12/2/2015

College students’ academic motivation, media engagement and fear of missing out
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Computers in Human Behavior
Volume 49, August 2015, Pages 111–119

107578||

College students’ academic motivation, media engagement and fear of missing out
Dorit Alt Show more doi:10.1016/j.chb.2015.02.057 Highlights
• Possible links between FoMO, social media engagement, and three motivational constructs were examined.
• A new scale was designed to measure the extent to which students used social media tools in the classroom.
• The links between social media engagement and motivational factors were mediated by FoMO.

Abstract
The concerns about the consequences of mental problems related to use of social media among university students have recently raised consciousness about a relatively new phenomenon termed Fear of Missing Out (FoMO). Drawing on the self­determination theory and on the assumption that low levels of basic need satisfaction may relate to
FoMO and social media engagement, the aim of the present research was to examine for the first time possible links between FoMO, social media engagement, and three motivational constructs: Intrinsic, extrinsic and amotivation for learning. Data were gathered from 296 undergraduate students by using the following scales: Social Media
Engagement (SME), Fear of Missing Out (FoMOs) and Academic Motivation. The SME is a new scale, specifically designed for this study to measure the extent to which students used social media in the classroom. This scale includes three categories: Social engagement, news information engagement and commercial information engagement.
Path analysis results indicated that the positive links between social media engagement and two motivational factors: Extrinsic and amotivation for learning are more likely to be mediated by FoMO. Interpretation of these results, their congruence within the context of the theoretical frameworks and practical implications are discussed.

Keywords
Fear of missing out; Social media engagement; Self­determination theory; Academic motivation; Higher education

1. Introduction
Students attending colleges today, known as the ‘Millennials’ (Jonas­Dwyer & Pospisil,
2004), are heavy users of social media tools relative to the general population, and use them extensively for communication with peers, including other students in their courses http://www.sciencedirect.com.ezaccess.library.uitm.edu.my/science/article/pii/S0747563215001788?np=y 1/32

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College students’ academic motivation, media engagement and fear of missing out

(Ophus and Abbitt, 2009 and Subrahmanyam et al., 2008). These technologies might play a key role in keeping college students connected to family and friends to obtain social support (Gemmill & Peterson, 2006). However, extensive social media use could also negatively affect psychological outcomes, such as well­being (Alabi, 2013 and Alavi et al., 2011). These concerns about the consequences of mental problems related to use of social media among university students have recently raised consciousness about a relatively new phenomenon termed Fear of Missing Out, popularly referred to as FoMO.
This phenomenon has been defined as a “pervasive apprehension that others might be having rewarding experiences from which one is absent, FoMO is characterized by the desire to stay continually connected with what others are doing” (Przybylski, Murayama,
DeHaan, & Gladwell, 2013, p. 1841).
Drawing on the self­determination theory (SDT; Deci and Ryan, 1985 and Deci and
Ryan, 2008), Przybylski et al. (2013) suggest that FoMO could serve as a mediator linking deficits in psychological needs to social media engagement. Their study showed that FoMO plays an essential role in the explanation of social media engagement over and above several individual factors, such as levels of need satisfaction. Based on this motivation­based perspective, the current study aims to further explore FoMO and its set of connections to Millennials’ social media engagements in higher education settings.
Motivation is considered to be a significant psychological construct in the learning process, and highly connected to academic achievement and persistence in college
(Donche et al., 2014, Linnenbrink and Pintrich, 2002 and Ratelle et al., 2007), therefore seems as a useful perspective for framing an empirically based understanding of FoMO.
The current study aims to assess this psychological construct’s connections to college students’ social media engagement during lessons, mediated by FoMO, hence enables to delve further into the newly defined phenomenon of FoMO by investigating its correlates with learning motivations.
The current work represents a twofold effort. First, from a methodological point of view and with the dearth of empirically­based assessment instruments, a new scale, designed to measure features of social media activities in higher education settings, will be constructed and validated. Moreover, Przybylski et al.’s (2013) single­factor scale will be adapted to include different facets of FoMO, corresponding to the different social media utilities suggested by theory. Thus, in contrast to previous work, the current study could point to specific elements of FoMO and social media engagements, which may be connected to learning motivations. These efforts might allow for the examination of more components or dimensions based on theoretical considerations than have been assessed thus far.
Second, with relation to college students’ learning processes, this study could illustrate the role of motivational constructs in explaining FoMO and social media engagement, when the latter is not harnessed for pedagogical purposes. This potentially new avenue of research might encourage a future discussion related to Millennials’ engagement in current higher education learning environments, and to the investigation of new instructional approaches incorporating social media usages into current pedagogical applications. 2. Theoretical framework
2.1. Psychological correlates of social media engagement
Social media provides a platform for active communication between friends and an access to new information through a diverse set of acquaintances (Burke, Marlow, &
Lento, 2010). Lankshear and Knobel (2011) describe social media as new ways of participating and communicating that rely on collaboration, remixed texts, and self­ publishing. Social media utilities afford easy access to real­time information about the activities, events, and conversations happening across diverse social networks
(Przybylski et al., 2013). These utilities enable users to articulate a network of connections of people with whom they wish to share access to diverse forms of content, such as profile information, news, or status updates (Steinfield, Ellison, Lampe, & Vitak, http://www.sciencedirect.com.ezaccess.library.uitm.edu.my/science/article/pii/S0747563215001788?np=y 2/32

