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Conceptual analysis article, the effect of social media on the development of students’ affective variables.
- 1 Science and Technology Department, Nanjing University of Posts and Telecommunications, Nanjing, China
- 2 School of Marxism, Hohai University, Nanjing, Jiangsu, China
- 3 Government Enterprise Customer Center, China Mobile Group Jiangsu Co., Ltd., Nanjing, China
The use of social media is incomparably on the rise among students, influenced by the globalized forms of communication and the post-pandemic rush to use multiple social media platforms for education in different fields of study. Though social media has created tremendous chances for sharing ideas and emotions, the kind of social support it provides might fail to meet students’ emotional needs, or the alleged positive effects might be short-lasting. In recent years, several studies have been conducted to explore the potential effects of social media on students’ affective traits, such as stress, anxiety, depression, and so on. The present paper reviews the findings of the exemplary published works of research to shed light on the positive and negative potential effects of the massive use of social media on students’ emotional well-being. This review can be insightful for teachers who tend to take the potential psychological effects of social media for granted. They may want to know more about the actual effects of the over-reliance on and the excessive (and actually obsessive) use of social media on students’ developing certain images of self and certain emotions which are not necessarily positive. There will be implications for pre- and in-service teacher training and professional development programs and all those involved in student affairs.
Social media has turned into an essential element of individuals’ lives including students in today’s world of communication. Its use is growing significantly more than ever before especially in the post-pandemic era, marked by a great revolution happening to the educational systems. Recent investigations of using social media show that approximately 3 billion individuals worldwide are now communicating via social media ( Iwamoto and Chun, 2020 ). This growing population of social media users is spending more and more time on social network groupings, as facts and figures show that individuals spend 2 h a day, on average, on a variety of social media applications, exchanging pictures and messages, updating status, tweeting, favoring, and commenting on many updated socially shared information ( Abbott, 2017 ).
Researchers have begun to investigate the psychological effects of using social media on students’ lives. Chukwuere and Chukwuere (2017) maintained that social media platforms can be considered the most important source of changing individuals’ mood, because when someone is passively using a social media platform seemingly with no special purpose, s/he can finally feel that his/her mood has changed as a function of the nature of content overviewed. Therefore, positive and negative moods can easily be transferred among the population using social media networks ( Chukwuere and Chukwuere, 2017 ). This may become increasingly important as students are seen to be using social media platforms more than before and social networking is becoming an integral aspect of their lives. As described by Iwamoto and Chun (2020) , when students are affected by social media posts, especially due to the increasing reliance on social media use in life, they may be encouraged to begin comparing themselves to others or develop great unrealistic expectations of themselves or others, which can have several affective consequences.
Considering the increasing influence of social media on education, the present paper aims to focus on the affective variables such as depression, stress, and anxiety, and how social media can possibly increase or decrease these emotions in student life. The exemplary works of research on this topic in recent years will be reviewed here, hoping to shed light on the positive and negative effects of these ever-growing influential platforms on the psychology of students.
Significance of the study
Though social media, as the name suggests, is expected to keep people connected, probably this social connection is only superficial, and not adequately deep and meaningful to help individuals feel emotionally attached to others. The psychological effects of social media on student life need to be studied in more depth to see whether social media really acts as a social support for students and whether students can use social media to cope with negative emotions and develop positive feelings or not. In other words, knowledge of the potential effects of the growing use of social media on students’ emotional well-being can bridge the gap between the alleged promises of social media and what it actually has to offer to students in terms of self-concept, self-respect, social role, and coping strategies (for stress, anxiety, etc.).
Exemplary general literature on psychological effects of social media
Before getting down to the effects of social media on students’ emotional well-being, some exemplary works of research in recent years on the topic among general populations are reviewed. For one, Aalbers et al. (2018) reported that individuals who spent more time passively working with social media suffered from more intense levels of hopelessness, loneliness, depression, and perceived inferiority. For another, Tang et al. (2013) observed that the procedures of sharing information, commenting, showing likes and dislikes, posting messages, and doing other common activities on social media are correlated with higher stress. Similarly, Ley et al. (2014) described that people who spend 2 h, on average, on social media applications will face many tragic news, posts, and stories which can raise the total intensity of their stress. This stress-provoking effect of social media has been also pinpointed by Weng and Menczer (2015) , who contended that social media becomes a main source of stress because people often share all kinds of posts, comments, and stories ranging from politics and economics, to personal and social affairs. According to Iwamoto and Chun (2020) , anxiety and depression are the negative emotions that an individual may develop when some source of stress is present. In other words, when social media sources become stress-inducing, there are high chances that anxiety and depression also develop.
Charoensukmongkol (2018) reckoned that the mental health and well-being of the global population can be at a great risk through the uncontrolled massive use of social media. These researchers also showed that social media sources can exert negative affective impacts on teenagers, as they can induce more envy and social comparison. According to Fleck and Johnson-Migalski (2015) , though social media, at first, plays the role of a stress-coping strategy, when individuals continue to see stressful conditions (probably experienced and shared by others in media), they begin to develop stress through the passage of time. Chukwuere and Chukwuere (2017) maintained that social media platforms continue to be the major source of changing mood among general populations. For example, someone might be passively using a social media sphere, and s/he may finally find him/herself with a changed mood depending on the nature of the content faced. Then, this good or bad mood is easily shared with others in a flash through the social media. Finally, as Alahmar (2016) described, social media exposes people especially the young generation to new exciting activities and events that may attract them and keep them engaged in different media contexts for hours just passing their time. It usually leads to reduced productivity, reduced academic achievement, and addiction to constant media use ( Alahmar, 2016 ).
The number of studies on the potential psychological effects of social media on people in general is higher than those selectively addressed here. For further insights into this issue, some other suggested works of research include Chang (2012) , Sriwilai and Charoensukmongkol (2016) , and Zareen et al. (2016) . Now, we move to the studies that more specifically explored the effects of social media on students’ affective states.
Review of the affective influences of social media on students
Vygotsky’s mediational theory (see Fernyhough, 2008 ) can be regarded as a main theoretical background for the support of social media on learners’ affective states. Based on this theory, social media can play the role of a mediational means between learners and the real environment. Learners’ understanding of this environment can be mediated by the image shaped via social media. This image can be either close to or different from the reality. In the case of the former, learners can develop their self-image and self-esteem. In the case of the latter, learners might develop unrealistic expectations of themselves by comparing themselves to others. As it will be reviewed below among the affective variables increased or decreased in students under the influence of the massive use of social media are anxiety, stress, depression, distress, rumination, and self-esteem. These effects have been explored more among school students in the age range of 13–18 than university students (above 18), but some studies were investigated among college students as well. Exemplary works of research on these affective variables are reviewed here.
In a cross-sectional study, O’Dea and Campbell (2011) explored the impact of online interactions of social networks on the psychological distress of adolescent students. These researchers found a negative correlation between the time spent on social networking and mental distress. Dumitrache et al. (2012) explored the relations between depression and the identity associated with the use of the popular social media, the Facebook. This study showed significant associations between depression and the number of identity-related information pieces shared on this social network. Neira and Barber (2014) explored the relationship between students’ social media use and depressed mood at teenage. No significant correlation was found between these two variables. In the same year, Tsitsika et al. (2014) explored the associations between excessive use of social media and internalizing emotions. These researchers found a positive correlation between more than 2-h a day use of social media and anxiety and depression.
Hanprathet et al. (2015) reported a statistically significant positive correlation between addiction to Facebook and depression among about a thousand high school students in wealthy populations of Thailand and warned against this psychological threat. Sampasa-Kanyinga and Lewis (2015) examined the relationship between social media use and psychological distress. These researchers found that the use of social media for more than 2 h a day was correlated with a higher intensity of psychological distress. Banjanin et al. (2015) tested the relationship between too much use of social networking and depression, yet found no statistically significant correlation between these two variables. Frison and Eggermont (2016) examined the relationships between different forms of Facebook use, perceived social support of social media, and male and female students’ depressed mood. These researchers found a positive association between the passive use of the Facebook and depression and also between the active use of the social media and depression. Furthermore, the perceived social support of the social media was found to mediate this association. Besides, gender was found as the other factor to mediate this relationship.
Vernon et al. (2017) explored change in negative investment in social networking in relation to change in depression and externalizing behavior. These researchers found that increased investment in social media predicted higher depression in adolescent students, which was a function of the effect of higher levels of disrupted sleep. Barry et al. (2017) explored the associations between the use of social media by adolescents and their psychosocial adjustment. Social media activity showed to be positively and moderately associated with depression and anxiety. Another investigation was focused on secondary school students in China conducted by Li et al. (2017) . The findings showed a mediating role of insomnia on the significant correlation between depression and addiction to social media. In the same year, Yan et al. (2017) aimed to explore the time spent on social networks and its correlation with anxiety among middle school students. They found a significant positive correlation between more than 2-h use of social networks and the intensity of anxiety.
Also in China, Wang et al. (2018) showed that addiction to social networking sites was correlated positively with depression, and this correlation was mediated by rumination. These researchers also found that this mediating effect was moderated by self-esteem. It means that the effect of addiction on depression was compounded by low self-esteem through rumination. In another work of research, Drouin et al. (2018) showed that though social media is expected to act as a form of social support for the majority of university students, it can adversely affect students’ mental well-being, especially for those who already have high levels of anxiety and depression. In their research, the social media resources were found to be stress-inducing for half of the participants, all university students. The higher education population was also studied by Iwamoto and Chun (2020) . These researchers investigated the emotional effects of social media in higher education and found that the socially supportive role of social media was overshadowed in the long run in university students’ lives and, instead, fed into their perceived depression, anxiety, and stress.
Keles et al. (2020) provided a systematic review of the effect of social media on young and teenage students’ depression, psychological distress, and anxiety. They found that depression acted as the most frequent affective variable measured. The most salient risk factors of psychological distress, anxiety, and depression based on the systematic review were activities such as repeated checking for messages, personal investment, the time spent on social media, and problematic or addictive use. Similarly, Mathewson (2020) investigated the effect of using social media on college students’ mental health. The participants stated the experience of anxiety, depression, and suicidality (thoughts of suicide or attempts to suicide). The findings showed that the types and frequency of using social media and the students’ perceived mental health were significantly correlated with each other.
