Engaging Students via Social Media

Abstract

This article explores for the first time the moderating effect of students’ readiness for cocreation on the student social media engagement and perceived value relationship. Ping’s and Cadogan et al.’s procedures for assessing the structural model with interaction terms were followed. Results based on a sample of 353 university students demonstrated that students who are ready to participate in value creation tend to perceive more value from social media engagement. In particular, when the students perceive role clarity, have higher ability, and are motivated to take active part in creating value, they report high functional, social, and emotional value. This research is expected to impart key insights for scholars, as well as educators and policy makers in tertiary institutions seeking to further understand the nascent student social media engagement concept, and the nature of the student social media engagement/perceived value nexus. A series of recommendations are offered to assist faculty efforts to enhance students’ willingness to take active part in value creation. The article concludes with an overview of key research limitations and implications.

Keywords

student engagement social media value cocreation

The evolution of social media and Web 2.0 technology is extraordinary (Lenhart, Purcell, Smith, & Zickuhr, 2010; Tess, 2013). In the Web 2.0 context, social media are often defined as the usage of Web-based tools that link people and enable them to share information, videos, pictures, and so on. These tools and features include blogs, YouTube, wikis, podcasts, video blogs, Flickr, Slideshare, and social networks such as Facebook, Myspace, and Twitter. The existence of social media is no more apparent than among university students where the technology is changing the ways students communicate, interact, collaborate, and learn (Tess, 2013).

Recently, social media have had a crucial impact on teaching methodology (Bennett, Bishop, Dalgarno, Waycott, & Kennedy, 2012; Ellison & Wu, 2008). These media have been emphasized for their promising opportunity to be used in the teaching–learning process within higher education (Brown, 2012; Çağlar & Demirok, 2010; D. Churchill, 2009; Top, Yukselturk, & Inan, 2010; Ventura & Quero, 2013). The use of social media in university teaching adds a collaborative dimension to teaching and enhance interaction and communication between all those involved in the teaching–learning process, as well as enhancing the student experience by encouraging participation. Consequently, current perspectives recommend that the student should be engaged as an active coproducer of the university experience where the student assumes a more active and relevant role (Bowden & D’Alessandro, 2011; Wang, Hsieh, & Yen, 2011; Wodzicki, Schwämmlein, & Moskaliuk, 2012). Engaging students as proactive participants in collaborative, value cocreation learning processes (Sawhney, Verona, & Prandelli, 2005; Vargo & Lusch, 2004) mirrors the broader theoretical perspectives of the service-dominant logic and relationship marketing (Brodie, Ilic, Juric, & Hollebeek, 2011; Sweeney & Chew, 2010; Vargo & Lusch, 2008). In addition, the uprising range of challenges that tertiary institutions are now encountering, including high student dropout rates, high pressure to be more responsive to industry needs, as well as the growing globalization that increases the severity of the competitive environment (Bowden & D’Alessandro, 2011; Helgesen, 2008; Mansfield & Warwick, 2006; Yang, Alessandri, & Kinsey, 2008), have raised a need to more deeply understand the university experience from the student’s standpoint as well as the factors that lead to high levels of student satisfaction (Mansfield & Warwick, 2006). These challenges highlighted a growing need to find new ways to engage students and increase the value and satisfaction of their educational experience.

Despite the importance of engaging students in education via social media (see, e.g., Mason & Rennie, 2008; Mazer, Murphy, & Simonds, 2007; Pearson, 2009), how students perceive this phenomenon is still nebulous in the literature to date (Brodie et al., 2011; Hollebeek, 2011a, 2011b; Hollebeek, 2013; Meyer, 2010; Ventura & Quero, 2013). In addition, there are contradictory findings among the few researches that attempted to study the impact of students’ engagement in education on student-related outcomes such as perceived value and satisfaction. Some research documented negative impact of using social media in education. For example, some studies document a negative relationship between social media usage and grade point average (Bijaria, Javadiniab, Erfanianc, Abedinid, & Abassi, 2013; Junco, 2012; Kirschner & Karpinski, 2010). However, some other studies have shown that using Facebook has no effect on students’ academic performance (O’Brien, 2012). Furthermore, some studies reported the possible risks of using social media (see, e.g., Jahan & Ahmed, 2012). The mixed findings concerning the impact of social media usage in education might be justified by the different intention of customers’ to cooperate. Wang et al. (2011) argue that a supplier’s proactive initiatives to engage customer/student may not lead to expected outcomes (e.g., perceived value and customer satisfaction) because the customer may consider involving and engaging him or her in the value creation as an intrusion on privacy and/or he or she is just unaware of these initiatives. That is, proactive initiatives of service provider lead to effective outcomes only if the efforts are supported by customer collaboration or willingness to cooperate (Cao & Hong, 2011). Nevertheless, existing knowledge regarding why student engagement might not improve student-related outcomes value perception has received limited research attention. To address this gap, the current article investigates the moderating role of “customer readiness for cocreation” to explore student preparation to engage in cooperative behavior with academic staff in value cocreation. Considering that customers (students) generally lack the knowledge and skills to work with service providers (instructors) in performing a new task, Lengnick-Hall (1996) indicated three key factors that assist customers/students in coperforming a new task: clarity of the task, ability, and motivation. These three factors were conceptualized by Meuter, Bitner, Ostrom, and Brown (2005) as key components of “customer readiness.” Furthermore, Wang et al. (2011) proposed the notion of “customer readiness for co-creation,” which is defined as “the extent to which a consumer is prepared and likely to cooperate with his/her service provider in value co-creation (p. 136).” Consistently, the current research suggests that student readiness for value cocreation moderates student engagement–perceived value relationship.

