156 research outputs found

    Building an interactive simulator on a cloud computing platform to enhance students' understanding of computer systems

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    Cloud computing technologies have been widely adopted to improve the competitiveness and efficiency of core operations in many enterprises through additional computational resources and/or storage as provided on the underlying cloud platforms. Yet there are relatively few studies on how cloud computing may enhance students' understanding of a specific subject in e-learning systems. In a research project awarded by the Microsoft Research Asia, we successfully developed an interactive simulator aimed to enhance the students' understanding of essential concepts related to computer systems through live animations on a cloud computing platform. Essentially, we propose to integrate the latest technologies of cloud computing and learning objects into an efficient, flexible and interactive simulator to deliver powerful computing services for dynamic simulations of various computer systems specified as 'reactive' models of learning objects on the cloud storage. More importantly, through adopting the IEEE learning object metadata standard to represent each key concept/component in different computer systems, our proposed simulator can readily facilitate the sharing and reuse of relevant concepts for future e-learning applications. The system design and prototype implementation of our cloud-based interactive simulator is carefully considered with a thorough evaluation plan to investigate on how learners may benefit from our interactive simulator in various ways. And there are many directions for future extensions. © 2013 IEEE.published_or_final_versio

    Using cloud computing and mobile devices to facilitate students' learning through e-learning games

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    The recent advance in cloud computing and mobile devices empowers many innovative e-learning systems or games with increased interactivity and improved features. In this paper, we consider an innovative framework of cloud-based e-learning games that can be assessed through mobile devices to enhance students' learning anytime and anywhere. Being model-based, our proposal is adaptive and highly portable that can be easily customized to any existing cloud platform. Besides, our proposed framework allows course instructors or game designers to flexibly modify any part of an e-learning game, and continuously monitor the performance of individuals who try to compete with each other to attain better results. It is worth noting that this paper reports an on-going work, namely the iGame@Cloud system, for which a thorough evaluation will be conducted later. After all, our proposal stimulates many interesting directions for further exploration. © 2013 IEEE.published_or_final_versio

    Applying an evolutionary approach for learning path optimization in the next-generation e-learning systems

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    Learning analytics is targeted to better understand and optimize the process of learning and its environments through the measurement, collection and analysis of learners' data and contexts. To advise people's learning in a specific subject, most intelligent e-learning systems would require course instructors to explicitly input some prior knowledge about the subject such as all the pre-requisite requirements between course modules. Yet human experts may sometimes have conflicting views leading to less desirable learning outcomes. In a previous study, we proposed a complete system framework of learning analytics to perform an explicit semantic analysis on the course materials, followed by a heuristic-based concept clustering algorithm to group relevant concepts before finding their relationship measures, and lastly employing a simple yet efficient evolutionary approach to return the optimal learning sequence. In this paper, we carefully consider to enhance the original evolutionary optimizer with the hill-climbing heuristic, and also critically evaluate the impacts of various experts' recommended learning sequences possibly with conflicting views to optimize the learning paths for the next-generation e-learning systems. More importantly, the integration of heuristics can make our proposed framework more self-adaptive to less structured knowledge domains with conflicting views. To demonstrate the feasibility of our prototype, we implemented a prototype of the proposed e-learning system framework for learning analytics. Our empirical evaluation clearly revealed many possible advantages of our proposal with interesting directions for future investigation. © 2013 IEEE.published_or_final_versio

    Technology-enhanced learning for improving complex problem-solving expertise

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    Learning through complex problem solving has received increased attention in educational areas. This is particularly the case in challenging domains such as medical education, where problem-based learning (PBL) is widely adopted and found to be effective in helping students to improve their abilities in clinical reasoning, problem solving, and self-directed and cooperative learning. However, there are concerns about PBL’s effects on development of systemic knowledge structures and efficient reasoning processes, which are critical for expertise development. To address the challenge, a technology-enhanced learning environment is proposed in this study, aiming to improve students’ complex problem-solving expertise by scaffolding their problem solving or reasoning processes as well as knowledge construction with support of expert knowledge.published_or_final_versio

    IClass assessment: a pen-based assessment and feedback platform

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    In recent years, the demand of in-class interaction and assessment for learning is rising. There is more emphasis on using electronic tools for assessment for learning in order to facilitate teachers seeking to identify and diagnose student learning problems, and providing quality feedback for students on how to improve their work. This paper discusses the challenges of e-assessment and introduced a pen-based assessment and feedback platform developed in Hong Kong. The platform can provide an efficient and effective channel for providing feedback so as to monitor any learning difficulties and help teachers to diagnose students' prior skills and abilities, providing feedback for them to adjust the curriculum or provide additional assistance accordingly. © 2013 IEEE.published_or_final_versio

    Assigning process-oriented roles in concept mapping mediated online group learning

