Social media use and student creativity: The mediating role of student engagement
Main Article Content
Fostering student creativity is widely accepted as an important goal in Chinese higher education, and social media is now integrated into students’ everyday lives. I investigated how social media use in study contexts is related to students’ engagement and creativity. A validated questionnaire was used to collect data from 652 undergraduate students at 3 Chinese public universities. Structural equation modeling results show that social media use in study contexts was related to student engagement and creativity, and that student engagement partially mediated the relationship between social media use and student creativity. This provides insight into how to promote student creativity. Theoretical and practical implications of the results are presented, and future directions for research are discussed.
China is encouraging mass entrepreneurship and innovation, and the implementation of students’ creativity and innovation has become imperative (Wang & Chen, 2016; Zhou, 2017). The development of student creativity in higher education has been widely discussed in the literature (e.g., Barrett & Donnelly, 2008; Cole et al., 1999; Gu et al., 2014; Yu, 2014). Much attention has been paid to identifying factors that might play a role in facilitating student creativity. For example, Barrett and Donnelly (2008) proposed a conceptual framework and suggested three approaches for fostering student creativity: participatory teaching techniques (including role playing, debates, poster presentations, and one-on-one tutorials), social and supportive factors (including coaching and feedback, formative assessment, self-review and peer review, and providing encouragement), and whole curriculum change (including problem solving, game-based learning, real-life scenarios, and group work). Niu (2007) found a significant association between Chinese students’ creativity and both individual factors—such as intelligence, knowledge, motivation, and thinking styles—and environmental factors—such as school and family environment. Recently, the proposed effects of social media, as a Web 2.0 tool, on higher education have attracted increased scholarly attention (Hull & Dodd, 2017; Selwyn, 2009). Previous research has revealed that social media use may enhance studying and learning in higher education, and improve students’ performance (Dzvapatsva et al., 2014; Evans, 2014).
Past research has mainly been focused on the impacts of social media use on academic performance, which aligns with educational policies (Dzvapatsva et al., 2014). Student creativity, which refers to “the tendency of a student to generate novel ideas that are useful in product or service implementation within an individual learning environment, through interaction and knowledge sharing with other students” (Tsai et al., 2015, p. 29), is accepted as an important educational goal (Lucas et al., 2013). Because of its openness and interactivity, social media is important for fostering student creativity in higher education (Jahnke, 2011). However, little research attention has been paid to this issue.
China has the largest number of Internet-using citizens, at 854 million, and they spend an average of 27.9 hours a week online (China Internet Network Information Center, 2019). Students comprise 26% of Chinese netizens (China Internet Network Information Center, 2019), which demonstrates that social media is integrated into students’ personal lives in China. Thus, I explored the relationship between social media use and student creativity as well as the mediating effect of student engagement in this relationship in the Chinese educational context. The conceptual framework for this research is presented in Figure 1.
Figure 1. Research Conceptual Framework
Literature Review and Hypotheses
The facilitation of student creativity depends on a positive educational environment (Deng et al., 2016; Wu et al., 2014). Tsai et al. (2015) found that positive environments can enhance student creativity, whereas negative environments are harmful to student creativity. Social media, which is defined as a “set of interactive technology tools designed to encourage social networking and dialogic communication in virtual communities and networks” (Kassamali et al., 2015, p. 491), can create positive student-centered environments by providing innovative ways for facilitating communication between teachers and students, as well as collaboration among students (Chan & Leung, 2016). In such learning environments, students’ creative skills will improve (Davies et al., 2013).
Information and communication technology (ICT) resources can be used to support students in developing their creativity (Wood & Ashfield, 2008). Access to new or different media and technologies has been shown to stimulate creativity (Halsey et al., 2006). Stolaki and Economides (2018) also found that students with greater knowledge and use of ICT scored higher on creativity. Social media, as an ICT-based tool (Jena, 2015), empowers an individual to participate in collaborative and conversational knowledge management, thus contributing to their cognitive and creative processes (Sigala & Chalkiti, 2015). In the work context, social media use has been found to be positively associated with employee innovative performance (Cheng et al., 2020). I expected to find a similar positive relationship between social media use and student creativity in a study context; therefore, I proposed the following hypothesis:
Hypothesis 1: Social media use will be positively related to student creativity.
