18,762 research outputs found

    A Phone Learning Model for Enhancing Productivity of Visually Impaired Civil Servants

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    Phone-based learning in civil service is the use of voice technologies to deliver learning and capacity building training services to government employees. The Internet revolution and advancement in Information and Communications Technology (ICT) have given rise to online and remote staff training for the purpose of enhancing workers productivity. The need for civil servants in Nigeria to develop capacity that will enhance knowledge is a key requirement to having competitive advantage in the work place. Existing online learning platforms (such as web-based learning, mobile learning, etc) did not consider the plight of the visually impaired. These platforms provide graphical interfaces that require sight to access. The visually impaired civil servants require auditory access to functionalities that exist in learning management system on the Internet. Thus a gap exist between the able-bodied and visually impaired civil servants on accessibility to e-learning platform. The objective of this paper is to provide a personalized telephone learning model and a prototype application that will enhance the productivity of the visually impaired workers in Government establishments in Nigeria. The model was designed using Unified Modeling Language (UML) diagram. The prototype application was implemented and evaluated. With the proposed model and application, the visually and mobility impaired worker are able to participate in routine staff training and consequently enhances their productivity just like their able-bodied counterparts. The prototype application also serves as an alternative training platform for the able-bodied workers. Future research direction for this study will include biometric authentication of learners accessing the applicatio

    A Phone Learning Model for Enhancing Productivity of Visually Impaired Civil Servants

    Get PDF
    Phone-based learning in civil service is the use of voice technologies to deliver learning and capacity building training services to government employees. The Internet revolution and advancement in Information and Communications Technology (ICT) have given rise to online and remote staff training for the purpose of enhancing workers productivity. The need for civil servants in Nigeria to develop capacity that will enhance knowledge is a key requirement to having competitive advantage in the work place. Existing online learning platforms (such as web-based learning, mobile learning, etc) did not consider the plight of the visually impaired. These platforms provide graphical interfaces that require sight to access. The visually impaired civil servants require auditory access to functionalities that exist in learning management system on the Internet. Thus a gap exist between the able-bodied and visually impaired civil servants on accessibility to e-learning platform. The objective of this paper is to provide a personalized telephone learning model and a prototype application that will enhance the productivity of the visually impaired workers in Government establishments in Nigeria. The model was designed using Unified Modeling Language (UML) diagram. The prototype application was implemented and evaluated. With the proposed model and application, the visually and mobility impaired worker are able to participate in routine staff training and consequently enhances their productivity just like their able-bodied counterparts. The prototype application also serves as an alternative training platform for the able-bodied workers. Future research direction for this study will include biometric authentication of learners accessing the applicatio

    Heuristic Evaluation for Serious Immersive Games and M-instruction

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    © Springer International Publishing Switzerland 2016. Two fast growing areas for technology-enhanced learning are serious games and mobile instruction (M-instruction or M-Learning). Serious games are ones that are meant to be more than just entertainment. They have a serious use to educate or promote other types of activity. Immersive Games frequently involve many players interacting in a shared rich and complex-perhaps web-based-mixed reality world, where their circumstances will be multi and varied. Their reality may be augmented and often self-composed, as in a user-defined avatar in a virtual world. M-instruction and M-Learning is learning on the move; much of modern computer use is via smart devices, pads, and laptops. People use these devices all over the place and thus it is a natural extension to want to use these devices where they are to learn. This presents a problem if we wish to evaluate the effectiveness of the pedagogic media they are using. We have no way of knowing their situation, circumstance, education background and motivation, or potentially of the customisation of the final software they are using. Getting to the end user itself may also be problematic; these are learning environments that people will dip into at opportune moments. If access to the end user is hard because of location and user self-personalisation, then one solution is to look at the software before it goes out. Heuristic Evaluation allows us to get User Interface (UI) and User Experience (UX) experts to reflect on the software before it is deployed. The effective use of heuristic evaluation with pedagogical software [1] is extended here, with existing Heuristics Evaluation Methods that make the technique applicable to Serious Immersive Games and mobile instruction (M-instruction). We also consider how existing Heuristic Methods may be adopted. The result represents a new way of making this methodology applicable to this new developing area of learning technology