Therefore, and based on the above discussion, examining the relationship between student experiences of social media engagement and perceived value is therefore becoming an increasingly important strategic theme for universities given that this allows institutions to achieve their organizational goals. Specifically, by investigating the student engagement–student perceived value interface, this research responds directly to Hollebeek’s (2013), Leeflang’s (2011), and Brodie et al.’s (2011) calls for research furthering scholarly insights in this emerging area. The objectives of this article are the following: (1) to develop a conceptual model of the student engagement–student perceived value interface for social media in education, (2) to empirically investigate the proposed model, and (3) to identify directions for future research arising from this study.

This article intends to answer the following research questions: What is the impact of students’ readiness for cocreation to the relationship between student’s engagement via social media and perceived value dimensions? Furthermore, does this in turn influence students’ likelihood of satisfaction?

To address this important gap in the literature, the article will be organized as following: First, this article will present a literature review of students’ engagement, perceived value, students’ readiness for value cocreation, and student satisfaction within the education sector and develop hypotheses based on the literature. Second, the study methodology is outlined. Third, analyses and discussion of findings are presented. Finally, the theoretical and managerial implications of the findings are discussed.

Literature Review and Hypotheses Development

Student Engagement via Social Media

Academic engagement refers to “the time and energy students devote to educationally purposeful activities” as proposed within the National Survey of Student Engagement framework (Taylor, Hunter, Melton, & Goodwin, 2011, p. 74). Academic engagement incorporates all aspects of a student’s education, including: assignment completion, class attendance, classmate communication, and external influences (Hu & Wolniak, 2010; Schoffstall, Arendt, & Brown, 2013).

Nowadays, social media are used as a tool to engage students in education. Social media usage in teaching currently takes place in a wide range of subjects, including business subjects (Liu & Olson, 2010), arts and sciences (Harley et al., 2006; Wankel, 2011), law and legal studies (Elefant & Black, 2011), and public management (Bryer & Chen, 2010).

Social media is a term that is broadly used to portray any technological tools related to collaboration and community (Joosten, 2012). While it seems that a specific definition of social media maybe elusive (Kaplan & Haenlein, 2010), it is often illustrated by example. Social networking sites (SNSs) include blogs, wikis, YouTube, podcasts, and Flickr (McEwan, 2012). For the purpose of this study, SNSs were chosen to be the focal point in recognition of the popularity of SNSs such as Facebook, Myspace, and LinkedIn. SNSs are Web-based services that enable users to make personal profiles, create content, and share messages by connecting with other users in the system (Boyd & Ellison, 2007).

Given the prevalence of social media in general, and of SNSs in particular, many higher education teachers have begun to explore their use in formal education to mediate and enhance their instruction as well as promote active learning for students (Bennett et al., 2012; McLoughlin & Lee, 2010). Of course, using the social media may require the instructor to take into account not only the practical integration of the tool into course goals but also (and more notably) the theoretical framework for implementing the technology as a learning tool. Scholars suggested that the latter has drawn little attention to date from either instructors or researchers (Merchant, 2012; Tess, 2013). The notion of encouraging more research into this area will be one of the study recommendations.

Students’ noticeable engagement with these tools in their daily lives has inspired interest within education because of possible new approaches of engaging students in individual and collaborative learning activities (Bennett et al., 2012). It is expected that students who are already using Web 2.0 technologies in their everyday lives would be likewise motivated to use them in an academic context and would already possess the needed technical skills (Bennett et al., 2012).

The next section proceeds by reviewing key literature in the area of student perceived value.

Student Perceived Value

The perceived value concept, which is documented as significantly contributing to consumer purchase intention and loyalty (Bove & Johnson, 2002; Howat & Assaker, 2013; Zeithaml, 1988), became prevalent in the literature since the 1990s (Slater, 1997; Sweeney & Soutar, 2001; Woodruff, 1997). Since then the concept has found various theoretical and contextual applications, including relationship marketing (McColl-Kennedy, Sweeney, Soutar, & Amonini, 2008; Tzokas & Saren, 1999), service-dominant logic literatures (Gummesson, 2008; Woodruff & Flint, 2006), and sports management (Howat & Assaker, 2013), as well as numerous application areas, including hospitality (Oh, 1999), e-commerce settings (Chen & Dubinsky, 2003), and telecommunication industry settings.

The perceived value concept, typically, has been considered as a multidimensional construct, although consensus concerning the dimensionality of perceived value is missing in the literature. For example, while Sheth, Newman, and Gross (1991) conceptualized perceived value as a five-dimension construct encompassing functional, social, emotional, epistemic, and conditional value, Holbrook (1994) proposed a three-dimensional conceptualization including intrinsic/extrinsic, self-oriented/other-oriented, and active/passive perceived value dimensions. Furthermore, Sweeney and Soutar (2001) proposed three dimensions incorporating emotional, social, and functional (price/value for money, performance quality) value. Consistent with extant research (e.g., Eid & El-Gohary, 2015; Sweeney & Soutar, 2001), the current research conceptualized students’ perceived value as comprising three dimensions, namely, functional, social, and emotional.

Functional value refers to the extent to which the service can achieve its utilitarian goals. In the educational context, functional value refers to students’ expectations that obtaining a university degree will allow them to attain their career objectives (Lai, To, Lung, & Lai, 2012; LeBlanc & Nguyen, 1999; Ledden, Kalafatis, & Samouel, 2007). Vekiri and Chronaki (2008) documented that students are expected to engage in academic activities that are deemed valuable and that are closely associated with their future career goals. Functional value has been found to be the chief determinant of perceived value in several settings and more specifically in the higher education sector where the trade-off between price and quality was found to predict student loyalty (Lai et al., 2012; LeBlanc & Nguyen, 1999; Ledden et al., 2007).

