The 3A Interaction Model and Relation-Based Recommender System:Adopting Social Media Paradigms in Designing Personal Learning Environments

We live in a rapidly changing digital world marked by technological advances, and fraught with online information constantly growing thanks to the Internet revolution and the online social applications in particular. Formal learning acquired in traditional academic and professional environments is not by itself sufficient to keep up with our information-based society. Instead, more and more focus is granted to lifelong, self-directed, and self-paced learning, acquired intentionally or spontaneously, in environments that are not purposely dedicated for learning. The concept of online Personal Learning Environments (PLEs) refers to the development of platforms that are able to sustain lifelong learning. PLEs require new design paradigms giving learners the opportunity to conduct autonomous activities depending on their interests, and allowing them to appropriate, repurpose and contribute to online content rather than merely consume pre-packaged learning resources. This thesis presents the 3A interaction model, a flexible design model targeting online personal and collaborative environments in general, and PLEs in particular. The model adopts bottom-up social media paradigms in combining social networking with flexible content and activity management features. The proposed model targets both formal and informal interactions where learning in not necessarily an explicit aim but may be a byproduct. It identifies 3 main constructs, namely actors, activities, and assets that can represent interaction and learning contexts in a flexible way. The applicability of the 3A interaction model to design actual PLEs and to deploy them in different learning modalities is demonstrated through usability studies and use-case scenarios. This thesis also addresses the challenge of dealing with information overload and helping end-users find relatively interesting information in open environments such as PLEs where content is not predefined, but is rather constantly added at run time, and differ in subject matter, quality, as well as intended audience. For that purpose, the 3A personalized, contextual, and relation-based recommender system is proposed, and evaluated on two real datasets

The Four Elements of a viable PLE

In this paper, we propose and discuss four fitness features considered as essential for developing personal learning environments (PLE) that are viable and ready for appropriation

Trust-Based Rating Prediction for Recommendation in Web 2.0 Collaborative Learning Social Software

Benefiting from the advent of social software, information sharing becomes pervasive. Personalized rating systems have emerged to evaluate the quality of user-generated content in open environment and provide recommendation based on users’ past experience. In this paper, a trust-based rating prediction approach for recommendation in Web 2.0 collaborative learning social software is proposed. Trust network is exploited in the rating prediction scheme and a multi-relational trust metric is developed in an implicit way. Finally the evaluation of the approach is performed using the dataset of collaborative learning social software, namely Remashed

Using Social Media for Collaborative Learning in Higher Education: A Case Study

This paper investigates the acceptability of using social media for collaborative learning in the context of higher education. A social media platform, Graasp, is used to support students’ learning activities in a project-based course. An evaluation of Graasp regarding its usefulness as a collaboration platform, a knowledge management site, and a gadget container, was conducted with the course participants. Quantitative and qualitative assessment methods used in the evaluation, as well as the main findings are presented

41P. Practical Lessons Learned while Developing Web 2.0 Collaboration Services for Communities of Practice

Although a plethora of Web 2.0 applications exist today, there is little literature reporting on experiences, concrete recommendations or best practices when developing such applications. The scarcity of such records makes it difficult for developers to determine how best to support the practices of communities with the use of Web 2.0 technologies. In this paper, we report on eight practical lessons learned while developing Web 2.0 collaboration services for Communities of Practice in the framework of a three years long European research project on Technology Enhanced Learning. The main objective of this project was to investigate how Web 2.0 technologies could impact the communication and collaboration needs of Communities of Practice interacting online and, conversely, how new interaction needs could impact Web 2.0 technology. The above lessons are presented in a way that could aid people engaged in various phases of the development of Web-based collaboration support services

A Federated Search and Social Recommendation Widget

This paper presents a federated search and social recommen- dation widget. It describes the widget’s interface and the un- derlying social recommendation engine. A preliminary eval- uation of the widget’s usability and usefulness involving 15 subjects is also discussed. The evaluation helped identify us- ability problems that will be addressed prior to the widget’s usage in a real learning context

Turning Web 2.0 Social Software into Versatile Collaborative Learning Solutions

In the framework of the European Integrated Project PALETTE, the École Polytechnique Fédérale de Lausanne (EPFL) is developing the eLogbook Web 2.0 social software. The purpose of eLogbook is to support tacit and explicit knowledge management in communities of practice. It can be customized by the users to serve as an asset management system, as a task management system or as a discussion platform. In this paper, the innovative Computer- Human Interaction features of eLogbook are introduced and its deployment scenario to support collaborative laboratory activities in engineering education is described. The main idea is to sustain interaction for learning purpose within self-organized teams that integrate students, teaching assistants, as well as laboratory equipment and instrumentation on a seamless leve

Graaasp: a web 2.0 research platform for contextual recommendation with aggregated data

In this paper we describe Graaasp, a social software currently under development to support the creation of a real usage database of social artifacts. Our goals are twofold: First to offer a generic aggregation service and user interface to people and communities. Second, to experiment with recommendation and reputation models and algorithms in e-learning

May I Suggest? Comparing Three PLE Recommender Strategies

Personal learning environment (PLE) solutions aim at empowering learners to design (ICT and web-based) environments for their learning activities, mashingup content and people and apps for different learning contexts. Widely used in other application areas, recommender systems can be very useful for supporting learners in their PLE-based activities, to help discover relevant content, peers sharing similar learning interests or experts on a specific topic. In this paper we examine the utilization of recommender technology for PLEs. However, being confronted by a variety of educational contexts we present three strategies for providing PLE recommendations to learners. Consequently, we compare these recommender strategies by discussing their strengths and weaknesses in general