Investigating Students’ Perception of Mobile-assisted English Learning with Big Data Analysis Techniques

Driven by the rapid development of mobile telecommunications technologies, mobile-assisted language learning (MALL) is gradually gaining momentum in the institutions of higher education in China. With a wealth of digital resources and a myriad of mobile apps readily available, it has rendered information sharing and communication much more efficient. Against this background, we should keep up with the times and proactively implement MALL. Many previous studies have focused on the necessity, process, and evaluation of this teaching paradigm; however, there remains an underrepresentation in the students’ attitudes towards the implementation of mobile-assisted English learning. Therefore, more in-depth studies are warranted to investigate the students’ perception of MALL. In the present study, we resort to the instruments of questionnaire and semi-structured interview to collect data and employ big data analysis techniques to better grasp students’ perception of mobile-assisted English learning. According to the results, most students hold a positive attitude toward mobile-assisted English learning. Specifically, they are most satisfied with the availability of mobile-assisted learning resources, but least satisfied with the engagement features of MALL platforms. In addition, the degree of satisfaction correlates with their English proficiency, with a higher degree of satisfaction among more proficient students. It is suggested that teachers should take into consideration the students’ individual differences and provide tailored mobile learning resources in the implementation of mobile-assisted English teaching.