Social value refers to the benefits resulting from the interface between the service provider and other customers within the service context. In the higher education context, social value refers to the value that students perceive from communicating with the instructor and the other students both inside and outside the class (Lai et al. 2012; LeBlanc & Nguyen, 1999; Ledden et al., 2007).

Emotional value refers to the various affective states that may occur as a result of a consumption experience. In the current high education context this is reflected in students’ perceptions of enjoyment and happiness in under taking their studies (Lai et al. 2012; LeBlanc & Nguyen, 1999; Ledden et al., 2007).

Therefore, understanding students’ perceptions of value can assist in customizing the educational offerings to the needs of the students. It can also contribute to maximizing the students’ learning experience (Ledden et al., 2007).

The next section proceeds by reviewing key literature in the area of student readiness for cocreation.

Student Readiness for Cocreation

Despite the good intentions underlying the initiative for encouraging students to play an active role through social media engagement, the value of such an initiative will be realized only when students take part and enjoy the benefits of their participation. Thus, the current research refers to Challagalla, Venkatesh, and Kohli (2009) and proposes the concept of student “readiness for cocreation” to illustrate this notion.

Considering that customers/students generally lack the knowledge and skills to work with service providers/tertiary institutions or instructors in performing a new task, Lengnick-Hall (1996) pointed out three crucial factors that help customers/students in coperforming a new task: clarity of the task, ability, and motivation. Meuter et al. (2005) further conceptualize these three factors as key elements of the “customer readiness” concept, which is defined as a state or condition in which a consumer is ready and likely to perform a new task. Accordingly, the current research refers to this notion and proposes “student readiness for co-creation,” which is defined as “the extent to which a (student) is prepared and likely to cooperate with his/her tertiary institutions or instructors in value co-creation” (Wang et al., p. 136). These three factors, namely, student’s role clarity, ability, and motivation, which are widely established in the literature as crucial for effective participation (Lengnick-Hall, 1996; Lengnick-Hall, Claycomb, & Inks, 2000; Rodie & Kleine, 2000) and as components of the latent concept of readiness for cocreation (Meuter et al., 2005; Wang et al., 2011), are discussed in greater detail below:

Role clarity reflects the degree to which a customer is aware about what is expected of him or her in cocreating value with his or her service provider. The customer/student roles, contributions, limitations, and ways for customer/student participation should be clear, known, and consistent (Lengnick-Hall, 1996).

Ability depicts the degree to which a customer/student is capable of engaging in cocreating value with his or her service provider. Rodie and Kleine (2000) broadly defined ability as including “all pertinent resources such as knowledge, skill, experience, energy, effort, money, or time” (p. 117).

Motivation is the driving force or the catalyst that causes a customer/student to willingly engage in cocreating value with his or her service provider/tertiary institutions or instructors. In the case of coproduction service tasks, customers/students must feel that there is some intrinsic or extrinsic reward involved (Wang et al., 2011).

Student Satisfaction

Consumer/student satisfaction not only is cognitive in nature but also involves emotional aspects. Satisfaction tends to include postconsumption evaluation of a service (Eid & El-Gohary, 2015; Gallarza, Gil-Saura, & Holbrook, 2011; Rodriguez del Bosque & San Martin, 2008). A prominent view of satisfaction is that proposed by Oliver (1997) who described satisfaction as “pleasurable fulfillment” of a person’s need, desire, or goal following the consumption of a product or service, with overall satisfaction possessing a strong affective orientation regarding customers’ overall experience with a service (Baker & Crompton, 2000). Overall satisfaction, therefore, is a summary assessment of customers’ overall experiences with a service (Li & Petrick, 2010), with multiple encounters with a service probably resulting in more stable cumulative satisfaction (Homburg, Koschate, & Hoyer, 2005).

Whereas previous research used a single-item overall satisfaction measure (e.g., Ganesh, Arnold, & Reynolds, 2000), recent studies conceptualized satisfaction as a multifaceted latent construct by using a combination of items for overall satisfaction and overall experience (Brady, Knight, Cronin, Hult, & Keillor, 2005; Li & Petrick, 2010). This is also the case in the present study, in which overall satisfaction is a combination of four items.

The Moderating Role of Students’ Readiness for Cocreation Between Student’s Engagement via Social Media and Students’ Perceived Value

Tensions remain between those who believe that social media can be used to strengthen and improve the teaching service of the higher education institution, and those who believe that social media exist to disrupt (and ultimately replace) the university altogether. Researchers examined the role that social media play in the higher education classroom. Findings recognized that although students are comfortable users of social media and Web 2.0 technology, they would need guidance as how to get benefits of its effective use in the education context (Sadaf, Newby, & Ertmer, 2012; Tess, 2013).

Paul, Baker, and Cochran (2012) concluded that time spent on SNSs can negatively influence student’s academic achievement. Since the usage of these networks can decrease the period of study, it could negatively affect academic performance of students. In addition, students who often used the social networks at night do not get enough time to rest, which results in daytime fatigue due to sleep disruption, thereby decreasing students’ academic performance (Farahani, Kazemi, Aghamohamadi, Bakhtiarvand, & Ansari, 2011). In addition, Kirschner and Karpinski (2010) documented a negative relationship between the use of Facebook, which is widely investigated than most SNSs as an educational tool in the university classroom, and grade point average.

Irwin, Ball, Desbrow, and Leveritt (2012) studied the use of Facebook within higher education courses. Findings revealed that only half of the students surveyed reported that the Facebook inclusion actually supported their learning. The researchers suggested that one reason for the average perception was that the instructors were inconsistent and unclear in their integration attempts and the direction given to students.

