guided, constructive discussions through natural language. The results of an experiment aimed at evaluating the performance of the proposed approach on an existing dataset are also presented, as well as the description of an application scenario that exploits the extracted information within a conversation agents’ framework.

DOI: 10.1007/978-3-030-33509-0_47, Springer Nature AG

Article BibTeX

Abstract: Due to the high number of students enrolled and the relatively small number of available tutors, the assessment of complex assignments is deemed as one of the most critical tasks in Massive Open On-line Courses (MOOCs). Peer assessment is becoming an increasingly popular tool to face this problem and many approaches have been proposed so far to make its outcomes more reliable. A promising approach is FOPA (Fuzzy Ordinal Peer Assessment) that adopts and integrates models coming from Fuzzy Set Theory and Group Decision Making. In this paper we propose a FOPA extension supporting multi-criteria assessment based on rubrics. Students are asked to rank a small number of peer submissions against specified criteria, provided rankings are then transformed in fuzzy preference relations, expanded to obtain missing values and aggregated to establish a global ranking between students’ works with respect to each criterion and globally. The absolute grades of all submissions are then calculated.

DOI: 10.1007/978-3-319-98557-2_34, Springer Nature AG

Article Presentation BibTeX

Abstract: Peer assessment has been used for many years as a tool to improve learning outcomes but, only recently, it is becoming an increasingly used support also in students evaluation. Many approaches have been proposed so far to make peer assessment as reliable as possible even in case of incorrect or inaccurate evaluations proposed by students. Among these approaches, Fuzzy Ordinal Peer Assessment (FOPA) relies on ordinal evaluations (rather than cardinal ones) and on the application of models coming from Fuzzy Set Theory and Group Decision Making. FOPA has already demonstrated good results in in-silico experiments. To complement these results, in the work presented in this paper, we experiment the same model in a University context to support formative evaluation. Obtained results show better performance of FOPA with respect to competitor models and a general attitude of peer assessment models to approximate instructor ratings.

DOI: 10.1007/978-3-319-69835-9_52, Springer International Publishing AG

Article Presentation BibTeX

Abstract: The increase in popularity of Massive Open Online Courses (MOOCs) requires the resolution of new issues related to the huge number of participants to such courses. Among the main challenges is the difficulty in students' assessment, especially for complex assignments, such as essays or open-ended exercises, which is limited by the ability of teachers to evaluate and provide feedback at large scale. A feasible approach to tackle this problem is peer assessment, in which students also play the role of assessor for assignments submitted by others. Unfortunately, as students may have different expertise, peer assessment often does not deliver accurate results compared to human experts. In this paper, we describe and compare different methods aimed at mitigating this issue by adaptively combining peer grades on the basis of the detected expertise of the assessors. The possibility to improve these results through optimized techniques for assessors' assignment is also discussed. Experimental results with synthetic data are presented and show better performances compared to standard aggregation operators (i.e. median or mean) as well as to similar existing approaches.

Keywords: e-Learning; MOOCs; Peer assessment

DOI: 10.1109/3PGCIC.2015.7, Institute of Electrical and Electronics Engineers Inc.

Article BibTeX

Abstract: The preparation of evacuation plans for public buildings and the related training is mandated by law in many countries. The traditional approaches for providing people with the correct emergency information tend to be based on long, written instructions, posted on doors and walls that are not necessarily read by occupants and on evacuation drills that are costly, rarely performed and focused on specific scenarios. To overcome these limits we propose an engaging approach for evacuation training, targeted towards primary and secondary school students and based on adaptive serious games. The student is immersed in a virtual environment representing his/her school during an emergency with the aim of evacuating and adopting the correct behaviour. Any performed action is evaluated by the system, feedback is provided immediately and also when the game ends. Recovery training material is automatically arranged and provided to the student to explain any errors he/she made and to help reach better subsequent performances. Ontologies have been used to represent emergency skills and to relate them to possible actions within the game environment. Action-based assessment and sequencing techniques have been applied to arrange useful training material.

Keywords: Adaptive learning systems; Emergency training; Knowledge representation; Serious games

DOI: 10.1109/INCoS.2015.32, Institute of Electrical and Electronics Engineers Inc.

Article Presentation BibTeX

Abstract: The paper reports the results related to the application of the FIBAC cultural re-mediation model for the development of an interactive educational experience. The FIBAC model remediates a cultural resource not only with regard to media and the ICT but mainly with regard to its meaning and associated knowledge generating, thus, knowledge paths able to add new meaning to a cultural resource. To contextualize this model for educational and scientific museums, we frame the re-mediation in a didactic model based on the Kolb learning cycle and Brousseau theory of didactic situations, namely the Virtual Scientific Experiment. We evaluated our results with a Proof-of-Concept based on a physic experiment exposed in a real Italian scientific museum.

Keywords: Cultural re-mediation; Didactic models; Digital storytelling; Virtual scientific experiments

DOI: 10.1109/INCoS.2014.56, Institute of Electrical and Electronics Engineers Inc.

Article BibTeX

Abstract: The paper describes a research aimed at defining theoretical and technological components enabling a citizen to obtain guidance and training on legal concepts starting from a textual description of a case. The defined system is able to detect relevant legal concepts from the textual description also relying on a ontology and on the enrichment of the case text with common-sense knowledge. Detected concepts are used to generate a training path aimed at providing the citizen with the basis for understanding legal issues the case deals with. The training path is then enriched with legal information like relevant laws and jurisprudence retrieved on an external legal repository. This research is part of an initiative aimed at defining innovative technologies to support on-line mediation.

Keywords: Adaptive learning systems; Knowledge representation; Online dispute resolution; Semantic search; Text analysis

DOI: 10.1109/INCoS.2014.32, Institute of Electrical and Electronics Engineers Inc.

Article Presentation BibTeX

Abstract: We describe a methodology for the automatic classification of legal cases expressed in natural language, which relies on existing legal ontologies and a commonsense knowledge base. This methodology is founded on a process consisting of three phases: an enrichment of a given legal ontology by associating its terms with topics retrieved from the Wikipedia knowledge base; an extraction of relevant concepts from a given textual legal case; and a matching between the enriched ontological terms and the extracted concepts. Such a process has been successfully implemented in a corresponding tool that is part of a larger framework for self-litigation and legal support for the Italian law.

Keywords: Text analysis; Law

DOI: 10.1145/2611040.2611048, Association for Computing Machinery

Article BibTeX

Abstract: The purpose of this paper is to describe a learning model based on Storytelling and its application in the context of legal education helping build challenging training resources that explain, to common citizens with little or no background about legal topics, concepts related to Legal Mediation in general and in specific areas like e-commerce and civil liability. The defined model has been contextualized with respect to relevant literature and implemented through the development of two software components that have been integrated in an existing e-learning environment. Such an e-learning environment is itself a module of a greater experimental system for on-Line Legal Mediation named eJRM. Copyright © 2014 IADIS Press All rights reserved.

