Staff Training in Higher Education Institutions: A Scoping Review of Dominant Themes and Methodological Approaches
Abstract
Staff training in institutions of higher learning is widely researched but the field is still fragmented as a wide variety of themes and methods is evident. This study reviewed 33 journal articles indexed in Scopus database, published between 2022 and 2026 with the objective of identifying dominant themes and dominant research methods used to study staff training in higher education. In order to identify the dominant themes and methods, the study analyzed the frequency of occurrence of the theme or method across the reviewed articles, because some studies engaged more than one theme or applied more than one methodological approach. Findings reveal that the most dominant theme between 2022 and 2026 is training for increased competence and individual performance (27 occurrences representing 34.62%). Although this theme dominated research focus during the reviewed period, its dominance fluctuated across the five years with most of the studies (about 52%) engaging this theme coming out in 2024. With regard to methodological orientation, the review finds that, due to the limitations of qualitative and quantitative methods there is a notable transition from paradigmatically positivist quantitative empirical studies that focus mainly on the impact of training programs towards qualitative and mixed-methods studies. Mixed methods are becoming more common because of the crucial importance of linking organizational strategic plans in the environment of new technological advancements to the actual practice of staff training and development. This review recommends more mixed-methods empirical studies that link institutional factors to training impact in order to strengthen research evidence on governance of staff training in higher education including lived experiences of the members of staff. This will take care of new emerging strategic themes like staff welfare, inclusivity and organizational leadership.