Previous research suggested that for the service customers to comprehend specific organizational values, they should have the ability to function within a specific service context, understand what is expected of them, and gain the necessary skills and knowledge to effectively cooperate with the service provider and with other customers and to perform their “coproduction” roles effectively, otherwise the desired outcomes will not be achieved (Zeithaml & Bitner, 1996). In support of this argument, Cabiddu, Lui, and Piccoli (2013) conducted a study in the hotel industry and concluded that some hotels could successfully capture more of the value cocreated in the partnership whereas others could not because of the different readiness level of the information technology, which in turn influences the value realized.

Literature suggests that “individual readiness” influences social media utilization. Based on results of qualitative and quantitative information collected from 249 full-time and part-time faculty members, Cao and Hong (2011) concluded that personal readiness is a crucial factor in determining the effectiveness of social media utilization in teaching and its consequence on perceived student satisfaction.

Based on the above discussion, the current research proposes that the more ready students feel they are, the more likely they will perceive value out of the social media usage in teaching.

Hypothesis 1: Student readiness for value cocreation positively moderates the relationship between student social media engagement and functional value such that role clarity positively strengthens the relationship between student social media engagement and functional value (Hypothesis 1a), student ability positively strengthens the relationship between student social media engagement and functional value (Hypothesis 1b), and student motivation positively strengthens the relationship between student social media engagement and functional value (Hypothesis 1c).

Hypothesis 2: Student readiness for value cocreation positively moderates the relationship between student social media engagement and social value such that role clarity positively strengthens the relationship between student social media engagement and social value (Hypothesis 2a), student ability positively strengthens the relationship between student social media engagement and social value (Hypothesis 2b), and student motivation positively strengthens the relationship between student social media engagement and social value (Hypothesis 2c).

Hypothesis 3: Student readiness for value cocreation positively moderates the relationship between student social media engagement and emotional value such that role clarity positively strengthens the relationship between student social media engagement and emotional value (Hypothesis 3a), student ability positively strengthens the relationship between student social media engagement and emotional value (Hypothesis 3b), and student motivation positively strengthens the relationship between student social media engagement and emotional value (Hypothesis 3c).

The Relationship Between Students’ Perceived Value and Students’ Satisfaction

Extent research (e.g., Cronin, Brady, & Hult, 2000; Eid & El-Gohary, 2015; Gallarza et al., 2011; Howat & Assaker, 2013; Li & Petrick, 2010) reported that value tends to be an antecedent to satisfaction rather than vice versa. The literature depicts that perceived value has a positive direct impact on satisfaction. Accordingly, the current research proposes that the three dimensions of student’s perceived value, namely, functional, social, and emotional value, have a positive impact on student satisfaction, leading to the following hypotheses:

Hypothesis 4: Functional value is positively related with student satisfaction.

Hypothesis 5: Social value is positively related with student satisfaction.

Hypothesis 6: Emotional value is positively related with student satisfaction.

To summarize, the current research proposes that the three dimensions of students’ readiness for cocreation (i.e., role clarity, ability, and motivation) positively moderate the relationship between students’ social media engagement and the three dimensions of students’ perceived value (i.e., functional, social, and emotional value). Furthermore, each of the three dimensions of perceived value is positively associated with student’s satisfaction. Figure 1 depicts this conceptual framework of the study.

Figure 1.

Conceptual model.

Method

Measures

The measures used in the research were adapted from established scales in the literature. All of the constructs were measured using multi-item scales (G. A. J. Churchill, 1979). Respondents were asked to indicate their level of agreement with each statement on a 7-point Likert-type scale (1 = strongly disagree, 7 = strongly agree).

Student social media engagement (SSME) was operationalized as a seven-item scale adapted from Ab Hamid, Akhir, and Cheng (2012). Perceived value was operationalized as a 26-item scale adapted from Floh, Zauner, Koller, and Rusch (2014), Walsh, Shiu, and Hassan (2014), and Ledden et al. (2007). Student satisfaction was measured using four items adapted from Bowden and D’Alessandro (2011) and Oliver and Swan (1989). Student readiness for cocreation is evaluated by assessing a student’s role clarity, motivation, and ability to cooperate with his or her instructor in value cocreation. Student readiness for cocreation was measured by using Wang et al.’s (2011) scale that was developed from previous studies (Dellande, Gilly, & Graham, 2004; Meuter et al., 2005) and that operationalized student readiness for cocreation as including three dimensions, namely, role clarity (measure by a five-item scale), ability (measured by a six-item scale), and motivation (measured by a six-item scale).

To assess the construct’s face validity, six academic staff evaluated this initial item set. Construct definitions were provided, and respondents were asked to evaluate each item with respect to wording, fit with construct, and completeness. Improperly worded items were rephrased, and those that did not fit the construct definition were deleted. Moreover, to ensure that the questionnaire was clear, readable, and easy to understand, that the flow of the questions occured in a logical order, and that constructs developed in one culture have the same meaning in a different culture, the questionnaire was administered to a sample of 25 university students in Egypt (Craig & Douglas, 2000; Dillman, 2007; Mostafa, Lages, & Sääksjärvi, 2014). Based on the pretest and the pilot study, the questionnaire was then modified and finalized.

Data Collection and Sampling

An online survey was created and administered to 985 students in a business school in an Egyptian university; 353 were completed and usable, yielding a usable response rate of 36%. This sample size meets the statistical sample requirement recommended by Hair, Black, Babin, and Anderson (2010) of 5 to 10 observations for each variable and mirrors earlier research in academic engagement contexts.

As illustrated in Table 1, 56% of the respondents are male (198) and 44% female (155), with respondents’ ages ranging from 17 years or younger (8.8%) to above 27 (2.5%), with the majority of the respondents ranging between 18 and 20 years (63.5%).

Table 1.

