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

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

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

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

Is adaptation of e-advertising the way forward?

E-advertising is a multi-billion dollar industry that has shown exponential growth in the last few years. However, although the number of users accessing the Internet increases, users don’t respond positively to adverts. Adaptive e-advertising may be the key to ensuring effectiveness of the ads reaching their target. Moreover, social networks are good sources of user information and can be used to extract user behaviour and characteristics for presentation of personalized advertising. Here we present a two-sided study based on two questionnaires, one directed to Internet users and the other to businesses. Our study shows that businesses agree that personalized advertising is the best way for the future, to maximize effectiveness and profit. In addition, our results indicate that most Internet users would prefer adaptive advertisements. From this study, we can propose a new design for a system that meets both Internet users’ and businesses’ requirements

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

A Social Personalized Adaptive E-Learning Environment: A Case Study in Topolor

Adaptive e-Learning is a process where learning contents are delivered to learners adaptively, namely, the appropriate contents are delivered to the learners in an appropriate way at an appropriate time based on the learners' needs, knowledge, preferences and other characteristics. Social e-Learning is a process where connections are made among like-minded learners, so they can achieve learning goals via communication and interaction with each other by sharing knowledge, skills, abilities and materials. This paper reports an extended case study that investigated the influence of social interactions in an adaptive e-Learning environment, by analyzing the usage of social interaction features of a Social Personalized Adaptive E-Learning Environment (SPAEE), named Topolor, which strives to combine the advantages from both social e-Learning and adaptive e-Learning. We present the results of a quantitative case study that evaluates the perceived usefulness and ease of use. The results indicated high satisfaction from the students who were using Topolor for their study and helped us with the evaluation processes. Based on the results, we discuss the follow-up work plan for the further improvements for Topolor

Multifaceted open social learner modelling

Open social learner modelling (OSLM) approaches are promoted in order to assist learners in self-directed and self-determined learning in a social context. Still, most approaches only focus on visualising learners’ performance, or providing complex tools for social navigation. Our proposal, additionally, emphasises the importance of visualising both learners’ performance and their contribution to a learning community. We seek also to seamlessly integrate OSLM with learning contents, in order for the multifaceted OSLM’s prospect for ubiquity and context-awareness to enrich the adaptive potential of social e-learning systems. This paper thus presents the design of multifaceted OSLM by introducing novel, personalised social interaction features into Topolor, a social personalised adaptive e-learning environment. The umbrella target is to create and study aspects of open social learner models. An experimental study is conducted to analyse the impact of the newly introduced features. The results are finally concluded to suggest future research and further improvements

Data-Driven Analysis of Engagement in Gamified Learning Environments: A Methodology for Real-Time Measurement of MOOCs

Welfare and economic development is directly dependent on the availability of highly skilled and educated individuals in society. In the UK, higher education is accessed by a large percentage of high school graduates (50% in 2017). Still, in Brazil, a limited number of pupils leaving high schools continue their education (up to 20%). Initial pioneering efforts of universities and companies to support pupils from underprivileged backgrounds, to be able to succeed in being accepted by universities include personalised learning solutions. However, initial findings show that typical distance learning problems occur with the pupil population: isolation, demotivation, and lack of engagement. Thus, researchers and companies proposed gamification. However, gamification design is traditionally exclusively based on theory-driven approaches and usually ignore the data itself. This paper takes a different approach, presenting a large-scale study that analysed, statistically and via machine learning (deep and shallow), the first batch of students trained with a Brazilian gamified intelligent learning software (called CamaleOn), to establish, via a grassroots method based on learning analytics, how gamification elements impact on student engagement. The exercise results in a novel proposal for real-time measurement on Massive Open Online Courses (MOOCs), potentially leading to iterative improvements of student support. It also specifically analyses the engagement patterns of an underserved community

MyAds: A Social Adaptive System for Online Advertisement from Hypotheses to Implementation

Online advertisement is one of the major incomes for many companies; it has a role in the overall business flow and affects the consumer behavior directly. Unfortunately most users tend to block their ads or ignore them. MyAds is a social adaptive hypermedia system for online advertising and its main goal is to explore how to make online ads more acceptable. In order to achieve such a goal, various technologies and techniques are used. This paper presents a theoretical framework as well as the system architecture for MyAds that was designed based on a set of hypotheses and an exploratory study. The system then was implemented and a pilot experiment was conducted to validate it. The main outcomes suggest that the system has provided personalized ads for users. The main implications suggest that the system can be used for further testing and validating