literature review about social media and academic performance

• Review article
• Open access
• Published: 27 February 2018

Efficient, helpful, or distracting? A literature review of media multitasking in relation to academic performance

• Kaitlyn E. May 1 &
• Anastasia D. Elder 2  

International Journal of Educational Technology in Higher Education volume  15 , Article number:  13 ( 2018 ) Cite this article

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Media multitasking, using two or more medias concurrently, prevails among adolescents and emerging adults. The inherent mental habits of media multitasking—dividing attention, switching attention, and maintaining multiple trains of thought— have significant implications and consequences for students’ academic performance. The goal of this review is to synthesize research on the impacts of media multitasking on academic performance. The research indicates that media multitasking interferes with attention and working memory, negatively affecting GPA, test performance, recall, reading comprehension, note-taking, self-regulation, and efficiency. These effects have been demonstrated during in- class activities (largely lectures) and while students are studying. In addition, students struggle to accurately assess the impact media multitasking will have on their academic performance. Further research should attend to understanding effects of media multitasking in more diverse instructional contexts and for varied academic tasks. Fostering students’ self-regulation around media multitasking is a promising area for future efforts towards improving academic performance of college students.

Introduction

According to the Kaiser Family Foundation (2010), media use is the dominant way adolescents and young adults spend their time, averaging more than 7.5 h of use daily—almost the equivalent in length of a full work day (Roberts, Foehr, & Rideout, 2010 ). Students increase media absorption by using two or more mediums simultaneously via media multitasking, experiencing 10 h and 45 min of media content within their daily 7.5 h. This behavior carries into college, where media use is largely unregulated. Hwang, Kim, and Jeong ( 2014 ) found that 90% of university students multitask when using media, and that more than half of time spent on media involves multitasking. Junco ( 2012 ) found that 69% of students reported text messaging during class, 28% reported using Facebook and email in class, with 21% using the mediums for off-task purposes. An examination of 3372 self-directed computer sessions by 1249 students via time logs revealed that 99% of sessions involved some multitasking (Judd, 2014 ).

College students commonly but erroneously report that multitasking increases productivity (Lin, Cockerham, Chang, & Natividad, 2015 ). Other students multitask on a situational basis according to motive. A student with a specific goal and sufficient motivation, such as studying for an upcoming exam in a difficult class, is less likely to multitask. On the other hand, students with less consequential goals, such as communicating with friends for leisure via Facebook or email, are more likely to multitask (Judd & Kennedy, 2011 ).

The ubiquity of media multitasking among today’s students raises concerns about its consequences and outcomes in relation to student learning and cognition. The aim of this paper is to synthesize existing research on the effects of media multitasking on academic performance, and to highlight implications for students and educators. This paper reviews pertinent theories and analyzes research evidence for the effects of media multitasking on aspects related to cognitive functioning in academic performance, including grade point average (GPA), efficiency, reading comprehension, self-regulation, and test performance. An initial review of the literature was conducted in the fall of 2015 through the PsychInfo database. An additional literature search was conducted in the summer of 2017, and a final search in the fall of 2017 during revisions to ensure comprehensiveness. Search words and phrases included media multitasking, cognition, multitasking, academic performance, and self-regulation. A “snowball” method of using the most recent works to find citations provided in them was used. This review analyzed 38 articles from 2003 to 2017 that primarily investigated academic effects of media multitasking habits of college-aged students. Articles were excluded if they did not involve multitasking but rather generalized media use, if they were published prior to 2000 (with the exception of theoretical articles), or if they were not primarily focused on investigating effects of multitasking on academic performance.

Cognitive functioning while multitasking: Theoretical foundation

Multitasking may impair learning through rapid use of the limited capacity of learners’ information processing channels, especially attention processes, leaving insufficient space for meaningful learning. This is based in information processing theory, the scattered attention hypothesis, and bottleneck theory in which attention is a limited resource (Maslovat et al., 2013 ; Van dur Schuur, Baumgartner, Sumter, & Valkenburg, 2015 ). The term ‘attention’ refers to how individuals actively process specific information in their environment. Attention is selective and enhances processing of the attended stimulus while diminishing processing of unattended stimuli. Collectively, these theories serve to elucidate the manner in which media multitasking decreases academic performance and impacts cognition.

Theories of attention

According to the bottleneck theory of attention, attention can be allocated to only one task at a time. Thus, multitasking is a myth; instead, the mind switches between tasks. Stimuli arrives at a processing ‘bottleneck,’ at which only one item can be processed at a time (Broadbent, 1958 ; Maslovat et al., 2013 ). Because attentional resources are limited, filtering of stimuli must occur. The bottleneck postpones aspects of processing of the secondary task until the primary task is completed.

Van dur Schuur and colleagues (van dur Schuur et al., 2015 ) suggest two opposing consequences of media multitasking with regards to cognitive control, which they referred to as the scattered attention and trained attention hypotheses. According to the scattered attention hypothesis, long-term media multitasking may lead to disrupted cognitive control in which the individual gravitates towards the preferred task rather than maintaining focus despite attentional distractions (van dur Schuur et al., 2015 ). Cognitive control includes several processes, such as focusing attention on goal-relevant information, filtering irrelevant information, switching efficiently between tasks, and retaining information temporarily (van dur Schuur et al., 2015 ; Uncapher, Thieu, & Wagner, 2016 ). Engaging in multiple tasks highly demands attentional capacity, resulting in deficits in cognitive control (Chinchanachokchai, Duff, & Sar, 2015 ; Miller & Cohen, 2001 ; Ophir, Nass, & Wagner, 2009 ; van dur Schuur et al., 2015 ). Thus, multitasking reduces performance by causing interference, distraction, and ultimately errors (Courage, Bakhtiar, Fitzpatrick, Kenny, & Brandeau, 2015 ).

The scattered attention hypothesis maintains the information processing theoretical approach to cognition, in which the brain is a device that employs mental resources to carry out operations and complete tasks. According to this theory, the executive system controls mental resources, allocating them where necessary. Per information processing theory, attention is a limited resource. According to the scattered attention hypothesis, media multitasking hastens the depletion of the attentional resource, consequently diminishing performance on the primary task. If—as is the case with media multitasking—attentional demand exceeds attentional capacity, the cognitive system overloads and performance suffers.