Keywords: Adaptive learning; Legal education; Legal mediation; Narrative based learning; Storytelling

ISBN: 978-989-8704-08-5, International Association for the Development of the Information Society

Article BibTeX

Abstract: The construction of personalized courses taking into account needs and preferences of each learner is one of the most studied topics within the field of adaptive learning systems. Such systems assume that learning needs are well know by the teacher or, in self directed learning settings, that learners can easily determine and express own needs. Nevertheless, in real situations, learning needs often remain latent and, for this reason, unsatisfied. To overcome this limitation we propose in this paper a methodology and a prototype system enabling the elicitation of latent learning needs, as well as the automatic generation of learning experiences capable of satisfying such needs. The proposed methodology applies principles of recommending systems and also relies on a semantic representation of topics to be taught. The encouraging experimental results obtained with University students are also discussed.

Keywords: Adaptive learning systems; Learning needs; Recommender systems; Self regulated e-learning

DOI: 10.1109/CISIS.2013.66, Institute of Electrical and Electronics Engineers Inc.

Article Presentation BibTeX

Abstract: Learning to behave in case of natural disaster is one of the most urgent challenges in our modern society. The school plays a major role in the development of educational plans for disaster reduction, designing appropriate resources and selecting didactic methods able to guarantee the retention and progression of the learning process. The challenge for the educational institutions is to introduce new learning and teaching approaches to engage the millennial students overcoming the main issues of traditional learning experience such as lack of empowerment, exploration, participation and locus of control. In order to contribute to overcoming these limitations with respect to learners' engagement, we implemented ALICE, an innovative adaptive environment for the e-learning able to combine personalization, interaction, emotional aspects. The experimentation and validation activities reported in this paper confirms the instructional value of complex didactic resources and the impact on learning process in risk education setting.

Keywords: Adaptive learning; Complex learning resource; Emotions; Learning engagement; Risk education

DOI: 10.1109/CISIS.2013.67, Institute of Electrical and Electronics Engineers Inc.

Article BibTeX

Abstract: The main problem that characterises the context of Special Education is the availability of a large amount of available information and its real, pertinent usability. The use of software systems for the semantic annotation and retrieval of teaching resources for this field appears to be still little explored, also due to the lack of specific semantic models for information description. This paper introduces the Knowledge Hub, a semantic repository of educational and information resources for Special Education, which is able to assist practitioners and teachers in finding the most interesting and useful digital resources for each special need by combining recommendation techniques with Semantic and Social Web models and tools. The paper also describes the encouraging results of a system experimentation with real users.

Keywords: Recommender systems; Semantic repository; Special needs education

DOI: 10.1109/INCoS.2013.48, Institute of Electrical and Electronics Engineers Inc.

Article BibTeX

Abstract: We describe a system for computer-assisted writing of legal documents via a question-based mechanism. This system relies upon an underlying ontological structure meant to represent the data flow from the user's input, and a corresponding resolution algorithm, implemented within a local engine based on a Last-State Next-State model, for navigating the structure and providing the user with meaningful domain-specific support and insight. This system has been successfully applied to the scenario of civil liability for motor vehicles and is part of a larger framework for self-litigation and legal support.

Keywords: Algorithm; Civil liability; Computer-assisted writing; Data flow; Ontology

DOI: 10.3233/978-1-61499-359-9-25, IOS Press

Article BibTeX

Abstract: Individualized teaching approaches try to find the best sequence of learning resources capable of satisfying individual goals and preferences. On the other side, intuitive guided learning approaches see the learning experience as "non-linear": each learner can chose a personal path across the material according to his/her interests and preferences. In this paper we present a method and a prototype able to combine the advantages of both approaches by introducing the concept of "compound learning resource": a complex didactic artifact bringing together multiple semantically connected learning resources that can be freely browsed by the learner. Included semantic connections have a twofold function: from one side they guide the learners' navigation, from the other side they allow the dynamic reconfiguration of the resource according to learners' needs and preferences (individualization). Experimental results with real users in a University context are also presented.

Keywords: Individualized teaching; Intuitive guided learning; Semantic link networks; Typed links

DOI: 10.1109/CISIS.2012.206, Institute of Electrical and Electronics Engineers Inc.

Article Presentation BibTeX

Abstract: Context-aware e-learning is an educational model that foresees the selection of learning resources to make the elearning content more relevant and suitable for the learner in his/her situation. The research reported in this paper was purposed to improve an existing system for personalized e-learning with contextualisation features. This has been done by defining a context model, an ontology-based model to represent a teaching domain that includes contextualization information and a methodology to generate personalized and context-aware learning experiences basing on such structures.

Keywords: Adaptive e-learning; Context-aware e-learning; Knowledge representation; Learning context; Learning design

DOI: 10.1109/INCoS.2011.53, Institute of Electrical and Electronics Engineers Inc.

Article Presentation BibTeX

Abstract: Designing effective CSCL processes is a complex task that can be supported by existing good practices formulated as pedagogical patterns or script. Over the past years the TEE research has shown that CSCL script acts as Mediating Artifacts (MA) designing educational scenarios and structuring and prescribing roles and activities. This work proposes an approach, based on Social NetworkAnalysis and Semantic Web, in order to improve definition and instantiation phases of IMS-LD scripts.

Keywords: CSCL; eLearning; Learning design; Semantic Web; Social Network Analysis

DOI: 10.1109/ICALT.2011.197, Institute of Electrical and Electronics Engineers Inc.

Article Presentation BibTeX

Abstract: Nowadays, the importance of knowledge management is well understood by managers in the organizations and, at the same time, the great significance of trust, in enabling effective knowledge sharing, is emerging. Presence or lack of trust can have serious implications for organizations with respect to the quality and of their business processes. Several scientific works have confirmed the direct correlation between social-cognitive capital, in terms of competencies and experiences, and a feeling of trust in both learning and working collaborative environments. On the other hand, Competency-Based Management allows organizations to link human resources processes to competencies in order to shape its workforce capabilities and to achieve better results. Typically, employees' competencies (and proficiency levels) are stored and used by specific enterprise software, whereas the trust is not considered or left to managers' feeling. This work proposes an approach to the improvement of collaborative learning activities by refining and allowing (at workers' level) competency-finding processes through the social calculus of trust-in- competencies degree.

Keywords: Competency-based management; Corporate learning; Semantic web; Social networking; Trust

DOI: 10.1109/ICALT.2011.102, Institute of Electrical and Electronics Engineers Inc.

