The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper proposes the design of an adaptive e- learning system with gamification elements. In the context of the increasing need to keep learners motivated among so many distractions, our project aims to help a user acquire knowledge at his own pace, in a captivating environment and as flexible as possible. To achieve that the solution focuses on the course model, adaptive questions and a reward...
A linear synthesis model-based dictionary learning framework has achieved remarkable performances in image classification in the last decade. Behaved as a generative feature model, it, however, suffers from some intrinsic deficiencies. In this paper, we propose a novel parametric nonlinear analysis cosparse model (NACM) with which a unique feature vector will be much more efficiently extracted. Additionally,...
Increasing user acceptance remains as a critical issue to be resolved in the implementation of any new technology. This research aims to empirically distinguish the factors leading to an e-audit system acceptance in the public sector. The theoretical framework used in this study was adapted from Technology Acceptance Model (TAM), as well as external variables gathered from previous studies. In this...
Cross-domain learning is a very promising technique to improve classification in the target (testing) domain whose data distributions are very different from the source (training) domain. Many cross-domain text classification methods are built on topic modeling approaches. However, topic model methods are unsupervised in nature without fully utilizing the label information of the source domain. In...
As e-training has shown great promise, Microsoft (China) and the Ministry of Education of China (MOE) have launched e-training for in-service teachers in order to improve teachers' instructional skills. 16,264 primary and secondary school teachers participated in this e-training. This study aims to evaluate the effectiveness of the e-training using the Kirkpatrick's four-level model. Discourse data,...
Error pattern detection is very helpful in Computer-Aided Pronunciation Training (CAPT). This paper reports the work of modeling and detecting Error Patterns defined by language teachers based on their linguist knowledge and pedagogical experiences. We develop a model generation framework to create the Error Pattern models from existing phoneme models. We also propose a serial structure for integrating...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.