On the other hand, the trained attention hypothesis argues that frequent media multitasking could positively affect cognitive control via eventual training and improvement of control processes. According to this theory, multitasking promotes mental flexibility that enables high-level efficiency and productivity, skills essential for success in modern work and learning environments (Courage et al., 2015 ). The trained attention hypothesis asserts that ability to filter irrelevant information could improve through frequent practice multitasking (Alzahabi & Becker, 2013 ; Ophir et al., 2009 ). Research is more consistent with the scattered attention hypothesis than the trained attention hypothesis (van der Schuur et al., 2015). This is because experimental literature to date on divided attention and dual-task performance demonstrates a limited processing system and consequential deterioration in performance and productivity when multitasking (Courage et al., 2015 ). Nevertheless, examination of distractor filtering in multitaskers of various frequencies presents a difference in performance, pointing to the potential validity of the trained attention hypothesis (Cain & Mitroff, 2011 ). Heavy and low media multitaskers (categorized by media multitasking index score via the Media Use Questionnaire; Ophir et al., 2009 ) completed a singleton distractor task with low working-memory demands. Students who were not frequent media multitaskers relied on top-down information to complete the experimental task, applying top-down distraction filtering to improve performance. Frequent media multitaskers, on the other hand, attended to and processed stimuli to the same degree regardless of whether or not the presented stimuli could be the target. Cain and Mitroff ( 2011 ) argue that the difference in performance on the attentional task affirm attentional differences in heavy media multitaskers; thus, frequent media multitaskers may maintain a wider attentional scope which allows attention to more visual information compared to infrequent multitaskers who maintain a narrower attentional scope.

Working memory theories

Theories of working memory also provide insight to the cognition of media multitasking. Attention biases towards objects that match the current contents of visual working memory (Hollingworth & Beck, 2016 ). Visual working memory is a cognitive system that holds a limited amount of visual information in a temporary storage buffer so that it may be accessed to efficiently achieve goals. Recent research points to working memory as a predictor of multitasking ability, more so than other cognitive, personality, and experience-based variables. For example, Cain, Leonard, Gabrieli, and Finn ( 2016 ) found that frequent media multitasking was associated with poorer performance on behavioral measures of working memory capacity. However, studies like that of Cain et al. ( 2016 ) rely on dual-task measures of working memory. Thus, Redick ( 2016 ) examined whether working memory measures must be dual-tasks to predict multitasking performance, finding that single-task working memory measures also predict multitasking performance. Accordingly, the relationship between working memory and multitasking is independent of the method of task used to assess working memory. This indicates that working memory is perhaps fundamental to individual multitasking ability.

This paper relies on the aforementioned models to examine the cognitive impact of media multitasking within the frame of a theoretical foundation, as well as to highlight existing evidence related to academic performance that confirm or oppose the discussed theories.

Multitasking effects related to academic performance

Empirical studies firmly establish a significant drop in academic performance due to media multitasking. According to the Kaiser Family Foundation, heavy media users (exposed to more than 16 h of media content per day, often via media multitasking) report receiving C’s or lower in school, getting in trouble often, frequently feeling sad or unhappy, and frequent boredom (Roberts et al., 2010 ). Survey data found frequent in-class multitaskers have lower current college GPAs (Al-Menayes, 2015 ; Bellur, Nowak, & Hull, 2015 ; Clayson & Haley, 2012 ; Junco, 2012 ; Lau, 2017 ). A longitudinal study examining women’s media use during their first year of college and associations with academic outcomes found that women reported nearly 12 h of media use per day (Walsh, Fielder, Carey, & Carey, 2013 ). Such amounts of media use imply multitasking; further, media use was negatively related to academic outcomes after controlling for demographics and prior academics, and there were significant, indirect effects of social networking on GPA.

In-class multitasking

In-class, mobile phone multitasking during direct instruction is heavily researched, as it is the technology of choice for many university students and the most prevalent. Rosen, Lim, Carrier, and Cheever ( 2011 ) examined the impact of in-class mobile phone usage during course lecture on test performance. Students responded to messages sent by researchers at even intervals throughout a 30-min videotaped lecture (Rosen et al., 2011 ). Students in the high text messaging group performed worse by one letter grade on an information post-test than the low text messaging group (10.6% lower score). However, the moderate text messaging group showed no score difference compared to the other two groups. Participants who received and sent more words in their texts performed worse on the test; however, this was moderated by elapsed time between receiving and sending a text, with longer delays resulting in better performance. Student metacognitive self-reports reflected test results. Nearly three-fourths of participants felt that receiving and sending text messages during class was disruptive to learning. Despite this, 40% felt it was acceptable to text in class.

Similar studies comparing test performance found the non-texting group outperformed regardless of gender and G.P.A. (Ellis, Daniels, & Jauregui, 2010 ; Froese et al., 2010 ). Ellis et al. ( 2010 ) examined the effect of texting multitasking on the grade performance of business students. Participants listened to a class lecture in a texting or no-texting condition. Scores on a post-lecture assessment indicated that exam scores of texting students were significantly lower. In a similar lecture format, Froese et al. ( 2010 ) demonstrated that students lost roughly 30% of accuracy on a quiz when texting.

A related study found similar results (Kuznekoff & Titsworth, 2013 ). Participants in three groups (non-multitasking, low-distraction, and high-distraction) watched a video lecture while taking notes and completed two post-lecture assessments. Students in the non-multitasking control group wrote down 62% more information, took notes with more details, were able to recall more detailed information, and scored a full letter grade and a half higher than students in the low-distraction and high-distraction groups. Further analysis found that message content influenced effect on class performance. In addition to participants who did not text, participants who sent texts related to the lecture earned a 10–17% higher letter grade, scored 70% higher on information recall, and scored 50% higher on note-taking than students sending texts unrelated to lecture content (Kuznekoff, Munz, & Titsworth, 2015 ). These results point to the purpose of usage, rather than multitasking itself, as the culprit for the negative effects of media multitasking on classroom performance. Thus, distinguishing on-task from off-task multitasking redefines the pragmatics of the in-class technology debate.

McDonald ( 2013 ) assessed the effect of three different in-class texting behaviors on course grade: (1) mild texting policy; "cell phones are to be turned off and not used during class. This is an issue of respect for others and your professor"; (2) strict cell phone policy; "students will lose 3% of their final grade each time they are caught texting"; (3) no presented texting policy; "students free to have cell phones on and text as desired" (McDonald, 2013, pg. 36). McDonald ( 2013 ) found a negative correlation between in-class texting and final grade score, regardless of texting condition. This negative correlation remained after controlling for GPA, ACT, and attendance. However, the higher the levels of in-class texting behavior by a student, the lower their final grade. In-class texting behavior contributed to 22% of the predictor value in final grade. This points to the potential of classroom policy to diminish, but not eliminate, the negative effects of in-class media multitasking.

A similar experiment examining in-class media multitasking with classroom performance expanded the experimental variables to reflect individualized preferences for both media use and notetaking (Wood et al., 2012 ). The study compared multitasking activities of various mediums to three methods of notetaking during a direct instruction lecture. Technological mediums assessed included texting, emailing, Instant Messaging (IM), and Facebook. All media use was for off-task purposes. Note-taking conditions were paper-and-pencil, word-processing, and a natural use of technology condition in which participants were allowed to use any technology they wished. The natural use of technology condition served to determine whether students choose to multitask during lectures, what technologies students tend to use, and how the choice to multitask affected learning. Across all sessions, only seven participants did not use technology at all. Almost half of participants used technology for every class when permitted. The experiment was conducted over three consecutive lectures. Results indicated that participants who did not use any technologies outperformed students who did multitask—regardless of medium— on a 15-item multiple-choice test. Participants in the Facebook and Instant Messaging conditions performed more poorly than those in the paper-and-pencil control. Wood et al. ( 2012 ) surmised that Facebook and IM were more likely to serve as distractors that yield negative impact on learning. Repeated practice with the various technologies did not improve performance over time in any condition.

