bao cao blended learning

Ngày tải lên: 09/10/2014, 23:10

Ngày tải lên: 17/10/2015, 20:52

Ngày tải lên: 11/08/2014, 05:21

Ngày tải lên: 11/08/2014, 16:20

Ngày tải lên: 23/10/2014, 07:52

... học 10 nâng cao  Nghiên cứu ứng dụng phần mềm mã nguồn mở Moodle vào xây đựng khóa học mạng 2.2 Phương pháp tham vấn chuyên gia Kết nghiên cứu: 3.1 Mô hình học kết hợp (Blended Learning) : 3.1.1 ... tượng cụ thể" Tác giả Victoria L Tinio cho "Học kết hợp (Blended Learning) để mô hình học kết hợp hình thức lớp học truyền thống giải pháp E - learning" [6,tr4] Các khái niệm dưa chủ yếu dựa kết hợp ... Nguyễn Danh Nam đưa nhận định: Sự kết hợp e - learning với lớp học truyền thống trở thành giải pháp tốt, tạo thành mô hình đào tạo gọi "Blended Learning" [3] Từ cách định nghĩa trên, hiểu cách...

Ngày tải lên: 14/01/2013, 11:16

... đề Phương Pháp Dạy Đại Học E -Learning Nhưng có tính mặt, pp Blended Learning có ưu khuyết điểm nó, xem thêm http://blendedlearningzone.com/pros-and-cons-of -blended- learning/ Theo thiển ý em, vòng ... E -Learning Mobile Learning (M -Learning) Vậy Mobile Learning ? - Mobile Learning cách học di động, sử dụng công cụ thiết bị di động điện thoại, máy tính bảng (tablet) để học lúc nơi - Mobile Learning ... hút Elearning Phần ta phân tích Xu hướng Elearning giới, thực trạng Elearning phân tích ưu khuyết điểm Elearning Trang: 40 Báo cáo chuyên đề Phương Pháp Dạy Đại Học E -Learning Các xu hướng Elearning...

Ngày tải lên: 09/01/2014, 12:20

... and Hal Daum´ III 2011 Learning speede accuracy tradeoffs in nondeterministic inference algorithms In COST: NIPS 2011 Workshop on Computational Trade-offs in Statistical Learning Jes´ s Gimnez ... Figure 3: NIST Results not to optimize it directly, but jointly with a more tunable metric BLEU The learning curve in Figure show that single-objective optimization of RIBES quickly falls into local ... Single−Objective RIBES 0.64 0.63 25 20 15 10 Pareto (PMO−PRO) 10 12 14 16 18 20 iteration Figure 4: Learning Curve on RIBES: comparing singleobjective optimization and PMO 0.35 Algorithm Runtime (seconds)...

Ngày tải lên: 19/02/2014, 19:20

... stochastic learning with feature selection inspired by multi-task learning The simple but effective idea is to randomly divide training data into evenly sized shards, use stochastic learning on ... applied multi-task learning for improved generalization in n-best reranking In contrast to our work, Duh et al (2010) did not incorporate multitask learning into distributed learning, but defined ... discriminative SMT is a special overfitting problem of current popular online learning techniques This is due to stochastic learning on a per-example basis where a weight update on a misclassified example...

Ngày tải lên: 19/02/2014, 19:20

... labeled training instances for supervised (Uzun et al., 2008) or semi-supervised (Han et al., 2008) learning algorithms Two state-of-the-art data-driven systems for English verbs are those that produced ... produce more accurate results on these complementary tasks while avoiding the use of any supervised learning Finally, a fundamental advantage of a datadriven, parse-free method is that it can be easily ... Andrew Ng, Michael Jordan, and John Lafferty 2003 Latent dirichlet allocation Journal of Machine Learning Research Olivier Bodenreider 2004 The Unified Medical Language System (UMLS): integrating...

Ngày tải lên: 19/02/2014, 19:20

... carried out by a virtual robot (MacMahon et al., 2006) 2.2 Lexicon Learning The central component of the system is the lexicon learning process which associates words and short phrases (n-grams) ... treating it as a ranking problem (Bordes et al., 2010), or a PCFG learning problem (Borschinger et al., 2011) Parallel to the work of learning from ambiguous supervision, other recent work has also ... 2010 Label ranking under ambiguous supervision for learning semantic correspondences In Proceedings of the 27th International Conference on Machine Learning (ICML-2010) Benjamin Borschinger, Bevan...

Ngày tải lên: 19/02/2014, 19:20

... inference algorithms to grounded learning problems An advantage of reducing grounded learning to grammatical inference is that it suggests new ways to generalise grounded learning models; we explore ... take social cues into account Reducing grounded learning with social cues to grammatical inference This section explains how we reduce ground learning problems with social cues to grammatical ... Johnson et al (2010) reduces grounded learning to grammatical inference for adaptor grammars and shows how it can be used to perform word segmentation as well as learning word-topic relationships,...

