Big Data Analytics and Electronic Resource Usage in Academic Libraries: A Case Study of a Private University in Kenya
Date
2019-05-01
Authors
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Publisher
European Scientific Journal
Abstract
The purpose of the study was to apply Big Data analytics as a tool for
evaluating electronic resources usage in the academic library setup in Kenya
with reference to the library of one private university. Log files of postgraduate
students were mined from the server where the offsite access platform
(ezproxy) has been installed. Descriptive statistical techniques such as mean,
standard deviation and percentages were computed. Data was transferred to
the Statistical Package for Social Sciences (SPSS) software was aided in the
analysis. Results revealed that in terms of usage intensity, total URL count
was 2,352, the highest user made 283 downloads and the mean URL count
was 49 downloads. Further findings revealed that no user utilized more than 5
databases over a period of one year. The mean usage intensity score for
respondents who were trained or orientated on e-resource usage was above
average at 69.0 while those who had not received training were below average
at 29.8. It was concluded that big data analytics is a necessary and powerful
tool for investigating electronic resources seeking and usage trends and
patterns within Kenyan university libraries. Through big data analysis and data
mining, usage patterns and trends such as usage intensity that might not have
accurately been revealed through other tools are unearthed. Big data analytics
has revealed user preferences and intensity of utilization of various databases
and helped in detection of redundant databases. From the usage patterns, it
was clear that the level of utilization of the University library’s e-resource
platform was very low. Most of the databases accessible through the platform
were redundant. Further, only two databases namely e-book central and
ebscohost were the most popular among users while the rest were barely being
utilized if at all. For most students, just one or two databases were sufficient
in meeting their research needs. An integrated data analytics model for
investigating university library’s e-resources usage is proposed.
Description
Keywords
Big Data Analytics, Electronic Resource, Usage Intensity, Academic Libraries