Students’ Profile (N = 353).

Sample charactristics	n	%
Gender
Male	198	56
Female	155	44
Age (years)
≤17	31	8.8
18-20	224	63.5
21-23	80	22.7
24-26	9	2.5
≥27	9	2.5
Year of study
1	166	47
2	80	22.7
3	52	14.7
4	12	3.4
Master’s	19	5.4
Others	24	6.8

Common Method Bias

Common method bias may be the cause of the observed relationships between the measures (Podsakoff, MacKenzie, Jeong-Yeon, & Podsakoff, 2003). In particular, variation in the dependent variables may not be attributed to their predictors. Collecting cross-sectional data from a single participant (key informant) about the cause and effect of a particular variable may expose research to common method bias. Consequently, the study employed procedural steps and statistical tests recommended by Podsakoff et al. (2003) to control and test for common method bias. First, anonymity of answers was guaranteed by assuring respondents that all responses would be treated with confidentiality. Second, respondents were encouraged to report their answers honestly by assuring them that there are no correct answers. Third, items measuring different constructs were mixed when designing the questionnaire. The aim is to restrict the respondents’ ability to predict the relationships among the measures. Fourth, all questions were worded carefully to avoid ambiguous and vague terminology.

In addition to the abovementioned procedural remedies, we statistically tested for common method bias. In particular, we conducted the Harman’s single-factor test (e.g., Kemper, Schilke, Reimann, Wang, & Brettel, 2013; Podsakoff et al., 2003; Robson, Katsikeas, & Bello 2008). We ran a single-factor confirmatory factor analysis (CFA) where all items were loaded on one construct (e.g., Iverson & Maguire, 2000; Korsgaard & Roberson, 1995; Mostafa, Lages, Shabbir, & Thwaites, 2015). The one-factor model yields a very poor model fit (χ² = 9736.59, degrees of freedom [df] = 779, p = .000; root mean square error approximation [RMSEA] = .181; goodness-of-fit index [GFI] = .43; adjusted goodness-of-fit index [AGFI] = .37). The improvement in the eight-factor model fit as compared to the one-factor model fit is significant (Δχ² = 8512.25, Δdf = 198, p < .05). Based on Harman’s single-factor test, we can conclude that common method bias is not a problem in this study.

Results

Measurement Model

Lisrel 8.80 (Jöreskog & Sörbom, 1996) was used to evaluate the measurement model and then test the research hypotheses through assessment of the structural model. First, the reliability of the model was tested using Cronbach’s alpha and Fornell’s composite reliability (Fornell & Larcker, 1981). Cronbach’s reliability coefficients and composite reliability should be greater than the benchmark of .7 to be considered adequate. All reliabilities of constructs have a value higher than the minimum cutoff score of .7. Table 2 reports the measures of key constructs and primary psychometric properties.

Table 2.

Measurement Scale.

Factor/item	Standardized factor loading	t	Cronbach’s α	AVE	CR
Student social media engagement (adapted from Ab Hamid, Akhir, & Cheng, 2012)			.80	.55	.89
I can share/exchange information with teaching staff using social media.	.78	a
I can share/exchange information with other students using social media.	.79	11.19
I can obtain useful information about the course from the online teaching staff and/or students using social media.	.77	10.90
The university makes good use of social media.^b	—	—
Comments from teaching staff and/or students on social media are useful to me.	.73	10.81
Comments from teaching staff and/or students helped me decide whether or not to use social media as an aid to my learning at university.^b	—	—
I like to share my learning experiences on social media.	.74	9.81
I like to read the course-related information available using social media.^b	—	—
Functional value (adapted from Ledden, Kalafatis, & Samouel, 2007; Walsh, Shiu, & Hassan, 2014)			.93	.60	.97
I believe that a degree from my university will guarantee future employment.	.79	a
The knowledge I have acquired while at university will enable me to get promoted in my future job.	.79	16.56
A degree from my university will enable me to earn a good salary.	.83	17.61
A degree from my university is a good investment.	.82	17.40
When considering the tuition fees I pay, I believe that the price/quality ratio is good at my university.^b	—	—
I believe employers would have positive things to say about my university.	.76	15.84
I believe employers are interested in hiring students from my university.	.74	15.15
I believe that my university is aligned with the needs of industry.	.73	14.98
A degree from my university will enable me to achieve my career goals.	.79	16.53
When considering the tuition fees I pay, I believe that my university offers sufficient services.	.71	14.03
Social value (adapted from Ledden et al., 2007; Walsh et al., 2014)			.80	.57	.84
I am happy when my friends are in my classes.^b	—	—
I find courses more interesting when my friends are in my classes.^b	—	—
Working in groups has a positive effect on the value of my education.	.71	a
Social activities at my university make my studies more interesting.	.78	10.28
The support from my lecturers and other students has been important in helping me through my course.	.75	11.05
The social interaction with my lecturers and fellow students on my course makes my studies more interesting.	.86	11.96
Emotional value (adapted from Ledden et al., 2007; Walsh et al., 2014)			.84	.65	.85
I am glad that I chose this university course.	.77	a
I find my course at university interesting.	.88	16.68
I like taking courses in my university.	.77	14.59
Student satisfaction (adapted from Bowden & D’Alessandro, 2011; Oliver & Swan, 1989)			.87	.64	.86
My choice to study at this university was a wise one.	.78	a
I am always delighted with the service at my university.	.71	13.82
Overall, I am satisfied with my university.	.79	15.78
I think I did the right thing when I decided to study at this university.	.90	18.06
Role clarity (adapted from Dellande, Gilly, & Graham, 2004; Meuter, Bitner, Ostrom, & Brown, 2005; Wang, Hsieh, & Yen, 2011)			.72	.55	.78
I feel confident about how to use social media effectively for learning purposes on my courses at university.	.73	a
I am not sure how to use social media properly for learning purposes on my course at university.^b	—	—
I know what is expected of me if I use social media for learning purposes on my course at university.	.77	10.24
I am clear about the process involved in using social media for learning purposes on my course at university.	.84	11.52
I believe there are only vague instructions regarding how to use social media for learning purposes on my course at university.^b	—	—
Ability (adapted from Dellande et al., 2004; Meuter et al., 2005; Wang et al., 2011)			.68	.62	.87
I am fully capable of using social media for learning purposes on my course at university.	.82	a
I am confident in my ability to use social media for learning purposes on my course at university.	.85	17.64
Using social media for learning purposes on my course at university is well within the scope of my abilities	.79	13.61
I do not feel I am qualified for the task of using social media for learning purposes on my course at university.^b	—	—
My past experiences increase my confidence that I will be able to successfully use social media for learning purposes during my course at university.	.75	15.05
Overall, using social media for learning purposes on my course at university sometimes involves things that are too difficult for me^d.	—	—
Motivation (adapted from Dellande et al., 2004; Meuter et al., 2005; Wang et al., 2011)			.82	.64	.92
I feel motivated to use social media for learning purposes on my course at university.	.84	a
I feel motivated to share/exchange information with teaching staff and other students using social media.	.87	20.41
I feel motivated to obtain useful information about the course from the online teaching staff and student members on social media.	.87	20.38
I feel motivated to receive comments from teaching staff and students through social media.	.72	14.57
I do not feel motivated to share my learning experience on social media.^b	—	—
I feel motivated to read the learning materials available via social media to help improve my learning experience at university.	.71	14.94