Downs, Tran, McMenemy, and Abegaze ( 2015 ) manipulated the multitasking environment rather than the note-taking method, finding that participants performed worst on a post-lecture exam when distracted with social media. Two-hundred and four university students were randomly assigned to one of six classroom conditions: (1) Facebook distracted; (2) paper note-taking; (3) no media use control group; (4) mixed distraction; (5) laptop note-taking; and (6) distracted combination. Participants in the Facebook condition used laptops to join a Facebook chat group created for the study through which they received questions to respond to at two-minute intervals. Participants in the note-taking condition received a sheet of notebook paper and instructions to take notes as they normally would during a lecture. Participants in the no media use control group were instructed to only watch the documentary. The mixed distraction group approximately half of the participants (every other seat) were asked to join the aforementioned Facebook chat group, while the other half watched the documentary without an additional distraction. Participants in the laptop note-taking group used a word processing program to take notes. Participants in the distracted combination condition followed the Facebook protocol for condition one while simultaneously taking notes on their laptop during the video. In all conditions, participants viewed a documentary video for 25 min and completed a subsequent, 15-question, multiple-choice exam assessing lecture content. Participants in distracted conditions (1, 4, & 6) performed worse on the post-test than participants in the non-distracted control, paper-and-pencil, and laptop note-taking groups.

Brooks ( 2015 ) further examined mobile phone multitasking in a natural classroom setting. Participants completed a pre-task survey before watching a 15-min video lecture. Participants received no instructions or study regarding social media or mobile phone usage prior to observing a 15-min video lecture. Following the video, participants completed a quiz over video content and a survey regarding social media use, attentional control, multitasking computer self-efficacy, technostress, and happiness. Participants were instructed to complete the tasks on their own time so that they would have access to their personal machines. Like prior studies, this study found that social media usage on mobile phones negatively affected performance. Attentional control and multitasking computer self-efficacy did not yield significant effect on this relationship. Thus, students are not as skilled at multitasking as they perceive themselves to be.

Conard and Marsh ( 2014 ) examined the effect of interruptions via Instant Messaging and situational interest on learning during multitasking. Participants viewed a video presentation in a simulated environment meant to emulate a standard working environment such as a business meeting, a training presentation, or a classroom lecture. During the 16-min video, participants responded to eight Instant Messages sent at specific times by research assistants. Following the video, participants completed a 22-item multiple choice test assessing lecture comprehension and responded to measure of situational interest. Multitasking interruptions reduced learning; furthermore, interest level was as strong a predictor of learning as being interrupted. However, interest did not moderate the effect of interruptions. This indicates a need for further research examining individual difference factors, such as interest levels, when assessing the effects of multitasking on learning.

Like mobile phone use, laptop use is commonplace in the university setting, yet presents unique issues concerning multitasking. Laptops provide a convenient means to connect with the lecture while simultaneously providing a major source of distraction. Self-report data by Fried ( 2008 ) showed that students using laptops in class spent considerable time multitasking. On average, students generate more than 65 new active windows on laptops per lecture, with 62% of these windows being classified as distractive and irrelevant to lecture content (Kraushaar & Novak, 2010 ). Laptop use negatively related to multiple learning outcomes including course grade, focus on lectures, reported clarity of lectures, exam performance, and comprehension (Fried, 2008 ; Kraushaar & Novak, 2010 ; Wood et al., 2012 ; Zhang, 2015 ). In a study by Hembrooke and Gay ( 2003 ), laptop use during lecture resulted in significantly lower recall and recognition test scores. Students in two conditions (laptop multitasking or no multitasking condition) listened to a lecture and completed a comprehension exam. Exam results indicated that multitasking students suffered memory decrements.

Students habitually using laptops in class report low satisfaction with their education, are more likely to multitask in class, and are more distracted (Wurst, Smarkola, & Gaffney, 2008 ). According to information processing theory, humans process stimuli, rather than merely responding, employing attention mechanisms such as working memory. Thus, laptops provide additional stimuli for students to process, distracting them from the academic task. This accounts for the decrements in performance seen as a result of in-class laptop multitasking. Because most technological mediums serve as a gateway to both productive and unproductive tasks, students are likely to engage in both over the course of a class period and struggle to resist temptation. These distractions prevent processing and learning of material.

Research involving undergraduate students indicate that laptop multitasking can hinder class learning for both users and nearby peers (Fried, 2008 ; Sana, Weston, & Cepeda, 2013 ). Fried ( 2008 ) administered surveys to a university course, assessing various aspects of class such as class attendance, classroom experiences, and laptop use, finding that students frequently cited personal and external laptop use as major sources of classroom distractions and hindrances of learning. Experimental evidence affirms this: Sana et al. ( 2013 ) simulated a classroom with 40 undergraduate students in which students viewed a 45-min PowerPoint lecture in a multitasking or non-multitasking condition and completed a multiple-choice comprehension test. Participants who multitasked on a laptop during lecture scored lower on the test than non-multitaskers. Moreover, participants in direct view of a multitasking peer scored 17% lower than those who were not. Distractions due to movement of images and laptop screen lighting, as well as multitasking activities, may cause involuntary shifts of attention among students in close proximity to laptop users. Thus, proximity to a multitasker—and not solely active multitasking—can be detrimental to academic performance. Understanding the effects of multitasking on others is an area of research deserving replication and further investigation.

Overall, this body of research regarding in-class multitasking affirms ideas purported by the bottleneck theory of attention as well as the scattered attention hypothesis, and presents evidence against the trained attention hypothesis. The literature indicates that attempting to attend to class material (mostly lectures) and engage in technologies simultaneously can have a detrimental impact on learning, likely due to inattention to course information. These negative effects on academics were demonstrated with varied outcomes-- test performance, grades, comprehension, recall, and note-taking. Yet, many of these studies involved measuring the impact of media multitasking during a short time span, so longer follow-up studies are needed to more fully investigate the claims of the trained attention hypothesis which states that repeated practice of media multitasking will improve performance over time.

Multitasking outside of class

Laptops and mobile phones are particularly distracting while studying or doing coursework outside of class, as students can easily access alternate media sources such as email, Facebook, or Instant Messaging (IM) on them. Much of the research to date primarily assessed the impact of media multitasking on in-class activities, such as test performance. Few studies have examined the role of media multitasking on assignments outside of class, such as homework or studying. A survey study of 1839 students revealed that using Facebook while doing schoolwork was negatively predictive of overall semester GPA. (Junco, 2012 ). Junco and Cotten ( 2012 ) surmised that Facebook or texting while completing schoolwork may tax students’ capacity for cognitive processing, inhibiting deeper learning. According to one experimental study, the more time participants reported spending on IM in class, the lower self-reported GPA. (Fox, Rosen, & Crawford, 2009 ).

