Identifying Predictors of Achievement in the Newly Defined Information Literacy: A Neural Network Analysis
Information Literacy is a concept that evolved as a result of efforts to move technology-based instructional and research efforts beyond the concepts previously associated with "computer literacy." While computer literacy was largely a topic devoted to knowledge of hardware and software, information literacy is concerned with students' abilities to construct/collect and analyze information for effective decision making. This study was designed to assess the information literacy achievement levels of college students and to identify variables associated with positive student achievement. Predictors of achievement on a standardized test of information literacy were identified, using a standardized instrument to capture student information literacy scores, and a Neural Network (NN) statistical analysis. Successful predictors included ACT scores, undergraduate major, number of classes, number of tasks completed, high school grade point average, ethnicity and work status. [ABSTRACT FROM AUTHOR] Copyright of College Student Journal is the property of Project Innovation, Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Information Technology and Cybersecurity
Sexton, Randall, Michael Hignite, Thomas M. Margavio, and Geanie W. Margavio. "Identifying Predictors of Achievement in the Newly Defined Information Literacy: A Neural Network Analysis." College Student Journal 43, no. 4 (2009): 1084-1083.
College Student Journal