The use of social networking services for classroom engagement? The effects of Facebook usage and the moderating role of user motivation

Abstract

Studies have examined the relationship between Facebook use and student engagement. With the growing use of social networking services in everyday life, there is an ongoing debate on the effect of Facebook usage outside the classroom on classroom learning. However, studies have been so far failed to examine how Facebook activities in everyday life differ according to individual characteristics. In order to answer that question, this study investigated how Facebook use affects student engagement in the classroom. The moderating role of user motivation was also examined, since students use Facebook for different purposes, which eventually determine whether they become engaged in their learning. The results revealed that students with more active Facebook use achieved significantly higher scores on student engagement than those with less active Facebook use. Image-management and social-pressure motivations have moderating effects on the relationship between the differing ways of using Facebook and student engagement. Students with high levels of image-management motivation who spent more time on Facebook gave learning with peers the lowest ratings of all the students surveyed. Those with high levels of social-pressure motivation who spent more time on Facebook also gave learning with peers lower ratings than all other students surveyed. Implications for future studies on instructional uses of social networking services are suggested.

Keywords

facebook social networking services student engagement user motivation

The use of social networking services in everyday life and its link with engagement

Social networking services (SNSs) are emerging as a new medium through which students learn, and these come with a variety of functions, such as communicating with others, creating and sharing new content, and strengthening interactions among users. Facebook is one of the most widely used SNSs. Studies have revealed that the use of SNSs in a classroom learning environment significantly increases student learning outcomes (Junco, 2012a). With far more time being spent on them in everyday life, the use of SNSs such as Facebook outside the classroom continues to be exploited as educational tools to support learning and teaching (Baldwin, 2015; Prescott, 2014). It is reported that students who use SNSs more often in everyday life are more likely to communicate and interact significantly with their peers (Ellison et al., 2007). Thus, the use of SNSs facilitates interactions with peers in class. Since SNSs are a medium for forming social relationships, their use in everyday life is expected to affect learning outcomes by influencing interactions in the classroom.

One important learning-outcome variable related to the social attributes of SNSs is student engagement. Student engagement refers to the time and effort invested by students in achieving desired outcomes and participating in course-related activities (Kuh, 2009). Student engagement is important in that it helps learners to adjust to academic life and to succeed (Lester and Perini, 2010). When students are engaged, they are likely to actively participate in learning processes, resulting in improved performance and higher levels of satisfaction (Ivala and Gachago, 2012; Junco, 2012a; Lester and Perini, 2010; Zepke and Leach, 2010). Given that the attributes of Facebook may include social connection, shared identity, social investigation, social network development, and status updating (Joinson, 2008), Facebook usage is likely to promote social aspects of student engagement in the classroom by facilitating and maintaining social relationships formed in class (Khosravi et al., 2016).

Since SNS technology provides students with directly perceivable affordances related to learning, Facebook usage in everyday life is expected to enable students to become more involved in social aspects of student engagement. Kassens-Noor (2012) suggests that the use of SNSs outside the classroom such as Twitter by college students can enhance learning due to enhanced communication and informal learning support. The use of Facebook is also viewed as important for learning. However, it is still not clear whether outside-of-class social interaction through Facebook leads to improved social interaction inside the classroom.

Studies have examined some aspects of the relationship between Facebook use and student engagement. Some have uncovered positive relationships between its use and student engagement. According to these studies, users who spend more than 6 hours a week on SNSs are reported to have more conversations and interactions with friends than non-users (Higher Education Research Institute (HERI), 2007). In addition, learners who use SNSs for more than 1 hour a day are more likely to be satisfied with their relationships with their friends and to participate in student groups than those who do not (Heiberger, 2007; Heiberger and Harper, 2008). However, others insist that merely accessing Facebook more often or spending more time on Facebook does not promote such an effect. Junco (2012b), for instance, found that time spent using Facebook was negatively related to scores for student engagement. He further argued that only specific Facebook activities are related to engagement. Therefore, studies are needed to examine if those who spend significant time on Facebook or access Facebook more become more engaged in classroom learning.