Outside of the classroom, mobile phone use is negatively associated with academic performance. Texting while studying was significantly and negatively associated with college GPA after controlling for demographic variables, self-efficacy for self-regulated learning, self-efficacy for academic achievement, and high school GPA (Junco, 2012 ; Junco & Cotten, 2012 ; Lepp, Barkley, & Karpinski, 2015 ). Amount of texting and texting while multitasking was negatively predictive of overall GPA for U.S. students (Karpinski, Kirschner, Ozer, Mellott, & Ochwo, 2013 ). Students who did not text while studying had a higher GPA than those who did text. Furthermore, GPA was higher for those who spent fewer minutes texting per day compared to increased levels of texting. Similar effects are elicited by other digital media technologies. Students’ media multitasking with various digital media technologies, including social networking platforms while studying suffer negative consequences. Students who used fewer forms of media multitasking (0–2 mediums) outperformed students who used more forms (7 or more mediums) on exam scores (Patterson, 2017 ). Yet, the amount of studying time between the two groups of students did not differ.

An experimental paradigm comparing the effect of laptop multitasking on reading comprehension and task performance cited differential effects (Subrahmanyam et al., 2013 ). The study comprised of two paradigms. In the first, participants read two passages of low and high difficulty on paper, a laptop, or on a tablet, in a multitasking or non-multitasking condition. Similar to the studies discussed above, neither medium nor multitasking condition affected reading comprehension; however, multitaskers demonstrated markedly reduced efficiency. In the second paradigm, participants synthesized multiple materials and wrote a one-page report. Sources were provided either on paper, on a computer screen without Internet or printer access, or on a computer screen with Internet and printer access. Source materials produced no differences in report quality or efficiency, despite students reporting a preference for paper sources. However, report quality was significantly improved when participants had sources on a computer without Internet compared to a computer with Internet access. Furthermore, active use of paper for note-taking greatly reduced the negative impact of Internet access.

Hence, it appears that these effects are not limited to learning while just attending class, but that media multitasking has harmful effects as students engage in learning activities outside the classroom, too. Multitasking outside of class— while completing homework or studying— is similar to multitasking during class; it requires task-switching, may overload students’ capacity for cognitive processing and hence preclude deeper learning. As in bottleneck theory, incoming information arrives at a processing bottleneck, at which only one item can be processed at a time. The consequence of this is diminished performance. According to the scattered attention hypothesis (van dur Schuur et al., 2015 ) media multitasking negatively affects cognitive control through distraction from the primary activity. Engaging in multiple tasks highly demands attentional capacity, resulting in deficits in performance. Multitasking reduces performance by causing interference, distraction, and errors. Thus, effects of multitasking outside of class parallel those of multitasking within the classroom.

Perceptions of multitasking and self-regulation

One important aspect for understanding multitasking while engaged in learning activities for class is the issue of students’ beliefs and perceptions surrounding multitasking. In Downs et al. ( 2015 ) study, participants completed a pre-test examining their perceptions of their multitasking abilities. The same questionnaire was administered following a multiple-choice exam. Participants in various conditions (e.g. distracted by social media and/or taking notes) reported significantly less confidence in their ability to effectively multitask. This is particularly interesting considering students never received their individual scores on the multiple-choice assessment. Students felt less confident in their ability to learn, pointing to the fact that students self assess themselves as less capable when engaged in multitasking.

Multitasking students typically predict lower scores on academic performance than on-task students. Experimental data of 34 students failed to indicate difference in quiz scores of those who used devices while listening to a lecture and those who did not; however, when asked to predict scores prior to taking a comprehension quiz, students who used their cell phones during lecture anticipated lower scores than students who did not (Elder, 2013 ). A more recent prediction study found similar results. Sixty college students predicted results of media multitasking while completing a homework assignment in various media availability conditions (Calderwood, Green, Joy-Gaba, & Moloney, 2016 ). Participants received instructions to bring 3 h of homework of different subjects and any media items of their choice to the laboratory. Upon arrival, participants were instructed to complete their homework as they typically would. At the beginning of each hour, participants completed a 34-item measure of state affect, fatigue, self-efficacy, and positive motivation. Students predicted media use to result in lower negative affect and less self-control. While the direction of their predictions was accurate, students underestimated the effect of media multitasking on their performance.

Although students recognize potential negative impact of multitasking with media, they continue to do it. Survey responses assessing frequency and duration of media use in an introductory psychology class indicate that students discount the effect of media on learning over time (Ravizza, Hambrick, & Fenn, 2014 ). Five-hundred and eight students completed a nine-question survey assessing the frequency and duration of texting, using Facebook, checking email, and non-class related Internet use during lectures. For each media, participants reported how frequently they used the technology and estimated the average amount of time spent on these activities during lecture. The final question examined the degree to which students perceived internet and phone use to affect their learning. Students demonstrate poor awareness of how media multitasking affects their learning. Kraushaar and Novak ( 2010 ) reported students underreported email multitasking by 7% and IM by 40%. In Elder’s ( 2013 ) study, questionnaire data of 88 college students’ beliefs indicated an acceptance of in-class use and neutral beliefs about whether multitasking affects study time. Similarly, Clayson and Haley ( 2012 ) reported that 68% of students believed they could attend to a lecture and text at the same time, yet students who texted received lower grades. This suggests an incapability of students to make accurate and discerning decisions about multitasking while completing academic tasks.

Another study combining survey with experimental methods found that participants predicted losing close to 30% accuracy on a quiz when using cell phones and indeed lost close to 30% when texting (Froese et al., 2010 ). Non-multitasking students feel more confident in their ability to predict scores accurately. In an experiment asking lecture-only and lecture-texting groups to predict their performance on a quiz assessing lecture content retention, the lecture-only group had higher scores on the quiz and felt more confident in their predictions (Gingerich & Lineweaver, 2014 ). This, coupled with data regarding multitaskers’ metacognitive beliefs, indicates that students are poor at recognizing and regulating inhibitors of performance.

Self-regulation requires conscious personal management and guiding of one’s thoughts, behaviors, and feelings to achieve goals. Although there is some evidence that students adjust reading time, adolescents do not effectively self-regulate their media multitasking. Despite students readily acknowledging multitasking divides attention, media multitasking persists. Furthermore, students do not accurately predict its impact on task performance. A possible explanation is that multitasking while studying hinders the implementation of an appropriate learning strategy. Thus, media multitasking inhibits metacognition and self-regulation, preventing implementation of the appropriate learning strategy and reducing performance (Lee, Cho, Kim, & Noh, 2015 ).

Wei, Wang, and Klausner ( 2012 ) examined the impact of texting on students’ cognitive learning with surveys of 190 college students. They found that college students’ self-regulation negatively related to text messaging use during class; text messaging use during class negatively related to student sustained attention to classroom learning. Structural equation modeling analysis found texting during class to partially mediate effect of students’ self-regulation on their sustained attention to classroom learning. Moreover, students’ sustained attention fully mediates effect of in-class texting on experience-oriented learning. Thus, college students with high levels of self-regulation are less likely to text during class and more likely to maintain attention to classroom learning.

