Dana Al Qudah

Topolor: A Social Personalized Adaptive E-Learning System

This paper briefly introduces Topolor, a social personalized adaptive e-learning system, which aims at improving fine-grained social interaction in the learning process in addition to applying classical adaptation based on user modeling. Here, we present the main features of Topolor and its preliminary evaluation that showed high system usability from a student’s perspective. The intention is to demonstrate Topolor hands-on at the conference.

Social Personalized Adaptive E-Learning Environment: Topolor - Implementation and Evaluation

This paper presents a quantitative study on the use of Topolor - a prototype that introduces Web 2.0 tools and Facebook-like appearance into an adaptive educational hypermedia system. We present the system design and its evaluation using system usability scale questionnaire and learning behavior data analysis. The results indicate high level of student satisfaction with the learning experience and the diversity of learning activities.

Designing social personalized adaptive e-learning

We introduce Topolor, a social personalized adaptive e-learning system aiming to improve social interaction in learning process, and apply classical adaptation based on user modeling. Here, we focus on the system architecture and preliminary evaluation.

Evaluation of Social Interaction Features in Topolor - A Social Personalized Adaptive E-Learning System

Here we present a case study that analyzed the social interaction features in Topolor, an adaptive personalized social e-learning system. This paper focuses on the evaluation of the perceived usefulness and usability. The results show a considerably high satisfaction of the students. We discuss the evaluation results and outline the further improvement plan.

MyAds—A Proposed Adaptive Social Online Advertising Framework

The seemingly ‘magical’ developments of the World Wide Web have challenged the computer science researchers, analysts, designers and developers to think outside the box and apply their creativity. One of the main sectors that have paid great attention to the World Wide Web is the advertisement sector. Online advertisement is known to be one of the major incomes for many companies, social networks and search engines online. This paper proposes a framework that provides adaptive advertisements to be displayed to online users based on their social network profiles via creating an individual user model for each user. The framework was built based on literature research and an exploratory study conducted with actual web users. The framework is a layered model, where each layer provides a different functionality, but works towards a homogenous outcome of adaptive ads.