785 resultados para learning analytics framework
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This mixed method study aimed to redress the gap in the literature on academic service-learning partnerships, especially in Eastern settings. It utilized Enos and Morton's (2003) theoretical framework to explore these partnerships at the American University in Cairo (AUC). Seventy-nine community partners, administrators, faculty members, and students from a diverse range of age, citizenship, racial, educational, and professional backgrounds participated in the study. Qualitative interviews were conducted with members of these four groups, and a survey with both close-ended and open-ended questions administered to students yielded 61 responses. Qualitative analyses revealed that the primary motivators for partners' engagement in service-learning partnerships included contributing to the community, enhancing students' learning and growth, and achieving the civic mission of the University. These partnerships were characterized by short-term relationships with partners' aspiring to progress toward long-term commitments. The challenges to these partnerships included issues pertaining to the institution, partnering organizations, culture, politics, pedagogy, students, and faculty members. Key strategies for improving these partnerships included institutionalizing service-learning in the University and cultivating an institutional culture supportive of community engagement. Quantitative analyses showed statistically significant relationships between students' scores on the Community Awareness and Interpersonal Effectiveness scales and their overall participation in community service activities inside and outside the classroom, as well as a statistically significant difference between their scores on the Community Awareness scale and department offering service-learning courses. The study's outcomes underscore the role of the local culture in shaping service-learning partnerships, as well as the role of both curricular and extracurricular activities in boosting students' awareness of their community and interpersonal effectiveness. Cultivating a culture of community engagement and building support mechanisms for engaged scholarship are among the critical steps required by public policy-makers in Egypt to promote service-learning in Egyptian higher education. Institutionalizing service-learning partnerships at AUC and enhancing the visibility of these partnerships on campus and in the community are essential to the future growth of these collaborations. Future studies should explore factors affecting community partners' satisfaction with these partnerships, top-down and bottom-up support to service-learning, the value of reflection to faculty members, and the influence of students' economic backgrounds on their involvement in service-learning partnerships.
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The exponential growth of the subjective information in the framework of the Web 2.0 has led to the need to create Natural Language Processing tools able to analyse and process such data for multiple practical applications. They require training on specifically annotated corpora, whose level of detail must be fine enough to capture the phenomena involved. This paper presents EmotiBlog – a fine-grained annotation scheme for subjectivity. We show the manner in which it is built and demonstrate the benefits it brings to the systems using it for training, through the experiments we carried out on opinion mining and emotion detection. We employ corpora of different textual genres –a set of annotated reported speech extracted from news articles, the set of news titles annotated with polarity and emotion from the SemEval 2007 (Task 14) and ISEAR, a corpus of real-life self-expressed emotion. We also show how the model built from the EmotiBlog annotations can be enhanced with external resources. The results demonstrate that EmotiBlog, through its structure and annotation paradigm, offers high quality training data for systems dealing both with opinion mining, as well as emotion detection.
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The overarching purpose of this research program was to describe how intervening for academic deficits may be accompanied by changes in mental health. This multi-dimensional, multi-perspective, and iterative research program was developed to report on two distinct but related studies that addressed the same issue: in what ways does the mental health of students change as they transition from being struggling readers to more able readers? To describe the changes, these studies used a number of qualitative research methodologies—focus groups, individual interviews, and ethnographic case studies. Themes that emerged from the focus group and interview data in the first study were used to create a model that guided observations and interview questions in the second study. The first study described what parents, classroom teachers, and two reading instructors of nine previously struggling readers reported as the outcomes of becoming a more proficient reader. Data from this study indicated three broad domains in which change, as perceived by participants, occurred―cognitive/learning, behavioural/social, and psychological/emotional. Within these three domains, six dimensions were identified as having changed as reading improved: (a) academic achievement, (b) attitude, (c) attention, (d) behaviour, (e) mental health, and (f) empowerment. These domains, dimensions, and 15 constituent elements were used to create the model to guide the subsequent study. The purpose of the second study was to validate and refine this model by using an ethnographic case study approach to explore the ways in which the model accounted for the changes in reading and mental health seen in three boys over the months they participated in the intervention. By investigating the relationship between learning to read and mental health, this research aimed to enhance our understanding of how gains in reading may also improve the mental health of struggling readers. The model was found to be robust and a convenient conceptual framework to further our understanding of this relationship. Importantly, gains made in the cognitive/learning domain through an effective reading intervention, offered in a supportive learning environment, were shown to be accompanied by concomitant gains in both the behavioural/social and psychological/emotional domains—all of which enhance student thriving.
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This paper was prepared as a Policy Brief for discussion at the final conference of the project on Involuntary Loss of European Citizenship: Exchanging Knowledge and Identifying Guidelines for Europe, 11-12 December 2014. Co-funded by the European Commission’s DG for Justice, Citizenship and Fundamental Rights, the ILEC project has aimed to establish a framework for debate on international norms on involuntary loss of nationality. For more information visit: www.ilecproject.eu.