Article Presentation BibTeX

Abstract: Lo scritto, partendo dalla crisi vissuta dal diritto d’autore nel confronto con i nuovi strumenti tecnologici, affronta la tematica dell’applicabilità all’e-learning di alcune eccezioni o limitazioni ai diritti di riproduzione e di comunicazione al pubblico di opere dell’ingegno allorché l’utilizzo abbia esclusivamente finalità illustrativa per uso didattico. Analizzando tali eccezioni, contenute nella Direttiva Comunitaria del 22 maggio 2001 n. 29 “sull’armonizzazione di taluni aspetti del diritto d’autore nella società dell’informazione” e nella normativa italiana di recepimento, si forniranno considerazioni sulla possibilità e sulle modalità di utilizzo di materiale coperto da copyright nell’ambito di attività didattiche a distanza e basate sull’utilizzo delle nuove tecnologie.

Keywords: Diritto d’autore, Teaching exception, Riproduzione per uso didattico

ISBN: 978-8-89599-476-5, Edizioni LediPublishing

Article Presentation BibTeX

Abstract: This paper describes a work performed in the framework of the HealthOnNet project purposed to define and implement an Internet-based repository of diagnostic exams and medical reports connecting several Italian hospitals. The repository, which will be used as an historical and legal archive of clinical data, offers second opinion teleconsulting features as well as advanced categorization and filtering services. The paper is focused on this latter point and describes the process and the algorithms we defined to automatically classify medical documents (with respect to the widely adopted International Classification of Diseases and Related Health Problems of the World Health Organization) and to filter them on the basis of a user defined profile. Then it describes the developed prototype and some experimentation results.

Keywords: ICD; Information filtering; Matchmaking; Text categorization; User profiling

ISBN: 9789896740160, INSTICC Press

Article BibTeX

Abstract: The term Enterprise 2.0 applies to the use of Web 2.0 technologies as a support for business activities within the organizations. These technologies are exploited to foster inter-persons collaboration, information exchange and knowledge sharing, also outside the organization, to establish relationships based on conversational modalities rather than on traditional business communication. The vision of Enterprise 2.0 places a high value on the importance of social networks inside and outside the organization stimulating flexibility, adaptability and innovation between workers, managers, customers, suppliers and consultants. The integration between the Web 2.0 tools with traditional enterprise software, the aggregation of organization inner data with external data and the choice of adequate knowledge representations are critical aspects to be faced in order to further the growth of smart applications in the Enterprise 2.0 context. In this work we propose an approach, based on Semantic Web techniques, to relax the aforementioned critical issues.

DOI: 10.1109/CISIS.2010.54, Institute of Electrical and Electronics Engineers Inc.

Article BibTeX

Abstract: This study presents new approaches for the detection and treatment of the attention of a student by an e-learning system through the use of the information given by the implicit interaction of the student with the system and the data coming from non-invasive devices such as webcams. Furthermore, the paper proposes two models for the treatment of the attention of students to be applied to an existing e-learning environment, in order to provide personalized content to the students and thus improving their learning experience.

ISBN: 1891706284; 9781891706288, Knowledge Systems Institute

Article BibTeX

Abstract: Computer Supported Collaborative Learning and Computer Supported Cooperative Work are research domains whose methodological instances are vaguely recognized and even more rarely modeled. The goal of this paper is to present a new approach for the construction of dynamic collaborative learning experiences and their devolution inside an Intelligent Tutoring System. The presented approach is based on the pedagogical templates metaphor and also uses methodological services and opportunities given by the Web 2.0. In order to experiment the proposed approach, a tool purposed to design and execute dynamic collaborative learning experiences has been developed and experimented in formal e-learning settings.

Keywords: Adaptive learning; Collaboration; Learning design; Learning experiences; Learning methods; Template, Computer aided instruction; E-learning; Education computing; Learning systems, Design

DOI: 10.1109/INCOS.2010.29, Institute of Electrical and Electronics Engineers Inc.

Article Presentation BibTeX

Abstract: The purpose of this paper is twofold. On the one hand it aims at presenting the "pedagogical template" methodology for the definition of didactic activities, through the aggregation of atomic learning entities on the basis of pre-defined schemas. On the other hand it proposes a Web-based authoring tool to build learning resources applying a defined methodology. The authoring tool is inspired by mashing-up principles and allows the combination of local learning entities with learning entities coming from external sources belonging to Web 2.0 like Wikipedia, Flickr, YouTube and SlideShare. Eventually, the results of a small-scale experimentation, inside a University course, purposed both to define a pedagogical template for "virtual scientific experiments" and to build and deploy learning resources applying such template are presented.

Keywords: Learning design; Mashup; Web 2.0

DOI: 10.1145/1631111.1631126, Association for Computing Machinery

Article BibTeX

Abstract: The ontologies are used to state the meaning of the terms used in data produced, shared and consumed within the context of Semantic Web applications. The folksonomies instead are an emergent phenomenon of the Social Web and represent the result of free tagging of information and objects in a social environment. Both ontologies and folksonomies are considered useful mechanisms to manage the information and are pretty always exploited, independently, in several areas of interest in order to cope with different problems related to searching, filtering, categorization and organization of content within some applications for e-commerce, e-learning, e-science, etc. In our opinion the two mechanisms are not in opposition but could be synergically used. In this paper we propose an approach based on the convergence between ontologies and folksonomies in order to improve personalised e-learning processes.

ISBN: 9789898111968, INSTICC Press

Article Presentation BibTeX

Abstract: Nowadays, the use of domain ontologies in e-Learning applications is rapidly increasing due to the important role they play in knowledge representation, sharing of didactical material and content personalization. However, the ontology building processes is still extremely difficult to achieve. In this paper we present a semi-automatic process based on knowledge extraction from existing SCORM educational content aimed to speed up and facilitate the realization of domain ontologies and the breakdown of SCORM packages in fine-grained, rearrangeable learning objects appropriate for building personalized e-Learning experience.

DOI: 10.1109/ICSC.2009.69, Institute of Electrical and Electronics Engineers Inc.

Article BibTeX

Abstract: The paper presents the main findings of the ELeGI project, namely its learning model and software architecture to support the creation and execution of complex learning processes. The learning model defined in ELeGI promotes and supports a learning paradigm centred on knowledge construction using experiential based and collaborative learning approaches in a contextualised, personalised and ubiquitous way. The software architecture has been designed and developed taking into account the learning model for the personalisation of complex learning experiences. In order to validate our results, the paper presents and describes a case study relating to the implementation of a Unit of Learning for explanation of the Torricelli's law, and its execution on top of the Service OrientedArchitecture.

DOI: 10.1109/CISIS.2009.129, Institute of Electrical and Electronics Engineers Inc.

