Self-directedinformation literacy scale: A comprehensive validation study

Kerrie Douglas

doi:10.1002/jee.20355

2020-09-24

PRE

DOI：10.1002/jee.20355

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摘要

En 中文

Background Engineering and technology students need to acquire, evaluate, apply, and document information to solve complex ill-defined problems. However, there are few assessment tools to evaluate how these students approach information. Purpose The authors integrated information literacy standards with self-directed learning theory to create the self-directed information literacy (SIL) scale as an assessment of students' self-directedness using high-quality information skills in engineering projects. The purpose of this research is to examine the measurement properties of SIL to inform the use and interpretation of SIL's scores among diverse learners. Method The authors administered SIL to first-year engineering and technology students (n= 1,603). To test three hypotheses about SIL scores related to validity, reliability, and fairness, we conducted a series of psychometric analyses, including confirmatory factor analysis (CFA) and measurement invariance between groups. Results The results of the CFA were acceptable for the proposed higher-order factor structure of SIL and a separateBeginner Behaviorfactor. Measurement models for male and female scores were found invariant; however, there were measurement differences between groups of students based on their experience with instruction in the English language. Conclusions SIL can be scored to assess engineering and technology students' specific SIL subfactors (Recognize,Seek,Evaluate,Apply,Document, andReflect) or scored as an overall broader measure of self-directedness with information. A separate factor,Beginner Behavior, can be used to moderate ceiling effects. SIL scores can be used for gender comparisons but should be carefully evaluated when the sample includes students who are new to curriculum and instruction in the English language.

Keyword:

assessment

confirmatory factor analysis

engineering design

engineering students

information literacy

measurement invariance

self-directed learning theory