Note. AVE = average variance extracted; CR = composite reliability. Fit indices: normed fit index = .96, nonnormed fit index = .98, comparative fit index = .98, incremental fit index = .98, root mean square error approximation = .054, χ² (degrees of freedom) = 1224.34 (601).

Item fixed to set scale. ^bItem dropped during scale purification.

Second, to assess the convergent validity, the individual indicator loadings, composite reliability, and average variance extracted (AVE) were calculated to evaluate the adequacy of measurement models. As shown in Table 2, all indicator loadings are greater than the recommended .7 and are statistically significant (t > |1.96|; Hair et al., 2010), thus demonstrating satisfactory explanatory power to the measurement models of the key model constructs. In addition, all composite reliabilities, ranging from .80 to .97, were above the threshold of .70 (Nunally, 1978). AVE values for all constructs, ranging from .55 to .65, were above .50. These findings demonstrate adequate convergent validity of the measurement models.

Finally, to assess the discriminant validity of the key constructs, procedures outlined by Fornell and Larcker (1981) were followed. Results showed no evidence for discriminant validity as the square roots of the AVE values are consistently greater than all corresponding correlations (see Table 2). Therefore, CFA results provides evidence of high internal consistency as well as convergent and discriminant validity.

Structural Model

The current article assumes that the effect of students’ social media engagement on perceived value depends on students’ readiness for value cocreation. A structural model with an interaction term was carried out using Lisrel 8.80. To test the moderation effect, Ping’s (1995) and Cadogan, Cui, Morgan, and Story’s (2006) procedures for assessing the structural model with interaction terms were followed. Consequently, the following five steps were carried out when preparing the data for the analysis and testing the moderating effect of SSME.

First, single indicators were created for constructs that are involved in the multiplicative interactions (SSME and the three dimensions of students’ readiness for value cocreation, namely, role clarity, ability, and motivation). However, full information scales were used for constructs that are not involved in the multiplicative interaction (functional value, social value, emotional value, and student satisfaction). Using single scores in structural models with an interaction term is recommended to minimize model complexity (e.g., Cadogan et al., 2006; Ping, 1995; Robson et al., 2008).

Second, the variables involved in the multiplicative interactions were mean centered to overcome the multi-colinearity problems resulting from the introduction of interaction terms in the structural model and to yield unbiased parameter estimates (Cadogan et al. 2006; Kemper et al., 2013; Robson et al. 2008).

Third, a main-effect CFA model was carried out where the factor loading of each of the single indicators were set at unit. Moreover, the error variance of each of these single indicators was fixed at [(1 − ρ) × σ²], where ρ is the composite reliability of the scale and σ is the indicator’s standard deviation. Based on this model, the new factor loading, error variance, and sample variance for each factor were recorded.

Fourth, the interaction term created by multiplying the score of role clarity by the score of SSME to create a new variable called “role clarity * SSME” interaction term. Similarly, interaction terms were created for both “ability” and “motivation”. As a result, another two interaction terms were created, namely, “ability * SSME” and “motivation * SSME.”

Fifth, estimates obtained in the third step were introduced to Ping’s(1995) equations to calculate the factor loading and the error variances of the interaction terms. Those equations are as follows:

λ_{xz} = λ_{x} λ_{z},

θ_{ε x z} = λ_{x}^{2} Var (X) θ_{ε z} + λ_{z}^{2} Var (Z) θ_{ε x} {+ θ}_{ε x} θ_{ε z},

where λ_xz is the loading of the interaction term,

λ_x and λ_z are the loadings of the indicators x and z on the latent variables X and Z,

$θ_{ε x z}$ is the error variance of the interaction term,

Var (X) and Var (Z) are the variances of the latent variables X and Z, and

θ_εx and θ_εz are the variances of the error terms ε_x and ε_z.

