Awareness and Preparedness for Predictive Analytics: A Case Study of Universities in North-Central Nigeria
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1147-1162
Digital Object Identifier:
10.58578/ijhess.v3i3.7291
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Authors:
Dorcas Sola Daramola1, Jumoke Oladele2*, Moruf O. Aileru3 
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Abstract
Big data analytics (BDA) is increasingly central to decision-making in higher education, enabling institutions to process and analyze large datasets to improve operations and outcomes. This study aimed to assess awareness and preparedness for predictive analytics in Nigerian universities. A non-experimental descriptive survey design was employed, targeting academic and top-level non-academic staff drawn purposively from university employees. Data were collected via a self-developed questionnaire—Big Data and Assessment for Learning in Nigerian Higher Institutions Questionnaire (BiDAL; reliability coefficient = 0.96)—administered through Google Forms; research questions were analyzed using percentages and frequencies, and hypotheses were tested with chi-square statistics. Key findings indicate an average level of awareness of predictive analytics across higher education institutions, alongside established preparedness for deploying predictive analytics to improve educational assessment. The study concludes that Nigerian universities demonstrate baseline readiness for predictive analytics despite moderate awareness levels. The contribution/implication is the provision of empirical evidence on institutional awareness and preparedness that can inform subsequent assessment, planning, and implementation efforts within Nigerian higher education.
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