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Data literacy for teaching and learning in higher education institutions


Purpose
The purpose of this study is to investigate data literacy (DL) for teaching and learning in higher education institution, as data has become a crucial component in the accomplishment of task and decision-making in diverse sector, specifically higher education institutions (HEIs), where students’ records, results and research activities are managed in data form.


Design/methodology/approach
This study adopted the interpretive content/document analysis harvested from database of Web of Science in this study. The use of content/document analysis became essential to establish appropriate empirical evidence that relates to this study. This was to support the argument of detailed systematic examination, which the author establishes in the study. The interpretive content/document analysis was based on systematic literature review on specific objectives.


Findings
Findings indicates that DL is crucial in HEIs. Different types of data collection methods, such as rating scale, reporting, questionnaire, interview, observation, checklist, project, registration, assignment and performance test, were noticed in specific institutional cases. Subsequent conceptual and pedagogical foundations in processing data were obtain through continuous reskilling to acquire adequate knowledge and skills of DL. Social media and institutional repository are now used to digitise data. Different types of skills and abilities were used to search, analyse, adopt and share data in HEIs. This study recommends strategies of the use of different databases for data digitisation and creation of awareness on DL education in HEIs in Africa, specifically Nigeria.


Originality/value
This study is insightful with the understanding of DL in HEIs. The significance in this era of digital literacy become essential, as the need to have the knowledge and application of the use of data is important because of how it serves scholar in decision-making and planning in organisational productivity. The rationale towards this study on DL was on the basis that the world is a global village and without data, no organisation or HEIs could function adequately. Several types of data collected, such as rating scale, reporting, questionnaire, interview, observation, checklist, project, registration, assignment and performance test, have transformed institutional cases, for better and quality management operations. The subsequent conceptual and pedagogical foundations in processing data resulted in continuous reskilling, to sharpen learn and unlearn enterprise.