The body of research on the effect of social media on students’ affective and emotional states has led to mixed results. The existing literature shows that there are some positive and some negative affective impacts. Yet, it seems that the latter is pre-dominant. Mathewson (2020) attributed these divergent positive and negative effects to the different theoretical frameworks adopted in different studies and also the different contexts (different countries with whole different educational systems). According to Fredrickson’s broaden-and-build theory of positive emotions ( Fredrickson, 2001 ), the mental repertoires of learners can be built and broadened by how they feel. For instance, some external stimuli might provoke negative emotions such as anxiety and depression in learners. Having experienced these negative emotions, students might repeatedly check their messages on social media or get addicted to them. As a result, their cognitive repertoire and mental capacity might become limited and they might lose their concentration during their learning process. On the other hand, it should be noted that by feeling positive, learners might take full advantage of the affordances of the social media and; thus, be able to follow their learning goals strategically. This point should be highlighted that the link between the use of social media and affective states is bi-directional. Therefore, strategic use of social media or its addictive use by students can direct them toward either positive experiences like enjoyment or negative ones such as anxiety and depression. Also, these mixed positive and negative effects are similar to the findings of several other relevant studies on general populations’ psychological and emotional health. A number of studies (with general research populations not necessarily students) showed that social networks have facilitated the way of staying in touch with family and friends living far away as well as an increased social support ( Zhang, 2017 ). Given the positive and negative emotional effects of social media, social media can either scaffold the emotional repertoire of students, which can develop positive emotions in learners, or induce negative provokers in them, based on which learners might feel negative emotions such as anxiety and depression. However, admittedly, social media has also generated a domain that encourages the act of comparing lives, and striving for approval; therefore, it establishes and internalizes unrealistic perceptions ( Virden et al., 2014 ; Radovic et al., 2017 ).
It should be mentioned that the susceptibility of affective variables to social media should be interpreted from a dynamic lens. This means that the ecology of the social media can make changes in the emotional experiences of learners. More specifically, students’ affective variables might self-organize into different states under the influence of social media. As for the positive correlation found in many studies between the use of social media and such negative effects as anxiety, depression, and stress, it can be hypothesized that this correlation is induced by the continuous comparison the individual makes and the perception that others are doing better than him/her influenced by the posts that appear on social media. Using social media can play a major role in university students’ psychological well-being than expected. Though most of these studies were correlational, and correlation is not the same as causation, as the studies show that the number of participants experiencing these negative emotions under the influence of social media is significantly high, more extensive research is highly suggested to explore causal effects ( Mathewson, 2020 ).
As the review of exemplary studies showed, some believed that social media increased comparisons that students made between themselves and others. This finding ratifies the relevance of the Interpretation Comparison Model ( Stapel and Koomen, 2000 ; Stapel, 2007 ) and Festinger’s (1954) Social Comparison Theory. Concerning the negative effects of social media on students’ psychology, it can be argued that individuals may fail to understand that the content presented in social media is usually changed to only represent the attractive aspects of people’s lives, showing an unrealistic image of things. We can add that this argument also supports the relevance of the Social Comparison Theory and the Interpretation Comparison Model ( Stapel and Koomen, 2000 ; Stapel, 2007 ), because social media sets standards that students think they should compare themselves with. A constant observation of how other students or peers are showing their instances of achievement leads to higher self-evaluation ( Stapel and Koomen, 2000 ). It is conjectured that the ubiquitous role of social media in student life establishes unrealistic expectations and promotes continuous comparison as also pinpointed in the Interpretation Comparison Model ( Stapel and Koomen, 2000 ; Stapel, 2007 ).
Implications of the study
The use of social media is ever increasing among students, both at school and university, which is partly because of the promises of technological advances in communication services and partly because of the increased use of social networks for educational purposes in recent years after the pandemic. This consistent use of social media is not expected to leave students’ psychological, affective and emotional states untouched. Thus, it is necessary to know how the growing usage of social networks is associated with students’ affective health on different aspects. Therefore, we found it useful to summarize the research findings in recent years in this respect. If those somehow in charge of student affairs in educational settings are aware of the potential positive or negative effects of social media usage on students, they can better understand the complexities of students’ needs and are better capable of meeting them.
Psychological counseling programs can be initiated at schools or universities to check upon the latest state of students’ mental and emotional health influenced by the pervasive use of social media. The counselors can be made aware of the potential adverse effects of social networking and can adapt the content of their inquiries accordingly. Knowledge of the potential reasons for student anxiety, depression, and stress can help school or university counselors to find individualized coping strategies when they diagnose any symptom of distress in students influenced by an excessive use of social networking.
Admittedly, it is neither possible to discard the use of social media in today’s academic life, nor to keep students’ use of social networks fully controlled. Certainly, the educational space in today’s world cannot do without the social media, which has turned into an integral part of everybody’s life. Yet, probably students need to be instructed on how to take advantage of the media and to be the least affected negatively by its occasional superficial and unrepresentative content. Compensatory programs might be needed at schools or universities to encourage students to avoid making unrealistic and impartial comparisons of themselves and the flamboyant images of others displayed on social media. Students can be taught to develop self-appreciation and self-care while continuing to use the media to their benefit.
The teachers’ role as well as the curriculum developers’ role are becoming more important than ever, as they can significantly help to moderate the adverse effects of the pervasive social media use on students’ mental and emotional health. The kind of groupings formed for instructional purposes, for example, in social media can be done with greater care by teachers to make sure that the members of the groups are homogeneous and the tasks and activities shared in the groups are quite relevant and realistic. The teachers cannot always be in a full control of students’ use of social media, and the other fact is that students do not always and only use social media for educational purposes. They spend more time on social media for communicating with friends or strangers or possibly they just passively receive the content produced out of any educational scope just for entertainment. This uncontrolled and unrealistic content may give them a false image of life events and can threaten their mental and emotional health. Thus, teachers can try to make students aware of the potential hazards of investing too much of their time on following pages or people that publish false and misleading information about their personal or social identities. As students, logically expected, spend more time with their teachers than counselors, they may be better and more receptive to the advice given by the former than the latter.
Teachers may not be in full control of their students’ use of social media, but they have always played an active role in motivating or demotivating students to take particular measures in their academic lives. If teachers are informed of the recent research findings about the potential effects of massively using social media on students, they may find ways to reduce students’ distraction or confusion in class due to the excessive or over-reliant use of these networks. Educators may more often be mesmerized by the promises of technology-, computer- and mobile-assisted learning. They may tend to encourage the use of social media hoping to benefit students’ social and interpersonal skills, self-confidence, stress-managing and the like. Yet, they may be unaware of the potential adverse effects on students’ emotional well-being and, thus, may find the review of the recent relevant research findings insightful. Also, teachers can mediate between learners and social media to manipulate the time learners spend on social media. Research has mainly indicated that students’ emotional experiences are mainly dependent on teachers’ pedagogical approach. They should refrain learners from excessive use of, or overreliance on, social media. Raising learners’ awareness of this fact that individuals should develop their own path of development for learning, and not build their development based on unrealistic comparison of their competences with those of others, can help them consider positive values for their activities on social media and, thus, experience positive emotions.
At higher education, students’ needs are more life-like. For example, their employment-seeking spirits might lead them to create accounts in many social networks, hoping for a better future. However, membership in many of these networks may end in the mere waste of the time that could otherwise be spent on actual on-campus cooperative projects. Universities can provide more on-campus resources both for research and work experience purposes from which the students can benefit more than the cyberspace that can be tricky on many occasions. Two main theories underlying some negative emotions like boredom and anxiety are over-stimulation and under-stimulation. Thus, what learners feel out of their involvement in social media might be directed toward negative emotions due to the stimulating environment of social media. This stimulating environment makes learners rely too much, and spend too much time, on social media or use them obsessively. As a result, they might feel anxious or depressed. Given the ubiquity of social media, these negative emotions can be replaced with positive emotions if learners become aware of the psychological effects of social media. Regarding the affordances of social media for learners, they can take advantage of the potential affordances of these media such as improving their literacy, broadening their communication skills, or enhancing their distance learning opportunities.
A review of the research findings on the relationship between social media and students’ affective traits revealed both positive and negative findings. Yet, the instances of the latter were more salient and the negative psychological symptoms such as depression, anxiety, and stress have been far from negligible. These findings were discussed in relation to some more relevant theories such as the social comparison theory, which predicted that most of the potential issues with the young generation’s excessive use of social media were induced by the unfair comparisons they made between their own lives and the unrealistic portrayal of others’ on social media. Teachers, education policymakers, curriculum developers, and all those in charge of the student affairs at schools and universities should be made aware of the psychological effects of the pervasive use of social media on students, and the potential threats.
It should be reminded that the alleged socially supportive and communicative promises of the prevalent use of social networking in student life might not be fully realized in practice. Students may lose self-appreciation and gratitude when they compare their current state of life with the snapshots of others’ or peers’. A depressed or stressed-out mood can follow. Students at schools or universities need to learn self-worth to resist the adverse effects of the superficial support they receive from social media. Along this way, they should be assisted by the family and those in charge at schools or universities, most importantly the teachers. As already suggested, counseling programs might help with raising students’ awareness of the potential psychological threats of social media to their health. Considering the ubiquity of social media in everybody’ life including student life worldwide, it seems that more coping and compensatory strategies should be contrived to moderate the adverse psychological effects of the pervasive use of social media on students. Also, the affective influences of social media should not be generalized but they need to be interpreted from an ecological or contextual perspective. This means that learners might have different emotions at different times or different contexts while being involved in social media. More specifically, given the stative approach to learners’ emotions, what learners emotionally experience in their application of social media can be bound to their intra-personal and interpersonal experiences. This means that the same learner at different time points might go through different emotions Also, learners’ emotional states as a result of their engagement in social media cannot be necessarily generalized to all learners in a class.
As the majority of studies on the psychological effects of social media on student life have been conducted on school students than in higher education, it seems it is too soon to make any conclusive remark on this population exclusively. Probably, in future, further studies of the psychological complexities of students at higher education and a better knowledge of their needs can pave the way for making more insightful conclusions about the effects of social media on their affective states.
Suggestions for further research
The majority of studies on the potential effects of social media usage on students’ psychological well-being are either quantitative or qualitative in type, each with many limitations. Presumably, mixed approaches in near future can better provide a comprehensive assessment of these potential associations. Moreover, most studies on this topic have been cross-sectional in type. There is a significant dearth of longitudinal investigation on the effect of social media on developing positive or negative emotions in students. This seems to be essential as different affective factors such as anxiety, stress, self-esteem, and the like have a developmental nature. Traditional research methods with single-shot designs for data collection fail to capture the nuances of changes in these affective variables. It can be expected that more longitudinal studies in future can show how the continuous use of social media can affect the fluctuations of any of these affective variables during the different academic courses students pass at school or university.
As already raised in some works of research reviewed, the different patterns of impacts of social media on student life depend largely on the educational context. Thus, the same research designs with the same academic grade students and even the same age groups can lead to different findings concerning the effects of social media on student psychology in different countries. In other words, the potential positive and negative effects of popular social media like Facebook, Snapchat, Twitter, etc., on students’ affective conditions can differ across different educational settings in different host countries. Thus, significantly more research is needed in different contexts and cultures to compare the results.
There is also a need for further research on the higher education students and how their affective conditions are positively and negatively affected by the prevalent use of social media. University students’ psychological needs might be different from other academic grades and, thus, the patterns of changes that the overall use of social networking can create in their emotions can be also different. Their main reasons for using social media might be different from school students as well, which need to be investigated more thoroughly. The sorts of interventions needed to moderate the potential negative effects of social networking on them can be different too, all requiring a new line of research in education domain.