Multitasking reduces efficiency when performing academic tasks. Survey data of 361 college students who reported texting while doing homework, also reported spending more time studying outside of class, as multitasking contributes to inefficient study habits (Bellur et al., 2015 ). Participants who IMed while completing a reading task took significantly longer to complete the task (12.56 min compared to 8.23 min by non-multitasking participants; Fox et al., 2009 ). In a similar study of the same experimental design, participants who IM while reading took 22%–59% longer to complete the task than those who IMed before reading or did not IM at all, even after deducting the time spent on Instant Messaging (Bowman, Levine, Waite, & Gendron, 2010 ).

Although multitasking reduces efficiency, comprehension is not always affected. Participants may re-read certain parts of the article after interruption; although this increases reading time, it can make up for deficits in comprehension (Bowman et al., 2010 ; Fox et al., 2009 ). In both of the aforementioned studies, although statistically significant differences were found in student time to complete the reading passage, comprehension was not harmed. Thus, students who are particularly metacognitive can overcome the effects of media multitasking on comprehension, especially when students control the pace of presented information. Comparisons of various multitasking conditions indicate this (Pashler, Kang, & Ip, 2013 ). Participants read or listened to several short historical narratives while engaging in five to eight brief conversations simulating Instant Messaging in various conditions: (1) reading narratives; (2) audio narratives paused during message conversing; and (3) audio narratives not paused during message conversing. When reading narratives and attending to messages, multitasking marginally increased reading time but comprehension was not significantly affected. This repeated when narratives were presented in audio format and paused during messaging. However, when audio narratives did not pause, interruptions reduced comprehension performance. This may be suggestive of the trained attention hypothesis, which holds that frequent media multitasking could have a positive effect on cognitive control via eventual training and improvement of control processes.

The role of media multitasking on comprehension is dependent on self-regulation and self-awareness. Students who are particularly metacognitive or self-aware recognized deficits in comprehension upon returning to the primary task and subsequently re-read portions of the article after interruption. Although this increases reading time, it can make up for deficits in comprehension. While this is acceptable for academic tasks which are not completed under time-constraints such as homework assignments, multitasking during time-contingent academic tasks such as an essay or in-class lecture is problematic; the student cannot make up for deficits in comprehension via repeated exposure to the text without costs to performance. Thus, the type of work matters when examining the impact of media multitasking on performance. Some research suggests that regardless of context, whether learning in class, studying outside class, or engaging in homework alone or in collaboration, most students tend to multitask with smartphones (Jacobsen & Forste, 2011 ; Junco, 2012 ). Although media, such as smartphones, provide access to educational resources and facilitate collaboration, studies indicate that technology-related distractions are negatively related to homework effort and environment (Chan, Walker, & Gleaves, 2015 ; Hawi & Samaha, 2016 ; Xu, 2015 ).

Media multitasking is detrimental to academic capacities of college learners. Cognitive effects of media multitasking were found to be negative across a range of outcomes (see Table  1 ). Inside of the classroom, media multitasking is negatively associated with GPA, test performance, information recall, comprehension, and note-taking, especially when students multitask to engage in off task activities. These effects are not mediated by achievement level and negatively impact non-multitasking peers. Outside of the classroom, media multitasking is also tied to poorer classroom performance along with students predicting less confidence and lower scores. Furthermore, media multitasking is negatively associated with efficiency and reading comprehension. These effects are mediated by self-regulation and metacognition; students may account for deficits in comprehension by rereading, thus improving comprehension but diminishing efficiency. This is indicative of information processing theory, because attention is a limited resource, media multitasking hastens depletion of attentional resources, thus diminishing performance on the primary task.

One primary differential distinguishing the influence of media multitasking on academic performance out of class versus in-class is that the lack of time contingencies or instructional proctorship heighten the mediating influence of metacognition and self-awareness. As seen in research examining the effect of media multitasking on reading comprehension, students can account for deficits in performance by re-reading or re-doing a task when working outside of the classroom. This cannot occur in the classroom due to time constraints, especially when the instructor controls the pace of instruction and under largely lecture format contexts. This suggests the need for further research examining the role of various educational contexts to understand more fully the effects of media multitasking on academic performance. Most existing research was accomplished in college classes utilizing a traditional, lecture format. These teacher- directed instructional contexts do not allow the student to control the rate nor amount of incoming information. Whether nontraditional methods of instruction such as flipped classrooms, collaborative learning, or participatory learning exhibit different relationships with media multitasking is largely unexplored to date. These nontraditional formats are increasingly popular and may be more conducive to successful media multitasking in academic arenas since students can direct and regulate their attention as they control the amount and pace of incoming information. Conversely, media multitasking while engaging in these alternate instructional structures may reveal a lack of depth of student thinking and understanding since they require them to synthesize information from discussions. Thus, further research in this area is needed to fully investigate effects of media multitasking in a variety of instructional formats.

In addition to types of instructional contexts, further research examining the types of academic tasks and assessments, including assignment formats, levels of difficulty, and interest level, is warranted, especially when students are studying on their own. These may be factors that account for variations in the relationship between students’ sustained attention, multitasking behaviors, and measured academic performance. Students pay attention, potentially engage in multitasking, and study differently depending on nature of tasks demanded of them and their motivations and perceived ability in completing them. The frequency, duration, and conditions under which students choose to multitask or not are important issues to ponder. Hence, to gain a better understanding of the effects of multitasking for college students, additional investigations of types of tasks and motivation are required.

Research on the relationship of metacognition and the effects of multitasking on reading comprehension illustrate the intersection of self-regulation and working memory. Visual working memory theories examine the role of self-regulation in selecting and maintaining task-relevant visual targets. Thus, self-awareness is critical in mitigating the effects of media multitasking. Yet, students do not effectively self-regulate their media multitasking and are poor at recognizing and regulating inhibitors of performance. While students recognize that multitasking divides their attention, media multitasking reduces both accuracy and confidence in predicting impact on task performance. Self-regulation is an important skill in addressing multitasking and is an area of interest for future research, as students are not successful in managing their multitasking to avoid inhibiting performance or efficiency. Research on methods to foster student recognition of the deleterious effects of media multitasking, as well as development of self-regulation skills, can offer insight to classroom technology policy and instruction.

Implications

Technology does offer benefits to the educational experience. In balancing these benefits with the negative effects of media multitasking, the issue becomes one of appropriate implementation of technology in the classroom. Fostering development of self-monitoring skills in students thus becomes critical. Research on laptop use in the classroom reveals effects dependent upon classroom environment (i.e., structured vs. unstructured use of technology) and the way in which the laptop was used (i.e., on-task vs. off-task multitasking). Structured tasks with specific and clearly indicated requirements for technology usage are less likely to catalyze off-task multitasking than unstructured tasks. Complex tasks emphasizing project-based, constructivist learning encouraged on-task laptop use, as opposed to recitation or drill-and-practice tasks that led to off-task usage (Mouza, 2008 ). As demonstrated by Judd and Kennedy ( 2011 ), a student with a specific goal and sufficient motivation, such as studying for an upcoming exam in a difficult class, is less likely to multitask. On the other hand, students with less consequential goals, such as communicating with friends for leisure via Facebook or email, are more likely to multitask. Thus, complex activities will promote task-relevant technology usage,employing the many benefits technology offers, while diminishing opportunities to multitask. Class observation indicated that laptops may enhance student-centered, hands-on, and exploratory learning, as well as increase student-to-student and student-to-instructor interactions (Barak, Lipson, & Lerman, 2006 ). Clearly stated mobile phone policy on a syllabus can decrease phone use in the classroom (Chen & Yan, 2016 ). Suggested methods include employing classroom curriculum in which laptops are incorporated strategically with a pedagogy to maximize potential benefits and minimize distractions. With careful implementation, these methods potentially harness the positive effects of educational technology while diminishing the negative effects of media multitasking.

