Conference paper 2024

A Tool for Gaining Insight into Students' Self-Directed Learning Skills

ASEE Annual Conference and Exposition, Conference Proceedings
Conference
Abstract

New engineering educators need to be equipped with instruments that can provide easy and meaningful insight into students' self-directed learning (SDL) status so they can better foster students' success.Students who are self-directed learners can independently initiate and take full responsibility for learning, effectively utilize available resources in the pursuit of their goals, develop awareness of their learning, and demonstrate the appropriate attitude essential for individual and collaborative learning.Despite these benefits, developing SDL skills in engineering students is often overlooked.To address this, educators have a facilitating role to play in the development of engineering students' SDL skills, however, this role can be challenging for them due to the (a) high cost of using SDL instruments, especially in a large classroom and (b) uncertainty about the validity of SDL instruments.Moreover, these challenges may be more pronounced for new engineering educators.This study addresses these challenges by reporting the validity evidence for an SDL assessment instrument called the Self-Rating Scale of Self-Directed Learning (SRSSDL).The SRSSDL instrument has been widely utilized in medical education, but in this study, it was modified for the engineering education context.The utility of this 8-constructs, 46-item scale was demonstrated in engineering education with 111 undergraduate students across all academic levels, and the validity test was conducted in line with the contemporary validity framework.The result of the validity test of the SRSSDL revealed inconsistencies or instability of its constructs in the engineering education context. © American Society for Engineering Education, 2024.

Keywords

Author Keywords

lifelong learning self-directed learning validity confirmatory factor analysis Undergraduate Instrument Psychometric Analysis

Index Keywords

Teaching Engineering education medical education Students validity Cost engineering confirmatory factor analysis Life long learning Self-directed learning Learning skills New Engineering Educators Psychometric analysis Rating scale Self-ratings Undergraduate
Author Affiliations
University of Nebraska–Lincoln, Lincoln, NE, United States
Funding & Acknowledgements
National Science Foundation, NSF
Grant: 2235227
This paper is based upon work supported by the National Science Foundation under Grant Number #2235227.Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
National Science Foundation, NSF
This paper is based upon work supported by the National Science Foundation under Grant Number #2235227.Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
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Document Identifiers
  • EID 2-s2.0-85202019571
  • Language English