Finally, there are hopes that considering the ever-increasing popularity of social networking in education, the potential psychological effects of social media on teachers be explored as well. Though teacher psychology has only recently been considered for research, the literature has provided profound insights into teachers developing stress, motivation, self-esteem, and many other emotions. In today’s world driven by global communications in the cyberspace, teachers like everyone else are affecting and being affected by social networking. The comparison theory can hold true for teachers too. Thus, similar threats (of social media) to self-esteem and self-worth can be there for teachers too besides students, which are worth investigating qualitatively and quantitatively.
Probably a new line of research can be initiated to explore the co-development of teacher and learner psychological traits under the influence of social media use in longitudinal studies. These will certainly entail sophisticated research methods to be capable of unraveling the nuances of variation in these traits and their mutual effects, for example, stress, motivation, and self-esteem. If these are incorporated within mixed-approach works of research, more comprehensive and better insightful findings can be expected to emerge. Correlational studies need to be followed by causal studies in educational settings. As many conditions of the educational settings do not allow for having control groups or randomization, probably, experimental studies do not help with this. Innovative research methods, case studies or else, can be used to further explore the causal relations among the different features of social media use and the development of different affective variables in teachers or learners. Examples of such innovative research methods can be process tracing, qualitative comparative analysis, and longitudinal latent factor modeling (for a more comprehensive view, see Hiver and Al-Hoorie, 2019 ).
Both authors listed have made a substantial, direct, and intellectual contribution to the work, and approved it for publication.
This study was sponsored by Wuxi Philosophy and Social Sciences bidding project—“Special Project for Safeguarding the Rights and Interests of Workers in the New Form of Employment” (Grant No. WXSK22-GH-13). This study was sponsored by the Key Project of Party Building and Ideological and Political Education Research of Nanjing University of Posts and Telecommunications—“Research on the Guidance and Countermeasures of Network Public Opinion in Colleges and Universities in the Modern Times” (Grant No. XC 2021002).
Conflict of interest
Author XX was employed by China Mobile Group Jiangsu Co., Ltd.
The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
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Keywords : affective variables, education, emotions, social media, post-pandemic, emotional needs
Citation: Chen M and Xiao X (2022) The effect of social media on the development of students’ affective variables. Front. Psychol. 13:1010766. doi: 10.3389/fpsyg.2022.1010766
Received: 03 August 2022; Accepted: 25 August 2022; Published: 15 September 2022.
Copyright © 2022 Chen and Xiao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
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The Roles of Social Media in Education: Affective, Behavioral, and Cognitive Dimensions
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Literature review; THE EFFECTS OF SOCIAL MEDIA ON STUDENT PERFORMANCE Literature review
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Analysing the Impact of Social Media on Students’ Academic Performance: A Comparative Study of Extraversion and Introversion Personality
International Management Institute (IMI), Bhubaneswar, India
Complete data and material is available to support transparency.
The advent of technology in education has seen a revolutionary change in the teaching–learning process. Social media is one such invention which has a major impact on students’ academic performance. This research analyzed the impact of social media on the academic performance of extraversion and introversion personality students. Further, the comparative study between these two personalities will be analysed on education level (postgraduate and undergraduate) and gender (male and female). The research was initiated by identifying the factors of social media impacting students’ academic performance. Thereafter, the scale was developed, validated and tested for reliability in the Indian context. Data were collected from 408 students segregated into 202 males and 206 females. Two hundred and thirty-four students are enrolled in postgraduation courses, whereas 174 are registered in the undergraduate programme. One-way ANOVA has been employed to compare the extraversion and introversion students of different education levels and gender. A significant difference is identified between extraversion and introversion students for the impact of social media on their academic performance.
Social Networking Sites (SNS) gained instant popularity just after the invention and expansion of the Internet. Today, these sites are used the most to communicate and spread the message. The population on these social networking sites (SNS) has increased exponentially. Social networking sites (SNS) in general are called social media (Boyd & Ellison, 2008 ). Social media (SM) is used extensively to share content, initiate discussion, promote businesses and gain advantages over traditional media. Technology plays a vital role to make SM more robust by reducing security threats and increasing reliability (Stergiou et al., 2018 ).
As of January 2022, more than 4.95 billion people are using the Internet worldwide, and around 4.62 billion are active SM users (Johnson, 2022 ). In India, the number of Internet users was 680 million by January 2022, and there were 487 million active social media users (Basuray, 2022 ). According to Statista Research Department ( 2022 ), in India, SM is dominated by two social media sites, i.e. YouTube and Facebook. YouTube has 467 million users followed by Facebook with 329 million users.
Although almost all age groups are using SM platforms to interact and communicate with their known community (Whiting & Williams, 2013 ), it has been found that social media sites are more popular among youngsters and specifically among students. They use SM for personal as well as academic activities extensively (Laura et al., 2017 ). Other than SM, from the last two years, several online platforms such as Microsoft Teams, Zoom and Google Meet are preferred to organize any kind of virtual meetings, webinars and online classes. These platforms were used worldwide to share and disseminate knowledge across the defined user community during the pandemic. Social media sites such as Facebook, YouTube, Instagram, WhatsApp and blogs are comparatively more open and used to communicate with public and/or private groups. Earlier these social media platforms were used only to connect with friends and family, but gradually these platforms became one of the essential learning tools for students (Park et al., 2009 ). To enhance the teaching–learning process, these social media sites are explored by all types of learning communities (Dzogbenuku et al., 2019 ). SM when used in academics has both advantages and disadvantages. Social media helps to improve academic performance, but it may also distract the students from studies and indulge them in other non-academic activities (Alshuaibi et al., 2018 ).
Here, it is important to understand that the personality traits of students, their education level and gender are critical constructs to determine academic performance. There are different personality traits of an individual such as openness, conscientiousness, extraversion and introversion, agreeableness and neuroticism (McCrae & Costa, 1987 ). This cross-functional research is an attempt to study the impact of social media on the academic performance of students while using extraversion and introversion personality traits, education levels and gender as moderating variables.
There has been a drastic change in the internet world due to the invention of social media sites in the last ten years. People of all age groups now share their stories, feelings, videos, pictures and all kinds of public stuff on social media platforms exponentially (Asur & Huberman, 2010 ). Youth, particularly from the age group of 16–24, embraced social media sites to connect with their friends and family, exchange information and showcase their social status (Boyd & Ellison, 2008 ). Social media sites have many advantages when used in academics. The fun element of social media sites always helps students to be connected with peers and teachers to gain knowledge (Amin et al., 2016 ). Social media also enhances the communication between teachers and students as this are no ambiguity and miscommunication from social media which eventually improves the academic performance of the students (Oueder & Abousaber, 2018 ).
When social media is used for educational purposes, it may improve academic performance, but some associated challenges also come along with it (Rithika & Selvaraj, 2013 ). If social media is incorporated into academics, students try to also use it for non-academic discussions (Arnold & Paulus, 2010 ). The primary reason for such distraction is its design as it is designed to be a social networking tool (Qiu et al., 2013 ). According to Englander et al. ( 2010 ), the usage of social media in academics has more disadvantages than advantages. Social media severely impacts the academic performance of a student. The addiction to social media is found more among the students of higher studies which ruins the academic excellence of an individual (Nalwa & Anand, 2003 ). Among the social media users, Facebook users’ academic performance was worse than the nonusers or users of any other social media network. Facebook was found to be the major distraction among students (Kirschner & Karpinski, 2010 ). However, other studies report contrary findings and argued that students benefited from chatting (Jain et al., 2012 ), as it improves their vocabulary and writing skills (Yunus & Salehi, 2012 ). Social media can be used either to excel in academics or to devastate academics. It all depends on the way it is used by the students. The good or bad use of social media in academics is the users’ decision because both the options are open to the students (Landry, 2014 ).
Kaplan and Haenlein ( 2010 ) defined social media as user-generated content shared on web 2.0. They have also classified social media into six categories:
- Social Networking Sites: Facebook, Twitter, LinkedIn and Instagram are the social networking sites where a user may create their profile and invite their friends to join. Users may communicate with each other by sharing common content.
- Blogging Sites: Blogging sites are individual web pages where users may communicate and share their knowledge with the audience.
- Content Communities and Groups: YouTube and Slideshare are examples of content communities where people may share media files such as pictures, audio and video and PPT presentations.
- Gaming Sites: Users may virtually participate and enjoy the virtual games.
- Virtual Worlds: During COVID-19, this type of social media was used the most. In the virtual world, users meet with each other at some decided virtual place and can do the pre-decided things together. For example, the teacher may decide on a virtual place of meeting, and students may connect there and continue their learning.
- Collaborative Content Sites: Wikipedia is an example of a collaborative content site. It permits many users to work on the same project. Users have all rights to edit and add the new content to the published project.
Massive open online courses (MOOCs) are in trend since 2020 due to the COVID-19 pandemic (Raja & Kallarakal, 2020 ). MOOCs courses are generally free, and anyone may enrol for them online. Many renowned institutions have their online courses on MOOCs platform which provides a flexible learning opportunity to the students. Students find them useful to enhance their knowledge base and also in career development. Many standalone universities have collaborated with the MOOCs platform and included these courses in their curriculum (Chen, 2013 ).
Security and privacy are the two major concerns associated with social media. Teachers are quite apprehensive in using social media for knowledge sharing due to the same concerns (Fedock et al., 2019 ). It was found that around 72% teachers were reluctant to use social media platforms due to integrity issues and around 63% teachers confirmed that security needs to be tightened before using social media in the classroom (Surface et al., 2014 ). Proper training on security and privacy, to use social media platforms in academics, is needed for students and teachers (Bhatnagar & Pry, 2020 ).
The personality traits of a student also play a significant role in deciding the impact of social media on students’ academic performance. Personality is a dynamic organization which simplifies the way a person behaves in a situation (Phares, 1991 ). Human behaviour has further been described by many renowned researchers. According to Lubinski ( 2000 ), human behaviour may be divided into five factors, i.e. cognitive abilities, personality, social attitudes, psychological interests and psychopathology. These personality traits are very important characteristics of a human being and play a substantial role in work commitment (Macey & Schneider, 2008 ). Goldberg ( 1993 ) elaborated on five dimensions of personality which are commonly known as the Big Five personality traits. The traits are “openness vs. cautious”; “extraversion vs. introversion”; “agreeableness vs. rational”; “conscientiousness vs. careless”; and “neuroticism vs. resilient”.
It has been found that among all personality traits, the “extraversion vs. introversion” personality trait has a greater impact on students’ academic performance (Costa & McCrae, 1999 ). Extrovert students are outgoing, talkative and assertive (Chamorro et al., 2003 ). They are positive thinkers and comfortable working in a crowd. Introvert students are reserved and quiet. They prefer to be isolated and work in silos (Bidjerano & Dai, 2007 ). So, in the present study, we have considered only the “extraversion vs. introversion” personality trait. This study is going to analyse the impact of social media platforms on students’ academic performance by taking the personality trait of extraversion and introversion as moderating variables along with their education level and gender.
