The psychometric properties of the lifelong learning measurement scale (LLMS): the study of validation in higher education setting
Abstract
In the dynamic world of higher education, lifelong learning is important to both individuals and institutions, and measuring it can provide insightful data for both. The purpose of this study is therefore to refine and validate the psychometric qualities of the Lifelong Learning Measurement Scale (LLMS), created to measure academic staff’s engagement with lifelong learning in higher education institutions. Using a cross-sectional study design, the current study validated the scale using rigorous psychometric procedures. The study involved 396 participants, who were selected using a simple random sampling technique. The collected data were analysed using factorial analysis methods. The results provide a theoretically based four-factor structure consisting of 16 items of the LLMS. Strong evidence for the validity of the scale comes from its content validity, construct-related validity, and criterion-related validity. In addition, the scale and its factors demonstrate excellent levels of trustworthiness, according to estimates of composite reliability and internal consistency. The impartial and fair use of the scale is further supported by strong evidence for measurement invariance across gender groups. In conclusion, these results confirm that the LLMS is a legitimate and trustworthy tool that can be used in a variety of research and practices related to lifelong learning in a higher education setting. Furthermore, it is important to note that further research is needed to examine its applicability in different contexts. Subsequent research on its longitudinal stability and sensitivity to different cultural characteristics could also confirm LLMS as a reliable and integrative assessment tool for lifelong learning. © 2024 Informa UK Limited, trading as Taylor & Francis Group.
Author(s)
Assefa, Yalalem, Moges, Bekalu Tadesse, Tilwani, Shouket Ahmad, Ray, Samrat
Year
2024
Countries
Ethiopia
Language
English
Research Method
Quantitative
Article Type
Peer-Reviewed Articles
Keywords
Higher education | Assessment | Excel Import
Full Citation Style
Research Team
Assefa, Yalalem
Moges, Bekalu Tadesse
Tilwani, Shouket Ahmad
Ray, Samrat
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