Given that Facebook offers a way to conveniently maintain social relationships and facilitates the sharing of ideas, its effect could be dependent on whether it is actively or passively used. In fact, studies overwhelmingly show that general use of Facebook has a negative impact on performance (Kirschner and Karpinski, 2010). Davenport et al. (2014) insist that only active SNSs usage affects learning outcomes, while Ellison et al. (2007) indicate that using Facebook to seek social information is related to growth of social capital rather than using Facebook to simply maintain relationships. Thus, more research is needed to determine whether active participation on Facebook leads to active participation in course learning.

To further explore the unique effects of different types of Facebook usage on student engagement, the specific conditions that make Facebook usage effective need to be examined. Individual characteristics may be significant variables in determining the effects of SNSs; some students are very active on them, frequently updating their own posts and responding to others’, while others are more passive, simply checking other people’s posts. Thus, attention should be paid to learners’ personal characteristics as they relate to their Facebook usage.

Facebook usage types and motivation

One personal characteristic that can be considered is motivation. Students use SNSs for different purposes (Skues et al., 2012). In other words, student’s motivations for using social media vary. According to uses and gratification theory, people use media with different purposes, depending on their specific needs (Okazaki, 2006; Shen and Khalifa, 2008). For instance, studies on Internet uses and gratification have identified a variety of motivating factors, determining that people use the Internet to find information, to communicate with others, to maintain personal relationships, and to seek peer identification, good feelings, status, and personal insight. In the case of social media usage, users have motivations such as escaping negative feelings; seeking social contact, affection, recognition, and entertainment; and fulfilling cognitive needs. User motivation is essential to explaining learners’ differing behaviors (Shen and Khalifa, 2008); it has been reported to affect both communication activities and satisfaction (Baek et al., 2011; Smock et al., 2011). Ross et al. (2009) report that outcomes related to Facebook use depend on motivation because motivation affects a person’s manner of using Facebook and consequently their level of participation in learning. The effects of the use of SNSs on student engagement may differ depending on the student’s motivation type.

Given that SNSs have many different purposes, the effectiveness of Facebook usage can be perceived differently. People’s motivations in using Facebook may be expected to vary, from maintaining relationships, managing images, and participating habitually as a way to spend leisure time or, for no special reason, to being involved with the people around them, taking an interest in others, or seeking private information about others (Yang et al., 2012). People’s affective characteristics can influence engagement. In fact, one study has indicated that learners with higher levels of “grit,” meaning consistency of interest and perseverance of effort, engage more in active learning (Yoon et al., 2018). Hence, Facebook users with different types of motivation should be expected to engage differently in classroom learning activities.

Therefore, this study aims to investigate whether significant use of SNSs in everyday life affects student engagement in classroom learning and whether active usage leads to student engagement. This study also investigates whether different levels of user motivation have a moderating effect on the relationship between the use of SNSs and student engagement. The following research questions were generated:

Does frequency and time of the use of an SNS such as Facebook in everyday life have an impact on student engagement?

Does active usage of an SNS such as Facebook have an impact on student engagement?

Does type of user motivation moderate the relationship between Facebook use and student engagement?

Methods

Sample

Undergraduate students from a large university in Seoul, Korea, participated in an online survey. The participants were recruited through an email invitation to all students by the Center for Teaching and Learning as part of an annual student survey. Incentives were provided to participants. Of a total of 592 questionnaires returned, 405 respondents answered that they used Facebook. Of these, 349 responses were used for the data analysis, while the remaining responses were excluded due to missing data. In terms of demographic characteristics, the participants consisted of 226 males and 123 females, including 133 first-year students, 112 second-year students, 41 third-year students, and 63 fourth-year students. These students represented more than 20 degree programs in the colleges of Business Administration, Education, Liberal Arts, and Engineering. In terms of grade point average (GPA; ranging from 0.0 to 4.5), 30.2% of participants had GPAs above 4.0, 61.6% had GPAs between 3.0 and 4.0, and 8.2% had GPAs below 3.0. In terms of parents’ educational background, 74.4% of fathers held college degrees, 22.3% were high school graduates, and 3.3% were middle school graduates; 60.1% of mothers held college degrees, 36.6% were high school graduates, and 3.3% were middle school graduates.

