There are increasing demands to improve the quality of higher education to facilitate the development of 21st Century professional competencies such as lifelong learning, critical thinking and creativity. Learning analytics is an emerging approach that can provide educators with the necessary information to understand learners then assist them to develop such skills. In this paper, we introduce career dispositions as a 6-dimesional model comprises core skills that engender professional actions, and influence the ability to manage career growth. We then present the process to develop and validate a new scale to evaluate career readiness along these dimensions. The developed scale is a self-report instrument that consists of 22 items and six subscales was validated using exploratory factor analysis (EFA). EFA results demonstrated discreet item loadings into the six factors ranging from 0.3 to 0.8 representing an acceptable level of convergent validity. The developed instrument can be integrated into a career readiness platform and used as analytical tool to identify and analyze the complexity and diversity of student's learning behaviors and skills that may impact their future career readiness and professional performance. © 2014 Springer International Publishing.
CITATION STYLE
Abu Khousa, E., & Atif, Y. (2014). A learning analytics approach to career readiness development in higher education. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8613 LNCS, pp. 133–141). Springer Verlag. https://doi.org/10.1007/978-3-319-09635-3_14
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