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College students’ academic motivation, media engagement and fear of missing out

2013). In the field of marketing, the emergence of Internet­based social media has made it possible for individuals to communicate with other people about products and the companies that provide them (Kietzmann et al., 2011 and Mangold and Faulds, 2009).
Social media has also dramatically reduced the cost to produce, distribute, and access diverse news information. With the rise of social media sites, such as Facebook and
Twitter, individuals can share their favorite stories with hundreds of their contacts.
According to Mitchell and Guskin’s (2013) report, nearly one­in­ten U.S. adults (8%) get news through Twitter and 30% of Americans get news on Facebook.
Previous research on social media has been mainly focused on the influence of technological tools for seeking social connections on attitudes and behaviors that enhance individuals’ social capital (Acquisti and Gross, 2006, Ellison et al., 2007,
Putnam, 2000 and Steinfield et al., 2013). Several studies have examined the underlying mechanisms through which social capital benefits are generated by the use of social media. These studies have indicated several advantages of social tools like Facebook and Twitter for the general population. For instance, use of these sites has been associated with greater levels of emotional support from close friends (Putnam, 2000).
Steinfield et al. (2013) maintain that these social media utilities have become important for managing relationships with a large network of people who provide social support and serve as conduits for useful information. Other studies show that young people are motivated to join social media sites to keep strong ties with friends and to strengthen ties with new acquaintances (Acquisti and Gross, 2006 and Ellison et al., 2007). In a similar route, Steinfield, Ellison, and Lampe (2008) found that the intensity of Facebook use strongly predicted higher levels of social capital outcomes. Social networks could also enable individuals to develop norms of trust and reciprocity, which are necessary for successful engagement in collective activities (Valenzuela, Park, & Kee, 2009).
While the aforementioned studies reveal positive associations between online social network use and well­being, others suggest the opposite. For instance, Chou and Edge
(2012) have examined the impact of using Facebook on undergraduate students’ perceptions of others’ lives. Their study indicated that those who have used Facebook longer, agreed more that others were happier and had better lives, and agreed less that life is fair; furthermore, students who included more people whom they did not personally know as their Facebook ‘friends’ agreed more that others had better lives. Kross et al.’s
(2013) study indicated that Facebook use could predict declines in two components of subjective wellbeing: How people feel moment to moment and how satisfied they are with their lives.
2.2. FoMO and social media use in college
The generation of students attending colleges today is known as the ‘Millennials’. The characteristics typically attributed to millennial students are an information technology mindset and a highly developed skill in multitasking. Millennials are described as having a focus on social interaction and connectedness with friends, family and colleagues by using SMS, mobile phones, chat­rooms and email while they simultaneously play computer games, listen to music and watch TV (McMahon & Pospisil, 2005). Gemmill and Peterson (2006) posit that on the up side, these technologies might play a significant role in keeping college students connected to family and friends to obtain social support, as a buffer to “excessive” levels of stress they experience as they grapple with a host of academic, personal, and social pressures. On the down side, their study on college students indicated that technology may also disrupt and occupy the time of a college student, and that could enhance higher levels of perceived stress. Others suggest that social media could also afford an outlet for addictive behaviors (Alabi, 2013), or psychiatric symptoms, such as sensitivity, depression and anxiety (Alavi et al., 2011).
2.3. Psychological correlates of FoMO
Whereas the above­surveyed studies have focused on the impact of social media use on psychological outcomes, such as well­being, a recent study (Przybylski et al., 2013) examined possible potential personal predictors of social media engagement, in http://www.sciencedirect.com.ezaccess.library.uitm.edu.my/science/article/pii/S0747563215001788?np=y 3/32