Student engagement refers to “both the time and energy students invest in educationally purposeful activities” (Rutherford, 2010, p. 704). More and more students are using social media in their academic life to communicate with others about course-related topics, collaborate on assignments, coordinate study groups, and contact faculty, all of which enhance student engagement (Brooks, 2016; Laird & Kuh, 2005). Ivala and Gachago (2012) suggested that social media has the potential to increase students’ levels of engagement in learning both on- and off-campus through its promotion of enhanced interaction and communication between students and lecturers. Prior researchers have observed that social media sites like Twitter and Facebook can be utilized in higher education to foster student engagement (Dragseth, 2020; Glowatz & Bofin, 2014).
Individual creativity has been linked to individual engagement (Georgiades, 2015), and Gardiner (2017) argued that student engagement and creativity are also fundamentally and reciprocally linked. Richardson and Mishra (2018) pointed out that a learning environment characterized by student engagement; the physical environment (e.g., furniture and workspaces); and a learning climate of community, care, and cooperation that emphasizes positive student–teacher relationships all play an essential role in supporting student creativity. Alexander (2009) revealed that students who manifest higher levels of engagement with technology, learning tasks, and content demonstrate more higher order thinking and creativity. As such, by facilitating communication among students and teachers about studying, social media use will influence student engagement, which will have a powerful effect on student creativity. Therefore, I proposed the following hypothesis:
Hypothesis 2: Social media use will have an indirect positive relationship with student creativity via the mediator of student engagement.
Method
Participants and Procedure
Participants were undergraduate students from three Chinese public universities with which I have a close connection. After obtaining approval from the ethics committee and permission from the school authorities concerned, I distributed 685 paper-based questionnaires to students via faculty members at each university. I received back 652 valid forms, resulting in a response rate of 95.2%. Among the participants, 45% were men and 55% were women. Their average age was 20.40 years (SD = 1.04, range = 18–21), and 27% were first-year students, 38% were second-year students, and 35% were third-year students. (Fourth-year students were in internships during the study.)
Measures
The questionnaire was translated into Chinese and back-translated into English by bilingual researchers to ensure semantic equivalence across the two cultures. After 20 students participated in the pilot test, I revised the wording and meaning of some items for ease of understanding in Chinese. All measures were rated on a 5-point Likert scale ranging from 1 = strongly disagree to 5 = strongly agree.
Social Media Use
Social media use was assessed with a three-item scale taken from Cao et al. (2016). The original items were modified to relate specifically to usage in study contexts: “I use social media to maintain and strengthen communication with schoolmates and teachers when I am studying,” “I use social media to obtain study-related information and knowledge,” and “I often use social media when I am studying.” Cronbach’s alpha for this scale was .91.
Student Engagement
Student engagement was assessed with Maroco et al.’s (2016) 15-item University Student Engagement Inventory. This consists of five items each for behavioral engagement (e.g., “I pay attention in class”), emotional engagement (e.g., “I like being at school”), and cognitive engagement (e.g., “I try to integrate the acquired knowledge in solving new problems”) dimensions. Cronbach’s alphas for behavioral, emotional, and cognitive engagement were .85, .80, and .83, respectively.
Student Creativity
Student creativity was assessed with a five-item scale taken from Tsai et al. (2015), which is based on Zhou and George’s (2001) creativity scale. A sample item is “I come up with creative solutions to problems.” Cronbach’s alpha for this measure was .83.
Results
Measurement Model
The scales were validated using confirmatory factor analysis. As shown in Table 1, the proposed three-factor model (social media use, student engagement, and student creativity) had a good fit to the data, with composite reliability > .70 and average variance extracted > .50. These results provide support for the measures’ convergent and discriminant validity.
Table 1. Descriptive Statistics, Composite Reliability, Average Variance Extracted, and Fit Indices for Study Variables
Note. CR = composite reliability; AVE = average variance extracted; χ2/df = chi square/degrees of freedom; RMSEA = root mean square error of approximation; CFI = comparative fit index; IFI = incremental fit index.
** p < .01.
Hypothesis Testing
In line with the conceptual framework, social media use was positively related to student creativity, β = .37, 95% confidence interval (CI) [.23, .51], supporting Hypothesis 1. Further, the relationships between social media use and student engagement, β = .44, 95% CI [.28, .61], and between student engagement and student creativity, β = .27, 95% CI [.13, .41], were both significant. Additionally, results of a bootstrapping analysis of 5,000 replications with bias-corrected 95% CI show that the indirect effect of social media use on student creativity through student engagement was significant, effect size = .12, 95% CI [.07, .22]. Thus, Hypothesis 2 was supported.