Measures

Facebook usage behaviors

Facebook is one of the SNSs used most widely by higher education learners (Hew, 2011; Lampe et al., 2011; Mazman and Usluel, 2011), so Facebook was chosen. SNS usage was measured by the number of times the student accessed Facebook each day, the total time spent on Facebook per day, and the active or passive nature of the student’s daily Facebook usage (Junco, 2012b; Suwannatthachote and Tantrarungroj, 2012):

The number of times Facebook was accessed: The number of times Facebook was accessed by each student was measured by simply recording use frequencies. Students were asked to answer questions related to their average frequency of access per day (e.g. “On average, how frequently do you access Facebook?”). For statistical purposes, students were categorized into groups with more and less SNS usage based on the number of times they accessed Facebook. In terms of numbers, Level 1 was assessed as 5 points or less, Level 2 was assessed as 6 to 11 points, and Level 3 was assessed as above 11 points.

Time spent: Time spent was measured by students’ own estimates of the time they spent on Facebook. Students were asked to respond to questions related to the average time they spent on Facebook per day (e.g. “On average, about how much time per day do you spend on Facebook?”). In terms of time, Level 1 was assessed as 10 minutes or less per day, Level 2 was assessed as 11 to 30 minutes per day, Level 3 was assessed as 31 to 60 minutes, and Level 4 was assessed as over 1 hour.

Facebook usage type: Facebook use was classified into active and passive types. Active use referred to activities requiring the user’s initiative, such as uploading photos, creating posts, changing profile photos, commenting on other people’s statuses (timeline posts), and commenting on other people’s photos (Junco, 2012b; Pempek et al., 2009); for statistical purposes, students with more and less active Facebook usage were categorized based on the mean scores of all the participants. Passive use referred to viewing other people’s photos, comments, and posts without commenting on them; for statistical purposes, students with more and less passive Facebook usage were categorized based on the mean scores of all the participants.

Facebook user motivation

Yang et al.’s (2012) five-motivation classification of Facebook use was modified and adopted. Students responded to questions using a Likert-type 5-point scale (ranging from not at all = 1 to very = 5), and the reliability (Cronbach’s α) of this scale was .861. The questionnaire included a total of 17 items: 3 items in relationship maintenance, 4 items in image management, 3 items in habitual use, 4 items in social pressure, and 3 items in searching for others:

The maintenance of relationships is the most basic motivation for using Facebook and involves human network management, formation or maintenance of relationships, and formation of bonds. Items included “I use Facebook to maintain relationships with people whom I do not meet frequently” and “I use Facebook to remain in contact with people that I already know.”

Image-management motivation refers to the desire to portray oneself in a particular way to others or to create a positive image. Items included “I want to hear that I am a good person from another person” and “I want to show off my experience to others.”

Habitual use motivation is use of Facebook without any special reason. Items included “I use Facebook habitually without a specific reason” and “having fun without a specific reason.”

Social-pressure motivation refers to Facebook use as a trend rather than out of willingness or intention. Items included “I am asked by those who are using Facebook” and “Most of my friends are using it.”

Searching-for-others motivation means that Facebook use is motivated by an interest in others or curiosity to know about others’ lives, for example, “I am curious about the private lives of others” and “I want to know about other people’s pasts.”

Student engagement

Student engagement was measured by modifying the National Survey of Student Engagement (NSSE). The NSSE originally consisted of five factors. Three relevant factors were chosen for this study. The questionnaire included 12 items scored on a 5-point Likert-type scale: 4 items (i.e. presenting activities during class, project learning with peers during class, homework preparation after class, and use of electronic devices for class activities) referred to active collaborative learning, 3 items (i.e. teaching peers, discussing the contents of lessons with outsiders, and conversations with students with different personal values) referred to learning with peers, and 5 items (i.e. number of reading assignments completed, number of reports written, and time spent on class preparation) referred to academic challenges. Students were asked to describe their experiences in their classes from the previous semester. The other two NSSE factors were excluded from this study. Faculty–student exchanges were excluded from consideration because they included items related to faculty career counseling. Supportive college/university environment was also excluded due to the items related to the university environment.