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Network governance of collective learning processes is an essential approach to sustainable development. The first section of the article briefly refers to recent theories about both market and government failures that express scepticism about the way framework conditions for market actors are set. For this reason, the development of networks for collective learning processes seems advantageous if new solutions are to be developed in policy areas concerned with long-term changes and a stepwise internalisation of externalities. With regard to corporate actors’ interests, the article shows recent insights from theories about the knowledge-based firm, where the creation of new knowledge is based on the absorption of societal views. This concept shifts the focus towards knowledge generation as an essential element in the evolution of sustainable markets. This involves at the same time the development of new policies. In this context innovation-inducing regulation is suggested and discussed. The evolution of the Swedish, German and Dutch wind turbine industries are analysed based on the approach of governance put forward in this article. We conclude that these coevolutionary mechanisms may take for granted some of the stabilising and orientating functions previously exercised by basic regulatory activities of the state. In this context, the main function of the governments is to facilitate learning processes that depart from the government functions suggested by welfare economics.
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This report offers a comparative policy study on adult learning within the scope of complementary research conducted by Beblavý et al. (2013) on how people upgrade their skills during their adult lifetimes. To achieve our objectives, we identified regulatory policies and financial support in 11 countries for two main categories of learning: formal higher education and employer-based training. Drawing upon the results of the country reports carried out by our partners in the MoPAct project, we found that in none of the countries examined is there an ‘older student’ policy. In most cases grants and financial support are awarded only up until a certain age. In all of the countries studied, standard undergraduate and post-graduate studies are available for part-time students. The distribution of full-time students and part-time students in tertiary education varies from one country to another as well as from one age group to another. The participation in full-time tertiary education programmes decreases with the age of students. In Lithuania, Latvia, Poland and the UK, there are no mandatory policies to ensure employer-based training. However, in Belgium, Czech Republic, Denmark, Estonia, Germany, Italy, the Netherlands and Spain, employer-based training is more clearly regulated and the employers might have obligations to provide training for their staff. Taking into consideration Beblavý et al. (2013), we observe that comparative differences across countries can be related to policy differences only in some cases. The policy framework seems to impact more the employer-based training than the educational attainment (upgrade of ISCED level). In Denmark, the Netherlands, Latvia, Lithuania, Czech Republic and Poland, we find a perfect match between policy outcomes and the results of Beblavý et al. (2013) related to employer-based training. This is not the case in the United Kingdom, where the two aspects observed are not correlated.
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Thesis (Ph.D.)--University of Washington, 2016-08
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Thesis (Ph.D.)--University of Washington, 2016-06
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Thesis (Ph.D.)--University of Washington, 2016-06
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Thesis (Ph.D.)--University of Washington, 2016-06
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Thesis (Master's)--University of Washington, 2016-06
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This article considers the question of what specific actions a teacher might take to create a culture of inquiry in a secondary school mathematics classroom. Sociocultural theories of learning provide the framework for examining teaching and learning practices in a single classroom over a two-year period. The notion of the zone of proximal development (ZPD) is invoked as a fundamental framework for explaining learning as increasing participation in a community of practice characterized by mathematical inquiry. The analysis draws on classroom observation and interviews with students and the teacher to show how the teacher established norms and practices that emphasized mathematical sense-making and justification of ideas and arguments and to illustrate the learning practices that students developed in response to these expectations.
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The Virtual Learning Environment (VLE) is one of the fastest growing areas in educational technology research and development. In order to achieve learning effectiveness, ideal VLEs should be able to identify learning needs and customize solutions, with or without an instructor to supplement instruction. They are called Personalized VLEs (PVLEs). In order to achieve PVLEs success, comprehensive conceptual models corresponding to PVLEs are essential. Such conceptual modeling development is important because it facilitates early detection and correction of system development errors. Therefore, in order to capture the PVLEs knowledge explicitly, this paper focuses on the development of conceptual models for PVLEs, including models of knowledge primitives in terms of learner, curriculum, and situational models, models of VLEs in general pedagogical bases, and particularly, the definition of the ontology of PVLEs on the constructivist pedagogical principle. Based on those comprehensive conceptual models, a prototyped multiagent-based PVLE has been implemented. A field experiment was conducted to investigate the learning achievements by comparing personalized and non-personalized systems. The result indicates that the PVLE we developed under our comprehensive ontology successfully provides significant learning achievements. These comprehensive models also provide a solid knowledge representation framework for PVLEs development practice, guiding the analysis, design, and development of PVLEs. (c) 2005 Elsevier Ltd. All rights reserved.
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A manager's perception of industry structure (dynamism) has the potential to impact various organizational strategies and behaviors. This may be particularly so with regard to perceptions driving organizational learning orientations and innovation based marketing strategy. The position taken here suggests that firms operating within a competitive industry tend to pursue innovative ways of performing value-creating activities, which requires the development of learning capabilities. The results of a study of SMEs suggest that market focused learning, relative to other learning capabilities plays a key role in the relationships between industry structure, innovation and brand performance. The findings also show that market focused learning and internally focused learning influence innovation and that innovation influences a brand's performance. (c) 2005 Elsevier Inc. All rights reserved.
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In this article, we propose a framework, namely, Prediction-Learning-Distillation (PLD) for interactive document classification and distilling misclassified documents. Whenever a user points out misclassified documents, the PLD learns from the mistakes and identifies the same mistakes from all other classified documents. The PLD then enforces this learning for future classifications. If the classifier fails to accept relevant documents or reject irrelevant documents on certain categories, then PLD will assign those documents as new positive/negative training instances. The classifier can then strengthen its weakness by learning from these new training instances. Our experiments’ results have demonstrated that the proposed algorithm can learn from user-identified misclassified documents, and then distil the rest successfully.