    IMPROVING THE DEPENDABILITY OF DESTINATION RECOMMENDATIONS USING INFORMATION ON SOCIAL ASPECTS

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    Prior knowledge of the social aspects of prospective destinations can be very influential in making travel destination decisions, especially in instances where social concerns do exist about specific destinations. In this paper, we describe the implementation of an ontology-enabled Hybrid Destination Recommender System (HDRS) that leverages an ontological description of five specific social attributes of major Nigerian cities, and hybrid architecture of content-based and case-based filtering techniques to generate personalised top-n destination recommendations. An empirical usability test was conducted on the system, which revealed that the dependability of recommendations from Destination Recommender Systems (DRS) could be improved if the semantic representation of social attributes information of destinations is made a factor in the destination recommendation process

    Case studies of personalized learning

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    Deliverable 4.1, Literature review of personalised learning and the Cloud, started with an evaluation and synthesis of the definitions of personalized learning, followed by an analysis of how this is implemented in a method (e-learning vs. i-learning, m-learning and u-learning), learning approach and the appropriate didactic process, based on adapted didactic theories. From this research a list of criteria was created needed to implement personalised learning onto the learner of the future. This list of criteria is the basis for the analysis of all case studies investigated. – as well to the learning process as the learning place. In total 60 case studies (all 59 case studies mentioned in D6.4 Education on the Cloud 2015 + one extra) were analysed. The case studies were compared with the list of criteria, and a score was calculated. As a result, the best examples could be retained. On average most case studies were good on: taking different learning methods into account, interactivity and accessibility and usability of learning materials for everyone. All had a real formal education content, thus aiming at the core-curriculum, valuing previous knowledge, competences, life and work skills, also informal. Also the availability of an instructor / tutor or other network of peers, experts and teachers to guide and support the learning is common. On the other hand, most case studies lack diagnostics tests as well at the start (diagnostic entry test), during the personalized learning trajectory and at the end (assessment at the end). Also most do not include non-formal and informal learning aspects. And the ownership of personalized learning is not in the hands of the learner. Five of the 60 case studies can as a result be considered as very good examples of real personalized learning

    User-centred design of flexible hypermedia for a mobile guide: Reflections on the hyperaudio experience

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    A user-centred design approach involves end-users from the very beginning. Considering users at the early stages compels designers to think in terms of utility and usability and helps develop the system on what is actually needed. This paper discusses the case of HyperAudio, a context-sensitive adaptive and mobile guide to museums developed in the late 90s. User requirements were collected via a survey to understand visitors’ profiles and visit styles in Natural Science museums. The knowledge acquired supported the specification of system requirements, helping defining user model, data structure and adaptive behaviour of the system. User requirements guided the design decisions on what could be implemented by using simple adaptable triggers and what instead needed more sophisticated adaptive techniques, a fundamental choice when all the computation must be done on a PDA. Graphical and interactive environments for developing and testing complex adaptive systems are discussed as a further step towards an iterative design that considers the user interaction a central point. The paper discusses how such an environment allows designers and developers to experiment with different system’s behaviours and to widely test it under realistic conditions by simulation of the actual context evolving over time. The understanding gained in HyperAudio is then considered in the perspective of the developments that followed that first experience: our findings seem still valid despite the passed time

    Evaluation of mobile health education applications for health professionals and patients

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    Paper presented at 8th International conference on e-Health (EH 2016), 1-3 July 2016, Funchal, Madeira, Portugal. ABSTRACT Mobile applications for health education are commonly utilized to support patients and health professionals. A critical evaluation framework is required to ensure the usability and reliability of mobile health education applications in order to facilitate the saving of time and effort for the various user groups; thus, the aim of this paper is to describe a framework for evaluating mobile applications for health education. The intended outcome of this framework is to meet the needs and requirements of the different user categories and to improve the development of mobile health education applications with software engineering approaches, by creating new and more effective techniques to evaluate such software. This paper first highlights the importance of mobile health education apps, then explains the need to establish an evaluation framework for these apps. The paper provides a description of the evaluation framework, along with some specific evaluation metrics: an efficient hybrid of selected heuristic evaluation (HE) and usability evaluation (UE) factors to enable the determination of the usefulness and usability of health education mobile apps. Finally, an explanation of the initial results for the framework was obtained using a Medscape mobile app. The proposed framework - An Evaluation Framework for Mobile Health Education Apps – is a hybrid of five metrics selected from a larger set in heuristic and usability evaluation, filtered based on interviews from patients and health professionals. These five metrics correspond to specific facets of usability identified through a requirements analysis of typical users of mobile health apps. These metrics were decomposed into 21 specific questionnaire questions, which are available on request from first author
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