Data collection and analysis

Three methods of analysis were used. First, a one-way analysis of variance (ANOVA) was conducted to examine the effects of Facebook usage on student engagement. Second, a t-test was conducted to examine the effects of active and passive SNS usage on student engagement. Third, a Moderated Multiple Regression (MMR) was conducted to determine moderating effects on student engagement in the relationship between SNS usage and motivation type. In terms of demographic variables that could potentially impact student engagement, gender, GPA, and parents’ educational backgrounds were included as control variables.

Table 1 reports the means, standard deviations, and correlations for each of the variables in this study. Prior to testing the hypotheses, we performed diagnostic tests of our data. The variable distributions were determined to be close to normal. The univariate distribution and multivariate normality were found to be acceptable. No multicollinear problem was shown to exist between the three independent variables (number of times accessed, time spent, and usage type). The first research question investigated the effects of Facebook usage on student engagement using a one-way ANOVA. The second research question used a t-test to investigate the effects of active and passive Facebook usage on student engagement. The third research question investigated whether type of motivation moderates the relationship between Facebook use and student engagement. In terms of demographic variables that could potentially impact student engagement, gender, GPA, and parents’ educational backgrounds were included as control variables.

Table 1.

Means, standard deviation, and correlations for all measures.

	Facebook use types				Facebook use motivation					Student engagement
	1.	2.	3.	4.	5.	6.	7.	8.	9.	10.	11.	12.	13.
1.	−
2.	.70**	−
3.	.33**	.27**	−
4.	.31**	.34**	.47**	−
5.	.09	.16**	.31**	.27**	−
6.	.23**	.18**	.55**	.31**	.34**	−
7.	.48**	.49**	.20**	.35**	.03	.14*	−
8.	.04	.09	.18***	.24**	.24**	.26**	.05	−
9.	.09	.13*	.31**	.47**	.28**	.38**	.18**	.34**	−
10.	.01	.07	.26**	.05	.15**	.14*	−.11*	.09	.13*	−
11.	.04	.09	.20**	.13*	.13*	.06	−.04	.04	.10	.77**	−
12.	.05	.07	.23**	.04	.14**	.15**	−.09	.11*	.14**	.81**	.40**	−
13.	−.09	−.03	.15**	−.07	.06	.09	−.12*	.06	.04	.70**	.35**	.37**	−
M	7.17	49.47	2.6	3.33	2.75	2.03	3.47	2.17	2.22	2.38	3.28	2.44	1.42
SD	7.45	44.81	0.83	0.81	0.93	0.88	1.0	0.93	0.99	0.52	0.72	0.77	0.55

SD: standard deviation.

Number of access, 2. Time spent, 3. Active usage, 4. Passive usage, 5. Relation maintenance, 6. Image management, 7. Habitual use, 8. Social pressure, 9. Searching for others, 10. Student engagement total, 11. Active collaboration, 12. Learning with peers, and 13. Academic challenge.

p < .05; **p < .01.

Findings

Does frequency and time of the use of an SNS such as Facebook in everyday life have an impact on student engagement?

No significant differences were found between the number of times Facebook was accessed and the three factors of student engagement, nor were any significant differences found between time spent on Facebook and those three factors (see Table 2). The results show that the level of Facebook use does not affect student engagement in terms of both numbers and time.

Table 2.

Means and standard deviation for Facebook use level and student engagement.

Engagement type	Level of use	n	M	SD	F
Number of times accessed
Overall	1 (less than 5)	215	2.39	0.52
	2 (6–10)	85	2.30	0.50	1.63
	3 (over 11)	49	2.45	0.53
	Total	349	2.38	0.52
Active collaborative learning	1 (less than 5)	215	3.30	0.70
	2 (6–10)	85	3.19	0.65	1.31
	3 (over 11)	49	3.39	0.81
	Total	349	3.28	0.71
Learning with peers	1 (less than 5)	215	2.43	0.74
	2 (6–10)	85	2.37	0.86	1.16
	3 (over 11)	49	2.58	0.74
	Total	349	2.44	0.77
Academic challenge	1 (less than 5)	215	1.46	0.56
	2 (6–10)	85	1.33	0.47	1.81
	3 (over 11)	49	1.38	0.58
	Total	349	1.42	0.55
Time spent
Overall	1 (below 10 minutes)	56	2.42	0.60
	2 (11–30 minutes)	123	2.32	0.48
	3 (31–60 minutes)	108	2.35	0.50
	4 (over 60 minutes)	62	2.52	0.54
	Total	349	2.38	0.52
Active collaborative learning	1 (below 10 minutes)	56	3.26	0.81
	2 (11–30 minutes)	123	3.25	0.64	1.81
	3 (31–60 minutes)	108	3.23	0.69
	4 (over 60 minutes)	62	3.47	0.74
	Total	349	3.28	0.71
Learning with peers	1 (below 10 minutes)	56	2.46	0.82
	2 (11–30 minutes)	123	2.33	0.78
	3 (31–60 minutes)	108	2.42	0.72	2.22
	4 (over 60 minutes)	62	2.64	0.79
	Total	349	2.44	0.77
Academic challenge	1 (below 10 minutes)	56	1.54	0.56
	2 (11–30 minutes)	123	1.37	0.50	1.51
	3 (31–60 minutes)	108	1.39	0.51
	4 (over 60 minutes)	62	1.45	0.65
	Total	349	1.42	0.55