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College students’ academic motivation, media engagement and fear of missing out

particular aspects of deficits in psychological need satisfactions. Drawing on the self­ determination theory (SDT; Deci and Ryan, 1985 and Deci and Ryan, 2008), Przybylski et al. contend that FoMO could serve as a mediator linking deficits in psychological needs to social media engagement. Their study’s results indicated that individuals who evidenced less satisfaction of the basic psychological needs for competence (efficacy), autonomy (meaningful choice), and relatedness (connectedness to others) also reported higher levels of FoMO.
In the field of educational psychology, the psychological construct of motivation for learning, is one of the most highly studied variable, and has been extensively investigated in previous research (Donche et al., 2014, Linnenbrink and Pintrich,
2002 and Ratelle et al., 2007). Therefore, in the context of higher education, the SDT regarding learning motivation appears to be a particularly useful perspective to empirically explore FoMO.
Previous studies on learning motivations have placed an emphasis on the motivation behind the choices that students make, and on how social factors affect their sense of volition and initiative, as well as their well­being and the quality of their academic performance (Linnenbrink and Pintrich, 2002 and Ratelle et al., 2007). The SDT defines intrinsic and extrinsic sources of motivation. Intrinsic motivation refers to internal factors, such as enthusiasm and pleasure experienced while engaging in a task. In contrast, extrinsic motivation refers to external factors, such as obtaining good grades or passing exams. Studies on the quality of motivation (e.g., Donche et al., 2014) suggest that although basically distinguished as intrinsic and extrinsic, it can be further refined by making a distinction between autonomous and controlled motivation. Studies assessing the connections between these motivations, learning strategies and achievements have associated controlled motivation with surface processing and weak coping strategies in the case of failing (Ryan & Connell, 1989). The surface approach to learning is based on an intention that is extrinsic to the real purpose of the task (Biggs, 2001). One of the most common strategies for the surface approach is rote learning content without understanding, in order to subsequently reproduce the material. The surface approach is generally related to lower quality outcomes of learning (Kyndt, Dochy, & Cascallar,
2014).
Autonomous motivation has been found directly and positively connected to a deep approach to learning, that is the use of more information processing, high concentration while studying and better time management, and indirectly to higher academic achievement (Vansteenkiste, Zhou, Lens, & Soenens, 2005). A deep approach is based on a perceived need, such as an intrinsic interest to engage the task appropriately and meaningfully. Examples of deep­approach strategies are reflecting, using various information sources, relating ideas and looking for patterns (Kyndt et al., 2014).
According to Burnett, Pillay, and Dart’s (2003) study, students who adopted a deep approach liked learning new things and indirectly viewed learning as experiential, involving social interaction, and directly viewed learning as personal development.
Apart from intrinsic and extrinsic motivations, a third construct assessed in the present study is amotivation (an absence of motivation) for learning (Ratelle et al., 2007).
Amotivated students are neither intrinsically nor extrinsically motivated. They cannot predict the consequences of their behavior, and may feel disintegrated or detached from their action and will thus invest little effort in its effectuation (Deci & Ryan, 1985). In the academic domain, amotivation has been associated with boredom and poor concentration in class (Vallerand et al., 1993), poor psychosocial adjustment to college
(Baker, 2004), and dropout (Vallerand, Fortier, & Guay, 1997).
Despite increased interest in FoMO, there has been to date scant scholarly literature on its potential links with psychological health and well­being. In fact, Przybylski et al.’s
(2013) research was the first to provide a number of insights into how fear of missing out constellates with motivational, behavioral, well­being, and demographic factors. Their study mainly showed that FoMO plays a key role in explaining social media engagement over and above several individual factors, such as levels of need satisfaction, general mood, and overall life satisfaction. The concerns about the consequences of the http://www.sciencedirect.com.ezaccess.library.uitm.edu.my/science/article/pii/S0747563215001788?np=y 4/32