Ngày tải lên: 19/02/2014, 19:20

... term on the Web, a promising approach is automatically learning to extract phrasal translations or transliterations of phrase based on machine learning, or more specifically the conditional random ... Distance Label 14 O 13 O 12 O 11 B 10 I I O O O O O O O O E E -1 O Figure Example training data use a learning based approach to find translations In contrast to previous work described above, we exploit ... candidates, which are then ranked and returned as output Preliminary experiments and evaluations show our learning- based method cleanly combining various features, producing quality translations and transliterations...

Ngày tải lên: 19/02/2014, 19:20

... 600 300 100 Table 1: Three possible hypotheses of latent vectors for the definition of bank#n#1 Learning Latent Semantics of Definitions 2.1 Intuition Given only a few observed words in a definition, ... David M Blei, Andrew Y Ng, and Michael I Jordan 2003 Latent dirichlet allocation Journal of Machine Learning Research, Samuel Brody, Roberto Navigli, and Mirella Lapata 2006 Ensemble methods for unsupervised ... Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning Christiane Fellbaum 1998 WordNet: An Electronic Lexical Database MIT Press Thomas L Griffiths...

Ngày tải lên: 19/02/2014, 19:20

... remarks in Section The Learning Games A game platform should include several functional components such as the management of players’ accounts and the maintenance of players’ learning profiles Yet, ... approach to Chinese characters learning: System design and development, Proc of the Int’l Conf on Edutainment, 559–564 C.-Y Lee 2009 The cognitive and neural basis for learning to reading Chinese, ... Language Learning: The Use of Embodied Animation for Beginning Learners of Chinese Characters, Ph.D Diss., Columbia University, USA J R Saffran, R N Aslin, and E L Newport 1996 Statistical learning...

Ngày tải lên: 19/02/2014, 19:20

... algorithm in Figure does not generate every pair of bunsetsus.3 Active Learning for Parsing Most of the methods of active learning for parsing in previous work use selection of sentences that ... general framework of active learning, since the selection strategy with large margin classifiers (Section 2.2) is much simpler and seems more practical for active learning in Japanese dependency ... program of active learning and some additional scripts in Perl and sh Case if (j < i = k), then generate • {k − 1, k, “D”} if k − > j, • and {j, k, “D”} 6.5 Settings of Active Learning For initial...

Ngày tải lên: 20/02/2014, 04:20

... word of each n-gram • We had a separate learning rate for the embeddings and for the neural network weights We found that the embeddings should have a learning rate generally 1000–32000 times ... Unlike our Collobert and Weston (2008) embeddings, we did not extensively tune the learning rates for HLBL We used a learning rate of 1e-3 for both model parameters and embedding parameters We induced ... architecture for natural language processing: Deep neural networks with multitask learning ICML Liang, P (2005) Semi-supervised learning for natural language Master’s thesis, Massachusetts Institute of...

Ngày tải lên: 20/02/2014, 04:20

... effectiveness on a physical robot, but did not address the learning problem More generally, apprenticeship learning is well studied in the reinforcement learning literature, where the goal is to mimic the ... θ we use SARSA (Sutton and Barto, 1998), an online learning algorithm similar to Q -learning (Watkins and Dayan, 1992) Algorithm details the learning algorithm, which we follow here We iterate ... Abbeel and Andrew Y Ng 2004 Apprenticeship learning via inverse reinforcement learning In Proceedings of the Twenty-first International Conference on Machine Learning ACM Press A Anderson, M Bader,...

Ngày tải lên: 20/02/2014, 04:20

... machine active learning with applications to text classification Journal of Machine Learning Research (JMLR), 2:45–66 David Vickrey, Oscar Kipersztok, and Daphne Koller 2010 An active learning approach ... stopping active learning based on stabilizing predictions and the need for user-adjustable stopping In Proceedings of the Thirteenth Conference on Computational Natural Language Learning (CoNLL-2009), ... Natural Language Learning (CoNLL-2005), pages 144–151, Ann Arbor, Michigan, June Association for Computational Linguistics Vamshi Ambati, Stephan Vogel, and Jaime Carbonell 2010 Active learning and...

Ngày tải lên: 20/02/2014, 04:20

... Colorado, USA Ismail Fahmi and Gosse Bouma 2006 Learning to identify definitions using syntactic features In Proceedings of the EACL 2006 workshop on Learning Structured Information in Natural Language ... anyway: Automatic hypernym discovery In Proceedings of the 2009 AAAI Spring Symposium on Learning by Reading and Learning to Read, pages 88–93 Horacio Saggion 2004 Identifying denitions in text collections ... JJ indicate the noun and adjective classes, respectively ωi = 3.2 Algorithm We now describe our learning algorithm based on Word-Class Lattices The algorithm consists of three steps: 1320 [In...

Ngày tải lên: 20/02/2014, 04:20