Discussion
Recently, the Chinese Ministry of Education has been promoting the integration of information technology into higher education, and has set a goal of developing student creativity. This study provides evidence concerning the associations between social media use, student engagement, and student creativity (Dragseth, 2020; Gardiner, 2017; Glowatz & Bofin, 2014). Consistent with my hypotheses, I found direct and indirect relationships between social media use and student creativity, with student engagement acting as a mediator of this relationship.
Theoretical and Practical Implications
This study contributes to the literature on the social media use–student creativity relationship in two ways: First, the positive relationship I observed between social media use and student creativity aids understanding of the positive consequences of social media use. This finding lends support to the view that the use of social media in learning is advantageous (Hashim et al., 2017) because it facilitates collaborative work and sparks reflective thinking (Wakefield et al., 2011). In such environments, social media tools offer students the ability to think critically and creatively (Tadros, 2011). Second, this study provides empirical evidence and a theoretical explanation for why students are more creative when using social media while learning. Student engagement exerts a mediating effect on social media use because learning outcomes depend on the degree of students’ engagement in school (Ko et al., 2015). Thus, to enhance student creativity, it is important to cultivate student engagement.
From a practical perspective, this study provides insight into how social media use in study contexts facilitates student creativity partially through the enhancement of student engagement. Thus, for universities that want to enhance their students’ creativity, it is beneficial to endorse social media tools and encourage students to incorporate these into their learning experiences. Teachers may use social media tools to integrate informal learning into formal learning environments, offer course content in a more participatory manner, deliver group assignments, and facilitate online course discussion (Chen & Bryer, 2012; Guy, 2012). Meanwhile, educators should engage with opportunities provided by social media tools to bring change to the learning process and curriculum, which will significantly improve the effectiveness of social media use.
Limitations and Future Research Directions
One limitation in this study is that cross-sectional data do not allow for the inference of causal relationships. Future researchers could adopt a longitudinal design to confirm causality. Another limitation is that I explored only the advantages of social media use in learning; disadvantages for students might also exist. Raut and Patil (2016) argued that the primary negative impact of social media is addiction, which can negatively affect valuable activities such as students’ concentration on their studies and time spent researching additional information to increase their knowledge base. Comparing the advantages and disadvantage of social media would extend understanding of their value for student creativity. Finally, generalization of my findings to other populations, such as students in private universities in China and students in other countries, should be undertaken with caution.
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Chan, W. T. Y., & Leung, C. H. (2016). The use of social media for blended learning in tertiary education. Universal Journal of Educational Research, 4(4), 771–778.
https://doi.org/10.13189/ujer.2016.040414
Chen, B., & Bryer, T. (2012). Investigating instructional strategies for using social media in formal and informal learning. The International Review of Research in Open and Distance Learning, 13(1), 87–100.
https://doi.org/10.19173/irrodl.v13i1.1027
Cheng, T., Zhang, P., Wen, Y., & Wang, L. (2020). Social media use and employee innovative performance: Work engagement as a mediator. Social Behavior and Personality: An international journal, 48(1), Article e8698.
https://doi.org/10.2224/sbp.8698
China Internet Network Information Center. (2019). The 44th China statistical report on Internet development [In Chinese]. https://bit.ly/2NDbmt5
Cole, D. G., Sugioka, H. L., & Yamagata-Lynch, L. C. (1999). Supportive classroom environments for creativity in higher education. Journal of Creative Behavior, 33(4), 277–293.
https://doi.org/10.1002/j.2162-6057.1999.tb01407.x
Davies, D., Jindal-Snape, D., Collier, C., Digby, R., Hay, P., & Howe, A. (2013). Creative learning environments in education—A systematic literature review. Thinking Skills and Creativity, 8, 80–91.
https://doi.org/10.1016/j.tsc.2012.07.004
Deng, L., Wang, L., & Zhao, Y. (2016). How creativity was affected by environmental factors and individual characteristics: A cross-cultural comparison perspective. Creativity Research Journal, 28(3), 357–366.
https://doi.org/10.1080/10400419.2016.1195615
Dragseth, M. R. (2020). Building student engagement through social media. Journal of Political Science Education, 16(2), 243–256.
https://doi.org/10.1080/15512169.2018.1550421
Dzvapatsva, G. P., Mitrovic, Z., & Dietrich, A. D. (2014). Use of social media platforms for improving academic performance at further education and training colleges. SA Journal of Information Management, 16(1), Article a604.
https://doi.org/10.4102/sajim.v16i1.604
Evans, C. (2014). Twitter for teaching: Can social media be used to enhance the process of learning? British Journal of Educational Technology, 45(5), 902–915.
