136,289 research outputs found

    Culture and E-Learning: Automatic Detection of a Users’ Culture from Survey Data

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    Knowledge about the culture of a user is especially important for the design of e-learning applications. In the experiment reported here, questionnaire data was used to build machine learning models to automatically predict the culture of a user. This work can be applied to automatic culture detection and subsequently to the adaptation of user interfaces in e-learning

    A Longitudinal Study on the Effect of Hypermedia on Learning Dimensions, Culture and Teaching Evaluation

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    Earlier studies have found the effectiveness of hypermedia systems as learning tools heavily depend on their compatibility with the cognitive processes by which students perceive, understand and learn from complex information\ud sources. Hence, a learner’s cognitive style plays a significant role in determining how much is learned from a hypermedia learning system. A longitudinal study of Australian and Malaysian students was conducted over two semesters in 2008. Five types of predictor variables were investigated with cognitive style: (i) learning dimensions (nonlinear learning, learner control, multiple tools); (ii)\ud culture dimensions (power distance, uncertainty avoidance, individualism/collectivism, masculinity/femininity, long/short term orientation); (iii) evaluation of units; (iv) student demographics; and (v) country in which students studied. This study uses both multiple linear regression and linear mixed effects to model the relationships among the variables. The results from this study support the findings of a cross-sectional study conducted by Lee et al. (2010); in particular, the predictor variables are significant to determine students’ cognitive style

    Raising students' awareness of cross-cultural contrastive rhetoric in English writing via an e-learning course

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    This study investigated the potential impact of e-learning on raising overseas students' cultural awareness and explored the possibility of creating an interactive learning environment for them to improve their English academic writing. The study was based on a comparison of Chinese and English rhetoric in academic writing, including a comparison of Chinese students' writings in Chinese with native English speakers' writings in English and Chinese students' writings in English with the help of an e-course and Chinese students' writings in English without the help of an e-course. Five features of contrastive rhetoric were used as criteria for the comparison. The experimental results show that the group using the e-course was successful in learning about defined aspects of English rhetoric in academic writing, reaching a level of performance that equalled that of native English speakers. Data analysis also revealed that e-learning resources helped students to compare rhetorical styles across cultures and that the interactive learning environment was effective in improving overseas students' English academic writing

    Capture, Learning, and Synthesis of 3D Speaking Styles

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    Audio-driven 3D facial animation has been widely explored, but achieving realistic, human-like performance is still unsolved. This is due to the lack of available 3D datasets, models, and standard evaluation metrics. To address this, we introduce a unique 4D face dataset with about 29 minutes of 4D scans captured at 60 fps and synchronized audio from 12 speakers. We then train a neural network on our dataset that factors identity from facial motion. The learned model, VOCA (Voice Operated Character Animation) takes any speech signal as input - even speech in languages other than English - and realistically animates a wide range of adult faces. Conditioning on subject labels during training allows the model to learn a variety of realistic speaking styles. VOCA also provides animator controls to alter speaking style, identity-dependent facial shape, and pose (i.e. head, jaw, and eyeball rotations) during animation. To our knowledge, VOCA is the only realistic 3D facial animation model that is readily applicable to unseen subjects without retargeting. This makes VOCA suitable for tasks like in-game video, virtual reality avatars, or any scenario in which the speaker, speech, or language is not known in advance. We make the dataset and model available for research purposes at http://voca.is.tue.mpg.de.Comment: To appear in CVPR 201

    Representing Style by Feature Space Archetypes: Description and Emulation of Spatial Styles in an Architectural Context

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    The role of unit evaluation, learning and culture dimensions related to student cognitive style in hypermedia learning

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    Recent developments in learning technologies such as hypermedia are\ud becoming widespread and offer significant contributions to improving the delivery\ud of learning and teaching materials. A key factor in the development of hypermedia\ud learning systems is cognitive style (CS) as it relates to users‟ information\ud processing habits, representing individual users‟ typical modes of perceiving,\ud thinking, remembering and problem solving.\ud \ud \ud \ud \ud A total of 97 students from Australian (45) and Malaysian (52) universities\ud participated in a survey. Five types of predictor variables were investigated with\ud the CS: (i) three learning dimensions; (ii) five culture dimensions; (iii) evaluation\ud of units; (iv) demographics of students; and (v) country in which students studied.\ud Both multiple regression models and tree-based regression were used to analyse\ud the direct effect of the five types of predictor variables, and the interactions within\ud each type of predictor variable. When comparing both models, tree-based\ud regression outperformed the generalized linear model in this study. The research\ud findings indicate that unit evaluation is the primary variable to determine students‟\ud CS. A secondary variable is learning dimension and, among the three dimensions,\ud only nonlinear learning and learner control dimensions have an effect on students‟\ud CS. The last variable is culture and, among the five culture dimensions, only\ud power distance, long term orientation, and individualism have effects on students‟\ud CS. Neither demographics nor country have an effect on students‟ CS.\ud These overall findings suggest that traditional unit evaluation, students‟\ud preference for learning dimensions (such as linear vs non-linear), level of learner\ud control and culture orientation must be taken into consideration in order to enrich\ud students‟ quality of education. This enrichment includes motivating students to\ud acquire subject matter through individualized instruction when designing,\ud developing and delivering educational resources

    Information systems for interactive learning: Design perspective

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    This paper aims to present and discuss educational issues and relevant research to universities and colleges in the Arabian Gulf Region. This include cultural, students’ learning preferences and the use of information and communication technology. It particularly focuses on interactive learning through the consideration of learning styles. It explores the sequential-global learning styles profile of undergraduate students as part of a continuous research in Information Systems design with a particular focus on the design of Interactive Learning Systems (ILSs). A study to examine the learning style profile of undergraduate students in a cohort of Management Information Systems at a UAE university has been conducted, and a discussion and recommendations on how these findings can be reflected on the design of ILSs are provided
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