For the most part, students do not recognize the extent of the negative consequences of media multitasking on academic performance. College students commonly report that multitasking increases productivity (Lin et al., 2015 ). Because research indicates that student media multitasking extends to outside of the classroom, and because studies establish the negative impact of multitasking on academic performance, students should be advised to carefully monitor their technology use when working on school assignments. Requiring schoolwork to be complete before using technology, keeping technology in communal areas, or providing other measures to discourage off-task multitasking help facilitate learning and efficient studying. Likewise, choosing to study in communal areas, such as the library, may facilitate on-task engagement. Students are not particularly metacognitive in relation to their abilities to multitask, nor to the effects of media multitasking. There is a tendency of students to overestimate their multitasking ability. This indicates the need for educators and parents to encourage students’ self-regulation of laptop and cell phone multitasking behaviors, and the importance of fostering student self-efficacy and learning motivations.

Though educators promote productive use of classroom technology with policies limiting off-task media multitasking, the collegiate education system relies on the increasing independence and self-regulation on the part of students. Educating students about the impacts of media multitasking on academic performance will potentially foster self-awareness, and perhaps self-regulation of multitasking habits. Self-regulation of multitasking habits is a necessary skillset for the modern student, and upon graduation, the modern professional. Developing self-regulation skills and positive technology habits while in school prepares the student for balancing the modern workplace. This may redefine the problematic variables of the educational technology debate, shifting the criticism from technology implementation to the manner in which usage is monitored.

Abbreviations

Grade Point Average

Instant Message

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May, K.E., Elder, A.D. Efficient, helpful, or distracting? A literature review of media multitasking in relation to academic performance. Int J Educ Technol High Educ 15 , 13 (2018). https://doi.org/10.1186/s41239-018-0096-z

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Impact of social media on the academic performance of undergraduate medical students

Ajay m. bhandarkar.

a Associate Professor (ENT), Kasturba Medical College, Manipal Academy of Higher Education, Manipal, India

Arvind Kumar Pandey

b Associate Professor (Anatomy), Kasturba Medical College, Manipal Academy of Higher Education, Manipal, India

Ramya Nayak

c Assistant Professor (Pediatrics), Melaka Manipal Medical College, Manipal Academy of Higher Education, Manipal, India

Kailesh Pujary

d Professor (ENT), Kasturba Medical College, Manipal Academy of Higher Education, Manipal, India

Ashwini Kumar

e Associate Professor (Forensic Medicine), Kasturba Medical College, Manipal Academy of Higher Education, Manipal, India

Associated Data

Social media has become an integral part in the life of every individual in the 21st century. Social media addiction in the younger age group is a major problem. The objective of this study was to find a correlation between academic performance and social media use.

This was a cross-sectional questionnaire-based study conducted in a medical school over a period of 3 months (Nov 2018–Jan 2019), where 400 medical undergraduates who use social media participated in the study. Data collected from the questionnaire included the academic performance in terms of university examination marks, the duration of social media use per day and the social media addiction score. Data correlation was done using the Pearson’s correlation factor.

41.5% of students used social media for upto 3 h per day. Whatsapp (98.25%) and Youtube (91.75%) were the most commonly used social media applications. 73.5% used social media to read health-related news, 71.5% used it to complete assignments and more than 50% used it for seminar preparation, test preparation and research-related purposes. Academic performance of female students was better than male students. There was a significantly higher use of social media among academically low-performing medical students compared with high-performing medical students. There was a weak negative correlation between academic performance and social media usage and a strong positive correlation between social media usage and the social media addiction score.

Conclusions

Social media has a negative impact on the academic performance of 21st-century undergraduate medical students.

Introduction

Social media is a network of websites and applications which enables individuals to converse with each other. 1 It also allows users to generate, use, exchange and discuss the content available in the worldwide web. 2

In 2016, it was reported that there are 2.31 billion social media users reported with a global diffusion of 31%. 2 Studies have reported Facebook, Whatsapp and Twitter as the most commonly used social media among students. 1 , 2 , 3 , 4 Usage of social media in the age group of 18–29 years jumped from 12% in 2005 to 90% in 2015. 4 Facebook statistics reveal a login of more than half its users daily. 5 Twitter usage started with less than 5000 tweets/day in 2007 to an average of 500 million tweets/day in 2013 over just six years. 5 Alkhalaf et al 1 reported daily average use of 320 min of Whatsapp by a single individual. There are currently more than 500 million Whatsapp users worldwide and 700 million photos and 100 million videos shared and exchanged every day on this application. 6 The advent of smartphones has increased the usage of social media and the internet exponentially. 5

Excessive usage of social media has not yet been termed a mental disorder, although the term social media addiction is in vogue. 1 Social media on a general platform has been shown to assemble information into learning and research, use reduced time to provide clear communication and produce access to required information. 1 , 2 It facilitates generation of ideas, resource exchange(notes and lectures), provides a clear insight of concepts and improves student engagement in classrooms. 4 It is useful in enhancing collaborations, professional development and academic research. 2 , 4 On the contrary, social media can also reduce cognition and enhance academic distraction which can lead to poor performance in academic engagements. 2 , 3 , 4 Psychological issues such as depression, anxiety, sleep disorders or exposure to health risks such as smoking and alcoholism may follow poor academic outcomes. 1 , 4 , 7

The main aim of our study was to determine the correlation between social media usage and academic performance with a standardised questionnaire in medical undergraduates, which would give us an insight about the impact of social media on medical education and to determine the correlation between the social media addiction score and academic performance.

Materials and methods

This cross-sectional questionnaire-based study was conducted at a medical institution over a period of 3 months (November 2018 to January 2019). We invited medical students of second, third and fourth professional years to participate in the study. Four hundred students volunteered to participate in the study. The sampling technique used was purposive sampling. Medical undergraduate students who did not consent to the study or did not use social media were excluded from the study.

Ethical approval was obtained from the Institutional Ethics Committee before administration of the questionnaire. The participant information sheet was given to the students before the study, explaining the purpose of this questionnaire study and informed consent was obtained.

