James Prendergast, Eammon Murphy and Malcom Stephenson
Argues that in the coming years the present methods of demonstrating reliability will no longer be feasible and alternative methods must be found. Deals with building‐in…
Abstract
Argues that in the coming years the present methods of demonstrating reliability will no longer be feasible and alternative methods must be found. Deals with building‐in reliability (BIR) and the necessity to change from the standard end‐of‐line‐measurement technique of life test to a more proactive in‐line approach, where reliability can be measured by process parameters and reaction time is immediate, resulting in a continuous flow of reliable product to the end user. This approach will not eliminate the use of end‐of‐line monitoring, but will reduce the amount which needs to be carried out. Suggests that it will only be done to demonstrate that processes are operating to certain maximum failure rates, where the online controls will in fact guarantee that the reliability is much greater than that being demonstrated. Examines the customers’ attitude towards reliability, and points out that sharing of data will be essential if the BIR approach is to be successful. Outllines two examples which demonstrate the effectiveness of a BIR program and explains how, if implemented, it can be used to prevent the manufacture of potentially unreliable product.
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Sarah Amber Evans, Lingzi Hong, Jeonghyun Kim, Erin Rice-Oyler and Irhamni Ali
Data literacy empowers college students, equipping them with essential skills necessary for their personal lives and careers in today’s data-driven world. This study aims to…
Abstract
Purpose
Data literacy empowers college students, equipping them with essential skills necessary for their personal lives and careers in today’s data-driven world. This study aims to explore how community college students evaluate their data literacy and further examine demographic and educational/career advancement disparities in their self-assessed data literacy levels.
Design/methodology/approach
An online survey presenting a data literacy self-assessment scale was distributed and completed by 570 students at four community colleges. Statistical tests were performed between the data literacy factor scores and students’ demographic and educational/career advancement variables.
Findings
Male students rated their data literacy skills higher than females. The 18–19 age group has relatively lower confidence in their data literacy scores than other age groups. High school graduates do not feel proficient in data literacy to the level required for college and the workplace. Full-time employed students demonstrate more confidence in their data literacy than part-time and nonemployed students.
Originality/value
Given the lack of research on community college students’ data literacy, the findings of this study can be valuable in designing and implementing data literacy training programs for different groups of community college students.