The influence of smartphones on academic performance

Abstract

Purpose The purpose of this paper is to investigate the factors that influence college students’ smartphone use for academic purposes by identifying the task-technology fit (TTF) of smartphones. A research model is proposed to explain how TTF of smartphones affects college students’ perceived academic performance and smartphone use. Design/methodology/approach Online surveys were administered to college students at a South Korean university that has offered online academic services for more than five years, and 1,923 valid responses were analyzed. The study used partial least squares path modeling to evaluate the measurement model, and the bootstrapping technique to test the significance of the hypotheses. Findings The findings highlight that the TTF of smartphones has a direct influence on students’ perceptions of performance impact and an indirect influence on smartphone use through a precursor of utilization, such as attitude toward smartphone use, social norms and facilitating conditions. Research limitations/implications Despite a reasonably large sample, a single cross-sectional survey has a likelihood of selection bias in the sample. Practical implications This study applies the TTF model to smartphone use among college students and suggests an effective way to motivate them to use mobile technologies for their academic activities. Originality/value The present study develops an empirical model to assess the adoption of smartphones and its effect on college students’ academic performance. Above all, the study identifies a causal relationship among TTF, precursor of utilization, smartphone use and a perceived impact on academic performance based on the development and validation of the TTF constructs of smartphones.

A quasi-experiment on using guided mobile learning interventions in ESL classrooms: Time use and academic performance

“…The current quasi experimental study confirms the previous findings that by providing guidance in the use of mobile devices will encourage students to demonstrate greater interest in learning (Barrs 2011;Chen 2013)) for educational purposes Mills 2014a, 2014b) and subsequently lead to the enhancement of performance (Woodcock et al 2012a(Woodcock et al , 2012bYi et al, 2016;Ng et al 2017).…”

Digital technologies in support of students learning in Higher Education: literature review

“…The use of mobile technologies by students was covered in 11 papers, none of which referred to specific sets of tools. Its use integrated mobile learning settings (Aldhafeeri & Male, 2016;Yi, You, & Bae, 2016) combining both face-to-face and at a distance learning (Jabbour, 2014;Klimova & Poulova, 2016). Students perceive its use has a positive effect in their learning process in class and when using them outside to complement class activities and strengthen academic tasks, in example, to search using the online library (Jabbour, 2014;Klimova & Poulova, 2016;Sánchez-Lugo & Domínguez-Flores, 2013;Viberg & Grönlund, 2013).…”

“…Students perceive its use has a positive effect in their learning process in class and when using them outside to complement class activities and strengthen academic tasks, in example, to search using the online library (Jabbour, 2014;Klimova & Poulova, 2016;Sánchez-Lugo & Domínguez-Flores, 2013;Viberg & Grönlund, 2013). However, students are aware that an effective use may impact their performance depending on their domain of information literacy (Carmen-Ricoy & Da Silva-Couto, 2016), and the technology fit tasks (Yi et al, 2016). These technologies were most used by undergraduate (4) and post graduate (1) students.…”

A Scoping Review of the Application of the Task-Technology Fit Theory

“…Measurements [6,9,15] Model [3,17,[22][23][24][25] Summarize [8] Test [26,27] Assess Phenomena Antecedents [5,13,[28][29][30][31] Effects Impact/Benefit [32,33,42,[34][35][36][37][38][39][40][41] (Intention to) Use [4,12,16,[43][44][45][46][47] The two high level categories were used to determine the trends in the type of studies published over time. The cumulative number of studies published for the two highest-level categories was calculated over time and depicted in Fig.…”