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    Group interaction is a key component of group-based learning. However, its implementation in existing learning practices is inefficient. Previous studies discussed the use of concept mapping in group learning. Apart from its clear benefits for group learning and interaction, deficiencies of using concept mapping in distance groups were also recognized, mainly related to labor division, group coordination, and collaboration strategies. This study aims to address the challenge by proposing an intervention strategy of assigning process-oriented roles, i.e., cognitive leader, met cognitive leader, and socio-emotional leader, to students in concept mapping mediated online group learning to facilitate group learning processes. An experimental study in authentic teaching practices was implemented to evaluate the effectiveness of the proposed strategy. © 2013 IEEE.published_or_final_versio

    Facilitating social collaboration in mobile cloud-based learning: a teamwork as a service (TaaS) approach

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    Mobile learning is an emerging trend that brings many advantages to distributed learners, enabling them to achieve collaborative learning, in which the virtual teams are usually built to engage multiple learners working together towards the same pedagogical goals in online courses. However, the socio-technical mechanisms to enhance teamwork performance are lacking. To meet this gap, we adopt the social computing to affiliate learners’ behaviors and offer them computational choices to build a better collaborative learning context. Combining the features of the cloud environment, we have identified a learning flow based on Kolb team learning experience to realize this approach. Such novel learning flow can be executed by our newly designed system, Teamwork as a Service (TaaS), in conjunction with the cloud-hosting learning management systems. Following this learning flow, learners benefit from the functions provided by cloud-based services when cooperating in a mobile environment, being organized into cloud-based teaching strategies namely “Jigsaw Classroom”, planning and publishing tasks, as well as rationalizing task allocation and mutual supervision. In particular, we model the social features related to the collaborative learning activities, and introduce a genetic algorithm approach to grouping learners into appropriate teams with two different team formation scenarios. Experimental results prove our approach is able to facilitate teamwork, while learners’ capabilities and preferences are taken into consideration. In addition, empirical evaluations have been conducted to show the improvement of collaborative learning brought by TaaS in real university level courses

    A Closer Look into Recent Video-based Learning Research: A Comprehensive Review of Video Characteristics, Tools, Technologies, and Learning Effectiveness

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    People increasingly use videos on the Web as a source for learning. To support this way of learning, researchers and developers are continuously developing tools, proposing guidelines, analyzing data, and conducting experiments. However, it is still not clear what characteristics a video should have to be an effective learning medium. In this paper, we present a comprehensive review of 257 articles on video-based learning for the period from 2016 to 2021. One of the aims of the review is to identify the video characteristics that have been explored by previous work. Based on our analysis, we suggest a taxonomy which organizes the video characteristics and contextual aspects into eight categories: (1) audio features, (2) visual features, (3) textual features, (4) instructor behavior, (5) learners activities, (6) interactive features (quizzes, etc.), (7) production style, and (8) instructional design. Also, we identify four representative research directions: (1) proposals of tools to support video-based learning, (2) studies with controlled experiments, (3) data analysis studies, and (4) proposals of design guidelines for learning videos. We find that the most explored characteristics are textual features followed by visual features, learner activities, and interactive features. Text of transcripts, video frames, and images (figures and illustrations) are most frequently used by tools that support learning through videos. The learner activity is heavily explored through log files in data analysis studies, and interactive features have been frequently scrutinized in controlled experiments. We complement our review by contrasting research findings that investigate the impact of video characteristics on the learning effectiveness, report on tasks and technologies used to develop tools that support learning, and summarize trends of design guidelines to produce learning video

    Learning Buckets: Helping Teachers Introduce Flexibility in the Management of Learning Artifacts Across Spaces

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    Producción Científicaechnology offers rich opportunities for learning across different physical and virtual spaces. However, most of current across-spaces proposals are either highly teacher-centered, inflexible in the students’ self-management of learning artifacts during the enactment, or allow the teacher little/no control of such students’ management of artifacts. Moreover, these proposals tend to be disconnected from the practices and tools that are usual in the classroom. How can we achieve a middle ground between keeping the teacher in control of across-spaces situations and, at the same time, providing students with a degree of flexibility to manage learning artifacts? Aiming to address such challenge we propose the notion of learning bucket, and the Bucket-Server, a system implementing such notion. A learning bucket is a container of learning artifacts which are generated and/or accessed across-spaces by the students during the enactment, according to constraints configured by teachers at design time. The responsive evaluation conducted, based on a feature analysis and a pilot study with experts, suggests that learning buckets can help evolve from teacher- to student-centered approaches, while maintaining the teacher in control of students’ actions. The evaluation also indicates that the Bucket-Server surpasses the support provided by alternative proposals to across-spaces learning.Ministerio de Economía, Industria y Competitividad (Project TIN2014- 53199-C3-2- R)Junta de Castilla y León (programa de apoyo a proyectos de investigación – Ref. VA277U14
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