Article BibTeX

Abstract: Nowadays, the Semantic Web technologies are exploited also in the e-learning domain in order to provide personalized and adaptive learning experiences, semantic annotation of learning contents and learner profiling. The approaches of the Web 2.0, instead, are used to implement and deploy knowledge exchange services based on the concept of social collaboration. In this work, we propose an approach resulted from the convergence between Semantic Web and Social Web to manage, agilely and easily, the contingent learning needs of workers within organizations. Our intention is to support the use of natural languages to express the learning needs for either driving the automatic generation of learning units or effectively adapting learning pathways. © 2009 IEEE.

DOI: 10.1109/ICALT.2009.53, Institute of Electrical and Electronics Engineers Inc.

Article BibTeX

Abstract: The Semantic Web seems to be a challenge for educational system aiming to accomplish the AAAL: Anytime, Anywhere, Anybody Learning. In this scenario an innovative e-learning solution named IWT, Intelligent Web Teacher, coming from Italian and European research projects, actually employed in many Italian high schools, enterprises and university departments, started to do it some years ago. IWT is able to model educational domains knowledge, users’ competences and preferences by a Semantic Web approach in order to create personalized and contextualized learning activities and to allow users to communicate, to cooperate, to dynamically create new content to deliver and information to share as well as enabling platform for e-learning 2.0.

Keywords: Semantic Web-based Educational System, Personalized e-Learning, Semantic Web, Web 2.0, IWT, e-Learning 2.0, Artificial Intelligence

ISBN: 9788890358111, Italian Association for Artificial Intelligence

Article BibTeX

ISBN: 9788895028590, SIe-L

Article BibTeX

Abstract: This paper presents a Service Oriented Architecture to manage the lifecycle of a federation in a secure Business to Business (B2B) environment. The main contribution of the authors to Grid and SOA communities is related to the definition and development of a set of design patterns and software components to support the creation, management and dissolution of a federation of different administrative domains. As case of study we present the application of our components to a concrete business scenario relating to the on-line game application provision, providing also an overview of the main business benefits assessed during the evaluation of the components.

ISBN: 9781586039240, IOS Press

Article BibTeX

Abstract: The purpose of this paper is to propose an overview of the Knowledge Virtual Enterprise model, where the Virtual Enterprise vision is extended with Knowledge-based assets in order to provide an agreement model to support the interoperability among organizations. Every enterprise or organization, by itself, is a source of original knowledge that, if exploited, can contribute to its competitiveness. If this is true inside the enterprise walls, it is more relevant when extended to Virtual Enterprises, especially when they operate in a tumultuous and unsettled context, like ICT, strongly bound to the so called soft skills and even more to the capability of carrying out just-in-time knowledge takeover and transfer. In order to explain the advantages of the Knowledge Virtual Enterprise model we define some real-world business scenarios, to be executed within the context of a Knowledge Virtual Enterprise instance. The scenarios are based on the idea that several organizations could put together their competences, human resources, expertise, technologies, etc. to carry out complex project activities, requiring resources that are usually difficult to be found in a single organization. The scenarios are particularly focused on how the Knowledge Virtual Enterprise model can support personalized, contextualized, effective and efficient e-learning at work experiences. Finally, the Knowledge Virtual Enterprise model vision is concretized through the description of a feasible technological mapping between its main concerns and existing software technologies and specifications.

DOI: 10.1109/CISIS.2008.87, Institute of Electrical and Electronics Engineers Inc.

Article BibTeX

Abstract: This paper illustrates the work done and the results achieved within the ELeGI project about the orchestration and the delivery of Learning Services lying in the GRID inside an IMS Learning Design (IMS-LD) Unit of Learning and running under an enhanced version of the CopperCore Player. The added value of GRID technologies for the creation and the execution of dynamic learning experiences is evidenced as well as the experimentation performed to overcome the original IMS-LD limitation on running services is presented. The aim of the ELeGI project is to promote and support a learning paradigm centred on the knowledge construction using experiential based and collaborative learning approaches in a contextualised, personalised and ubiquitous way through the definition and implementation of a service oriented Grid based software architecture.

Article Presentation BibTeX

Abstract: Learning GRID is both a concept and a Special Interest Group of the European Network of Excellence Kaleidoscope. Kaleidoscope is a Network of Excellence funded by the European Commission which brings together European research teams in Technology Enhanced Learning (TEL). The Learning GRID Special Interest Group gathers researchers who want to contribute to an improvement of e-learning practices through the use of the Learning GRID concept. Its key idea reads as Learning Grid technology allows for a direct and personalized experience in realistic contexts and boosts creation of virtual dynamic communities. After introducing briefly Kaleidoscope, this article presents the learning GRID concept and several scenarios that this technology makes possible.

Article Presentation BibTeX

Abstract: We present a computer-based system for the automatic generation and personalization of courses. The system takes trace of the student’s behavior by analyzing the results of suitable on-line tests. The tests are used to infer information on both the student’s knowledge about the topics of the system’s domain and her/his learning preferences. Both kinds of data are stored in the Student Model and subsequently used in order to customize future courses. The pedagogical approach we have adopted refers to the Felder and Silverman’s proposal in which both learning material and students are categorized in different teaching/learning style classes and then matched together

ISBN: 0805858075, MIRA Digital Publishing

Article BibTeX

Abstract: Nowadays, the need for e-learning systems supporting a rich set of pedagogical requirements has been identified as an important issue in the field of distance learning. Several initiatives take place in order to meet this need. Maybe, the most important of these initiatives is IMS Learning Design [6] that provides a framework to depict pedagogies. Furthermore, we are aware that the provision of different learning paths tailored on learner’s characteristics and preferences guarantees the learner to reach a cognitive excellence. In this paper, we first illustrate an extension for IMS Learning Design in order to overcome its limitations forcing instructional designers only describing domain-dependent pedagogies. Then, we propose a mechanism to build units of learning by merging domainindependent pedagogies with educational objectives selected by teachers inside a specific didactic domain modelled by a graph structure called ontology. Finally, we illustrate a delivery networked infrastructure able to execute units of learning in a personalized way based on learner preferences.

British Computer Society

Article BibTeX

Abstract: We present in this paper the results of an European funded project Diogene, finished in October 2004, whose aim has been the design and the development of a distributed e-learning system able to perform several automatic actions such as course customization and information retrieval on the Semantic Web. The Diogene architecture is based on a network of specialized Organizations each of which has been realized as an independent Web Service.

British Computer Society

Article BibTeX

Abstract: In this paper we present our work on the extension of a state-of-the-art e-learning system – the Intelligent Web Teacher (IWT) – to support multimodal mobile access in order to offer a complete set of learning experiences, services and models that are able to fit the complex and variegated mobile world. The extended platform can offer customised e-learning experiences depending on the type and capabilities of the user’s mobile device. After a brief overview of the IWT e-learning platform, the paper describes how we approached the extension of IWT to provide browser-, SMSand voice-based interactions. Some first experimental results are then given in the last section. The work described here was realised in the context of the EC-funded m-learning project.

