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

Evaluation of social interaction features in topolor - a social personalized adaptive e-learning system

Here we present a case study that analyses 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 plan for improvement

Investigating the impact of social interactions in adaptive E-Learning by learning behaviour analysis

Adaptive Educational Hypermedia Systems (AEHSs) allow for personalization of e-learning1 . Social media tools enable learners to create, publish and share their study, and facilitate interaction and collaboration2 . The integration of social media tools into AEHS offers novel opportunities for learner engagement and extended user modelling, and thereby fosters so-called Social Personalized Adaptive E-learning Environments (SPAEEs) 3. However, there has been a lack of empirical design and evaluation to elaborate methods for SPAEEs. The goal of research, therefore, is to investigate 1) the learning behaviour patterns within SPAEEs and the use of these patterns for learner engagement, 2) the evaluation methodologies for SPAEEs, and 3) the design principles for SPAEEs. Topolor4 is a SPAEE that has been under iterative development for achieving our research goals. The first prototype was used as an online learning system for MSc level students in the Department of Computer Science, at the University of Warwick, and usage data was anonymously collected for analysis5 . This poster focuses on system features and learning behaviour analysis. We firstly present the methodologies applied in the research, followed by the social and adaptive features that Topolor provides6 . Then we revisit the analysis of learning behaviours7 . Finally we propose the follow-up work based on the evaluation results

Social e-learning in topolor : a case study

Social e-learning is a process through which learners achieve their learning goals via social interactions with each other by sharing knowledge, skills, abilities and educational materials. Adaptive e-learning enables adaptation and personalization of the learning process, based on learner needs, knowledge, preferences and other characteristics. In this paper, we present a case study that analyzes the social interaction features of a social personalized adaptive e-learning system developed at the University of Warwick, called Topolor. We discuss the results of a quantitative case study that evaluates the perceived usefulness and usability. The results demonstrate a generally high level of learner satisfaction with their learning experience. We extend the discussion of the results to explore future research directions and suggest further improvements for the studied social personalized adaptive e-learning system

Investigating the Impact of Social Interactions in Adaptive E-Learning by Learning Behaviour Analysis

Adaptive Educational Hypermedia Systems (AEHSs) allow for personalization of e-learning. Social media tools enable learners to create, publish and share their study, and facilitate interaction and collaboration. The integration of social media tools into AEHS offers novel opportunities for learner engagement and extended user modelling, and thereby fosters so-called Social Personalized Adaptive E-learning Environments (SPAEEs). However, there has been a lack of empirical design and evaluation to elaborate methods for SPAEEs. The goal of the research, therefore, is to investigate 1) the learning behaviour patterns within SPAEEs and the use of these patterns for learner engagement, 2) the evaluation methodologies for SPAEEs, and 3) the design principles for SPAEEs. Topolor4 is an SPAEE that has been under iterative development for achieving our research goals. The first prototype was used as an online learning system for MSc level students in the Department of Computer Science, at the University of Warwick, and usage data was anonymously collected for analysis. This poster focuses on system features and learning behaviour analysis. We first present the methodologies applied in the research, followed by the social and adaptive features that Topolor provides. Then we revisit the analysis of learning behaviours. Finally, we propose the follow-up work based on the evaluation results

Evaluation of social personalized adaptive E-Learning environments : end-user point of view

The use of adaptations, along with the social affordances of collaboration and networking, carries a great potential for improving e-learning experiences. However, the review of the previous work indicates current e-learning systems have only marginally explored the integration of social features and adaptation techniques. The overall aim of this research, therefore, is to address this gap by evaluating a system developed to foster social personalized adaptive e-learning experiences. We have developed our first prototype system, Topolor, based on the concepts of Adaptive Educational Hypermedia and Social E-Learning. We have also conducted an experimental case study for the evaluation of the prototype system from different perspectives. The results show a considerably high satisfaction of the end users. This paper reports the evaluation results from end user point of view, and generalizes our method to a component-based evaluation framework

Evaluation of social personalized adaptive E-Learning environments : end-user point of view

The use of adaptations, along with the social affordances of collaboration and networking, carries a great potential for improving e-learning experiences. However, the review of the previous work indicates current e-learning systems have only marginally explored the integration of social features and adaptation techniques. The overall aim of this research, therefore, is to address this gap by evaluating a system developed to foster social personalized adaptive e-learning experiences. We have developed our first prototype system, Topolor, based on the concepts of Adaptive Educational Hypermedia and Social E-Learning. We have also conducted an experimental case study for the evaluation of the prototype system from different perspectives. The results show a considerably high satisfaction of the end users. This paper reports the evaluation results from end user point of view, and generalizes our method to a component-based evaluation framework

To build light gamification upon social interactions : requirement analysis for the next version of Topolor

The introduction of social dimension enables traditional adaptive educational hypermedia systems to provide more versatile personalized services. Topolor has been developed to investigate the impacts of social interaction and feasible engagement strategies in such a system. We have evaluated Topolor’s social features from the perspectives of usefulness and ease of use. We intend to develop the next version of Topolor, starting with enhancing relatively lower rated social features. This paper presents our plan of building light gamification upon the evaluated social interaction features with relatively lower rating

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

Here we introduce Topolor, a social personalized adaptive elearning system aiming to improve social interaction in the learning process as well as applying classical adaptation based on user modeling. Here, we focus on the system architecture and preliminary evaluation that showed high system usability