Past research by Choney ( 2010 ), Karpinski and Duberstein ( 2009 ), Khan ( 2009 ) and Kubey et al. ( 2001 ) was done mostly in developed countries to analyse the impact of social media on the students’ academic performance, effect of social media on adolescence, and addictiveness of social media in students. There are no published research studies where the impact of social media was studied on students’ academic performance by taking their personality traits, education level and gender all three together into consideration. So, in the present study, the impact of social media will be evaluated on students’ academic performance by taking their personality traits (extraversion and introversion), education level (undergraduate and postgraduate) and gender (male and female) as moderating variables.
Objectives of the Study
Based on the literature review and research gap, the following research objectives have been defined:
- To identify the elements of social media impacting student's academic performance and to develop a suitable scale
- To test the validity and reliability of the scale
- To analyse the impact of social media on students’ academic performance using extraversion and introversion personality trait, education level and gender as moderating variables
Convenience sampling was used for data collection. An online google form was floated to collect the responses from 408 male and female university students of undergraduation and postgraduation streams.
Objective 1 To identify the elements of social media impacting student's academic performance and to develop a suitable scale.
A structured questionnaire was employed to collect the responses from 408 students of undergraduate and postgraduate streams. The questionnaire was segregated into three sections. In section one, demographic details such as gender, age and education stream were defined. Section two contained the author’s self-developed 16-item scale related to the impact of social media on the academic performance of students. The third section had a standardized scale developed by John and Srivastava ( 1999 ) of the Big Five personality model.
There were 408 respondents (students) of different education levels consisting of 202 males (49.5%) and 206 females (50.5%). Most of the respondents (87%) were from the age group of 17–25 years. 234 respondents (57.4) were enrolled on postgraduation courses, whereas 174 respondents (42.6) were registered in the undergraduate programme. The result further elaborates that WhatsApp with 88.6% and YouTube with 82.9% are the top two commonly used platforms followed by Instagram with 76.7% and Facebook with 62.3% of students. 65% of students stated that Google doc is a quite useful and important application in academics for document creation and information dissemination.
Validity and Reliability of Scale
Objective 2 Scale validity and reliability.
Exploratory factor analysis (EFA) and Cronbach’s alpha test were used to investigate construct validity and reliability, respectively.
The author’s self-designed scale of ‘social media impacting students’ academic performance’ consisting of 16 items was validated using exploratory factor analysis. The principle component method with varimax rotation was applied to decrease the multicollinearity within the items. The initial eigenvalue was set to be greater than 1.0 (Field, 2005 ). Kaiser–Meyer–Olkin (KMO) with 0.795 and Bartlett’s test of sphericity having significant values of 0.000 demonstrated the appropriateness of using exploratory factor analysis.
The result of exploratory factor analysis and Cronbach’s alpha is shown in Table Table1. 1 . According to Sharma and Behl ( 2020 ), “High loading on the same factor and no substantial cross-loading confirms convergent and discriminant validity respectively”.
Exploratory factor analysis and Cronbach’s alpha for the self-developed scale of “Social media impact on academic performance”
The self-developed scale was segregated into four factors, namely “Accelerating Impact”, “Deteriorating Impact”, “Social Media Prospects” and “Social Media Challenges”.
The first factor, i.e. “Accelerating Impact”, contains items related to positive impact of social media on students’ academic performance. Items in this construct determine the social media contribution in the grade improvement, communication and knowledge sharing. The second factor “Deteriorating Impact” describes the items which have a negative influence of social media on students’ academic performance. Items such as addiction to social media and distraction from studies are an integral part of this factor. “Social Media Prospects” talk about the opportunities created by social media for students’ communities. The last factor “Social Media Challenges” deals with security and privacy issues created by social media sites and the threat of cyberbullying which is rampant in academics.
The personality trait of an individual always influences the social media usage pattern. Therefore, the impact of social media on the academic performance of students may also change with their personality traits. To measure the personality traits, the Big Five personality model was used. This model consists of five personality traits, i.e. “openness vs. cautious”; “extraversion vs. introversion”; “agreeableness vs. rational”; “conscientiousness vs. careless”; and “neuroticism vs. resilient”. To remain focussed on the scope of the study, only a single personality trait, i.e. “extraversion vs. introversion” with 6 items was considered for analysis. A reliability test of this existing scale using Cronbach’s alpha was conducted. Prior to the reliability test, reverse scoring applicable to the associated items was also calculated. Table Table2 2 shows the reliability score, i.e. 0.829.
Cronbach’s alpha test for the scale of extraversion vs. introversion personality traits
Objective 3 To analyse the impact of social media on students’ academic performance using extraversion and introversion personality traits, education level and gender as moderating variables.
The research model shown in Fig. 1 helps in addressing the above objective.
Social media factors impacting academic performances of extraversion and introversion personality traits of students at different education levels and gender
As mentioned in Fig. 1 , four dependent factors (Accelerating Impact, Deteriorating Impact, Social Media Prospects and Social Media Challenges) were derived from EFA and used for analysing the impact of social media on the academic performance of students having extraversion and introversion personality traits at different education levels and gender.
Students having a greater average score (more than three on a scale of five) for all personality items mentioned in Table Table2 2 are considered to be having extraversion personality or else introversion personality. From the valid dataset of 408 students, 226 students (55.4%) had extraversion personality trait and 182 (44.6%) had introversion personality trait. The one-way ANOVA analysis was employed to determine the impact of social media on academic performance for all three moderators, i.e. personality traits (Extraversion vs. Introversion), education levels (Undergraduate and Postgraduate) and gender (Male and Female). If the sig. value for the result is > = 0.05, we may accept the null hypothesis, i.e. there is no significant difference between extraversion and introversion personality students for the moderators; otherwise, null hypothesis is rejected which means there is a significant difference for the moderators.
Table Table3 3 shows the comparison of the accelerating impact of social media on the academic performance of all students having extraversion and introversion personality traits. It also shows a comparative analysis on education level and gender for these two personality traits of students. In the first comparison of extraversion and introversion students, the sig. value is 0.001, which indicates that there is a significant difference among extraversion and introversion students for the “Accelerating Impact” of social media on academic performance. Here, 3.781 is the mean value for introversion students which is higher than the mean value 3.495 of extraversion students. It clearly specifies that the accelerating impact of social media is more prominent in the students having introversion personality traits. Introversion students experienced social media as the best tool to express thoughts and improve academic grades. The result is also consistent with the previous studies where introvert students are perceived to use social media to improve their academic performance (Amichai-Hamburger et al., 2002 ; Voorn & Kommers, 2013 ). Further at the education level, there was a significant difference in postgraduate as well as undergraduate students for the accelerating impact of social media on the academic performance among students with extraversion and introversion, and introverts seem to get better use of social media. The gender-wise significant difference was also analysed between extraversion and introversion personalities. Female introversion students were found to gain more of an accelerating impact of social media on their academic performance.
One-way ANOVA: determining “Accelerating Impact” among extraversion and introversion personality traits students at different education levels and genders
Significant at the 0.05 level
Like Table Table3, 3 , the first section of Table Table4 4 compares the deteriorating impact of social media on the academic performance of all students having extraversion and introversion personality traits. Here, the sig. value 0.383 indicates no significant difference among extraversion and introversion students for the “Deteriorating Impact” of social media on academic performance. The mean values show the moderating deteriorating impact of social media on the academic performance of extraversion and introversion personality students. Unlimited use of social media due to the addiction is causing a distraction in academic performance, but the overall impact is not on the higher side. Further, at the education level, the sig. values 0.423 and 0.682 of postgraduate and undergraduate students, respectively, show no significant difference between extraversion and introversion students with respect to “Deteriorating Impact of Social Media Sites”. The mean values again represent the moderate impact. Gender-wise, male students have no difference between the two personality traits, but at the same time, female students have a significant difference in the deteriorating impact, and it is more on extroverted female students.
One-way ANOVA: Examining “Deteriorating Impact” among extraversion and introversion personality traits students at different education levels and genders
The significant value, i.e. 0.82, in Table Table5 5 represents no significant difference between extraversion and introversion personality students for the social media prospects. The higher mean value of both personality students indicates that they are utilizing the opportunities of social media in the most appropriate manner. It seems that all the students are using social media for possible employment prospects, gaining knowledge by attending MOOCs courses and transferring knowledge among other classmates. At the education level, postgraduation students have no significant difference between extraversion and introversion for the social media prospects, but at the undergraduate level, there is a significant difference among both the personalities, and by looking at mean values, extroverted students gain more from the social media prospects. Gender-wise comparison of extraversion and introversion personality students found no significant difference in the social media prospects for male as well as female students.
One-way ANOVA: Examining “Social Media Prospects” among extraversion and introversion personality traits students at different education levels and genders
Table Table6 6 shows the comparison of the social media challenges of all students having extraversion and introversion personality traits. It is also doing a comparative analysis on education level and gender for these two personality traits of students. All sig. values in Table Table6 6 represent no significant difference between extraversion and introversion personality students for social media challenges. Even at the education level and gender-wise comparison of the two personalities, no significant difference is derived. The higher mean values indicate that the threat of cyberbullying, security and privacy is the main concern areas for extraversion and introversion personality students. Cyberbullying is seen to be more particularly among female students (Snell & Englander, 2010 ).
One-way ANOVA: Examining “Social Media Challenges” among extraversion and introversion personality traits students at different education levels and genders
The use of social media sites in academics is becoming popular among students and teachers. The improvement or deterioration in academic performance is influenced by the personality traits of an individual. This study has tried to analyse the impact of social media on the academic performance of extraversion and introversion personality students. This study has identified four factors of social media which have an impact on academic performance. These factors are: accelerating impact of social media; deteriorating impact of social media; social media prospects; and social media challenges.
Each of these factors has been used for comparative analysis of students having extraversion and introversion personality traits. Their education level and gender have also been used to understand the detailed impact between these two personality types. In the overall comparison, it has been discovered that both personalities (extraversion and introversion) have a significant difference for only one factor, i.e. “Accelerating Impact of Social Media Sites” where students with introversion benefited the most. At the education level, i.e. postgraduate and undergraduate, there was a significant difference between extraversion and introversion personalities for the first factor which is the accelerating impact of social media. Here, the introversion students were found to benefit in postgraduate as well as undergraduate courses. For the factors of deteriorating impact and social media challenges, there was no significant difference between extraversion and introversion personality type at the different education levels.
Surprisingly, for the first factor, i.e. the accelerating impact of social media, in gender-wise comparison, no significant difference was found between extraversion and introversion male students. Whereas a significant difference was found in female students. The same was the result for the second factor, i.e. deteriorating impact of social media of male and female students. For social media prospects and social media challenges, no significant difference was identified between extraversion and introversion students of any gender.
Findings and Implications
The personality trait of a student plays a vital role in analysing the impact of social media on their academic performance. The present study was designed to find the difference between extraversion and introversion personality types in students for four identified factors of social media and their impact on students’ academic performance. The education level and gender were also added to make it more comprehensive. The implications of this study are useful for institutions, students, teachers and policymakers.