SD: standard deviation.

Does active usage of an SNS such as Facebook have an impact on student engagement?

In terms of active use level, significant differences were found, t(347) = –4.17, p < .01, as can be seen from Table 3. Students with more active use achieved significantly higher scores on student engagement than those with less active use. More active students achieved significantly higher scores than less active students on three factors of student engagement: active and collaborative learning, t(347) = –3.04, p < .01; learning with peers, t(347) = –3.58, p < .01; and academic challenge, t(347) = –2.75, p < .01. Significant differences were not found depending on passive use level, for all three types of engagement.

Table 3.

Means and standard deviation for active Facebook use level and student engagement.

Engagement type	Use group	n	M	SD	t
Overall	1 (less active)	160	2.26	0.52	−4.17**
Overall	2 (more active)	189	2.48	0.49	−4.17**
Active collaborative learning	1 (less active)	160	3.16	0.73	−3.04**
Active collaborative learning	2 (more active)	189	3.39	0.67	−3.04**
Learning with peers	1 (less active)	160	2.28	0.79	−3.58**
Learning with peers	2 (more active)	189	2.57	0.74	−3.58**
Academic challenge	1 (less active)	160	1.33	0.50	−2.75**
Academic challenge	2 (more active)	189	1.490	0.57	−2.75**

SD: standard deviation.

p < .01.

Does type of user motivation moderate the relationship between Facebook use and student engagement?

The results showed that only two types of motivation had a moderating effect on the relationship between Facebook use and one factor of student engagement. Both image-management and social-pressure motivations were shown to have moderating effects on the relationship between Facebook use and learning with peers.

Table 4 shows the moderating effect of image-management motivation on the relationship between type of use and learning with peers. In Model 2, only active use significantly influenced (β = .29, p < .001) learning with peers, and the explanatory power of the model increased from 4% to 11%. In Model 3, image-management motivation was added but was not found to be significant. In Model 4, the input of the interaction variable increased explanatory power of the model by about 3%. Significant relationships were found between the number of times Facebook was accessed and learning with peers (β = .28, p < .001), and between time spent on Facebook and learning with peers (β = –.20, p < .05).

Table 4.

Moderating effect of image-management motivation on the relationship between usage behavior and learning with peers.

	Model 1		Model 2		Model 3		Model 4
	B (SE)	β	B (SE)	β	B (SE)	β	B (SE)	β
Intercept	1.24 (.39)		1.27 (.38)		1.27 (.38)		1.24 (.38)
Control variable
Gender	0.19 (.09)	.12*	0.24 (.08)	.15**	0.24 (.09)	.15**	0.24 (.08)	.15**
GPA	0.24 (.08)	.16**	0.23 (.08)	.15**	0.23 (.08)	.15**	0.25 (.08)	.15**
Father’s education	−0.01 (.02)	−.04	−0.02 (.02)	−.06	−0.02 (.02)	−.06	−0.02 (.02)	−.08
Mother’s education	0.03 (.02)	.09	0.03 (.02)	.10	0.03 (.02)	.10	0.03 (.02)	.11
Independent variables
Number			0.06 (.07)	−.06	−0.06 (.07)	−.06	−0.11 (.08)	−.11
Time			0.06 (.06)	.08	0.06 (.06)	.08	0.07 (.06)	.09
Active use			0.27 (.06)	.29***	0.26 (.06)	.28***	0.25 (.06)	.26***
Passive use			−0.08 (.06)	−.08	−0.08 (.06)	−.08	−0.10 (.06)	−.11
Image-management motivation					0.01 (.05)	.02	0.02 (.06)	.02
Interaction
Number × image							0.30 (.08)	.28***
Time × image							−0.19 (.08)	−.20*
Active × image							−0.06 (.07)	−.06
Passive × image							−0.02 (.07)	−.02
R ²	.04		.11		.11		.14
ΔR²	.04		.07		.00		.03
F	3.68**		5.20***		4.62***		4.24***
ΔF	3.68**		6.48***		.06		3.12*

