3,960 research outputs found

    E-learning and e-systems to facilitate learning from marked student work : a thesis presented in partial fulfillment of the requirements for the degree of Master of Science in Computer Science at Massey University

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    Heinrich (2004a) first introduced the concept of 'electronic repositories of marked student work' and suggested an innovative approach of learning from marked student work. This research project further develops this e-learning approach. The learning approach was analyzed in the framework of modern educational theories, especially those relevant to formative assessment. Learning activities that mostly suit this new approach were identified. These activities show a large degree of variation in cognitive complexity and learning effectiveness, and according to their characteristics, can be associated with various learning styles. A range of factors that need to be considered in constructing learning processes based on these learning activities were investigated. The conceptualization of an e-learning environment to support the approach of learning from marked student work was developed. Three major objectives of developing such an e-learning environment were identified. Based on these objectives the general framework of e-learning from marked student work was outlined. There were very few applications of this approach in teaching practice and no study has been done on its effectiveness in the practical teaching before this research. An initial learning experiment using this approach was carried out. The effectiveness of this approach was evaluated and various aspects associated with this approach were investigated. To fully support this new learning approach, a web-based prototype system named E-Repositories of Marked Student Work, was developed. This research project developed opportunities for student learning and provided guidelines for teaching staff on how to reuse valuable learning resources in their teaching practice in the e-learning context

    ALT-C 2010 - Conference Proceedings

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    ALT-C 2010 - Conference Introduction and Abstracts

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    Beyond “Data Thrifting”: An Investigation of Factors Influencing Research Data Reuse In the Social Sciences

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    The development of e-Research infrastructure has enabled data to be shared and accessed more openly. Policy mandates for data sharing have contributed to the increasing availability of research data through data repositories, which create favorable conditions for the reuse of data for purposes not always anticipated by original collectors. Despite the current efforts to promote transparency and reproducibility in science, data reuse cannot be assumed, nor merely considered a “thrifting” activity where scientists shop around in data repositories considering only the ease of access to data. This research was driven by three main questions: 1) What are the factors that influence scientists’ research data reuse? 2) To what degree do these factors influence scientists’ research data reuse? and 3) To what extent do scientists reuse research data? Following a sequential mixed-method approach, this study sought to provide a more nuanced view of the underlying factors that affect social scientists’ intentions to reuse data, as well as the impact of these factors on the actual reuse of data. Findings from a preliminary small-scale exploratory study with 13 social scientists produced 25 factors that were found to influence their perceptions and experiences, including both their unsuccessful and successful attempts to reuse data. These factors were grouped into six theoretical variables: perceived benefits, perceived risks, perceived effort, social influence, facilitating conditions, and perceived reusability. The variables were articulated in a conceptual model drawing upon the Unified Theory of Acceptance and Use of Technology (UTAUT) in order to examining social scientists’ intentions and behaviors towards the reuse of research data. The proposed hierarchical component model and the research hypotheses were validated through a survey, which was distributed to 4,500 social scientists randomly selected from the Pivot/Community of Science (CoS) database. A total of 743 social scientists participated in the survey, of which 564 cases were included in the analysis. The survey data were analyzed using the Partial Least Square Structural Equation Modeling (PLS-SEM) technique, and supplemented by ad-hoc group comparison analyses. Survey results demonstrated that social scientists’ data reuse intention and reuse behavior were indeed influenced by different factors beyond frugality. More specifically, the more practical and social benefits social scientists perceive from reusing research data, the more likely they intended to reuse data. Similarly, peer and disciplinary influence had a positive effect on social scientists’ intention to reuse data collected/produced by others. On the contrary, the construct perceived risks was found to negatively influence social scientists’ intention to reuse existing research data collected by others. Facilitating conditions and intention to reuse were found to positively correlate to actual data reuse behavior. Perceived effort was found not statistically significant, indicating that reusing data from others did not involve as much effort as collecting/producing primary data. Perceived reusability failed to be measured, due to the lack of convergent validity. Ad-hoc group comparison tests found that intention and data reuse behavior depended on sub-disciplines’ traditions and the methodological approach social scientists followed. The findings of this research provide an in-depth understanding about the reuse of research data in the context of open science, and provide a collection of factors that influence social scientists’ decisions to reuse research data collected by others. Additionally, they update our knowledge of data reuse behavior and contribute to the body of data reuse literature by establishing a conceptual model that can be validated by future research. In terms of practice, it offers recommendations for policy makers, data scientists, and stakeholders from data repositories on defining strategies and initiatives to leverage data reuse and make publicly available data more actionable