This study will help the institutions to identify the right mix of social media based on the personality, education level and gender of the students. For example, technological challenges are faced by all students. It is important for the institutions to identify the challenges such as cyberbullying, security and privacy issues and accordingly frame the training sessions for all undergraduate and postgraduate students. These training sessions will help students with extraversion and introversion to come out from possible technological hassles and will create a healthy ecosystem (Okereke & Oghenetega, 2014 ).
Students will also benefit from this study as they will be conscious of the possible pros and cons that exist because of social media usage and its association with students’ academic performance. This learning may help students to enhance their academic performance with the right use of social media sites. The in-depth knowledge of all social media platforms and their association with academics should be elucidated to the students so that they may explore the social media opportunities in an optimum manner. Social media challenges also need to be made known to the students to improve upon and overcome with time (Boateng & Amankwaa, 2016 ).
Teachers are required to design the curriculum by understanding the learning style of students with extraversion and introversion personality type. Innovation and customization in teaching style are important for the holistic development of students and to satisfy the urge for academic requirements. Teachers should also guide the students about the adverse impacts of each social media platform, so that these can be minimized. Students should also be guided to reduce the time limit of using social media (Owusu-Acheaw & Larson, 2015 ).
Policymakers are also required to understand the challenges faced by the students while using social media in academics. All possible threats can be managed by defining and implementing transparent and proactive policies. As social media sites are open in nature, security and privacy are the two major concerns. The Government of India should take a strong stand to control all big social media companies so that they may fulfil the necessary compliances related to students’ security and privacy (Kumar & Pradhan, 2018 ).
The overall result of these comparisons gives a better insight and deep understanding of the significant differences between students with extraversion and introversion personality type towards different social media factors and their impact on students’ academic performance. Students’ behaviour according to their education level and gender for extraversion and introversion personalities has also been explored.
Limitation and Future Scope of Research
Due to COVID restrictions, a convenient sampling technique was used for data collection which may create some response biases where the students of introversion personality traits may have intentionally described themselves as extroversion personalities and vice versa. This study also creates scope for future research. In the Big Five personality model, there are four other personality traits which are not considered in the present study. There is an opportunity to also use cross-personality comparisons for the different social media parameters. The other demographic variables such as age and place may also be explored in future research.
All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Dr. SS and Prof. RB. The first draft of the manuscript was written by Dr. SS, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
No funds, grants, or other support was received.
Availability of data and material
The authors declare that they have no conflict of interest.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.
Verbal informed consent was obtained from the participants.
Verbal consent is obtained for publication
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Sourabh Sharma, Email: ni.ude.hbimi@hbaruos .
Ramesh Behl, Email: ude.imi@lhebr .
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- Review article
- Open access
- Published: 30 January 2021
Understanding students’ behavior in online social networks: a systematic literature review
- Maslin Binti Masrom 1 ,
- Abdelsalam H. Busalim ORCID: orcid.org/0000-0001-5826-8593 2 ,
- Hassan Abuhassna 3 &
- Nik Hasnaa Nik Mahmood 1
International Journal of Educational Technology in Higher Education volume 18 , Article number: 6 ( 2021 ) Cite this article
The use of online social networks (OSNs) has increasingly attracted attention from scholars’ in different disciplines. Recently, student behaviors in online social networks have been extensively examined. However, limited efforts have been made to evaluate and systematically review the current research status to provide insights into previous study findings. Accordingly, this study conducted a systematic literature review on student behavior and OSNs to explicate to what extent students behave on these platforms. This study reviewed 104 studies to discuss the research focus and examine trends along with the important theories and research methods utilized. Moreover, the Stimulus-Organism-Response (SOR) model was utilized to classify the factors that influence student behavior. This study’s results demonstrate that the number of studies that address student behaviors on OSNs have recently increased. Moreover, the identified studies focused on five research streams, including academic purpose, cyber victimization, addiction, personality issues, and knowledge sharing behaviors. Most of these studies focused on the use and effect of OSNs on student academic performance. Most importantly, the proposed study framework provides a theoretical basis for further research in this context.
The rapid development of Web 2.0 technologies has caused increased usage of online social networking (OSN) sites among individuals. OSNs such as Facebook are used almost every day by millions of users (Brailovskaia et al. 2020 ). OSNs allow individuals to present themselves via virtual communities, interact with their social networks, and maintain connections with others (Brailovskaia et al. 2020 ). Therefore, the use of OSNs has continually attracted young adults, especially students (Kokkinos and Saripanidis 2017 ; Paul et al. 2012 ). Given the popularity of OSNs and the increased number of students of different ages, many education institutions (e.g., universities) have used them to market their educational programs and to communicate with students (Paul et al. 2012 ). The popularity and ubiquity of OSNs have radically changed education systems and motivated students to engage in the educational process (Lambić 2016 ). The children of the twenty-first century are technology-oriented, and thus their learning style differs from previous generations (Moghavvemi et al. 2017a , b ). Students in this era have alternatives to how and where they spend time to learn. OSNs enable students to share knowledge and seek help from other students. Lim and Richardson ( 2016 ) emphasized that one important advantage of OSNs as an educational tool is to increase connections between classmates, which increases information sharing. Furthermore, the use of OSNs has also opened new communication channels between students and teachers. Previous studies have shown that students strengthened connections with their teachers and instructors using OSNs (e.g., Facebook, and Twitter). Therefore, the characteristics and features of OSNs have caused many students to use them as an educational tool, due to the various facilities provided by OSN platforms, which makes learning more fun to experience (Moghavvemi et al. 2017a ). This has caused many educational institutions to consider Facebook as a medium and as a learning tool for students to acquire knowledge (Ainin et al. 2015 ).
OSNs including Facebook, YouTube, and Twitter have been the most utilized platforms for education purposes (Akçayır and Akçayır 2016 ). For instance, the number of daily active users on Facebook reached 1.73 billion in the first quarter of 2020, with an increase of 11% compared to the previous year (Facebook 2020 ). As of the second quarter of 2020, Facebook has over 2.7 billion active monthly users (Clement 2020 ). Lim and Richardson ( 2016 ) empirically showed that students have positive perceptions toward using OSNs as an educational tool. A review of the literature shows that many studies have investigated student behaviors on these sites, which indicates the significance of the current review in providing an in-depth understanding of student behavior on OSNs. To date, various studies have investigated why students use OSNs and explored different student behaviors on these sites. Although there is an increasing amount of literature on this emerging topic, little research has been devoted to consolidating the current knowledge on OSN student behaviors. Moreover, to utilize the power of OSNs in an education context, it is important to study and understand student behaviors in this setting. However, current research that investigates student behaviors in OSNs is rather fragmented. Thus, it is difficult to derive in-depth and meaningful implications from these studies. Therefore, a systematic review of previous studies is needed to synthesize previous findings, identify gaps that need more research, and provide opportunities for further research. To this end, the purpose of this study is to explore the current literature in order to understand student behaviors in online social networks. Accordingly, a systematic review was conducted in order to collect, analyze, and synthesize current studies on student behaviors in OSNs.
This study drew on the Stimulus-Organism-Response (SOR) model to classify factors and develop a framework for better understanding of student behaviors in the context of OSNs. The S-O-R model suggests that various aspects of the environment (S), incite individual cognitive and affective reactions (O), which in turn derives their behavioral responses (R) (Mehrabian and Russell 1974 ). In order to achieve effective results in a clear and understandable manner, five research questions were proposed as shown below.
What was the research regional context covered in previous studies?
What were the focus and trends of previous studies?
What were the research methods used in previous studies?
What were the major theories adopted in previous studies?
What important factors were studied to understand student usage behaviors in OSNs?
This paper is organized as follows. The second section discusses the concept of online social networks and their definition. The third section describes the review method used to extract, analyze, and synthesize studies on student behaviors. The fourth section provides the result of analyzing the 104 identified primary studies and summarizes their findings based on the research questions. The fifth section provides a discussion on the results based on each research question. The sixth section highlights the limitations associated with this study, and the final section provides a conclusion of the study.
- Online social networks
Since online social networks such as Facebook were introduced last decade, they have attracted millions of users and have become integrated into our daily routines. OSNs provide users with virtual spaces where they can find other people with similar interests to communicate with and share their social activities (Lambić et al. 2016 ). The concept of OSNs is a combination of technology, information, and human interfaces that enable users to create an online community and build a social network of friends (Borrero et al. 2014 ). Kum Tang and Koh ( 2017 ) defined OSNs as “web-based virtual communities where users interact with real-life friends and meet other people with shared interests” . A more detailed and well-cited definition of OSN was introduced by Boyd and Ellison ( 2008 ) who defined OSNs as “web-based services that allow individuals to (1) construct a public or semipublic profile within a bounded system, (2) articulate a list of other users with whom they share a connection, and (3) view and traverse their list of connections and those made by others within the system” . Due to its popularity, many researches have examined the effect of OSNs on different disciplines such as business (Kujur and Singh 2017 ), healthcare (Chung 2014 ; Lin et al. 2016 ; Mano 2014 ), psychology (Pantic 2014 ), and education (Hamid et al. 2016 , 2015 ; Roblyer et al. 2010 ).
The heavy use of OSNs by students has led many studies to examine both positive and negative effects of these sites on students, including the time spent on OSNs usage (Chang and Heo 2014 ; Wohn and Larose 2014 ), engagement in academic activities (Ha et al. 2018 ; Sheeran and Cummings 2018 ), as well as the effect of OSN on students’ academic performance. Lim and Richardson ( 2016 ) stated that the main reasons for students to use OSNs as an educational tool is to increase their interactions and establish connections with classmates. Tower et al. ( 2014 ) found that OSN platforms such as Facebook have the potential to improve student self-efficacy in learning and develop their learning skills to a higher level. Therefore, some education institutions have started to develop their own OSN learning platforms (Tally 2010 ). Mazman and Usluel ( 2010 ) highlighted that using OSNs for educational and instructional contexts is an idea worth developing because students spend a lot of time on these platforms. Yet, the educational activities conducted on OSNs are dependent on the nature of the OSNs used by the students (Benson et al. 2015 ). Moreover, for teaching and learning, instructors have begun using OSNs platforms for several other purposes such as increasing knowledge exchanges and effective learning (Romero-Hall 2017 ). On the other hand, previous studies have raised some challenges of using OSNs for educational purposes. For example, students tend to use OSNs as a social tool for entraining rather than an educational tool (Baran 2010 ; Gettman and Cortijo 2015 ). Moreover, the active use of OSNs on daily basis may develop students’ negative behavior such as addiction and distraction. In this context, Kitsantas et al. ( 2016 ) found that college students in the United States reported some concerns such as the OSNs usage can turn into addictive behavior, distraction, privacy threats, the negative impact on their emotional health, and the inability to complete the tasks on time. Another challenge of using OSNs as educational tools is gender differences. Kim and Yoo ( 2016 ) found some differences between male and female students concerning the negative impact of OSNs, for example, female students are more conserved about issues related to security, and the difficulty of task/work completion. Furthermore, innovation is a key aspect in the education process (Serdyukov 2017 ), however, using OSNs as an educational tool, students could lose creativity due to the easy access to everything using these platforms (Mirabolghasemi et al. 2016 ).