SE: standard error; GPA: grade point average.

Gender: male = 1, female = 0.

p < .05; **p < .01; ***p < .001.

Frequency of access and time spent were shown to have distinct effects according to students’ level of image-management motivation. This moderating effect is shown in Figure 1. The findings show that the number of times Facebook is accessed has a positive influence on learning with peers, whereas time spent on Facebook has a negative effect. In terms of frequency of Facebook access, students with a strong image-management motivation were likely to get higher scores on learning with peers as they accessed Facebook more often. In contrast, students with a weak image-management motivation were likely to get lower scores on learning with peers as they accessed Facebook more often. On the other hand, in terms of time spent on Facebook, students with a strong image-management motivation were likely to get lower scores on learning with peers when they spent more time on Facebook, but students with a weak image-management motivation were likely to get higher scores on learning with peers when they spent more time using Facebook.

Figure 1.

Moderating effect of image-management motivation according to the number of times accessing Facebook and time spent.

Table 5 shows the moderating effect of social-pressure motivation on the relationship between Facebook use and learning with peers. In Model 2, only active use significantly influenced (β = .29, p < .001) learning with peers, and the explanatory power of the model increased from 4% to 11%. In Model 3, social-pressure motivation did not show a significant main effect (β = .28, p < .001). The explanatory power of the model was 12%, and it was statistically significant, F(9, 339) = 4.91, p < .001. In Model 4, the input of the interaction variables increased by 3% in comparison with Model 3, resulting in an explanatory power of 15%, F(13, 338) = 4.51, p < .001. Frequency of Facebook access and time spent on Facebook exhibited distinct effects on learning with peers according to the level of social-pressure motivation. As social-pressure motivation increased, the impact of frequency of Facebook access on learning with peers increased, β = .17, p < .05. However, the impact of time spent on Facebook on learning with peers decreased, β = –.26, p < .001.

Table 5.

Moderating effects of social-pressure motivation on the relationship between usage behavior and learning with peers.

	Model 1		Model 2		Model 3		Model 4
	B (SE)	β	B (SE)	β	B (SE)	β	B (SE)	β
Intercept	1.24 (.39)		1.27 (.38)		1.27 (.38)		1.33 (.37)
Control variable
Gender	0.19 (.09)	.12*	0.24 (.08)	.15**	0.25 (.08)	.15**	0.24 (.08)	.15**
GPA	0.24 (.08)	.16**	0.23 (.08)	.15**	0.23 (.08)	.15**	0.23 (.08)	.16**
Father’s education	−0.01 (.02)	−.04	−0.02 (.02)	−.06	−0.02 (.02)	−.06	−0.02 (.02)	−.06
Mother’s education	0.03 (.02)	.09	0.03 (.02)	.10	0.03 (.02)	.10	0.02 (.02)	.08
Independent variables
Number			−0.06 (.07)	−.06	−0.05 (.07)	−.05	−0.05 (.07)	−.05
Time			0.06 (.06)	.08	0.06 (.06)	.07	0.04 (.06)	.05
Active participation			0.27 (.06)	.29***	0.26 (.06)	.28***	0.25 (.06)	−.26***
Passive participation			−0.08 (.06)	−.08	−0.09 (.06)	−.10	−0.08 (.06)	−.09
Social-pressure motivation					0.07 (.04)	.08	0.08 (.04)	.09
Interaction
Number × social							0.17 (.08)	.17**
Time × social							−0.22 (.07)	−.26*
Active × social							−0.02 (.06)	−.02
Passive × social							0.12 (.06)	.12
R ²	.04		.11		.12		.15
ΔR²	.04		.07		.01		.03
F	3.68**		5.20***		4.91***		4.51***
ΔF	3.68**		6.48***		2.47		3.31*

SE: standard error; GPA: grade point average.