https://doi.org/10.1111/bjet.12099
Gardiner, P. (2017). Playwriting and flow: The interconnection between creativity, engagement and skill development. International Journal of Education & the Arts, 18(6). https://bit.ly/2Wcyljk
Georgiades, S. (2015). Employee engagement implementation leading towards employee creativity. In S. Georgiades (Ed.), Employee engagement in media management (pp. 83–100). Springer International Publishing.
https://doi.org/10.1007/978-3-319-16217-1_5
Glowatz, M., & Bofin, L. (2014). Enhancing student engagement through social media: A school of business case study. BLED 2014 Proceedings, 37, Article 15. https://bit.ly/2Wd5rj6
Gu, J., Zhang, Y., & Liu, H. (2014). Importance of social capital to student creativity within higher education in China. Thinking Skills and Creativity, 12, 14–25.
https://doi.org/10.1016/j.tsc.2013.12.001
Guy, R. (2012). The use of social media for academic practice: A review of literature. The Kentucky Journal of Higher Education Policy and Practice, 1(2), Article 7.
https://doi.org/10.13023/KJHEPP.2012.01.2.7
Halsey, K., Jones, M., & Lord, P. (2006). What works in stimulating creativity amongst socially excluded young people. National Foundation for Educational Research. https://bit.ly/3gVc9C2
Hashim, K., Kutbi, I., & Al-Sharqi, L. (2017). University students’ perceptions of social media as a learning tool: A science discipline perspective. Advances in Social Sciences Research Journal, 4(19), 9–31.
Hull, K., & Dodd, J. E. (2017). Faculty use of Twitter in higher education teaching. Journal of Applied Research in Higher Education, 9(1), 91–104.
https://doi.org/10.1108/JARHE-05-2015-0038
Ivala, E., & Gachago, D. (2012). Social media for enhancing student engagement: The use of Facebook and blogs at a university of technology. South African Journal of Higher Education, 26(1), 152–167.
https://doi.org/10.20853/26-1-156
Jahnke, I. (2011). How to foster creativity in technology enhanced learning? In B. White, I. King, & P. Tsang (Eds.), Social media tools and platforms in learning environments: Present and future (pp. 95–116). Springer.
https://doi.org/10.1007/978-3-642-20392-3_6
Jena, R. K. (2015). Technostress in ICT enabled collaborative learning environment: An empirical study among Indian academician. Computers in Human Behavior, 51(B), 1116–1123.
https://doi.org/10.1016/j.chb.2015.03.020
Kassamali, R. H., Palkhi, E. Y. A., & Hoey, E. T. (2015). Social media in clinical radiology: Have you updated your status? Quantitative Imaging in Medicine and Surgery, 5(4), 491–493.
https://doi.org/10.3978/j.issn.2223-4292.2015.07.05
Ko, J. W., Park, S., Yu, H. S., Kim, S.-J., & Kim, D. M. (2015). The structural relationship between student engagement and learning outcomes in Korea. The Asia-Pacific Education Researcher, 25, 147–157.
https://doi.org/10.1007/s40299-015-0245-2
Laird, T. F. N., & Kuh, G. D. (2005). Student experiences with information technology and their relationship to other aspects of student engagement. Research in Higher Education, 46, 211–233.
https://doi.org/10.1007/s11162-004-1600-y
Lucas, B., Claxton, G., & Spencer, E. (2013). Progression in student creativity in school: First steps towards new forms of formative assessments. OECD Education Working Papers, 86.
https://doi.org/10.1787/5k4dp59msdwk-en
Maroco, J., Maroco, A. L., Campos, J. A. D. B., & Fredricks, J. A. (2016). University student’s [sic] engagement: Development of the University Student Engagement Inventory (USEI). Psicologia: Reflexão e Crítica, 29, Article 21.
https://doi.org/10.1186/s41155-016-0042-8
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Figure 1. Research Conceptual Framework
Table 1. Descriptive Statistics, Composite Reliability, Average Variance Extracted, and Fit Indices for Study Variables
Note. CR = composite reliability; AVE = average variance extracted; χ2/df = chi square/degrees of freedom; RMSEA = root mean square error of approximation; CFI = comparative fit index; IFI = incremental fit index.
** p < .01.
The author thanks Dr. Liyin Wang for assistance with the survey and helpful discussion.
Xiaomeng Sun, Graduate School, University of Perpetual Help System DALTA, Alabang-Zapote Avenue, Pamplona 3, Las Piñas, 1740, Manila City, Republic of the Philippines. Email: [email protected]