Questionnaire development

Two experts in the field of medical education evaluated the previous literature and selected the attributes for the study questionnaire. A logical sequence of the attributes presented in simple statements was followed to maintain the flow of the questionnaire. The questions were prepared to cover all areas related to the study objectives. An initial pilot study was conducted among 20 students across various professional years, and the elements of the questionnaire were refined after the feedback received on the initial questionnaire. The questionnaire consisted of the following categories: (A) demographic characteristics, including marks secured in the university examination (percentage) which includes the internal assessment and final assessment for the previous professional year examination; (B) various types of social media used; (C) duration of social media use; (D) purposes of social media use in medical education; and (E) the social Media addiction scale. For our study, social media included applications that could be used to converse, exchange and share information. Instant messaging and texting were also included as social media. The students answered the items of item E on a five-point Likert scale with 1 being “strongly disagree” and 5 being “strongly agree.” The social media addiction scale is a validated psychometric measuring scale containing 29 items related to four domains (virtual tolerance – 5 items, virtual communication – 9 items, virtual problem – 9 items and virtual information – 6 items) ( Supplementary File ). 8 The questionnaire forms were distributed to the students after lecture classes and collected after completion of the same.

Statistical analysis

Statistical analysis was done using SPSS v16.0 software. Demographic characteristics were analysed using descriptive statistics. The correlation was measured between social media usage duration and the social media addiction scale score using Pearson's correlation coefficient. The correlation was also measured between academic performance and social media usage duration per day.

The chi-square test was done to compare the academic performance of male and female medical students. We have considered students scoring above 75% as high performers and below 65% as low performers.

Demographics

187 (46.8%) male and 213 (53.2%) female students were a part of the study. The distribution of students of each professional year has been represented in Table 1 . The mean percentage mark secured in university examinations was 69.04 ± 7.59.

Distribution of study participants as per professional year and gender.

Social media used

The social media used most commonly by students have been shown in Fig. 1 . Whatsapp (98.25%) and Youtube (91.75%) were the most commonly used social media. The type of use in gaining academic medical knowledge and learning has been shown in Fig. 2 .

Commonly used social media by medical students.

Common uses of social media in academics by medical students.

Social media usage and academic performance

Duration of social media usage per day has been depicted in Fig. 3 . The comparison of social media usage per day and academic performance status (high performers and low performers) has been depicted in Table 2 . 61.2% low performers and 51.3% of high performers used social media more than 3 h per day. There was a significantly higher use of social media amongst low performers when compared with high performers (p = 0.02).

Duration of social media per day.

Comparison of social media usage to high and low performers.

n = number of students.

Gender and academic performance

Female medical students using social media demonstrated a significantly better academic performance when compared with male medical students (p < 0.001) as demonstrated in Table 3 .

Comparison of gender with academic performance of students.

Social media addiction scale

The mean scores of the various domains in the social media addiction scale have been depicted in Table 4 .

Domain scores of social media addiction scale.

Statistical correlations

There was a significant correlation between the duration of social media usage and the social media addiction score. There was a weak negative correlation between the marks secured in the university examination and duration of social media usage as shown in Table 5 .

Pearson's correlation between social media usage with university examination marks and the social media addiction score.

Whatsapp (98.25%) and Youtube (91.75%) were the most popular social media applications used in our study. In contrast, other studies in Europe, Asia and the United States have shown Facebook as the most followed site in college-going students. 2 The reason for this may be the varied time frame across which the studies were conducted. Social media applications are constantly evolving their range of features, improving their user-friendliness and expanding their access to information to attract more users and gain popularity over other social media platforms. 2 Whatsapp is practically a combination of every existent social medium as it allows to communicate with each other and form peer groups, discuss and obtain feedback, and share information pertaining to medical education from any other social media platform. 9 , 10 , 11 , 12 , 13 , 14 Youtube provides free educational information, professional training and instructional videos, common theme vodcasts and Powerpoint presentations from top universities and organisations, which aid the medical students in enhancing their visual learning. 10 , 11 , 15 , 16 , 17 Facebook and LinkedIn provide opportunities for closed group teacher–student interactions, educational lectures, embedded videos and assignments with feedback being shared on a common platform. 9 , 10 , 11 , 12 , 13 This is based on the fact that current students prefer interactive web-based, self-directed learning compared with lectures. 15

41.5% and 30% of our students use social media on an average of 1–3 h and 3–5 h, respectively. An average social media use of 50 min to 1.5 h daily has been noted in most previous studies. 2 A credible explanation for this could be the advancement of technology over the past decade which had led to the development of multiple user-friendly and attractive social media platforms which impart extensive information to the users. 2 Other factors that can influence the increased time spent on social media can be explained by the gratification theory which includes needs fulfilment, relevance to user curiosity and social norms. 18 Whatsapp, Youtube, Facebook, Instagram, Snapchat, Google Plus, Wikis, Blogs and Forums, Impartus lecture capture and Twitter were the social media platforms used in completing assignments, preparing for tests and seminars, conducting research and imparting health-related news. An average of 67% of students incorporated the use of social media for their education purposes, in contrast, to the study by AlFaris et al 2 which showed 55% social media involvement in medical education.

Our study revealed a better academic performance in female medical students using social media, but there was also evidence that with increased duration of social media use per day the academic performance deteriorated. Alnjadat et al 19 reported that social media addiction is higher in the male student population because the primary aim of social media in the male student population is to find friends with similar interests which certainly affects their academic performance. The female student population in their study opined that social media addiction affected their academic performance. 19

We used a validated social media addiction scale in our study to understand whether the duration of social media usage amounted to addiction. It is imperative from our findings that there is a weak negative impact of social media on academic performance. Contrary to the findings of our study, the literature has evidence that the relation between social media usage and academic performance is debatable. Studies showing a negative correlation between social media use and academic performance attribute it to distraction caused by multitasking, thereby adversely affecting learning. 20 , 21 Second, social media usage amounting to addiction increases academic procrastination and reduces sleep time and quality, thereby increasing academic stress. 22 Studies showing a positive impact of social media on academic performance attribute it to its usage as a learning tool to enhance the academic engagement between peers and educators. 23 Thereby, it impresses upon the medical educators that the social media applications have a gamut of information and processes that can be utilised to enhance learning and academic performances of medical students. Furthermore, students also need to be sensitised on the positive and negative implications of social media early in their medical profession.

Limitations

We used a paper-based questionnaire with self-reporting of variables. This could pose a recall bias on the academic performance percentage and pattern of social media use. Secondly, gauging the in-depth duration and pattern of usage of social media application in medical education and performance was not determined which may be achieved by doing a qualitative analysis. Thirdly, psychological factors other than social media can impact a student’s performance which was not assessed in our study.

The present study suggests a negative impact of social media usage on academic performance. Therefore, student awareness on effective use of social media in medical education and training is crucial, and it should be included and delivered proactively in the foundation course for undergraduate medical students. In addition, medical educators should incorporate social media constructively into the medical curriculum by developing learner-centric modules and effective learning strategies on a social media base to enhance student engagement in learning.

Disclosure of competing interest

The authors have none to declare.

Acknowledgements

The authors thank Dr John Stephen and Dr Ishwara Bhat, St. John’s Medical College, for being instrumental in their support to develop this study project. They thank Dr Cengiz Sahin for letting them use the social media addiction scale-student form and letting them publish it with our manuscript.