Gender: male = 1, female = 0,

p < .05; **p < .01; ***p < .001.

The moderating effects are shown in Figure 2. In terms of frequency of Facebook access, students with a strong social-pressure motivation were likely to earn higher scores on learning with peers when they accessed Facebook more often. In contrast, students with a weak social-pressure motivation were likely to get lower scores on learning with peers when they accessed Facebook more often. Time spent on Facebook had the opposite effect, with students with a strong social-pressure motivation tending to get lower scores on learning with peers when they spent more time on Facebook and students with a weak social-pressure motivation tending to get higher scores on learning with peers when they spent more time using Facebook.

Figure 2.

Moderating effect of social pressure according to the number of times accessing Facebook and time spent.

Discussion

The effects of Facebook use on engagement in classroom learning

Since Facebook is the most popular SNS and, as a primarily social medium, has a potential link to learning, there is ongoing debate concerning Facebook usage outside the classroom and its effects on learning within it. This study focused on whether Facebook usage in everyday life enhances student engagement. There was no effect of access or time on any engagement variables. The results show that the number of times Facebook was accessed and the time spent on Facebook did not affect active and collaborative learning, learning with peers, or academic challenge in learning. This result is consistent with findings that merely using Facebook more often or spending more time on Facebook in everyday life, that is, for purposes other than studying, does not affect learning within the classroom (Jacobsen and Forste, 2011; Junco, 2012b). Social awareness brought about by Facebook use in everyday life might not directly lead to engagement in learning in the classroom. Junco (2012b) argues that spending large amounts of time on Facebook seems to decrease time spent focusing on academic work.

Effects of active Facebook use on active participation in course learning

The findings that showed a positive association between more active Facebook usage in everyday life and student engagement are in line with research (e.g. Junco, 2012b), since specific Facebook activities are related to engagement. Most studies on Facebook use have focused on the effects of frequency of access or time spent on Facebook on academic outcomes (Heiberger, 2007; HERI, 2007; Junco, 2012b; Karpinski and Duberstein, 2009; Kirschner and Karpinski, 2010). However, merely accessing or spending time on Facebook in everyday life might not lead to an increase in classroom learning. Active usage includes student-initiated activities that involve uploading, creating, changing, and commenting rather than just viewing. Students who are in the habit of engaging in these activities on Facebook in their everyday lives may be apt to participate more actively in interactive activities such as carrying out tasks with peers and seeking affective and emotional support. This kind of inference, however, needs validation, because active Facebook posting seemed to be associated with differences in students’ level of engagement. This finding was further supported by the fact that the level of passive Facebook use did not impact student engagement.

Moderating effects of motivation for using Facebook on peer learning

This study found a moderating effect based on user motivation, suggesting that the effects of Facebook use can differ according to individual characteristics. This moderating effect was found only on learning with peers, one factor of student engagement. By revealing that image-management and social-pressure motivations moderate the relationship between Facebook use and learning with peers, this study shows that students’ Facebook use had a strong impact on their relationships with others. The reason why two types of motivation have moderating effects might be explained by the common attributes of the motivations. Studies have noted that Facebook is an approachable service for people who are particularly inclined toward making themselves known to others (Choi et al., 2012; Yang et al., 2012). Image-management and social-pressure motivations are more closely related to social relationships than other types of motivations. For those who are motivated to use Facebook due to a desire to make themselves known to others, a higher frequency of Facebook access stimulated learning with peers in class, but more time spent on Facebook diminished learning with peers. Similarly, for those who used Facebook owing to social pressure, more frequent Facebook access stimulated learning with peers, but spending more time on Facebook caused learning with peers to decline.

