Smartphone technology adoption of university students for distance learning in Pakistan: COVID-19 data-driven decision tree learning

Abstract

This study aims to evaluate the effectiveness of smartphone technology in facilitating teaching and learning in Pakistani academic libraries during the COVID-19 lockdowns. Leveraging a questionnaire, we gathered data on students’ experiences, focusing on the challenges encountered, the usability and adoption rates of smartphones, and their impact on accessing academic library services amidst the pandemic. Through the application of a decision tree algorithm to the analyzed data, our objective was to identify key factors or patterns that influence the usability and adoption of smartphone technology in educational contexts. The study’s findings highlight that both challenges related to smartphone use and perceptions of its usability significantly affect its adoption for academic purposes. Notable challenges include information overload, connectivity issues, and difficulties in locating relevant academic materials. Moreover, the perception of smartphones as reliable and effective tools is crucial, especially concerning the ease of viewing and downloading academic resources. Furthermore, the study reveals that students’ intentions to use smartphones for educational purposes are influenced by their self-confidence in using the technology, a desire to be early adopters, and the degree of information overload they experience. These insights underscore the urgent need to address these challenges and bolster students confidence in utilizing smartphone technology for education. Our research contributes to the body of knowledge by offering new perspectives on the adoption of smartphone technology for academic purposes during pandemics, providing valuable recommendations for policymakers and educators to promote the effective use of smartphones in supporting quality education. This aligns with the Sustainable Development Goal (SDG) of ensuring inclusive and equitable quality education for all.