Appendix A Supplementary data to this article can be found online at https://doi.org/10.1016/j.mjafi.2020.10.021 .

Appendix A. Supplementary data

The following is the Supplementary data to this article:

An investigation of the social media overload and academic performance

• Published: 02 October 2023

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• Xiongfei Cao 1 , 2 ,
• Yuntao Wu 3 ,
• Bayi Cheng 1 , 2 &
• Ahsan Ali   ORCID: orcid.org/0000-0002-1079-804X 4  

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In the realm of online learning, social media is emerging as an indispensable tool for student learning. While social media offers benefits for students, it is important to acknowledge that it can also exert adverse effects on them. Drawing inspiration from stress dynamics, coping models, and existing social media literature, our study delves into the ways in which technical stressors (specifically, techno-invasion and techno-overload) and social stressors (encompassing the sense of belonging, social interaction, and social support) give rise to psychological stress among students who excessively depend on social media for learning. This heightened stress subsequently leads to feelings of exhaustion and perceived irreplaceability, ultimately impacting their behavioral outcomes, notably academic performance. The model was tested using survey data collected from a sample of 249 university students in China. From the perspective of technical and social systems, this study presents that excessive usage of social media has the potential to impact the students’ academic performance by contributing to their exhaustion and perceived irreplaceability.

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Ritchel Dampog

Cheska Piquero

This research paper investigates the effect of social networking on student performance those use the social websites. Variables which are used in this research paper are gender, education, age, academic performance and social influence. Our research is based on quantitative and descriptive research. Some data is collected from different websites, magazines and journals and 168 questioners are filled from different universities professors and students. The result shows that in age range between 15 to 25 mostly use social networking websites for enjoyment, 60% of male respondent used these websites for information. Inter and Graduation students mostly used these websites for enjoyment. The result also shows some people also used social websites for social influence. This study also shows these students also used social websites for relatives, professors and friends. Students whose gpa are 3.0 to 3.5 GPA (Grade Point Average) commonly use social networking websites for enjoyment 1.Introduction The impact of the Internet on education is important issues that become critical situation for us in recent year. Internet is a very essential part of life for enjoyment and education. It is a very large community which is using internet for pure education but unfortunately we have also a very large number of people including majority of youth and teenager using Internet only for enjoyment. Internet is very big evolution of technology but when we talk about the social networks it is extremely dangerous for youth because student involve in time wasting activities. Internet affects our social values and morality. This study is very important for any country tradition and morality base values. Recently Pakistan face different difficulties and issues one of important issue is that social network destroy our tradition and values. Social media also affect student life in wrong way.Kuppuswamy and Shankar (2010) social network websites grab attention of the students and diverts it towards non-educational and unproductive actions including useless chatting. On the basis of the above statement we can say that social networking sites may nagatively affect the academic life and learning experiences of the student.Liccardi et al (2007) argue that the students are socially connected with each other for sharing their different learning experiences and do conversation about different issues and topic. Trusov, Bucklin, and Pauwels (2009) says that the Internet is big evolution of technology but specifically social networks are extremely harmful for teenagers, social networks become common and well-known in past few years.In the same way Cain (2009) highlighted that social network websites can be practiced for good determinations but it used for Involvement of digital snapshots and information, exposing securities, and conducting online conversations because many other communities inside social networking websites motivate user for this kind of inappropriate actions.According to Ellison, Steinfield, and Lampe (2007) students use social networking websites approximately 30 minutes throughout the day as a part of their daily routine life. This statement shows the importance of social networking websites in students' life and his learning performance. Boyd & Ellison (2007) argued that the U.S. Congress has proposed legislation to ban youth from accessing social networking websites in schools and libraries. When the highly developed nations take stands over the use of social networking websites and cannot allow these social networking websites for countrymen, youth, students and working people. This research mainly focuses on such factors that affect student's academic life and learning experience.Tinto (1997) point out that extracurricular activities and academic activities are not enough to satisfy some student those who are suffered by social networking isolation. This shows that social networks are beneficial for the students in their learning experiences as well as in their academic life.Lenhart and Madden (2007) argued that the students strongly recommend social networking websites to stay in touch with

Sibghatullah Mujadidi

Shraddha Ratra

Social-Network-Sites (SNS) was developed to serve as a platform to connect people. Now a days its reach has magnified and it has become an integral parts of our lives. One can easily access the infinite pool of information, establish connection, share thoughts and videos and can also participate in interactive learning through SNS. It has completely revolutionized the society but what matters is how one is using these resources? The paper will focus on the positives and negatives of SNS, its impact on academic learning of the students and the frequency of them accessing these sites. The research is based on a sample of undergraduate students from Symbiosis International (Deemed University).

calqus wutos

Social networking media has been the major source of communication between individuals in the world over, hence, the label cyber-world. This includes Facebook, Twitter, MySpace, Instagram, Flicker, Frienster, Blogs, Podcast, Youtube, Tumblr and Skype, among others. Users of these forms of media made use of such technology gadgets as cell phones, tablets, laptops, desktop computers, and e-readers. Researchers all over the world have varied findings on the effects of these forms of media on the academic performance of students. Those students who used the media wisely, their academic performance improved. However, those who failed to regulate their use of these social networking tools negatively affected their studies which oftentimes led to their addicted use. In general, the study found out that the exposure of the IMEAS students to the social networking media positively affected their academic performance. Hence, the University must implement policies and projects designed for more easy access of the students to the Facebook network site in the school campus. In contrast, there is also this very disturbing finding of the study which disclosed that the students of IMEAS, University of Southern Mindanao, Kabacan, Cotabato used the social networking media almost daily since majority of them answered to have used said form of media 5-6 days a week at an average of about 1-2 hours every session. With this data, it is recommended that the USM must regulate the proper time usage by the students of social networking media in the campus in order not to destruct with their classroom activities.

EMMANUEL RYAN P. FRANCISCO

Emman Francisco RN

The main intention of this paper is to provide the readers a more comprehensive understanding of the effects of the use of the different social networking sites to the academic performance of the 4th year section Excellence of Baliuag University. This also aims to promote awareness on the role of advanced technology on the lives of students. An in-depth analysis on both positive and negative effects is made. The researchers are apt to determine the relationship between and among variables under investigation. They came up with two hypotheses :1) A person who spends longer hours in using SNS than studying is more likely to have poor academic performance, lower grades and difficult understanding of the lessons ; and 2) A person who spends longer hours in studying than using SNS is more likely to have good academic performance, higher grades and better understanding of the lessons. Guided by the purpose of this study, questionnaires were distributed to 4th year students, section Excellence. The Convenience Sampling was used. Most of the respondents are 15 to 16 years old. They are all users of SNS. The Facebook, Twitter, and Instagram are the three top SNS that most of the respondents use most of them claim that they spend 1-2 hours in using SNS while they spend 3 to 4 hours in studying. Most of them maintain their academic performance even after becoming active users of SNS. These students use SNS as additional references in their studies. On the other hand, the problems that other encountered on the use of SNS are time management and study habits related.

Awodo Stephen

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