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

Scaffolding for social personalised adaptive e-learning

This work aims to alleviate the weaknesses and pitfalls of the strong modern trend of e-learning by capitalising on and taking advantage of theoretical and implementation advances that have been made in the fields of adaptive hypermedia, social computing, games research and motivation theories. Whilst both demand for and supply of e-learning are growing, especially with the rise of MOOCs, the problems that it faces remain to be addressed, notably isolation, de-personalisation and lack of individual navigation. This often leads to poor learning experience. This work explores an innovative method of combining, threading and balancing the amount of adaptation, social interaction, gamification and open learner modelling for e-learning techniques and technologies. As a starting point, a novel combination of classical adaptation based on user modelling, fine-grained social interaction features and a Facebook-like appearance is explored. This has been shown to be able to ensure a high level of effectiveness, efficiency and satisfaction amongst learners when using the e-learning system. Contextual gamification strategies rooted in Self-Determination Theory (SDT) are then proposed, which have been shown to be able to ensure learners of the system adopt desirable learning behaviours and achieve pre-specified learning goals, thus providing a high level of motivation. Finally, a multifaceted open social learner modelling is proposed. This allows visualising both learners’ performance and their contributions to a learning community, provides various modes of comparison, and is integrated and adapted to learning content. Evidence has shown that this can provide a high level of effectiveness, efficiency and satisfaction amongst learners. Two innovative social personalised adaptive e-learning systems including Topolor and Topolor 2 are devised to enable the proposed approach to be tested in the real world. They have been used as online learning environments for undergraduate and postgraduate students in Western and Eastern Europe as well as Middle Eastern universities, including the University of Warwick, UK, Jordan University, Jordan, and Sarajevo School of Science and Technology, Bosnia and Herzegovina. Students’ feedback has shown this approach to be very promising, suggesting further implementation of the systems and follow-up research. The worldwide use of Topolor has also promoted international collaborations

Digital crowdsourcing in healthcare environment co-design

Improving user experiences of healthcare environments via their participation has become a central theme in healthcare studies and strategic agendas. The co-design approach is often utilized to take into account opinions from different stakeholders including hospital staff. However, there are a number of competing stimuli and demands on staff at any point in time potentially making it difficult for them to participate in the co-design processes. Digital crowdsourcing may engage staff in participating in the design and appraisal of hospital environments when they have a spare moment by collecting small amounts of relevant data. In order to explore this, we have implemented a digital crowdsourcing co-design prototype. As users’ perceived acceptance of technologies is among the determining factors for a successful digital approach, in this paper, we report on participants’ acceptance of the prototype, aiming to reflect if and to what extend they accept this prototype to aid further development

Revealing the hidden patterns : a comparative study on profiling subpopulations of MOOC students.

Massive Open Online Courses (MOOCs) exhibit a remarkable heterogeneity of students. The advent of complex “big data” from MOOC platforms is a challenging yet rewarding opportunity to deeply understand how students are engaged in MOOCs. Past research, looking mainly into overall behavior, may have missed patterns related to student diversity. Using a large dataset from a MOOC offered by FutureLearn, we delve into a new way of investigating hidden patterns through both machine learning and statistical modelling. In this paper, we report on clustering analysis of student activities and comparative analysis on both behavioral patterns and demographical patterns between student subpopulations in the MOOC. Our approach allows for a deeper understanding of how MOOC students behave and achieve. Our findings may be used to design adaptive strategies towards an enhanced MOOC experience

Demographic Indicators Influencing Learning Activities in MOOCs: Learning Analytics of FutureLearn Courses

Big data and analytics for educational information systems, despite having gained researchers’ attention, are still in their infancy and will take years to mature. Massive open online courses (MOOCs), which record learner-computer interactions, bring unprecedented opportunities to analyse learner activities at a very fine granularity, using very large datasets. To date, studies have focused mainly on dropout and completion rates. This study explores learning activities in MOOCs against their demographic indicators. In particular, pre-course survey data and online learner interaction data collected from two MOOCs, delivered by the University of Warwick, in 2015, 2016, and 2017, are used, to explore how learnerdemographic indicatorsmay influence learner activities. Recommendations for educational information system development and instructional design, especially when a course attracts a diverse group of learners, are provided

Investigating the Impact of Learners’ Learning Styles on the Acceptance of Open Learner Models for Information Sharing

Individual differences in learners’ learning styles can have a significant effect on their acceptance of collaboration technologies to facilitate the sharing of learning information in technology-based collaborative learning. There is, however, a lack of understanding of the impact of learning styles on the acceptance of open learner models as a collaboration technology for information sharing. This study investigates the impact of learners’ learning styles on their acceptance of open learner models for information sharing. A total of 240 undergraduate students in a university in Malaysia have participated in the online survey. A chi-square test is performed to explore the relationship between learning styles and the acceptance of open learner models for information sharing in technology-based collaborative learning. The result reveals that learning styles have no significant impact on learners’ acceptance of open learner models for information sharing. The implications of this study can assist open learner models designers to apply appropriate instructional design strategies in developing open learner models applications

Digital Crowdsourcing in Healthcare Environment Co-design

Improving user experiences of healthcare environments via their participation has become a central theme in healthcare studies and strategic agendas. The co-design approach is often utilized to take into account opinions from different stakeholders including hospital staff. However, there are a number of competing stimuli and demands on staff at any point in time potentially making it difficult for them to participate in the co-design processes. Digital crowdsourcing may engage staff in participating in the design and appraisal of hospital environments when they have a spare moment by collecting small amounts of relevant data. In order to explore this, we have implemented a digital crowdsourcing co-design prototype. As users’ perceived acceptance of technologies is among the determining factors for a successful digital approach, in this paper, we report on participants’ acceptance of the prototype, aiming to reflect if and to what extend they accept this prototype to aid further development

Effect of emotions and personalisation on cancer website reuse intentions

The effect of emotions and personalisation on continuance use intentions in online health services is underexplored. Accordingly, we propose a research model for examining the impact of emotion- and personalisation-based factors on cancer website reuse intentions. We conducted a study using a real-world NGO cancer-support website, which was evaluated by 98 participants via an online questionnaire. Model relations were estimated using the PLS-SEM method. Our findings indicated that pre-use emotions did not significantly influence perceived personalisation. However, satisfaction with personalisation, and perceived usefulness mediated by satisfaction, increased reuse intentions. In addition, post-use positive emotions potentially influenced reuse intentions. Our paper, therefore, illustrates the applicability of theory regarding continuance use intentions to cancer-support websites and highlights the importance of personalisation for these purposes