Web search engines as teaching and research resources : a perceptions survey of IT and CS staff from selected universities of the KwaZulu-Natal and Eastern Cape provinces of South Africa
Tamba, Paul A. Tamba
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This study examines the perceived effect of the following factors on web searching ability of academic staff in the computing discipline: demographic attributes such as gender, age group, position held by the academic staff, highest qualification, etc; lecturing experience, research experience, English language proficiency, and web searching experience. The research objectives are achieved using a Likert-scale based questionnaire for 61 academic staff from Information Technology and Computer Science departments from four Universities from the Kwazulu-Natal and Eastern Cape provinces of South Africa. Descriptive and inferential statistics were computed for data analysis from the questionnaire after performing data reliability and validity tests using factor analysis and Cronbach‟s coefficients methods on the PASW Statistics 18.0 (SPSS). Descriptive statistics revealed a majority of staff from IT as compared to staff in CS and, a majority of under qualified middle age male staff in junior positions with considerable years of lecturing experience but with little research experience. Inferential statistics show an association between web searching ability and demographic attributes such as academic qualifications, positions, and years of research experience, and also reveal a relationship between web searching ability and lecturing experience, and between web searching ability and English language ability. However, the association between position, English language ability, and searching ability was found to be the strongest of all. The novelty finding by this study is the effect of lecturing experience on web searching ability which has not been claimed by existing research reviewed. Ideas for future research include mentoring of academic staff by more experienced staff, training of novice web searchers, designing and using semantic search systems both in English and in local languages, publishing more web content in local languages, and triangulating various research strategies for the analysis of the usability of web search engines.