Big data analytics and electronic resource usage in Academic Libraries

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.