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College students’ academic motivation, media engagement and fear of missing out

alarming rate of mental problems related to use of social media among university students give additional reasons to expect FoMO linked to motivational deficits.
2.4. The present research
Based on the SDT and on the assumption that low levels of basic need satisfaction may relate to FoMO and social media engagement, the aim of the present research was to examine for the first time possible links between these constructs in the academic arena.
In order to properly assess these connections, a new scale was constructed and validated to map and measure social media activities students engaged in during classes. The following hypotheses were formulated to guide the study:
H1.
Students, who are high in basic need satisfaction, in terms of being intrinsically motivated for learning, would be less inclined toward social media use in the classroom. Whereas amotivated or extrinsically motivated students would tend toward using social media tools available.
H2.
Based on the assumption that psychological need deficits can lead some toward a general sensitivity to FoMO, it is hypothesized that FoMO would serve as a mediator linking motivational deficits to social media engagement. Furthermore, background variables, such as gender, age, and socio­economic status, will also be addressed in this research in order to assess how these variables intersect and may contribute to the measured variables. Fig. 1 demonstrates the theoretical structure of the proposed framework. Fig. 1.
Model 1. The theoretical structure of the proposed framework.
Figure options

3. Method
3.1. Participants
Data were gathered from 296 undergraduate Social­Science students (14.7% males and
85.3% females) from one major college located in the Northern Galilee. The distribution regarding ethnicity was: 65.9% Jewish students, 27.3% Muslim students, 5.1% Christian students, and 1.7% Druze students, with a mean age of 25.4 (SD = 7.1) years. Based on the report of The Central Bureau of Statistics, 2011 and The Council for Higher
Education, 2009 in Israel, the gender and ethnicity breakdown of Northern Galilee college students, majoring mainly in Social­Science studies is 20% males and 80% females of whom 50% Jews, 45% Muslims, and 5% belonging to other religions, thus the current study’s sample represents, to some extent, the gender breakdown of regional colleges located in the Northern Galilee. However, although including all four ethnic groups studying in Northern Galilee colleges, the sample is less representative concerning the distribution of ethnicity.
The distribution regarding the year of study was: 42.4% first­year students, 31% second­ year students and 26.6% third­year students. The participants’ faculty enrollment breakdown was as follows: Education – 35.1%, Criminology – 11.9%, Sociology – 8.4%,
Management – 36.5%, Economics – 6%, Political Science – 2.1%. http://www.sciencedirect.com.ezaccess.library.uitm.edu.my/science/article/pii/S0747563215001788?np=y 5/32

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College students’ academic motivation, media engagement and fear of missing out

3.2. Instrumentation
3.2.1. Student characteristics
Data were gathered using a questionnaire aimed at measuring the student’s cultural group, gender, age, socioeconomic­status (SES), year of study, and current education achievements. SES was assessed by the student’s father’s educational attainment
(FEA) and mother’s educational attainment (MEA), both defined on a six­level scale from
0 = lack of education, to 5 = doctoral degree. Another SES factor was the participants’ report on their current economic condition (EC), defined on a six­level scale from
1 = extremely difficult to 6 = comfortable, no financial worries. Finally, students’ current education achievements were measured by their self­reported grade point average
(GPA).
3.2.2. Social Media Engagement (SME) questionnaire
This scale was specifically designed for this study to measure the extent to which students used social media in the classroom. The scale was constructed in three steps.
The first step included collecting statements from 54 college students who were asked to describe their social media activities in the classroom. In the second step, duplicates and irrelevant statements were omitted. The rest were analyzed by three raters; all are experts in the research area of media and digital literacy. Inter­rater Cohen’s Kappa (k) reliability ( Cohen, 1960) was used. The raters were asked to categorize the students’ reports. The k values were interpreted as follows: k