Generating metadata to study and teach about African issues

Author:

Alshameri Faleh,Karim Bangura Abdul

Abstract

Purpose – After almost three centuries of employing western educational approaches, many African societies are still characterized by low western literacy rates, civil conflicts, and underdevelopment. It is obvious that these western educational paradigms, which are not indigenous to Africans, have done relatively little good for Africans. Thus, the purpose of this paper is to argue that the salvation for Africans hinges upon employing indigenous African educational paradigms which can be subsumed under the rubric of ubuntugogy, which the authors define as the art and science of teaching and learning undergirded by humanity toward others. Design/methodology/approach – Therefore, ubuntugogy transcends pedagogy (the art and science of teaching), andragogy (the art and science of helping adults learn), ergonagy (the art and science of helping people learn to work), and heutagogy (the study of self-determined learning). That many great African minds, realizing the debilitating effects of the western educational systems that have been forced upon Africans, have called for different approaches. Findings – One of the biggest challenges for studying and teaching about Africa in Africa at the higher education level, however, is the paucity of published material. Automated generation of metadata is one way of mining massive data sets to compensate for this shortcoming. Originality/value – Thus, the authors address the following major research question in this paper: What is automated generation of metadata and how can the technique be employed from an African-centered perspective? After addressing this question, conclusions and recommendations are offered.

Publisher

Emerald

Subject

Library and Information Sciences,Computer Science Applications,Information Systems

Reference58 articles.

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3. Allert, H. , Richter, C. and Nejdl, W. (2004), “Situated models and metadata for learning management from an organisational and personal perspective”, Journal of Universal Computer Science, Vol. 10 No. 1, pp. 4-13.

4. Alshameri, F.J. (2006), “Automated generation of metadata for mining image and text data”, doctoral dissertation, George Mason University, Fairfax, VA.

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