Accordingly, two nested models were carried out in which the loadings and the error variances of the interaction terms are fixed to the values estimated using the Ping’s (1995) equation. The first model is a restricted model in which the coefficients linking the interaction terms to their endogenous variable are fixed to zero. In other words, the γ parameters linking “role clarity * SSME,” “ability * SSME,” and “motivation * SSME” to functional value were fixed to zero. Also, the γ parameters linking “role clarity * SSME,” “ability * SSME,” and “motivation * SSME” to social value were fixed to zero. Similarly, the γ parameters linking “role clarity * SSME,” “ability * SSME,” and “motivation * SSME” to emotional value were fixed to zero. The second model is an unrestricted model in which all the γ parameters were freely estimated. Then the χ² of the constrained and the unconstrained model are compared as well as the model fit indices.

Results show that the unconstrained model is better than the restricted model (see Table 3). In other words, introducing the interaction term results in a decrease in χ²(3) by 321.09. The χ² difference with three degrees of freedom is significant at p < .001 (i.e., Δχ²(Δdf) = 321.09(3) > 11.34(3) at p < .01).

Table 3.

Statistics of the Constrained and the Unconstrained Models.

Model	χ² (df)	Δχ² (Δdf)	RMSEA	NNFI	CFI
Constrained	1632.52 (607)		.074	.79	.79
Unconstrained	1311.43 (604)	321.09 (3)	.064	.98	.98

Note. df = degrees of freedom; RMSEA = root mean square error approximation; NFI = nonnormed fit index; CFI = confirmatory factor analysis.

Main Effect

Student engagement via social media was found to positively affect functional value, social value, and emotional value. In other words, when the instructors engage the student via social media, the student perceives functional, social, and emotional value. This is in line with Gummerus, Liljander, Weman, and Pihlstrom’s (2012) work that concluded that engagement enhances the person perceived value of the subject of engagement. Furthermore, social media not only facilitate learning and the sharing of ideas but also represent a form of social capital and help students in facing challenges encountered during their educational experience. This finding is in line with Thomas (2002) who documented that collaborative teaching approaches that aim to cocreate the educational experience both with and between students increase students’ perceived value. The reason for this relationship could be due to the knowledge, fun, and amusement (Bijaria et al., 2013) that result from social media usage, which make the student perceives the good quality of education in relation to the cost or tuition fees he or she pays, beneficial interaction with the lecturers and other students, and a more interesting learning experience.

Moderating Effect

Hypothesis 1 (H1) proposes that student readiness for value cocreation moderates the relationship between student social media engagement and functional value. Results supported H1, that is, H1a, H1b, and H1c were supported. This findings imply that each of role clarity, student ability, and his or her motivation moderates the relationship between SSME and functional value. This means that when student understands what is expected of him or her in cocreating value via social media, he or she perceives the social media engagement to achieve its utilitarian value. In addition, H2 was supported, that is, H2a, H2b, and H2c. These findings imply that each of role clarity, student ability, and his or her motivation moderate the relationship between SSME and social value. This means that when the student is ready to take role in value creation via social media, he or she perceives the social media engagement to be contributing to social value. In other term, students’ readiness for value creation strengthens the consequences of social media engagement by enhancing student perception of social interaction with their lecturers and fellow students. Results showed partial support of H3, that is, H3a and H3b were supported but H3c was not supported. These findings imply that both role clarity and student ability moderate the relationship between SSME and emotional value. However, student motivation does not moderate the SSME and emotional value relationship.

H4, H5, and H6 were supported. These findings mean that the three dimensions of perceived value, that is, functional value (H4), social value (H5), and emotional value (H6), positively affect students’ satisfaction. These findings show that when the student perceives the academic engagement via social media to perform its utilitarian purposes, he or she becomes satisfied. In other words, student perception of being academically engaged via social media will enable him or her to achieve career goals, which in turn enhances his or her satisfaction. Consistent with previous research findings, the current research found functional value to be the primary determinant of value perceptions as in prior studies and more specifically in the higher education sector where the price–quality trade-off was found to predict student outcomes (LeBlanc & Nguyen, 1999).

In addition, when the student perceives the academic engagement via social media to be of social value, he or she becomes satisfied. In other words, student perceives being academically engaged via social media to be of value to the interaction with the instructors and other students, which in turn enhances his or her satisfaction. Furthermore, when the student perceives the academic engagement via social media to be of emotional value, he or she becomes satisfied. In other words, students perceived being academically engaged via social media to be a source of enjoyment and gladness in undertaking their studies, which in turn enhanced his or her satisfaction.

In addition, the R² values (explained variance) are reported in Table 4 and range from .33 to .60. The R² results of the tested model demonstrated that a substantial part of the variance of the endogenous latent constructs could be explained by the model since the exogenous variables explain more than the required 30% of the variance of the corresponding endogenous variables (Bruhn, Schnebelen, & Schäfer, 2014; Chin, 1998; Floh et al., 2014; Howat, & Assaker, 2013). In particular, the results indicate that 36% of the variance in functional value trust can be explained by the student engagement via social media and the interaction between student engagement via social media and each of the role clarity, ability, and motivation, and 44% of the variance in the social value can be explained by the student engagement via social media and the interaction between student engagement via social media and each of the role clarity, ability, and motivation. The percentage of variance in the emotional value, as explained by the student engagement via social and the interaction term represented by the student engagement via social media and each of the role clarity, ability, and motivation, was 33%. Likewise, the student engagement via social media and the interaction between student engagement via social media and each of the role clarity, ability, and motivation explain 60% of the variance in student satisfaction. Table 4 summarizes the results of the structural equation model.

Table 4.

Path Estimates, t Values, Hypotheses Assessment, and R² of the Unconstrained Model.

