Forming Homogeneous Classes for e-Learning in a Social Network Scenario

Comi, Antonello; Fotia, Lidia; Messina, Fabrizio; Pappalardo, Giuseppe; Rosaci, Domenico; Sarné, Giuseppe M. L.

doi:10.1007/978-3-319-25017-5_13

Cited by 8 publications

(7 citation statements)

References 23 publications

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“…In addition, the teacher took into account the convenience of the students, based on the confidence and interactions that the subjects had shown in previous group activities [9]. In relation to this, it is necessary to mention that, the greater the trust between the members of a group, the greater interest they will show to interact [144][145][146]. This is an important aspect in the study, since group interaction is essential to be able to evaluate the use or not of mobile technology in collaborative learning.…”

Section: Discussionmentioning

confidence: 99%

Use of Mobile Technologies in Personal Learning Environments of Intercultural Contexts: Individual and Group Tasks

2020

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This paper presents the results of the analysis of the personal learning environments (PLE) used individually and in groups by fifth grade primary education students. The main objective was to determine if the use of mobile technologies in the students’ PLEs encouraged their school integration and learning in intercultural communities. For this, a content analysis of the students’ responses to an ad hoc interview was carried out, with a content validity index of 0.89. The students represented their answers using 41 concept maps in the individual tasks and 5 in the group tasks, which were analyzed with the Nvivo software in its latest version. The results show the categorization of the students’ responses in three dimensions: read, make/reflection and relationship. Among the main conclusions, it was obtained that, in both types of tasks, the strategies and tools that fostered intercultural relationships, intercultural education and communication between the students, and therefore school integration, are mostly linked to the use of mobile technologies applications, such as Wikipedia, the internet, Word, PowerPoint, social networks and YouTube, although it is essential to develop more studies to have more data to understand the phenomenon in depth.

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Section: Discussionmentioning

confidence: 99%

Use of Mobile Technologies in Personal Learning Environments of Intercultural Contexts: Individual and Group Tasks

2020

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“…By our studies we can observe that trust has been conceptualized in several ways. Indeed in the literature, there are many trust models [7], [20]- [22], [32], [60], [62]. Moreover, some of them address behavioral problems [18], [32], [41].…”

Section: A Trust Model Conceptsmentioning

confidence: 99%

Trust and Reputation in the Internet of Things: State-of-the-Art and Research Challenges

et al. 2020

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This paper deals with the principal aspects emerging from the application of trust techniques to the IoT domains with respect to the particular viewpoint of an IoT environment. We consider intelligent agents technology to add social behavior to the community of the smart objects, and we analyze the fundamental role of the concepts of trust and reputation in this perspective. Also, we analyze the existing architectures for IoT and explain how to integrate IoT with fog/edge computing. Besides discussing the main proposals present in the literature, the key contribution of this paper consists of providing a comparative study of the main current architectures for modeling trust in IoT environments. In this setting, we propose a comparison based on the important characteristics of the IoT layer and the architecture type. Such an analysis allows us to highlight both advantages and limitations of each approach, and to discuss the emerging research challenges. INDEX TERMS Internet of Things, multi-agent system, reputation, trust, edge/fog computing.

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“…From the point of view of personalizing e-learning contents, many techniques have been applied, such as neuronal networks, adjacency matrices, constraint programming models, soft computing methods, integer programming, machine learning, multi-agent approaches, swarm intelligence models and recommendation techniques (Anaya et al, 2013;Brusilovsky & Vassileva, 2003;Comi et al, 2015a;de Oliveira et al, 2013;Essalmi et al, 2015;Garrido et al, 2008;Idris et al, 2009;Kurilovas et al, 2014Kurilovas et al, , 2015Martinez et al, 2004;Rosaci & Sarne, 2010). They all have in common the interest in simulating human decisionmaking and recommending course contents in the form of different learning tasks/objects (e.g.…”

Section: Related Workmentioning

confidence: 99%

“…The idea of combining both previous points of view naturally leads to a multiagent learning approach (Comi et al, 2015a;Garruzzo et al, 2007a,b;Messina et al, 2013;Rosaci & Sarne, 2010). In particular, Garruzzo et al (2007a,b) propose two learning systems, ISABEL and MASHA-EL, which associate to each student a device agent to autonomously monitor the student's behavior when accessing e-learning Web sites.…”

Section: Related Workmentioning

confidence: 99%

“…As proposed in related literature (Caputi & Garrido, 2015;Comi et al, 2015a;Essalmi et al, 2015;Garruzzo et al, 2007b;Kurilovas et al, 2015;Rosaci & Sarne, 2010), a revolutionary key challenge of the current century is advanced personalized learning to promote adaptivity and fully tailoring of the e-courses. The idea is to use intelligent systems to construct and recommend a personalized learning route of contents that fit the individual requirements of each student, and even the device each student is using at that moment (Garruzzo et al, 2007a;Rosaci & Sarne, 2010).…”

Section: Introductionmentioning

confidence: 99%

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On the use of case-based planning for e-learning personalization

Garrido

Morales

Serina

2016

Expert Systems with Applications

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In this paper we propose myPTutor, a general and effective approach which uses Al planning techniques to create fully tailored learning routes, as sequences of Learning Objects (LOs) that fit the pedagogical and students' requirements.\ud \ud myPTutor has a potential applicability to support e-learning personalization by producing, and automatically solving, a planning model from (and to) e-learning standards in a vast number of real scenarios, from small to medium large e-learning communities. Our experiments demonstrate that we can solve scenarios with large courses and a high number of students. Therefore, it is perfectly valid for schools, high schools and universities, especially if they already use Moodle, on top of which we have implemented myPTutor. It is also of practical significance for repairing unexpected discrepancies (while the students are executing their learning routes) by using a Case-Based Planning adaptation process that reduces the differences between the original and the new route, thus enhancing the learning process

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Forming Homogeneous Classes for e-Learning in a Social Network Scenario

Cited by 8 publications

References 23 publications

Use of Mobile Technologies in Personal Learning Environments of Intercultural Contexts: Individual and Group Tasks

Use of Mobile Technologies in Personal Learning Environments of Intercultural Contexts: Individual and Group Tasks

Trust and Reputation in the Internet of Things: State-of-the-Art and Research Challenges

On the use of case-based planning for e-learning personalization

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