This study employed a Systematic Literature Review (SLR) approach in order to answer the research questions. The SLR approach creates a foundation that advances knowledge and facilitates theory development for a specific topic (Webster and Watson 2002 ). Kitchenham and Charters ( 2007 ) defined SLR as a process of identifying, evaluating, and synthesizing all available research that is related to research questions, area of research, or new phenomenon. This study follows Kitchenhand and Charters’ guidelines (Kitchenham 2004 ), which state that the SLR approach involves three main stages: planning the review, conducting the review, and reporting the review results. There are several motivations for carrying out this systematic review. First, to summarize existing knowledge and evidence on research related to OSNs such as the theories, methods, and factors that influence student behaviors on these platforms. Second, to discover the current research focus and trends in this setting. Third, to propose a framework that classifies the factors that influence student behaviors on OSNs using the S-O-R model. The reasons for using S-O-R model in this study are twofold. First, S-O-R is a crucial theoretical framework to understand individuals’ behavior, and it has been extensively used in previous studies on consumer behavior (Wang and Chang 2013 ; Zhang et al. 2014 ; Zhang and Benyoucef 2016 ), and online users’ behavior (Islam et al. 2018 ; Luqman et al. 2017 ). Second, using the S-O-R model can provide a structured manner to understand the effect of the technological features of OSNs as environmental stimuli on individuals’ behavior (Luqman et al. 2017 ). Therefore, the application of the S-O-R model can provide a guide in the OSNs literature to better understand the potential stimulus and organism factors that drive a student’s behavioral responses in the context of OSNs. The SLR was guided by five research questions (see “ Introduction ” section), which provide an in-depth understanding of the research topic. The rationale and motivation beyond considering these questions are stated in Table 1 .
Stage one: Planning
Before conducting any SLR, it is necessary to clarify the goal and the objectives of the review (Kitchenham and Charters 2007 ). After identifying the review objectives and the research questions, in the planning stage, it is important to design the review protocol that will be used to conduct the review (Kitchenham and Charters 2007 ). Using a clear review protocol will help define criteria for selecting the literature source, database, and search keywords. Review protocol reduce research bias and specifies the research method used to perform a systematic review (Kitchenham and Charters 2007 ). Figure 1 shows the review protocol used for this study.
Stage two: Conducting the review
In this stage relevant literature was collected using a two-stage approach, which was followed by the removal of duplicated articles using Mendeley software. Finally, the researchers applied selection criteria to identify the most relevant articles to the current review. The details of each step of this stage are discussed below:
Literature identification and collection
This study used a two-stage approach (Webster and Watson 2002 ) to identify and collect relevant articles for review. In the first stage, this study conducted a systematic search to identify studies that address student behaviors and the use of online social networks using selected academic databases, including the Web of Science, Wiley Online Library ScienceDirect, Scopus, Emerald, and Springer. The choice of these academic databases is consistent with previous SLR studies (Ahmadi et al. 2018 ; Balaid et al. 2016 ; Busalim and Hussin 2016 ). Derived from the structure of this review and the research questions, these online databases were searched by focusing on title, abstract, and keywords. The search in these databases started in May 2019 using the specific keywords of “students’ behavior”, “online social networking”, “social networking sites”, and “Facebook”. This study performed several searches in each database using Boolean logic operators (i.e., AND and OR) to obtain a large number of published studies related to the review topic.
The results from this stage were 164 studies published between 2010 and 2018. In the second stage, important peer-reviewed journals were checked to ensure that all relevant articles were collected. We used the same keywords to search on information systems and education journals such as Computers in Human Behavior, International Journal of Information Management, Computers and Education, and Education and Information Technologies. These journals among the top peer-reviewed journals that publish topics related to students' behavior, education technologies, and OSNs. The result from both stages was 188 studies related to student behaviors in OSN. Table 2 presents the journals with more than two articles published in these areas.
Following the identification of these studies, and after deleting duplicated studies, this study examined title, abstract, or the content of each study using three selection criteria: (1) a focus on student behavior; (2) an examination of the context of online social networks; (3) and a qualification as an empirical study. After applying these criteria, a total of 96 studies remained as primary studies for review. We further conducted a forward manual search on a reference list for the identified primary studies, through which an additional 8 studies were identified. A total of 104 studies were collected. As depicted in Fig. 2 , the frequency of published articles related to student behaviors in online social networks has gradually increased since 2010. In this regard, the highest number of articles were published in 2017. We can see that from 2010 to 2012 the number of published articles was relatively low and significant growth in published articles was seen from 2013 to 2017. This increase reveals that studying the behavior of students on different OSN platforms is increasingly attractive to researchers.
Timeline of publication
For further analysis, this study summarized the key topics covered during the review timeline. Figure 3 visualizes the development of OSNs studies over the years. Studies in the first three years (2010–2012) revolved around the use of OSNs by students and the benefits of using these platforms for educational purposes. The studies conducted between 2013 and 2015 mostly focused on the effect of using OSNs on student academic performance and achievement. In addition, in the same period, several studies examined important psychological issues associated with the use of OSNs such as anxiety, stress, and depression. In the years 2016 to 2018, OSNs studies were expanded to include cyber victimization behavior, OSN addiction behavior such as Facebook addiction, and how OSNs provide a collaborative platform that enables students to share information with their colleagues.
Evolution of OSNs studies over the years
To analyze the identified studies, this study guided its review using four research questions. Using research questions allows the researcher to synthesize findings from previous studies (Chan et al. 2017 ). The following subsection provides a detailed discussion of each of these research questions.
RQ1: What was the research regional context covered in previous studies?
As shown in Fig. 3 , most primary studies were conducted in the United States (n = 37), followed by Asia (n = 21) and Europe (n = 15). Relatively few studies were conducted in Australia, Africa, and the Middle East (n = 6 each), and only five studies were conducted in more than one country. Most of these empirical studies used university or college students to examine and validate the research models. Furthermore, many of these studies examined student behavior by considering Facebook as an online social network (n = 58) and a few studies examined student behavior on Microblogging platforms like Twitter (n = 7). The rest of the studies used multiple online social networks such as Instagram, YouTube, and Moodle (n = 31).
As shown in Fig. 4 , most of the reviewed studies are conducted in the United States (US). Furthermore, these studies considered Facebook as the main OSN platform. However, the focus on examining the usage behavior of Facebook in Western countries, particularly the US, is one of the challenges of Facebook research, because Facebook is used in many countries with 80% of its users are outside of the US (Peters et al. 2015 ).
Distribution of published studies by region
RQ2: What were the focus and trends of previous studies?
The results indicate that the identified primary studies for student behaviors on online social networks covered a wide spectrum of different research contexts. Further examination shows that there are five research streams in the literature.
The first research stream focused on using OSNs for academic purposes. The educational usage of OSNs relies on their purpose of use. OSNs can improve student engagement in a course and provide them with a sense of connection to their colleagues (Lambić 2016 ). However, the use of OSNs by students can affect their education as students can easily shift from using OSNs for educational to entertainment purposes. Thus, many studies under this stream focus on the effect of OSNs use on student academic performance. For instance, Lambić ( 2016 ) examined the effect of frequent Facebook use on the academic performance of university students. The results showed that students using Facebook as an educational tool to facilitate knowledge sharing and discussion positively impacted academic performance. Consistent with this result, Ainin et al. ( 2015 ) found that data from 1165 university students revealed a positive relationship between Facebook use and student academic performance. On the other hand, Paul et al. ( 2012 ) found that time spent on OSNs negative impacted student academic behavior. Moreover, the results statistically highlight that increased student attention spans resulted in increased time spent on OSNs, which eventually results in a negatively effect on academic performance. The results from Karpinski et al. ( 2013 ) showed that the effect of OSNs usage on student academic performance could differ from one country to another.
In summary, previous studies on the relationship between OSN use and academic performance show mixed results. From the reviewed studies, there were disparate results due to a few reasons. For example, recent studies found that multitasking plays an important role in determining the relationship between OSN usage and student academic performance. Karpinski et al. ( 2013 ) found a negative relationship between using social network sites (SNSs) and Grade Point Average (GPA) that was moderated by multitasking. Moreover, results from Junco ( 2015 ), illustrated that besides multitasking, student class rank is another determinant of the relationship between OSN platforms like Facebook and academic performance. The results revealed that senior students spent significantly less time on Facebook while doing schoolwork than freshman and sophomore students.
The second research stream is related to cyber victimization. Studies in this stream focused on negative interactions on OSNs like Facebook, which is the main platform where cyber victimization occurs (Kokkinos and Saripanidis 2017 ). Moreover, most studies in this stream examined the cyberbullying concept on OSNs. Cyberbullying is defined as “any behavior performed through electronic media by individuals or groups of individuals that repeatedly communicates hostile or aggressive messages intended to inflict harm or discomfort on others” (Tokunaga 2010 , p. 278). For instance, Gahagan et al. ( 2016 ) investigated the experiences of college students with cyberbullying on SNSs, and the results showed that 46% of the tested sample witnessed someone who had been bullied through the use of SNSs. Walker et al. ( 2011 ) conducted an exploratory study among undergraduate students to investigate their cyberbullying experiences. The results of the study highlighted that the majority of respondents knew someone who had been bullied on SNSs (Benson et al. 2015 ).
The third research stream focused on student addiction to OSNs use. Recent research has shown that excessive OSN use can lead to addictive behavior among students (Shettar et al. 2017 ). In this stream, Facebook was the main addictive ONS platform that was investigated (Shettar et al. 2017 ; Hong and Chiu 2016 ; Koc and Gulyagci 2013 ). Facebook addiction is defined as an excessive attachment to Facebook that interferes with daily activities and interpersonal relationships (Elphinston and Noller 2011 ). According to Andreassen et al. ( 2012 ), Facebook addiction has six general characteristics including salience, tolerance, mood modification, withdrawal, conflict, and relapse. As university students frequently have high levels of stress due to various commitments, such as assignment deadlines, exams, and high pressure to perform, they tend to use Facebook for mood modification (Brailovskaia and Margraf 2017 ; Brailovskaia et al. 2018 ). On further analysis, it was noticed that Facebook addiction among students was associated with other factors such as loneliness (Shettar et al. 2017 ), personality traits (i.e., openness agreeableness, conscientiousness, emotional stability, and extraversion) (Błachnio et al. 2017 ; Tang et al. 2016 ), and physical activities (Brailovskaia et al. 2018 ). Studies have examined student addiction behavior on different OSNs platforms. For instance, Ndasauka et al. ( 2016 ), empirically examined excessive Twitter use among college students. Kum Tang and Koh ( 2017 ) investigated the prevalence of different addiction behaviors (i.e., food and shopping addiction) and effective disorders among college students. In addition, a study by Chae and Kim (Chae et al. 2017 ) examined psychosocial differences in ONS addiction between female and male students. The results of the study showed that female students had a higher tendency towards OSNs addiction than male students.
