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David Post Lutitia Clipper D. Enkhbaatar Anitra Manning Thomas Riley Husam Zaman 《Higher Education》2004,48(2):213-229
This essay review discusses the report of TheTask Force on Higher Education and Society(TFHES), convened in 1998 by the World Bank butindependently financed and staffed incollaboration with UNESCO and severalfoundations. Peril and Promise marks anhistoric turning point in the framework forpostsecondary educational planning. Rate-of-return analysis has been de-emphasized,while promotion of the public interest hasmoved front and center. The report of theTFHES, published in 2000 by the World Bank, hasreceived deserved attention in some parts ofthe world and has even developed an associatedwebsite (http://www.tfhe.net). As we explainbelow, the framework advocated by the TFHES isalready being used in official policy documentsof the World Bank, whose position will surelymultiply the influence of the Task Forcethrough its effect on other development banksas well as on programs of bilateral nationalassistance. And yet, despite its seminalimportance, the TFHES report has yet to befully appreciated by many researchers of highereducation. With this essay review, we hope tobroaden the discussion of the Task Force, and to offer a preliminary assessment of its impactin the 2002 World Bank policy document, and toconnect its arguments to questions that arecentral in the scholarly literature of ourfield. 相似文献
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This paper proposes an online video-based approach to handwritten Arabic alphabet recognition. Various temporal and spatial feature extraction techniques are introduced. The motion information of the hand movement is projected onto two static accumulated difference images according to the motion directionality. The temporal analysis is followed by two-dimensional discrete cosine transform and Zonal coding or Radon transformation and low pass filtering. The resulting feature vectors are time-independent thus can be classified by a simple classification technique such as K Nearest Neighbor (KNN). The solution is further enhanced by introducing the notion of superclasses where similar classes are grouped together for the purpose of multiresolutional classification. Experimental results indicate an impressive 99% recognition rate on user-dependant mode. To validate the proposed technique, we have conducted a series of experiments using Hidden Markov models (HMM), which is the classical way of classifying data with temporal dependencies. Experimental results revealed that the proposed feature extraction scheme combined with simple KNN yields superior results to those obtained by the classical HMM-based scheme. 相似文献
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Al-Adwan Ahmad Samed Yaseen Husam Alsoud Anas Abousweilem Fayrouz Al-Rahmi Waleed Mugahed 《Education and Information Technologies》2022,27(3):3567-3593
Education and Information Technologies - The key objective of this study was to reveal the key factors that impact university students’ continued usage intentions with respect to Learning... 相似文献
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