Keywords: e-learning, ITS (Intelligent Tutoring Systems), mobile technologies, SMS, IVR

ISBN: 1845723449, Learning and Skills Development Agency

Article BibTeX

Abstract: In this paper we present the main results of the DIOGENE project where the characteristics of Virtual Organisation for providing learning services has been identified and implemented using state of the art Web Services technologies. Moreover, we present, a possible migration path towards the Grid emphasising the advantages coming from the adoption of this technology.

Keywords: Virtual Organisations, Web services, GRID, Learning Services

British Computer Society

Article BibTeX

Abstract: IRMA is a set of multimedia and software tools implemented to encourage the dissemination of scientific culture. On the basis of web technologies we have developed an environment to help learner approaching some mathematical topics, which become accessible through historical news, simulation and interactive applications. In this paper, we will explore the main design and implementation issues of IRMA project and how it can be used in a didactical activity.

ISBN: 9574115283, ATCM

Article BibTeX

Abstract: The purpose of this paper is to describe the work in progress related to the design, the implementation and the evaluation of an innovative e-learning platform for ICT individual training in the framework of an EC funded project named Diogene. The present e-learning solution includes several state-of-the-art technologies and methodologies such as: metadata and ontologies for knowledge manipulation, fuzzy learner modelling, intelligent course tailoring, co-operative and online training support. The proposed solution is based on the distribution of working tasks among content provider services, content discovery services, content brokering services, training services, curriculum vitae searching services and collaboration services.

ISBN: 8496212106, Junta de Extremadura

Article BibTeX

Abstract: We propose a Web tutoring system in which Artificial Intelligence techniques and Semantic Web approaches are integrated in order to provide an automatic tool able both to completely customize learning on the student’s needs and to exchange learning material with other Web systems. IWT (Intelligent Web Teacher) is based on an ad hoc knowledge representation which describes the didactic domain by means of an Ontology. The student can select the concepts belonging to the Ontology she/he is interested in which. The system planning mechanism builds the most suitable Learning Path for that student.

Keywords: Intelligent web-based learning environments; Innovative use of AI languages in teaching and learning; Semantic Web.

Article BibTeX

Abstract: Knowledge management in the medical domain has been recognized as a critical issue in development of medical systems in all western countries. The increasing demand for health services is now facing the problematic aspect of delivering, organizing and saving resources in clinical contexts. An Italian research project, titled GECOSAN, is currently being developed in order to realize a digital environment aimed both at helping in the dissemination of world wide clinical knowledge to medical practitioners and at collecting feedback by the same practitioners so that to increase the knowledge base. The project focuses on the development and deployment of a SW platform based on the standards of “Web Services” so that to ensure full interoperability. This is then exploited to provide two basic services beyond any barrier of HW and SW diversity. The first service consists of making widely available, to medical practitioners, operational guidelines stemming from all known and scientifically approved clinical trials that make up the Evidence Based Medicine (EBM). The second service aims at supporting the efforts of Continuing Medical Education with events that are provided over the Web through the novel “Intelligent Tutoring System” technology, in order to eliminate the weaknesses of distance learning.

Keywords: Health information systems, Evidence Based Medicine, Intelligent Tutoring Systems, Medical informatics, Web Services

Article BibTeX

Abstract: Grid technologies promise to improve the way we think about e-learning allowing wide-scale learning resources sharing in heterogeneous and geographically distributed environments consenting, in this way, the implementation of distributed learning spaces where different organizations and individuals are able to cooperate in pursuing similar and complementary learning and training objectives. But is the e-learning ready for this evolution? In this paper we try, starting from an existing e-learning platform named IWT, to sketch a possible migration path toward a Grid based environment. IWT was selected because it presents a flexible, service-oriented, layered architecture suitable for migration in an OGSA compliant environment. The new approach will provide more flexibility, in fact, it will possible to leverage on the resources distributed across the Grid in order to build the learning experience that best fit student requirements. A use case scenario is also provided in order to emphasize differences between the two approaches.

British Computer Society

Article BibTeX

Abstract: The purpose of this paper is to describe the work in progress related to the customisation, the trial and the evaluation of an innovative e-learning platform for manager upgrade in Small and Medium Enterprises (SME) in the framework of an EC funded project named InTraServ and its forthcoming reengineering process aimed to the adoption of distributed services in the framework of another EC funded project named Diogene. The present e-learning solution includes several state-of-the-art technologies and methodologies such as: metadata and ontologies for knowledge manipulation, fuzzy learner modelling, intelligent course tailoring, case based reasoning, business games and simulation tools. The proposed solution is based on the distribution of working tasks among content provider services, content discovery services, content brokering services, training services, curriculum vitae searching services and collaboration services.

Keywords: e-Learning; Web Services; Distributed Environments

British Computer Society

Article Presentation BibTeX

Abstract: In this paper we propose a complete architecture of an automatic computer based educational system which exploits tools and methodologies taken from various Artificial Intelligence areas. We use a smart description of knowledge (concerning both the didactic domain knowledge and the student model) and inference mechanisms to achieve an efficient and reliable planning of the student course. Finally, we focused our attention also on standardization issues to allow portability to different e-learning platforms of all the didactic material.

ISBN: 0473088010, Institute of Electrical and Electronics Engineers Inc.

Article BibTeX

Abstract: FORMA MEnTIS is an interactive software tool able to encourage and support the diffusion and the dissemination of scientific culture through an innovative approach based on the integration of multimedia tools, Web and mathematical software. In this paper we will explore the main design and implementation issues of the FORMA MEnTIS project. In particular we will focus on tools to be used and how to use them in order to obtain a similar environment from scratch.

ISBN: 9746573624, ATCM

Article BibTeX

Abstract: One of the most interesting realm among those ones brought up to success by the development of the Internet is Distance Learning. A key issue in such a field is the development of systems for supporting Tutoring activities. This paper is concerned with the presentation of an innovative architecture for Intelligent Tutoring which make use of Software Agents. The way in which the knowledge is represented and stored is discussed together with the ability of our system to manage individual learning paths for different users. The rationale for using Agents is presented and the implementation of the system is discussed.

Article Presentation BibTeX

Abstract: Socratenon is a Web engine tuned to advanced Web education using the state-of-the-art Internet development technologies and tools. It enables interactive and creative learning/teaching management in four different domains (provider, administrator, teacher, and student). It also includes an interface to an artificial intelligence based tool for off-line improvement or learning curricula (ABITS or Aristotelon). One of the first applications of Socratenon was to help the learning of Italian language for Serbian students (the product was developed through a cooperation between universities in Salerno and Belgrade). This paper presents the basic elements of the Socratenon application and implementation philosophy, and discusses its possibilities in the general languagelearning environment. It describes three different experiments and explains the lessons learned. The stress is on the statistical analysis of success of those who used our Web-based product and those who relied on the classical approaches.

