Developing a Collaborative Learning Environment Using Web Services Techniques

Al-Abri, Amal; Al-Khanjari, Zuhoor; Jamoussi, Yassine; Kraïem, Naoufel

doi:10.17706/jsw.11.9.870-882

Cited by 5 publications

(3 citation statements)

References 21 publications

(19 reference statements)

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“…The third stage is the domain model creation from the cleaned data. As reported in [44], IMS Learning design is more effective in supporting collaborative and adaptive learning experiences because it can easily be understood by both educators and students. Therefore, the learning design adopted in this study is based on IMS learning design.…”

Section: Stagementioning

confidence: 99%

PerLCol: A Framework for Personalized e-Learning with Social Collaboration Support

Abri¹,

Jamoussi²,

Al-Khanjari³

et al. 2020

IJCDS

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The emergence of Web 2.0 technologies like social media has enhanced the interaction and social collaboration support in the educational field. On the one hand, the integration of such sources equips learners with channels to share information, resources, ideas, as well as expressing opinions and comments during the interactions. On the other hand, such integration raises some issues related to personalization by filtering the collaboration support and provide a tailored pedagogical intervention to provide adequate hints and feedback as a means of adaptivity. Existing learning management systems provide restricted collaboration features and are not tailored to students' characteristics like knowledge level and individual traits. In order to overcome these issues, we propose a framework to upgrade the virtual learning environment to provide flexible collaboration and be adaptive to learners' needs. The framework integrates social media tools for seamless collaboration. In addition, it utilizes the generated content during collaboration to identify discussed concepts and learners' characteristics to provide a personalized learning package accordingly. Descriptions of the notions required to develop the framework and an overview of its components and functionality are provided in this paper.

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Section: Stagementioning

confidence: 99%

PerLCol: A Framework for Personalized e-Learning with Social Collaboration Support

Abri¹,

Jamoussi²,

Al-Khanjari³

et al. 2020

IJCDS

Self Cite

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“…7 is quite good. However, there is a need to focus on adapting the learning resource development standards like SCORM, IMS-LD, IEE LOM and SOA [12] when developing the systems as it is presenting only 9% consideration.…”

Section: Tool View 1)mentioning

confidence: 99%

“…According to [11], collaborative learning could be defined as "a variety of educational practices in which interactions among peers constitute the most important factor in learning, although without excluding other factors, such as the learning material and interactions with teachers". The characteristics of social media tools enhanced the adoption of collaborative learning activities in the educational field via the learning environments [12]. The concept of collaborative learning environment requires establishing a networked environment to facilitate active participation, interaction, and collaboration [13].…”

Section: Introductionmentioning

confidence: 99%

Towards a Classification View of Personalized e-Learning with Social Collaboration Support

Al-Abri¹,

Jamoussi²,

Al-Khanjari³

et al. 2019

IJACSA

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With the emergence of Web 2.0 technologies, interaction and collaboration support in the educational field have been augmented. These types of support embrace researchers to enrich the e-learning environment with personalized characteristics with the utilization of the collaboration support outputs. Achieving this requires understanding the existing environments and highlights their eminence. As a result, there are many attempts to state the current status of personalized e-learning environment from different perspectives. However, these attempts targeted a specific view and direction which failed to provide us with the general view of the adoption of personalized e-learning environment with the support of social collaboration tools. This paper provides a classified view of the current status of personalized e-learning environments which incorporate social collaboration tools for providing the personalization feature. The classification adopts four different views to carry out the classification; these views are subject, purpose, method, and tool. The findings show that the utilization of the user-generated contents and social interaction functionalities for personalization is tight and not fully consumed. In short, the potential of providing personalized learning with social interaction and collaboration features remains not fully explored.

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Identifying Learning Styles from Chat Conversation using Ontology-Based Dynamic Bayesian Network Model

Al-Abri

Al-Khanjari

Jamoussi

et al. 2018

2018 8th International Conference on Computer Science and Information Technology (CSIT)

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Developing a Collaborative Learning Environment Using Web Services Techniques

Cited by 5 publications

References 21 publications

PerLCol: A Framework for Personalized e-Learning with Social Collaboration Support

PerLCol: A Framework for Personalized e-Learning with Social Collaboration Support

Towards a Classification View of Personalized e-Learning with Social Collaboration Support

Identifying Learning Styles from Chat Conversation using Ontology-Based Dynamic Bayesian Network Model

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