Hypothesis (H)	Independent variables	Dependent variables	Path estimate	t	Assessment	R ²
H1a	Social media engagement	Functional value	0.42	10.39***	S	.36
H1a	Social media engagement × role clarity		0.065	3.75***	S
H1b	Social media engagement		0.55	14.90***	S
H1b	Social media engagement × ability		0.048	10.88***	S
H1c	Social media engagement		0.51	13.60***
H1c	Social media engagement × motivation		0.052	11.23***
H2a	Social media engagement	Social value	0.56	11.93***	S	.44
H2a	Social media engagement × role clarity		0.042	10.60***	S
H2b	Social media engagement		0.32	9.09***	S
H2b	Social media engagement × ability		0.039	3.27***	S
H2c	Social media engagement		0.56	11.93***	S
H2c	Social media engagement × motivation		0.042	10.60***	S
H3a	Social media engagement	Emotional value	0.32	8.33***	S	.33
H3a	Social media engagement × role clarity		0.064	3.62**	S
H3b	Social media engagement		0.64	13.97***	S
H3b	Social media engagement × ability		0.17	9.19***	S
H3c	Social media engagement		0.52	11.86***	NS
H3c	Social media engagement × motivation		−0.022	−1.60	NS
H4	Functional value	Student satisfaction	0.36	4.42***	S	.60
H5	Social value		0.29	3.61***	S
H6	Emotional value		0.34	5.81***	S

Note. S = supported; NS = not significant.

p < .10. **p < .05. ***p < .01.

Discussion and Implications

The present research findings are expected to provide valuable insights both to scholars and tertiary institutions. For scholars, an enhanced understanding of the student engagement–perceived value interface provides a valuable addition to the existing customer value literature (e.g., Woodruff, 1997), as well as the emerging customer engagement literature (e.g., Van Doorn et al., 2010). Specifically, enhanced scholarly understanding of the customer engagement–perceived value interface is priceless based on its expected additional predictive or explanatory power of focal consumer/student behavior outcomes (Bowden, 2009; Wang et al., 2011). Moreover, this article contributes to the marketing literature by examining new relationships as following: (1) The moderating role of student readiness for cocreation to the relationship between student engagement via social media and each dimension of perceived value and (2) the impact of each of functional, social, and emotional value on student satisfaction.

For tertiary institutions and instructors, perhaps the most vital challenge for these higher education institutions at present is to engage in considered and realistic debates over how best to enhance students’ readiness to actively participate in value creation by using social media in appropriate ways that hopefully reduce disappointment and enhance positive learning experience. To earn customer cooperation in value cocreation, tertiary institutions and instructors can focus on improving customer readiness by increasing understanding, ability, and motivation toward activities related to value cocreation. Based on the research findings, six practical suggestions are provided for enhancing customer readiness for cocreation: First, tertiary institutions and instructors can provide rich information to students in order to prevent them from defecting and to maximize the utility of social media in education. Second, tertiary institutions and instructors should make the suitable changes that higher education needs to remain relevant in the apparently fast-changing digital age and to enhance the curriculum and design more engaging, interactive learning environments, which in turn improve learning outcomes. Third, tertiary institutions should take effective steps to reform education by promoting student learning via students’ engagement by improving the pedagogical practices (Taylor et al., 2011) that large universities are increasingly offering in classes of 300+ students (O’Reilly, Rahinel, Foster, & Patterson, 2007) as in the case of most of the Egyptian universities. Fourth, educators should explicitly make efforts to persuade students to be more engaged given Sierra’s (2010) findings that student perceptions of shared responsibility for learning are positively associated with attitudinal, emotional, and behavioral factors—in addition to grades. Students’ intrinsic motivation could be further encouraged by setting clear, understandable, and attainable expectations of cocreation of value early in academic programs of study and at the beginning of each course. Fifth, despite the vivid benefits of social media as a pedagogical tool in education, some academic departments in the universities have implemented strict rules against using social network sites in students’ computing labs and public access computers. It is now time for tertiary institutions to acknowledge the influential benefits of these sites in achieving educational goals.

Future Research

There is a paucity of research on student engagement, however this study is one of the first empirical studies to identify the moderating role of student readiness for cocreation in education to student engagement–student perceived value relationship and to study their impact on student satisfaction. In the future, more studies are needed on how to increase students’ readiness for value cocreation. For example, future research can study the role of student socialization in enhancing student readiness for value cocreation. Consistent with Hollebeek (2011b) and Gummerus et al. (2012), the current research agrees that there is a need for both theoretical and empirical studies on the nature and measurement of customer engagement and student engagement with new technological tools in particular. Furthermore, studies that help better identify the nomological framework within which student engagement operates are recommended. Despite the current research examined perceived value as an output of student engagement, the outcome of the latter should not be simplified to the element of perceived value. For example, future research examining other variables such as student learning outcomes, grades, loyalty, and student retention vis-à-vis student engagement appears worthy of additional work. Finally, future research can examine the research model in different cultures to investigate student readiness for cocreation in education to the student engagement–student perceived value relationship.

Conclusion

The wide use of social media is a promising venue in offering new ways of student engagement and educational settings. This article contributes to marketing literature by shedding light on the relationship between student engagement, perceived value, and satisfaction in the context of a social media in higher education. Although, previous research has suggested that perceived value positively affects satisfaction, this study contributed to knowledge by examining the impact of each dimension of perceived value (i.e., functional, social, and emotional) on satisfaction. Moreover, this article provides insightful suggestions for tertiary institutions where educators interested in positively increasing the perceived value of students in relation to student engagement with social media should consider enhancing role clarity, boosting student’s motivation, and increasing students’ ability to value cocreation. The results of the study show that the effect of students’ social media engagement on perceived value depends on students’ readiness for value cocreation. In addition, findings revealed that collaborative teaching approaches that aim to cocreate the educational experience both with and between students increase students’ perceived value and satisfaction.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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