Article BibTeX

Abstract: The purpose of this paper is to describe an Intelligent Tutoring Framework highly re-usable and suitable to several knowledge domains. In particular the system, named ABITS, has been realized in the context of the InTraSys ESPRIT project. It is able to support a Web-based Course Delivery Platform with a set of “intelligent” functions providing both student modeling and automatic curriculum generation. Such functions found their effectiveness on a set of rules for knowledge indexing based on Metadata and Conceptual Graphs following the IEEE Learning Object Metadata (LOM) standard. Moreover, in order to ensure the maximal flexibility, ABITS is organized as a Multi Agent System (MAS) composed by pools of three different kind of agents (evaluation, pedagogical and affective agents). Each agent is able to solve in autonomous way a specific task and they work together in order to improve the WBT learning effectiveness adapting the didactic materials to user skills and preferences.

Institute for Semantic Information Processing

Article BibTeX

Abstract: One of the most relevant problems in the extraction of scientifically useful information from wide field astronomical images (both photographic plates and CCD frames) is the recognition of the objects against a noisy background and their classification in unresolved (starlike) and resolved (galaxies) sources. In this paper we present a neural network based method capable to perform both tasks and discuss in detail the performance of object detection in a representative celestial field. The performance of our method is compared to that of other methodologies often used within the astronomical community.

ISBN: 0780355296, Institute of Electrical and Electronics Engineers Inc.

Article BibTeX

Abstract: The purpose of this paper is to introduce Artificial Intelligence in the field of data-security and to propose an easy to implement Neural Networks based method for user authentication. The problem has been faced exploiting an RBF-like Neural Net to recognize the typing style of users asking for connection. The introduction of Neural Nets allows to extract rules directly from row data (users typing times) without any assumption on these. This is the advantage of this approach.

ISBN: 8371745125, Wydawnictwo Adam Marszalek

Article Presentation BibTeX

Abstract: Astronomical wide field imaging deals with Terabytes data sets and requires new strategies for data reduction and analysis. We discuss here the application of different types of neural nets to the detection and extraction of celestial objects. Preliminary tests show that neural nets are more effective than traditional techniques.

ISBN: 1852330511, Springer-Verlag

Article BibTeX

Abstract: Discussion forums are popular tools in Massive Open Online Courses (MOOCs), used by students to express feelings, exchange ideas and ask for help. Due to the large number of enrolled students, several approaches to automated forum post analysis are emerging for helping instructors moderate and plan their interventions. Such approaches have the common drawback that, when trained on posts from one course or domain, their application on another course or domain is often unsatisfactory. To solve this problem, this chapter introduces a cross-domain text categorization tool that includes transfer learning capabilities for detecting intent, sentiment, confusion and urgency of MOOC forum posts. The tool, based on convolutional and recurrent neural networks, can be trained on a labeled dataset and then adapted to any course or domain by tuning it on a small set of labeled samples. The proposed tool has been experimented and compared with related works.

Keywords: Massive open online courses; Collaborative learning; Text categorization; Sentiment analysis; Artificial neural networks; Transfer learning

DOI: 10.1016/B978-0-12-823410-5.00014-0, Elsevier Ltd.

Chapter BibTeX

Abstract: The aim of a recommender system is to estimate the utility of a set of objects belonging to a given domain, starting from the information available about users and objects. Adaptive e-learning systems are able to automatically generate personalized learning experiences starting from a learner profile and a set of target learning goals. Starting form research results of these fields we defined a methodology to recommend learning goals and to generate learning experiences for learners of an adaptive e-learning system.

Keywords: e-Learning; Intelligent tutoring systems; Recommender systems

DOI: 10.1007/978-3-642-35879-1_64, Springer-Verlag GmbH

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ISBN: 978-1-932886-73-3, Informing Science Press

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Abstract: In questo contributo verrà descritta la metodologia sviluppata e utilizzata per la catalogazione di informazioni e conoscenze sull’homebound education (esperienze, progetti, comunità e bibliografie) e per lo sviluppo dello user-modelling finalizzato a descrivere il profilo e il contesto degli utenti nell’utilizzo del sistema WISE. Sia la catalogazione che lo usermodelling sono stati in parte sviluppati sulla base del modello bio-psicosociale dell’ICF.

ISBN: 9788856849240, Franco Angeli

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Abstract: Il problema principale che caratterizza il contesto delle comunità di interesse che operano nel campo della dell’Educazione Speciale è l’accesso alla grande quantità di informazioni (intese come dati strutturati, ossia forniti di significato), unitamente alla possibilità di trarre valore (sempre più spesso associata all’innovazione) da tali informazioni. Le tecnologie per la gestione della conoscenza in generale e la ricerca semantica in particolare vengono indicati da molti come il punto di partenza (infrastruttura di base) su cui costruire le risposte (soluzioni tecnologiche) a tali problemi. Il presente capitolo descrive il Knowledge Hub (KH), un repository semantico di risorse formative e informative per la Special Needs Education, realizzato nell’ambito del progetto Wise. Il capitolo descrive le principali funzionalità del sistema che fanno uso dei metadata e dei profili definiti nel precedente capitolo sulla modellizzazione. Tra le funzionalità più avanzate offerte dal sistema citiamo la raccomandazione di risorse sulla base del profilo dell’utente. Tale funzionalità viene descritta in dettaglio e contestualizzata rispetto alla letteratura di riferimento. Il capitolo descrive altresì l’architettura del KH e le modalità di interfacciamento con gli altri sistemi del progetto. Il KH è stato sperimentato sul campo e i risultati di tale sperimentazione saranno qui sinteticamente riportate.

ISBN: 9788856849240, Franco Angeli

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Abstract: In the Virtual Organization (VO) Management area the main challenge has been to develop policies and models for governance and lifecycle management of a business-to-business (B2B) collaboration. This work included research and development in the areas of federated identity management and semantics in addition to VO, business registries and B2B collaboration managements. The main results produced in the VO Management area include capabilities, patterns and software solutions to simplify governance and lifecycle management of B2B collaborations (VOs), and to manage applications distributed over several federated network hosts (e.g. Cloud Computing platforms).

DOI: 10.1007/978-3-642-04086-3_3, Springer-Verlag GmbH

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Abstract: Nowadays, every public or private company has to provide the access to their services through Internet. Unfortunately, the access channels and devices increase both in numbers and heterogeneity. We started few years ago with a PC, wired connected to Internet, moved to wireless access through mobile phone and looking, in the next future, at wearable devices. If we also would like to take into account the user's preferences and his possible handicap we easily realise that combinations increase exponentially making impossible to adapt everything. The paper presents a rule based framework allowing to automatically adapt contents and services according to device capability, communication channel, user preferences and access context. © 2009 Springer Berlin Heidelberg.