The fourth stream of research highlighted in this review focused on student personality issues such as self-disclosure, stress, depression, loneliness, and self-presentation. For instance, Chen ( 2017 ) investigated the antecedents that predict positive student self-disclosure on SNSs. Tandoc et al. ( 2015 ) used social rank theory and Facebook envy to test the depression scale between college students. Skues et al. ( 2012 ) examined the relationship between three traits in the Big Five Traits model (neuroticism, extraversion, and openness) and student Facebook usage. Chang and Heo ( 2014 ) investigated the factors that explain the disclosure of a student’s personal information on Facebook.
The fifth reviewed research stream focused on student knowledge sharing behavior. For instance, Kim et al. ( 2015 ) identified the personal factors (self-efficacy) and environmental factors (strength of social ties and size of social networks) that affect information sharing behavior amongst university students. Eid and Al-Jabri ( 2016 ) examined the effect of various SNS characteristics (file sharing, chatting and online discussion, content creation, and enjoyment and entertainment) on knowledge sharing and student learning performance. Moghavvemi et al. ( 2017a , b ) examined the relationship between enjoyment, perceived status, outcome expectations, perceived benefits, and knowledge sharing behavior between students on Facebook. Figure 5 provides a mind map that shows an overview of the research focus and trends found in previous studies.
Reviewed studies research focus and trends
RQ3: What were the research methods used in previous studies?
As presented in Fig. 6 , previous studies used several research methods to examine student behavior on online social networks. Surveys were the method used most frequently in primary studies to understand the different types of determinants that effect student behaviors on online social networks, followed by the experiment method. Studies used the experiment method to examine the effect of online social networks content and features on student behavior, For example, Corbitt-Hall et al. ( 2016 ) had randomly assigned students to interact with simulated Facebook content that reflected various suicide risk levels. Singh ( 2017 ) used data mining techniques to collect student interaction data from different social networking sites such as Facebook and Twitter to classify student academic activities on these platforms. Studies that investigated student intentions, perceptions, and attitudes towards OSNs used survey data. For instance, Doleck et al. ( 2017 ) distributed an online survey to college students who used Facebook and found that perceived usefulness, attitude, and self-expression were influential factors towards the use of online social networks. Moreover, Ndasauka et al. ( 2016 ) used the survey method to assess the excessive use of Twitter among college students.
Research method distribution
RQ4: What were the major theories adopted in previous studies?
The results from the SLR show that previous studies used several theories to understand student behavior in online social networks. Table 3 depicts the theories used in these studies, with Use and Gratification Theory (UGT) being the most popular theory use to understand students' behaviors (Asiedu and Badu 2018 ; Chang and Heo 2014 ; Cheung et al. 2011 ; Hossain and Veenstra 2013 ). Furthermore, the social influence theory and the Big Five Traits model were applied in at least five studies each. The theoretical insights into student behaviors on online social networks provided by these theories are listed below:
Motivation aspect: since the advent of online social networks, many studies have been conducted to understand what motivates students to use online social networks. Theories such as UGT have been widely used to understand this issue. For example, Hossain and Veenstra ( 2013 ) conducted an empirical study to investigate what drives university students in the United States of America to use Social Networking Sites (SNSs) using the theoretical foundation of UGT. The study found that the geographic or physical displacement of students affects the use and gratification of SNSs. Zheng Wang et al. ( 2012a , b ) explained that students are motivated to use social media by their cognitive, emotional, social, and habitual needs as well as that all four categories significantly drive students to use social media.
Social-related aspect: Social theories such as Social Influence Theory, Social Learning Theory, and Social Capital Theory have also been used in several previous studies. Social Influence Theory determines what individual behaviors or opinions are affected by others. Venkatesh, Morris, Davis, and Davis (2003) defined social influence as “the degree to which an individual perceives that important others believe he or she should use a new system” . Cheung et al. ( 2011 ) applied Social Influence Theory to examine the effect of social influence factors (subjective norms, group norms, and social identity) on intentions to use online social networks. The empirical results from 182 students revealed that only Group Norms had a significant effect on student intentions to use OSNs. Other studies attempted to empirically examine the effect of other social theories. For instance, Liu and Brown ( 2014 ) adapted Social Capital Theory to investigate whether college students' self-disclosure on SNSs directly affected their social capital. Park et al. ( 2014a , b ) investigated the effect of using SNSs on university student learning outcomes using social learning theory.
Behavioral aspect: This study have noticed that the Theory of Planned Behavior (TPB), Theory of Reasoned Action (TRA), Technology Acceptance Model (TAM), Unified Theory of Acceptance, and Use of Technology (UTAUT) were also utilized as a theoretical foundation in a number of primary studies. These theories have been widely applied in the information systems (IS) field to provide insights into information technology adoption among individuals (Zhang and Benyoucef 2016 ). In the context of online social networks, there were empirical studies that adapted these theories to understand student usage behaviors towards online social networks such as Facebook. For example, Doleck et al. ( 2017 ) applied TAM to investigate college student usage intentions towards SNSs. Chang and Chen ( 2014 ) applied TRA and TPB to investigate why college students share their location on Facebook. In addition, a recent study used UTAUT to examine student perceptions towards using Facebook as an e-learning platform (Moghavvemi et al. 2017a , b ).
RQ5: What important factors were studied to understand student usage behaviors in OSNs?
Throughout the SLR, this study has been able to identify the potential factors that influence student behaviors in online social networks. Furthermore, to synthesize these factors and provide a comprehensive overview, this study proposed a framework based on the Stimulus-Organism-Response (S-O-R) model. The S-O-R model was developed in environmental psychology by Mehrabian and Russell ( 1974 ). According to Mehrabian and Russell ( 1974 ), environmental cues act as stimuli that can affect an individual’s internal cognitive and affective states, which subsequently influences their behavioral responses. To do so, this study extracted all the factors examined in 104 identified primary studies and classified them into three key concepts: stimulus, organism, and response. The details on the important factors of each component are presented below.
Online social networks stimulus
Stimulus factors are triggers that encourage or prompt students to use OSNs. Based on the SLR results, there are three stimulus dimensions: social stimulus, personal stimulus, and OSN characteristics. Social stimuli are cues embedded in the OSN that drive students to use these platforms. As shown in Fig. 7 , this study has identified six social stimulus factors including social support, social presence, social communication, social enhancement, social network size, and strength of social ties. Previous studies found that social aspects are a potential driver of student usage of OSNs. For instance, Kim et al. ( 2011 ) explored the motivation behind college student use of OSNs and found that seeking social support is one of the primary usage triggers. Lim and Richardson ( 2016 ) stated that using OSNs as educational tools will increase interactions and establish connections between students, which will enhance their social presence. Consistent with this, Cheung et al. ( 2011 ) found that social presence and social enhancement both have a positive effect on student use of OSNs. Other studies have tested the effect of other social factors such as social communication (Lee 2015 ), social network size, and strength of social ties (Chang and Heo 2014 ; Kim et al. 2015 ). Personal stimuli are student motivational factors associated with a specific state that affects their behavioral response. As depicted in Table 4 , researchers have tested different personal student needs that stimulate OSN usage. For instance, Zheng Wang et al. ( 2012a , b ) examined the emotional, social, and cognitive needs that drive students to use OSNs. Moghavvemi et al. ( 2017a , b ) empirically showed that students with a hedonic motivation were willing to use Facebook as an e-learning tool.
Classification framework for student behaviors in online social networks
OSN website characteristics are stimuli related to the cues implanted in an OSN website. In the reviewed studies, it was found that the most well studied OSN characteristics are usefulness and ease of use. Ease of use refers to student perceptions on the extent to which OSN are easy to use whereas usefulness refers to the degree that students believed that using OSN was helpful in enhancing their task performance (Arteaga Sánchez et al. 2014 ). Although student behaviors in OSNs have been widely studied, few studies have focused on OSN characteristics that stimulate student behaviors. For example, Eid and Al-Jabri ( 2016 ) examined the effect of OSN characteristics such as chatting, discussion, content creation, and file sharing. The results showed that file sharing, chatting, and discussion had a positive impact on student knowledge sharing behavior. In summary, Table 4 shows the stimulus factors identified in previous studies and their classification.
Online social networks organisms
Organism in this study’s framework refers to student internal evaluations towards using OSNs. There are four types of organism factors that have been highlighted in the literature. These types include personality traits, values, social, and cognitive reactions. Student personality traits influence the use of OSNs (Skues et al. 2012 ). As shown in Table 4 , self-esteem and self-disclosure were the most examined personality traits associated with student OSN behaviors. Self-esteem refers to an individual’s emotional evaluation of their own worth (Chen 2017 ). For example, Wang et al. ( 2012a , b ) examined the effect of the Big Five personality traits on student use of specific OSN features. The results found that students with high self-esteem were more likely to comment on other student profiles. Self-disclosure refers to the process by which individuals share their feelings, thoughts, information, and experiences with others (Dindia 1995 ). Previous studies have examined student self-disclosure in OSNs to explore information disclosure behavior (Chang and Heo 2014 ), location disclosure (Chang and Chen 2014 ), self-disclosure, and mental health (Zhang 2017 ). The second type of organism factors is value. It has been noticed that there are several value related factors that affect student internal organisms in OSNs. As shown in Table 4 , entertainment and enjoyment factors were the most common value examined in previous studies. Enjoyment is one of the potential drivers of student OSN use (Nawi et al. 2017 ). Eid and Al-Jabri ( 2016 ) found that YouTube is the most dominant OSN platform used by students for enjoyment and entertainment. Moreover, enjoyment and entertainment directly affected student learning performance.
Social organism refers to the internal social behavior of students that affect their use of OSNs. Students interact with OSN platforms when they experience positive social reactions. Previous studies have examined some social organism factors including relationship with faculty members, engagement, leisure activities, social skills, and chatting and discussion. The fourth type of organism factors is cognitive reactions. Parboteeah et al. ( 2009 ) defined cognitive reaction as “the mental process that occurs in an individual’s mind when he or she interacts with a stimulus” . The positive or negative cognitive reaction of students influences their responses towards OSNs. Table 5 presents the most common organism reactions that effect student use of OSNs.
Online social networks response
In this study’s framework, response refers to student reactions to OSNs stimuli and organisms. As shown in Table 5 , academic related behavior and negative behavior are the most common student responses towards OSNs. Studying the effect of OSN usage on student academic performance has been the most common research topic (Lambić 2016 ; Paul et al. 2012 ; Wohn and Larose 2014 ). On the other hand, other studies have examined the negative behavior of students during their usage of ONS, mostly towards ONS addiction (Hong and Chiu 2016 ; Shettar et al. 2017 ) or cyberbullying (Chen 2017 ; Gahagan et al. 2016 ). Table 6 summarizes student responses associated with OSNs use in previous studies.
