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Titlebook: Current Developments in Web Based Learning; ICWL 2015 Internatio Zhiguo Gong,Dickson K. W. Chiu,Di Zou Conference proceedings 2016 Springer

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51#
發(fā)表于 2025-3-30 09:36:47 | 只看該作者
Women’s Football in Latin Americasers and learning materials. Thus, it is useful to manage various learners and share the data efficiently. We here develop a social network application, V-share to facilitate the learner communication and share the learning data based on cloud computing. The V-share has achieved functions of sending
52#
發(fā)表于 2025-3-30 14:28:22 | 只看該作者
Rosa López de D’Amico,Lesbia Verenzuelahese websites. Reviews written by a user and reviews rated by a user actually reflect a user’s interests and disinterest. Thus, they are very useful for user profiling. In this paper, we explore users’ reviews and ratings on reviews for personalized search and propose a review-based user profiling m
53#
發(fā)表于 2025-3-30 17:20:45 | 只看該作者
https://doi.org/10.1007/978-3-031-09253-4le helps the users to get familiar with the rhetorical moves and linguistic features found in the model essays; the second module trains the users to recognise the problems with content and form and prepare the users for peer review; the third module simulates the test environment for the users to p
54#
發(fā)表于 2025-3-30 21:53:25 | 只看該作者
55#
發(fā)表于 2025-3-31 03:11:53 | 只看該作者
56#
發(fā)表于 2025-3-31 08:53:19 | 只看該作者
978-3-319-32864-5Springer International Publishing Switzerland 2016
57#
發(fā)表于 2025-3-31 11:43:13 | 只看該作者
Towards an Architecture for e-Learning Infrastructures on a National Level: A Case Study of AfgRENian Education and Research Network (EENet) as an NREN example of a developed country, the Pakistan Education and the Research Network (PERN) as an example of a developing country and the Afghanistan Research and Education Network (AfgREN).
58#
發(fā)表于 2025-3-31 15:48:34 | 只看該作者
Predicting Pre-knowledge on Vocabulary from e-Learning Assignments for Language Learnersts such as writing assignments and reading essays. The experimental study on real participants shows that the proposed predicting model is very effective and can be exploited for various applications in the future.
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