Keywords: Context aware adaptive systems; Hypermedia Adaptive Systems; Rule based adaptation systems

DOI: 10.1007/978-3-642-04754-1_26, Springer-Verlag GmbH

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Abstract: The purpose of this chapter is to propose an overview of the Knowledge Virtual Enterprise model, where the Virtual Enterprise vision is extended with Knowledge-based assets in order to provide an agreement model to support the interoperability among organizations. Every enterprise or organization, by itself, is a source of original knowledge that, if exploited, can contribute to its competitiveness. If this is true inside the enterprise walls, it is more relevant when extended to Virtual Enterprises, especially when they operate in a tumultuous and unsettled context, like ICT, strongly bound to the so called soft skills and even more to the capability of carrying out just-in-time knowledge take-over and transfer. In order to explain the advantages of the Knowledge Virtual Enterprise model we define some real-world business scenarios, to be executed within the context of a Knowledge Virtual Enterprise instance. The scenarios are based on the idea that several organizations could put together their competences, human resources, expertise, technologies, etc. to carry out complex project activities, requiring resources that are usually difficult to be found in a single organization. The scenarios are particularly focused on how the Knowledge Virtual Enterprise model can support personalized, contextualized, effective and efficient e-learning at work experiences. Finally, the Knowledge Virtual Enterprise model vision is concretized through the description of a feasible technological mapping between its main concerns and existing software technologies and specifications.

DOI: 10.1007/978-3-642-04001-6_4, Springer-Verlag GmbH

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Abstract: Intelligent e-learning systems have revolutionized online education by providing individualized and personalized instruction for each learner. Nevertheless, till now very few systems were able to leave academic labs and be integrated in real commercial products. One of this few exceptions is the Learning Intelligent Advisor (LIA) described in this paper, built on results coming from several research projects and currently integrated in a complete e-learning solution named IWT. The purpose of this paper is to describe how LIA works and how it cooperates with IWT in the provisioning of an individualized and personalized e-learning experience. Results of experimentations with real users coming from IWT customers are also presented and discussed in order to demonstrate the benefits of LIA as an add-on in on-line learning.

Keywords: E-Learning; ITS; Knowledge Representation; Planning

DOI: 10.1007/978-3-540-87781-3_21, Springer-Verlag GmbH

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Abstract: In the context of the European Project BEinGRID (FP6), the authors have defined a set of design patterns to develop software components based on service oriented Grid technologies. Some of these patterns have been used to improve software components of a Service Oriented Grid Middleware, named GRASP, that the authors have defined, designed and implemented in the frame of a former homonymous European Project (FP5). The main improvement of GRASP due to the application of the BEinGRID design patterns is the support for the creation of Virtual Organizations. This paper presents the authors experience and lessons learnt in adopting the GRASP middleware to set up a business to business federated environment supporting collaborations among enterprises. The concrete case study relates to the on line gaming applications and the adoption of the Software as a Service business model to provide the game applications.

Keywords: Design patterns; Grid; SaaS; SOA; Virtual organization management

DOI: 10.1007/978-3-540-87783-7_49, Springer-Verlag GmbH

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Abstract: Grid technologies are rising as the next generation of Internet by defining a powerful computing paradigm by analogy with the electric Power Grid. A Grid user is able to use his private workplace to invoke any application from a remote system, use the system best suited for executing that application, access data securely and consistently from remote sites, exploit multiple systems to complete economically complex tasks or to solve large problems that exceed the capacity of a single system. Grid could be used as a technology “glue” providing users with a uniform way to access resources by means of several devices. These technologies can provide, in a natural way, a support for Technology Enhanced Learning (TEL) by enabling new learning environments based on collaboration, social interaction, experience, realism, personalisation, ubiquity, accessibility and contextualisation. Nevertheless, to be effectively used in TEL, Grid must be complemented with other elements like semantics and educational modelling so bringing to the concept of “Grid for Learning” whose description is the object of this paper.

Keywords: Distributed computing; Grid; Learning design; Ontologies; Semantics

DOI: 10.1007/978-3-540-87783-7_8, Springer-Verlag GmbH

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Abstract: This chapter analyses the adoption of the Learning Grid for the development of challenging Application Scenarios in the eLearning domain. The Application Scenarios described in this chapter create a breakthrough in current learning practices. Instead of adopting a traditional information transfer paradigm, the proposed scenarios, in fact, promote and support a learning paradigm centred on the learner and focused on knowledge construction using experiential based and collaborative learning approaches in a contextualised, personalised and ubiquitous way. The purpose of our analysis is to understand and argue about the potential advantages of adopting the Learning Grid for the proposed scenarios. Preliminary findings show that Learning Grid can be considered an enabling technology for the presented scenarios since its features (e.g. dynamicity, adaptiveness, support for Virtual Organisation creation and management, advanced mechanisms for resources and services discovery on the basis of Quality of Services) are key to improve personalisation and knowledge construction in the lear

Keywords: Technology Enhanced Learning; Application Scenarios; Pedagogy; Learning Design.

ISBN: 9781586038298, IOS Press

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Abstract: Over the last few years, Technology Enhanced Learning (TEL) needs have been changing in accordance with ever more complex pedagogical models as well as with technological evolution, demanding for high dynamic and configurable environments for running multiple teaching and learning scenarios. Grid technologies have started to be very popular even in education due to the advantages that they offer being based on a secure, flexible and coordinated way of sharing resources over Internet as well as on its enormous capability of information processing. A Grid may facilitate learning processes in allowing each learner to collaboratively use the resources already existing online, by facilitating and managing dynamic communication with other people and agents, through the implementation of dynamic Virtual Organizations allowing to share learning resources. Nevertheless, in order to be effectively used in TEL, Grid must be complemented with other technologies bringing to the concept of “Learning Grid” whose description is the object of this chapter.

Keywords: Technology Enhanced Learning; Application Scenarios; Pedagogy; Learning Design.

ISBN: 9781586038298, IOS Press

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Abstract: Grid technologies promise to improve the way we think about e-learning allowing wide-scale learning resources sharing in heterogeneous and geographically distributed environments, consenting, in this way, the implementation of distributed learning spaces where different organizations and individuals are able to cooperate in pursuing similar and complementary learning and training objectives. But is the e-learning ready for this evolution? In this paper we try, starting from an existing e-learning platform named IWT, to sketch a possible migration path toward a Grid based environment. IWT was selected because it presents a flexible, service-oriented, layered architecture suitable for migration in an OGSA compliant environment. The new approach will provide more flexibility, in fact, it could leverage on the resources distributed across the Grid in order to build the learning experience that best fit student requirements. A use case scenario is also provided in order to emphasize differences between the two approaches.

