Although earlier studies show the effects of device use on numerous aspects of college students' lives, the impact on personal self-efficacy has not been thoroughly examined. Nonetheless, the prior studies listed below address the many aspects of the research topic.
College Students' Use of Digital Devices
College students have access to and ownership of a variety of technology equipment. Smartphones (or general cell phones), tablets, TVs, laptops, PDAs, or hybrids are the most frequent (Haque et al., 2016; McCoy, 2013; McCoy, 2016; Poll, 2014; Sevillano-Garcia & Vanquez-Cano, 2015). However, most of these studies do not exhibit the influence of demographic characteristics or class level on the ownership and utilization of the items. Nonetheless, Poll (2014) in his Pearson Student Mobile Device Survey 2014 includes both the demographic and student profile in exhibiting device use. According to Poll (2014), African-American students are likely to use hybrids (more than one device) compared to White or Hispanic students (15% versus 8% versus 6% respectively). Similarly, Haque et al. (2016) focus on the demographic factors and college level to delineate ownership and use. For instance, regarding first-year students, females (74.7%) used laptops more than males (25.3%), and these trends are evident for smartphones and tablets, although the third-year students demonstrate modest difference among device users.
Prevalence of Digital Addictions among College Students
The extent and frequency of digital gadgets use are essential in the quantification of the addiction problem. In his article on Digital Distractions in the Classroom, McCoy (2013) highlights that students averagely spend 10.93 times on their mobile devices for non-class activities in a typical school day. This article is interesting because it notes that those activities involve emailing, texting, and social networking, which apparently is addictive with routine use. Although such as a high prevalence is alarming, McCoy (2016) subsequently revealed even higher statistical rates than previously reported. His findings demonstrate that students averagely use their devices 11.43 times for non-class activities, while 20.9% of them utilize class time for non-class-related uses. Apparently, the students are addicted to their digital devices owing to their inability to control the compulsion to use them in class. Crump (2015) attributes this behavior to the failure to distinguish life online and offline, consequently making the students Digital Natives. Similar findings by Ugur and Koc (2015) showed that about 32% of the students surveyed cannot do away with their mobile phones, irrespective of whether they are in class or not. These outcomes mean that phone Phubbing is a reality, and so is their addiction. Elsewhere, a study by Thenu and Sanjana (2013) investigating the prevalence of digital addiction among college students in India revealed that the addiction included television (40%), cell phones (37%), computers (19%), and video games (15%). In as much as this study does not highlight whether the addiction transcends class and non-class occasions, it presents useful methodological information.
Digital Devices and College Students’ Personal Self-Efficacy
Self-efficacy is a performance concept that evaluates individual’s abilities to accomplish personal goals. In this part, it is important to identify whether routine use of digital gadgets has an effect on the student’s self-efficacy. In response to this statement, Sevillano-Garcia and Vazquez-Cano (2015) in their investigation on the effect of digital devices on higher education, found that students believed digital mobile devices allowed them to accomplish tasks. I found the conclusion interesting because the authors argue that the tools aid in the improvement of generic competencies (especially "self-regulated learning"). Aside from this study, other researchers have shown positive performance correlations. Haque et al. (2016), in their exploration of the problem among medical students in Malaysia, found that the respondents admittedly used the digital devices in class, but for learning purposes, and realized an improvement in their academic performance. These findings are echoed by Farley et al. (2015) who contend that their exposure among college students in Australia can facilitate learning only if the right models are applied. However, a study by Duncan, Hoekstra, and Wilcox (2012) which examined the same problem using similar methodological applications as earlier mentioned, reported a substantial negative correlation between the digital device use and students’ final grades. The focus on learning is narrow since self-efficacy encompasses the student’s holistic being. Other aspects of the efficacy scope include social, physical, emotional, and mental performances. The limited nature of the studies is an impetus for this research.
Conclusion
The use of digital devices among college student is frequent and varied. In as much as the literature review has shown that there is a high prevalence of digital addiction among the students and that the devices improve academic performance, the inability of the previous studies to holistically address personal self-efficacy is an impetus to this research. Therefore, this research does not only intend to determine the prevalence of digital addition, but also the effect of the addiction on college students’ personal self-efficacy.
References
Crump, N. (2015). Digital natives: The nature of technology on college student mental health. Educational Specialist. Paper 4.
Duncan, D.K., Hoekstra, A.R., & Wilcox, B.R. (2012). Digital devices, distraction and student performance: Does in-class cell phone use reduce learning? Astronomy Education Review, 11, 1-4. DOI: 10.3847/AER2012011.
Farley, H., Murphy, A., Johnson, C., Carter, B., Lane, M., Midgley, W., Hafeez, B., Dekeyser, S., & Koronios, A. (2015). How do students use their mobile devices to support learning? A case study from an Australian Regional University. Journal of Interactive Media in Education, 2015(1), 1-13. DOI: 10.5334/jime.ar
Haque, A.T.M.E., Sugathan, S., Ali, O., Islam, Z., & Haque, M. (2016). Use of electronic devices by the medical students of UniKL-RCMP, Malaysia, and its influence on academic performances. National Journal of Physiology, Pharmacy, and Pharmacology, 6(1), 1-8. DOI: 10.5455/njppp.2015.5.2709201577
McCoy, B.R. (2013). Digital distractions in the classroom: Student classroom use of digital devices for non-class related purposes. Faculty Publications, College of Journalism & Mass Communications. Paper 71. Accessed on February 2, 2017, from http://digitalcommons.unl.edu/journalismfacpub/71
McCoy, B.R. (2016). Digital distractions in the classroom phase II: Student classroom use of digital devices for non-class related purposes. Faculty Publications, College of Journalism & Mass Communications. Paper 90. Accessed on February 2, 2017, from http://digitalcommons.unl.edu/journalismfacpub/90
Poll, H. (2014). Pearson student mobile device survey 2014. National Report: College Students. Pearson.
Sevillano-Garcia, M., & Vazquez-Cano, E. (2015). The impact of digital mobile devices on higher education. Educational Technology & Society, 18(1), 106-118.
Thenu, C.T., & Keerthi, S. (2013). Prevalence of digital addiction and use of digital devices by students. EXCEL International Journal of Multidisciplinary Management Studies, 3(7), 118-127.
Ugur, N.G., & Koc, T. (2015). Mobile phones as distracting tools in the classroom: College students’ perspectives. Alphanumeric Journal, 3(2), 57-62.
