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Correspondingly, executive functioning problems predicted more preference for multitasking which did not lead to worse course performance , another variable that has been shown to be influenced by attention and decision-making issues. This is also supported by the studying attention data showing that when students were distracted while studying the most common distractor was communication based, primarily texting and Facebook. These two variables were also shown to be the biggest distractors in the original study by Rosen, Carrier et al.
Junco, and are likely to bring about FOMO. The proposed model was adapted from a study predicting sleep problems among college students. The model tests in these two studies share some similarities and differences. In the sleep study the FOMO variable was by far the strongest predictor highlighting paths to sleep problems through daily smartphone use, nighttime phone location and nighttime phone awakenings while executive functioning problems showed only a direct path to sleep problems plus a concurrent path through nighttime phone awakenings.
The model in the present study showed no independent contribution from executive functioning problems but did show that unique contribution to course performance by FOMO. Interestingly, both independent variables operated on course performance by impacting classroom digital metacognition suggesting that this special type of metacognition may not simply be a function of our cognitive qualities but may also include some affective influences. One unique aspect of this study was the addition of a smartphone application to unobtrusively assess smartphone usage.
The application, which was found by two thirds of the participants to be easy to use, measured the number of minutes that the smartphone remained unlocked and showed that the typical college student spent more than 3. Using valid unlock data from Android users, it was found that the phone was unlocked more than 60 times a day which translated to three to four minutes per unlock.
Data reported by another application assessment Andrews et al. Participants were not instructed to examine daily application-reported data, although such data were easily available. Interestingly, although the course was on the global impact of technology, less than one in three monitored application data more than a few times during the semester even though a large portion of the course dealt with multitasking, attention and distraction. This might be a failure of metacognition or knowing that checking your phone too often or for too long can distract you from the task at hand learning.
Several variables were used to assess how technology was being used both in daily lives, in studying situations, in contemplating multitasking, and in the classroom. Although the total checks were not correlated with application-reported minutes of usage, the valid unlock data was correlated with self-reported checks, which suggests that there are different constructs being assessed by unlocks and minutes using a smartphone.
The fact that the average checks last only a few short minutes, as well as the Andrews et al. Future research might expand on this and use an application that cannot only monitor unlocks and minutes of usage but also accurately assess what is being accessed and how long that access lasts. This is vital if we are to understand what college students are doing with their smartphones in class and while studying and how that might impact learning. This study primarily used self-report measurement instruments although one was self-observational studying attention and one was application-reported.
The latter had some technological issues that required removing a small amount of data but overall the median participant provided 58 days of valid data. Given that not all students in the course participated in the study, it is an open question as to why some chose not to participate and whether those who might be willing to use a continual monitoring application are in any way different. A second limitation is the length of the study. Given that participants measured their application use across more than half the semester, with nearly all participants monitoring it the last third of the semester after the application bug was located and fixed, it is possible that participants changed their behavior based on the application-reported data.
Although self-report data suggest that this was not the case for two-thirds of the participants it is possible that they did make some changes and this should be investigated further. A final limitation comes from the model structure itself. In the study that observed students studying Rosen et al.
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Given the paths we have found that may lead to poor course performance, are there options for managing technology use inside and outside the classroom? These three suggestions directly relate to paths in the model that lead to course performance. Finally, Bowman et al. The current study has demonstrated that there are complex paths to college course performance and highlighted executive functioning and technological anxiety FOMO as being mediated by technology use as well as studying attention and classroom digital metacognition.
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In addition, the study highlighted the special role of FOMO in directly predicting poorer course performance. The independent variables of executive functioning problems and FOMO, plus the mediator variables of studying attention and classroom digital metacognition, should prove important in providing ways to promote solid college course performance and suggestions are offered to apply this model to the classroom.
Abel, J. Andrews, S. Beyond self-report: Tools to compare estimated and real-world smartphone use. PloS One, 10 10 , e Bagozzi, R. On the evaluation of structural equational models. Journal of the Academy of Marketing Science, 16 1 , Bellur, S. Make it our time: In class multitaskers have lower academic performance.
Computers in Human Behavior, 53, Beyens, I. Computers in Human Behavior, 64, Bjornsen, C.
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Scholarship of Teaching and Learning in Psychology, 1, Bowman, L. Multitasking and attention: Implications for college students.