Many researchers argue that students must be meaningfully engaged in the learning resources for effective learning to occur. However, current online learners still report a problematic lack of attractive and challenging learning resources that engage them in the learning process. This endemic problem is even more evident in online collaborative learning approaches whose resources lack of authentic interactivity, user empowerment, social identity and challenge, thus having a negative effect on learners' self-motivation and engagement. To overcome these and other limitations and deficiencies, in this paper, a new type of learning resource named Collaborative Complex Learning Resources (CC-LR) is presented based on the virtualization of collaborative learning with the aim of leveraging knowledge elicited during live sessions. During the CC-LR execution, the collaborative sessions are animated so learners can observe how avatars discuss and collaborate, how discussion threads grow and how knowledge is been constructed, refined and consolidated. In addition, complex aspects of the learning process can be incorporated in the CC-LRs during their creation, such as cognitive assessment and emotional awareness. The system produced from this research is tested to evaluate the CC-LR enriched with complex information and analyze its effects in the discussion process. The research reported in this paper was undertaken within the Seventh Framework Programme (FP7) European project called 'Adaptive Learning via Intuitive/Interactive, Collaborative and Emotional systems'.
In this paper we propose a framework for modeling, representing populating and enriching information from online collaborative sessions within Web forums. The main piece of the framework is an ontology called Collaborative Session Conceptual Schema (CS 2 ) that allows for specifying collaborative sessions. The paper describes the information this ontology needs to know, the alignment of the ontology with the ontologies of relevant specifications, how the ontology can be automatically populated from the data existent in forums, and how to model such data about what is happening during the collaboration by using a dialogue-based model. This model is based on primitive exchange moves found in any forum posts, which are then categorized at different description levels with the aim to effectively collect and classify the type and intention of the forum posts. An experiment has been conducted to assess the validity and usefulness of the presented approach. The research reported in this paper is currently undertaken within a FP7 European project called ALICE.
Purpose The purpose of this paper is to present an innovative web-based eLearning platform called ICT-FLAG that provides e-assessment tools with general-purpose formative assessment services featuring learning analytics and gamification. Design/methodology/approach The paper reports on the technical development of the platform driven by the Reference Model for Open Distributed Processing software methodology, which guides the platform construction, including the analysis and design steps. Findings The ICT-FLAG platform is technically tested by integrating it into a real e-assessment tool. Results are positive in terms of functional and non-functional aspects as well as user’s satisfaction on usability, emotional state, thus validating the platform as a valuable educational tool. Research limitations/implications Because of the chosen technical paper as article type, validation of the impact of the ICT-FLAG platform in the learning process is not provided. Ongoing research with this platform is to measure the learning outcomes of its use in a real context of eLearning. Practical implications The paper shows implications of the main technical issues and challenges encountered during the integration of the ICT-FLAG platform with external eLearning tools, involving relevant aspects of interoperability, security, modularity, scalability, portability and so on. Originality/value This platform can fill the gap of many e-assessment systems, which currently do not have built-in analytical and gamification tools for learning, thus providing them with the experience to improve the quality of education and learning.
Abstract-Nowadays, universities (on-site and online) have a large competition in order to attract more students. In this panorama, learning analytics can be a very useful tool since it allows instructors (and university managers) to get a more thorough view of their context, to better understand the environment, and to identify potential improvements. In order to perform analytics efficiently, it is necessary to have as much information as possible about the instructional context. The paper proposes a novel approach to gather information from different aspects within courses. In particular, the approach applies natural language processing (
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