    Editorial

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    Addressing efficiency and quality of marking in essay assessment with e-learning support

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    The value of formative assessment using essays is clearly defined in the educational literature. Essays focus on the highest-level learning outcomes of analysing, evaluating, and creating. Formative assessment provides students with feedback to guide their learning. Current e-learning systems largely focus on summative assessment and give only very limited support for the management and marking of essay assignments. After outlining the educational theories on essay assignments, this article introduces two novel e-learning applications, WebCTConnect and MarkTool. Functional descriptions of these applications and their grounding in assessment theory are given. It is argued that e-learning tools can increase the efficiency in dealing with essay assignments and that the quality of essay assessment can be improved by incorporating scoring rubrics, offering class-wide analysis of feedback, and providing tools for the cooperation of marking teams

    HaIRST: Harvesting Institutional Resources in Scotland Testbed. Final Project Report

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    The HaIRST project conducted research into the design, implementation and deployment of a pilot service for UK-wide access of autonomously created institutional resources in Scotland, the aim being to investigate and advise on some of the technical, cultural, and organisational requirements associated with the deposit, disclosure, and discovery of institutional resources in the JISC Information Environment. The project involved a consortium of Scottish higher and further education institutions, with significant assistance from the Scottish Library and Information Council. The project investigated the use of technologies based on the Open Archives Initiative (OAI), including the implementation of OAI-compatible repositories for metadata which describe and link to institutional digital resources, the use of the OAI protocol for metadata harvesting (OAI-PMH) to automatically copy the metadata from multiple repositories to a central repository, and the creation of a service to search and identify resources described in the central repository. An important aim of the project was to identify issues of metadata interoperability arising from the requirements of individual institutional repositories and their impact on services based on the aggregation of metadata through harvesting. The project also sought to investigate issues in using these technologies for a wide range of resources including learning, teaching and administrative materials as well as the research and scholarly communication materials considered by many of the other projects in the JISC Focus on Access to Institutional Resources (FAIR) Programme, of which HaIRST was a part. The project tested and implemented a number of open source software packages supporting OAI, and was successful in creating a pilot service which provides effective information retrieval of a range of resources created by the project consortium institutions. The pilot service has been extended to cover research and scholarly communication materials produced by other Scottish universities, and administrative materials produced by a non-educational institution in Scotland. It is an effective testbed for further research and development in these areas. The project has worked extensively with a new OAI standard for 'static repositories' which offers a low-barrier, low-cost mechanism for participation in OAI-based consortia by smaller institutions with a low volume of resources. The project identified and successfully tested tools for transforming pre-existing metadata into a format compliant with OAI standards. The project identified and assessed OAI-related documentation in English from around the world, and has produced metadata for retrieving and accessing it. The project created a Web-based advisory service for institutions and consortia. The OAI Scotland Information Service (OAISIS) provides links to related standards, guidance and documentation, and discusses the findings of HaIRST relating to interoperability and the pilot harvesting service. The project found that open source packages relating to OAI can be installed and made to interoperate to create a viable method of sharing institutional resources within a consortium. HaIRST identified issues affecting the interoperability of shared metadata and suggested ways of resolving them to improve the effectiveness and efficiency of shared information retrieval environments based on OAI. The project demonstrated that application of OAI technologies to administrative materials is an effective way for institutions to meet obligations under Freedom of Information legislation

    Immersive Telepresence: A framework for training and rehearsal in a postdigital age

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