The moderating effect of motivation can be further explained by goal orientation theory. Goal orientation is a particularly important motivation variable because it explains why learners engage in various learning activities. Dweck and Leggett (1988) have expanded their original goal theory to describe social interactions. A social learning goal is defined as an intention to develop social attributes and acquire social experience. Social performance goals are further divided into two components: approach and avoidance (Kuroda and Sakurai, 2011). Social performance–approach goals focus on obtaining positive evaluations of one’s social attributes, and social performance–avoidance goals focus on avoiding negative evaluations of one’s social attributes.

In terms of frequency of access, the results indicate that those with high levels of image-management motivation who accessed Facebook more often rated learning with peers higher than did all other students. A possible reason may be that these students have social performance–approach goals. Given that image-management motivation refers to a desire to portray oneself to others positively, the motivation is closely related to the social performance–approach goal orientation. Given that the nature of social performance–approach goals is to focus on obtaining positive evaluations of one’s social attributes, students with high levels of image-management motivation are likely to be more interested in building broader relationships and thus highly value learning with peers. In terms of time spent on Facebook, the results show that spending large amounts of time on Facebook did not lead to better learning with peers. Those with high social-pressure motivations who spent more time on Facebook rated learning with peers lower than did all other students. One possible reason for these low ratings may be that these students have a social performance–avoidance goal orientation. Given that those with social performance–avoidance goals tend to withdraw from peer relationships in order to avoid being negatively evaluated, students with a higher social–pressure motivation are likely to be more reluctant to communicate with others. Thus, more time might not lead to a broader range of relationships.

The idea of focusing on Facebook use in everyday life and its relationship to student engagement gives new impetus to research in SNSs. Everyday Facebook usage does not always lead to increased engagement in classes. Only active Facebook use empowers students to participate in active and collaborative work, learning with peers, and academic challenges in classroom learning. Facebook usage should be also approached carefully by reflecting on differences in user motivations.

Some limitations of this study should be mentioned. It is likely that those who are active in posting and commenting on Facebook are generally active in every aspect of their lives. They may not be engaged because of Facebook but rather because they have a predisposition to become engaged in whatever they are doing. Thus, future studies should investigate the genuine effects of Facebook usage in everyday life on student engagement through experimental methods. Given that active learning involves practices such as teamwork and discussion as well as the application of knowledge through engagement, there is a need to further investigate Facebook’s potential as an active learning tool. The study employed self-reported measures from undergraduates in a variety of disciplines, requiring heavy reliance on the memory and honesty of the participants in reporting on their experiences. Future studies should strive to include observable objective data, such as log data for Facebook access or measurements of actual access time for students of different ages and from different disciplines. Future research should also look at different cultural and racial groups, as the sample in this investigation consisted only of Koreans. It is possible that learners with different cultural backgrounds might have different motivations. Future research employing uses and gratification theory to study the use of SNSs should look at participants from diverse racial and cultural backgrounds. While acknowledging these limitations, we believe that these findings regarding the effects of everyday Facebook usage on student engagement will prompt researchers to identify more variables related to the use of SNSs and learning outcomes. Furthermore, it is evident that not all Facebook usage is equally effective, and that different kinds of use patterns (e.g. active use) and different kinds of motivations (e.g. image management and social pressure) will determine the meaningfulness of Facebook usage for classroom learning; thus, future research must engage in examinations of more unique affordances of Facebook usage.

Footnotes

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: This research was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2017S1A3A2066878).

ORCID iD

Ah Jeong Hong

Author biographies

Euna Park is a Researcher. Her research is focused on students’ learning motivation and innovative instructional design. Address: Korean Human Resource Development Strategy Institute, Chung-Ang University, 221 Heukseok-dong, Dongjak-gu, Seoul 156-756, Korea. [ email: mniea07@naver.com]

Hae-Deok Song, PhD is a Professor of Education. His research investigates active learning strategies, in particular, the motivation and engagement strategies. He also studies how technology enhances performance in both adults and students. Address: Department of Education, Chung-Ang University, 221 Heukseok-dong, Dongjak-gu, Seoul 156-756, Korea. [ email: hsong@cau.ac.kr]

Ah Jeong Hong, EdD is an Assoicate Professor of Education. Her research interests include adult learning and organizational development. Address: Department of Education, Chung-Ang University, 221 Heukseok-dong, Dongjak-gu, Seoul 156-756, Korea. [ email: ah454@cau.ac.kr]

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