dc.description.abstract | The purpose of the study was to investigate the application of big data analytics as a tool for
analyzing electronic resources usage in the academic library setup in Kenya with reference to
the library of Pan Africa Christian University. The objectives were: to examine the
application of big data analytics as a tool for investigating electronic resources seeking and
usage trends and patterns within academic libraries, to distinguish the appropriate
technologies applicable to data mining and analytics from e-resources usage in academic
libraries, and to ascertain the determinants of user interaction with the various websites and
e-resources platforms accessible to the library users. The study adopted a descriptive
research design. A stratified sample of 79 postgraduate students pursuing various master’s
and PhD programs was used. A structured questionnaire was used to collect data directly
from respondents while their log files were mined from the server. Data analysis was
performed using Statistical Package for Social Sciences software. In terms of usage intensity,
the total URL count was 2,352, the highest user made 283 downloads and the mean URL
count of 49 downloads. Although no respondent utilized more than 4 databases over the one
year period under review, results revealed the most popular databases were e-book central
and ebscohost collectively. Usage intensity was significantly correlated to behavioral control
factors such as knowledge, confidence and ability to use e-resources as well as possession
and control over e-resource devices such as laptops. Respondents trained or orientated on eresource
usage was above average at 69.0 while those not trained was below average at 29.8.
Big data analytics is a necessary and powerful tool for investigating electronic resources
seeking and usage trends and patterns within academic libraries. The overall efficiency of the
academic library’s e-resources should be improved by removing redundant databases from
the platform after a cost-benefit analysis. An integrated data analytics model for
investigating academic library’s e-resources usage is a necessary requirement in the internet
of things set up. How such a model can be developed into a software tool with commercial
value should the subject of further research. | en_US |