Bridging undergraduates with workplaces: development of statistical reasoning framework / Siti Aishah Sheikh Abdullah … [et al.]

The role of statistical ideas have become integral part of everyday life in the current information laden society. Malaysian universities therefore have an important role towards preparing tertiary students enroll in statistical program for optimum learning opportunity that are most valued by workpl...

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Bibliographic Details
Main Authors: Sheikh Abdullah, Siti Aishah, Yacob, Jusoh, Safii, Nafisah, Mat Lajis, Norhaini
Format: Research Reports
Language:English
Published: 2011
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/98629/1/98629.pdf
https://ir.uitm.edu.my/id/eprint/98629/
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Summary:The role of statistical ideas have become integral part of everyday life in the current information laden society. Malaysian universities therefore have an important role towards preparing tertiary students enroll in statistical program for optimum learning opportunity that are most valued by workplaces. This study aim to contribute at bridging the knowledge gap between statistical application at workplaces and tertiary learning experiences. This study used interpretative multiple case study where data were primarily qualitative. Eight industries were visited in various part of Malaysia to survey their statistical applications. Site visits and face to face interviews with participants from eight industries selected were the main data used. Secondary data were obtained form company leaflet, brochures or official informations. Data were later analysed each cases and between cases to categorise them systematically. By combining Abraham (1999) and Gal & Garfield (1997) statistical category and reasoning framework, type and categories of statistical applications were identified and compared to undergraduates statistical curricullum content. Findings of this study suggested that tertiary learning experiences ought not to focus entirely on formal techniques and procedures from textbooks. Rather quality of statistical learning must be improved by incooporating application of real-life problems, project work, case studies where students can generate their data and solve related problems.