Keywords: Grid technologies; e-Learning platforms; Grid aware applications; Distributed learning management systems

ISBN: 9781586035341, IOS Press

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Abstract: In this paper we present the main results of the DIOGENE project where the characteristics of Virtual Organisation for providing learning services has been identified and implemented using state of the art Web Services technologies. Moreover, we present, a possible migration path towards the Grid emphasising the advantages coming from the adoption of this technology.

Keywords: Web Services, e-Learning, Distributed Architectures

ISBN: 9781586035341, IOS Press

Chapter BibTeX

Abstract: The purpose of this paper is to describe the work related to the customisation, the trial and the evaluation of an innovative e-learning platform for manager upgrade in Small and Medium Enterprises (SME), in the framework of the EC funded project named InTraServ and its re-engineering process, aimed at adopting distributed services in the framework of another EC funded project named Diogene. The presented e-learning environment includes several state-of-the-art technologies and methodologies such as: metadata and ontologies for knowledge manipulation, fuzzy learner modelling, intelligent course tailoring, case based reasoning, business games and simulation tools. The proposed evolution is based on the distribution of working tasks among content provider services, content discovery services, content brokering services, training services, curriculum vitae searching services and collaboration services.

Keywords: e-Leraning; Web Services; Distributed Environments

ISBN: 9781586035341, IOS Press

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ISBN: 096403980X, Dynamic Publishers

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Abstract: One of the most interesting realm among those ones brought up to success by the development of the Internet is distance learning and training. For this reason, the investigation for adequate architectures and platforms supporting flexible and tailored training solutions is nowadays of great interests in the scientific community. This paper is concerned with the presentation of an original architecture for intelligent distance tutoring which make use of software agents. The way in which the knowledge is represented and stored is discussed together with the ability of our system to manage individual learning paths for different users. The rationale for using Agents is presented and the implementation of the system is discussed.

ISBN: 9780792375081, Kluwer Academic Publishers

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Abstract: The work presented in this Ph.D. thesis deals with the definition of new fuzzy models for Group Decision Making (GDM) aimed at improving two phases of the decision process: preferences expression and aggregation. In particular a new preferences model named Fuzzy Ranking has been defined to help decision makers express fuzzy statements on available alternatives in a simple and meaningful form, focusing on two alternatives at a time but, at the same time, without losing the global picture. This allows to reduce inconsistencies with respect to other existing models. Moreover a new preference aggregation model guided by social influence has been described. During a GDM process, in fact, decision makers interact and discuss each other exchanging opinions and information. Often, in these interactions, those with wider experience, knowledge and persuasive ability are capable of influencing the others fostering a change in their views. So, social influence plays a key role in the decision process but, differently from other aspects, very few attempts to formalize its contribution in preference aggregation and consensus reaching have been made till now. In order to validate the defined models, they have been instantiated in two application contexts: e-Learning and Recommender Systems. In the first context, they have been applied to the peer assessment problem in massive online courses. In such courses, the huge number of participants prevents their thorough evaluation by the teachers. A feasible approach to tackle this issue is peer assessment, in which students also play the role of assessor for assignments submitted by others. But students are unreliable graders so peer assessment often provides inaccurate results. By leveraging on defined GDM models, a new peer assessment model aimed at improving the estimations of student grades has been proposed. With respect to Recommender Systems, the group recommendation issue has been tackled. Instead of generating recommendations fitting individual users, Group Recommender Systems provide recommendations targeted to groups of users taking into account the preferences of any (or the majority of) group members together. The majority of existing approaches for group recommendations are based on the aggregation of either the preferences or the recommendations generated for individual group members. Customizing the defined GDM models, a new model for group recommendations has been proposed that also takes into account the personality of group members, their interpersonal trust and social influence. The defined models have been experimented with synthetic data to show how they operate and demonstrate their properties. Once instantiated in the defined application contexts, they have been experimented with real data to measure their performance in comparison to other context-specific methods. The obtained results are encouraging and, in most cases, better than those achieved by competitor methods.

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Abstract: Questo lavoro di Tesi si inserisce nell'ambito di CRoNaRio: una recente estensione di un progetto a lungo termine iniziato al Caltech nel 1993 e finalizzato alla costruzione del Palomar Norris Sky Catalog: un catalogo completo di tutti i corpi celesti presenti nella Second Palomar Sky Survey (POSS-II), che copre tutto l'emisfero Nord della sfera celeste, per un numero stimato di 2 miliardi di stelle e 50 milioni di galassie. Le lastre fotografiche che costituiranno la POSS-II vengono attualmente acquisite tramite il telescopio Schmidt del monte Palomar e, dopo essere state digitalizzate e linearizzate, vengono processate con il software SKICAT (sviluppato al Caltech) che provvede all'estrazione automatica dei cataloghi. SKICAT è attualmente il miglior software esistente per la generazione di cataloghi. Esso consta di una fase di segmentazione (nella quale identifica gli oggetti sulla lastra separandoli dal fondo altamente rumoroso) e di una fase di classificazione (nella quale, per ogni oggetto estratto, stabilisce la classe stella/galassia di appartenenza). Il presente lavoro di Tesi si propone di costruire un software che, tramite l'utilizzo di Reti Neurali, sia in grado di ottenere prestazioni migliori di SKICAT ovvero che riesca a: identificare gli oggetti con maggiore precisione riducendo al minimo la generazione di oggetti spuri (oggetti creati artificialmente a causa di anomalie di luminosità della lastra); classificare gli oggetti in maniera più accurata. L'accuratezza della separazione stelle/galassie determina infatti il vero limite della utilizzabilità scientifica dei dati ricavati dalle survey. Per molti programmi di processing dei dati è necessario ottenere, in questa fase, un'accuratezza maggiore del 90%. Ogni miglioramento, anche piccolo, nella percentuale di classificazioni corrette determinerebbe un salto di qualità nell'utilizzo scientifico dei cataloghi.

Dissertation BibTeX

DOI: 10.1016/j.iot.2024.101221, Elsevier

BibTeX

DOI: 10.1109/INCoS.2016.115, Institute of Electrical and Electronics Engineers Inc.

Editorial BibTeX

DOI: 10.3991/ijet.v11i07.6054, Kassel University Press GmbH

Editorial BibTeX

DOI: 10.1109/INCoS.2015.98, Institute of Electrical and Electronics Engineers Inc.

Editorial BibTeX

DOI: 10.3991/ijet.v10i7.4636, Kassel University Press GmbH

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DOI: 10.1109/INCoS.2014.128, Institute of Electrical and Electronics Engineers Inc.

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DOI: 10.1109/CISIS.2013.147, Institute of Electrical and Electronics Engineers Inc.

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DOI: 10.1109/CISIS.2012.46, Institute of Electrical and Electronics Engineers Inc.

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DOI: 10.1109/INCoS.2011.173, Institute of Electrical and Electronics Engineers Inc.

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