Discussion and implications
The last two decades have witnessed a dramatic growth in the number of online social networks used among the youth generation. Examining student behaviors on OSN platforms has increasingly attracted scholars. However, there has been little effort to summarize and synthesize these findings. In this review study, a systematic literature review was conducted to synthesize previous research on student behaviors in OSNs to consolidate the factors that influence student behaviors into a classification framework using the S-O-R model. A total of 104 journal articles were identified through a rigorous and systematic search procedure. The collected studies from the literature show an increasing interest in the area ever since 2010. In line with the research questions, our analysis offers insightful results of the research landscape in terms of research regional context, studies focus trends, methodological trends, factors, and theories leveraged. Using the S-O-R model, we synthesized the reviewed studies highlighting the different stimuli, organism, and response factors. We synthesize and classify these factors into social stimuli, personal stimuli, and OSN characteristics, organism factors; personality traits, value, social, and cognitive reaction, and response; academic related behavior, negative behavior, and other responses.
Research regional perspective
The first research question focused on research regional context. The review revealed that most of the studies were conducted in the US followed by European countries, with the majority focusing on Facebook. The results show that the large majority of the studies were based on a single country. This indicates a sustainable research gap in examining the multi-cultural factors in multiple countries. As OSN is a common phenomenon across many counties, considering the culture and background differences can play an essential role in understanding students’ behavior on these platforms. For example, Ifinedo ( 2016 ) collected data from four countries in America (i.e., USA, Canada, Argentina, and Mexico) to understand students’ pervasive adoption of SNSs. The results from the study revealed that the individualism–collectivism culture factor has a positive impact on students' pervasive adoption behavior of SNSs, and the result reported high level of engagement from students who have more individualistic cultures. In the same manner, Kim et al. ( 2011 ) found some cultural differences in use of the SNSs platforms between Korean and US students. For example, considering the social nature of SNSs, the study found that Korean students rely more on online social relationships to obtain social support, where US students use SNSs to seek entertainment. Furthermore, Karpinski et al. ( 2013 ) empirically found significant differences between US and European students in terms of the moderating effect of multitasking on the relationship between SNS use and academic achievement of students. The confirms that culture issues may vary from one country to another, which consequently effect students’ behavior to use OSNs (Kim et al. 2011 ).
Studies focus and trends
The second research question of this review focused on undersigning the topics and trends that have been discussed in extant studies. The review revealed evidence of five categories of research streams based on the research focus and trend. As shown in Fig. 5 , most of the reviewed studies are in the first stream, which is using OSNs for academic purposes. Moreover, the trend of these studies in this stream focus on examining the effect of using OSNs on students’ academic performance and investigating the use of OSNs for educational purposes. However, a number of other trends are noteworthy. First, as cyber victimization is a relatively new concept, most of the studies provide rigorous effort in exporting the concept, and the reasons beyond its existence among students; however, we have noticed that no effort has been made to investigate the consequences of this negative behavior on students’ academic performance, social life, and communication. Second, we identified only two studies that examined the differences between undergraduate and postgraduate students in terms of cyber victimization. Therefore, there are many avenues for further research to untangle the demographic, education level, and cultural differences in this context. Third, our analysis revealed that Facebook was the most studied ONS platform in terms of addiction behavior, however, over the last ten years, the rapid growth of using image-based ONS such as Instagram and Pinterest has attracted many students (Alhabash and Ma 2017 ). For example, Instagram represents the fastest growing OSNs among young adult users age between 18 and 29 years old (Alhabash and Ma 2017 ). The overwhelming majority of the studies focus on Facebook users, and very few studies have examined excessive Instagram use (Kırcaburun and Griffiths 2018 ; Ponnusamy et al. 2020 ). Although OSNs have many similar features, each platform has unique features and a different structure. These differences in OSNs platforms urge further research to investigate and understand the factors related to excessive and addiction use by students (Kircaburun and Griffiths 2018 ). Therefore, based on the current research gaps, future research agenda including three topics/trend need to be considered. We have developed research questions for each topic as a direction for any further research as shown in Table 7 .
Theories and research methods
The third and fourth research questions focused on understanding the trends in terms of research methods and theories leveraged in existing studies. In relation to the third research question, the review highlighted evidence of the four research methods (i.e., survey, experiment, focus group/interview, and mix method) with a heavy focus on using a quantitative method with the majority of studies conducting survey. This may call for utilizing a variety of other research methods and research design to have more in-depth understanding of students’ behavior on OSN. For example, we noticed that few studies leveraged qualitative methods such as interviews and focus groups (n = 5). In addition, using mix method may derive more results and answer research questions that other methods cannot answer (Tashakkori and Teddlie 2003 ). Experimental methods have been used sparingly (n = 10), this may trigger an opportunity for more experimental research to test different strategies that can be used by education institutions to leverage the potential of OSN platforms in the education process. Moreover, considering that students’ attitude and behavior will change over time, applying longitudinal research method may offer opportunities to explore students’ attitude and behavior patterns over time.
The fourth research question focused on understanding the theoretical underpinnings of the reviewed studies. The analysis revealed two important insights; (1) a substantial number of the reviewed studies do not explicitly use an applied theory, and (2) out of the 34 studies that used theory, nine studies applied UGT to understand the motivation beyond using the OSN. Our findings categorized these theories under three aspects; motivational, social, and behavioral. While each aspect and theory offers useful lenses in this context, there is a lack of leveraging other theories in the extant literature. This motivates researchers to underpin their studies in theories that provide more insights into these three aspects. For example, majority of the studies have applied UGT to understand students’ motivate for using OSNs. However, using other motivational theories could uncover different factors that influence students' motivation for using OSNs. For example, self-determination theory (SDT) focuses on the extent to which individual’s behavior is self-motivated and determined. According to Ryan and Deci ( 2000 ), magnitude and types both shape individuals’ extrinsic motivation. The extrinsic motivation is a spectrum and depends on the level of self-determination (Wang et al. 2019 ). Therefore, the continuum aspect proposed by SDT can provide in-depth understanding of the extrinsic motivation. Wang et al. ( 2016 ) suggested that applying SDT can play a key role in understanding SNSs user satisfaction.
Another theoretical perspective that is worth further exploration relates to the psychological aspect. Our review results highlighted that a considerable number of studies focused on an important issue arising from the daily use of OSNs, such as excessive use/addiction (Koc and Gulyagci 2013 ; Shettar et al. 2017 ), Previous studies have investigated the behavior aspect beyond these issues, however, understanding the psychological aspect of Facebook addiction is worth further investigation. Ryan et al. ( 2014 ) reviewed Facebook addiction related studies and found that Facebook addiction is also linked to psychological factors such as depression and anxiety.
Factors that influence students behavior: S-O-R Framework
The fifth research question focused on determining the factors studies in the extant literature. The review analysis showed that stimuli factors included social, personal, and OSNs website stimuli. However, different types of stimuli have received less attention than other stimuli. Most studies leveraged the social and students’ personal stimuli. Furthermore, few studies conceptualized the OSNs websites characterises in terms of students beliefs about the effect of OSNs features and functions (e.g., perceived ease of use, user friendly) on students stimuli; it would be significant to develop a typology of the OSNs websites stimuli and systematically examine their effect on students’ attitude and behavior. We recommend applying different theories (as mentioned in Theories and research methods section) as an initial step to further identify stimuli factors. The results also highlight that cognitive reaction plays an essential role in the organism dimension. When students encounter stimuli, their internal evaluation is dominated by emotions. Therefore, the cognitive process takes place between students’ usage behavior and their responses (e.g., effort expectancy). In this review, we reported few studies that examined the effect of the cognitive reaction of students.
Response factors encompass students’ reaction to OSNs platforms stimuli and organism. Our review revealed an unsurprisingly dominant focus on the academic related behavior such as academic performance. While it is important to examine the effect of various stimuli and organism factors on academic related behavior and OSNs negative behavior, the psychological aspect beyond OSNs negative behavior is equallty important.
Similar to other systematic review studies, this study has some limitations. The findings of our review are constrained by only empirical studies (journal articles) that meet the inclusion criteria. For instance, we only used the articles that explicitly examined students’ behavior in OSNs. Moreover, other different types of studies such as conference proceedings are not included in our primary studies. Further research efforts can gain additional knowledge and understanding from practitioner articles, books and, white papers. Our findings offer a comprehensive conceptual framework to understand students’ behavior in OSNs; future studies are recommended to perform a quantitative meta-analysis to this framework and test the relative effect of different stimuli factors.
The use of OSNs has become a daily habit among young adults and adolescents these days (Brailovskaia et al. 2020 ). In this review, we used a rigorous systematic review process and identified 104 studies related to students’ behavior in OSNs. We systematically reviewed these studies and provide an overview of the current state of this topic by uncovering the research context, research focus, theories, and research method. More importantly, we proposed a classification framework based on S-O-R model to consolidate the factors that influence students in online social networks. These factors were classified under different dimensions in each category of the S-O-R model; stimuli (Social Stimulus, Personal Stimulus, and OSN Characteristics), organism (Personality traits, value, social, Cognitive reaction), and students’ responses (academic-related behavior, negative behavior, and other responses). This framework provides the researchers with a classification of the factors that have been used in previous studies which can motivate further research on the factors that need more empirical examination (e.g., OSN characteristics).
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This paper is supported by Fundamental Research Grant Scheme (FRGS) (Vote No. R.K130000.7840.4F245), and UTM Razak School of Engineering and Advanced Technology research grant or DPUTMRAZAK (Vote No. R.K13000.7740.4J313).
Authors and affiliations.
Razak Faculty of Technology and Informatics, Universiti Teknologi Malaysia, 54100, Kuala Lumpur, Malaysia
Maslin Binti Masrom & Nik Hasnaa Nik Mahmood
Irish Institute of Digital Business, DCU Business School, Dublin City University, Dublin 9, Ireland
Abdelsalam H. Busalim
Faculty of Social Sciences & Humanities, School of Education, Universiti Teknologi Malaysia, UTM, 81310, Skudai, Johor, Malaysia
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The corresponding author worked in writing the paper, all authors worked collaboratively to write the literature review and discussion. All authors read and approved the final manuscript.
Correspondence to Abdelsalam H. Busalim .
This paper is an original work, this paper conducted a systematic literature review of students’ behavior and OSNs studies to explicate to what extent students behave on these platforms.
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Masrom, M.B., Busalim, A.H., Abuhassna, H. et al. Understanding students’ behavior in online social networks: a systematic literature review. Int J Educ Technol High Educ 18 , 6 (2021). https://doi.org/10.1186/s41239-021-00240-7
Received : 16 July 2020
Accepted : 13 January 2021
Published : 30 January 2021
DOI : https://doi.org/10.1186/s41239-021-00240-7
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- Students’ behavior
- Social media
- Systematic review
- Stimulus-organism-response model