Understanding the relationship between new media literacy,communication skills,and democratic tendency: Model development and testing

Abstract

New media provides new sources of information and communication that are crucial for participatory behaviors. Therefore, scholars conceptualize new media literacy (NML) that citizens should have to function successfully in this digital era. This study proposed and tested a structural model that examines multiple relationships among NML, communication skills (CS), and democratic tendency (DT). Data were collected from 1047 Turkish university students and analyzed through structural equation modeling. Using a comprehensive theoretical framework from the literature, NML was operationalized through four factors: functional consuming (FC), critical consuming (CC), functional prosuming (FP), and critical prosuming (CP). The results showed that FC and FP had a positive effect on CC, CP, and CS; CC had a positive effect on CP and DT; and CS had a positive effect on CC and DT. Findings of indirect effects revealed that CC and CS played mediation roles in the relationship of FC and FP with DT.

Keywords

Communication skills democratic tendency new media literacy structural equation modeling university students

Introduction

In the 21st century, digital technology–based new media provides more opportunities for deliberation, discussion, sharing, equity, and participation, thus aiding democratic processes. People can create free communication that is less susceptible to censorship and has a higher reach. Social networking sites can be used for not only keeping in touch with relatives but also forming political and social organizations, publishing news, marketing products, and so on. Therefore, today’s citizens can engage in new media and have a digital presence in order to reinforce the representation of their opinions and works in policy-making. Social media has become the driving force of mass public actions as experienced in contemporary social movements all over the world. Evidence suggests that social media provides new sources of information and channels of interpersonal communication that are crucial in shaping citizens’ participatory behaviors (Tufekci, 2017). Interacting with social, political, and cultural dynamics, new technologies play a significant role in the defense of democracy and human rights by offering greater access to information and connection with others. Social media facilitates participation and shapes public opinion through acting as a forum for gathering information, creating mobile network ties to various groups, and allowing for observation of peer actions (Boulianne, 2015). Such affordances of new media inherently bring along the necessity of new competencies that any citizen should have to function successfully in this digital era. Scholars attempt to describe the concept of new media literacy (NML), identify what kinds of proficiencies one needs to have to become new media competent, explore the roles NML plays in everyday life, and develop school curriculums to promote NML skills. With these developments in mind, in this study, we focus on the complex interplay of new media, communication, and democracy by investigating potential contributions of people’s new media competencies to their communication and democratization processes. Drawing on both theoretical and empirical findings from the prior literature on new media, we built an acceptable model addressing the relationships among NML, communication skills (CS), and democratic tendencies (DTs) and tested this model using structural equation modeling (SEM) techniques on a sample of university students. Our study has the potential to contribute to growing research body on new media by exploring how individuals’ use of new media affects their communicative and democratic competencies. In doing so, it can shed some light on a comprehensive assessment of the role of new media in people’s lives.

New media

New media is a relatively recent phenomenon and can be broadly defined as a combination of socio-cultural environments engendered by network technologies in which any messages are digitally created and distributed by any users (Koc and Barut, 2016). Major differentiating characteristics of new media from traditional media include digital nature, interactivity, collective participation, and user-generated content (Chen et al., 2011). Not only webmasters but also end users (i.e. consumers) can now produce media content by interacting with other users and using existing content. For this reason, the boundaries between media producers and consumers have become blurred to create a convergence culture. Web 2.0 tools including social networking sites, image and video sharing sites, and instant messaging applications are commonly used new media forms these days. Using Web 2.0, anyone can create media messages combined with their own texts, images and videos, and instantly share them with others anytime and anywhere by means of mobile devices. Therefore, technological advancements enable passive media consumers to become active media producers.

Besides the aforementioned opportunities, new media poses some challenges such as digital privacy management, cyberbullying, cyber security risks, skepticism about the reliability of online content, and so on. For example, the spread of fake news or a narrow network of like-minded individuals on social media may be conducive to an increase in polarization and fragmentation, endangering shared understandings that are crucial for a well-functioning democracy (Sunstein, 2017). New media users are likely to be exposed to digital messages which are actually recopied multiple times with large variations. Treating these as if they were independent and original induces amplification of information and sometimes polarization. Of course, disusing new media or staying away from it is not a wise decision for these uncertainties and challenges. Individuals rather need to understand ongoing digital transformations and gain the necessary knowledge and skills in order to both protect themselves against the risks and sustain themselves by harnessing maximum benefits.

NML

NML is an emerging concept and refers to a set of competencies that enables individuals to handle the challenges and demands of living in today’s increasingly digitalized society. Empowering students with NML is the most urgent issue of most countries’ educational agenda (Chen et al., 2018). Under the pressure of digital technologies, current schooling prioritizes digital intelligence in addition to language, math, and social skills. NML is not only about skills for using digital devices or applications, which are required but not enough to survive in the digital era. NML is also a multidimensional competence and goes beyond narrow skills to technical, social, emotional, and critical thinking skills. Brown (2018) states that 21st-century capabilities encompass both functional and critical skills including technical proficiency, communication and collaboration, digital content creation and sharing, active participation, problem-solving, digital identity and citizenship, online safety and well-being, and so on. He argues that today’s citizens should be equipped with critical mindsets rather than mere technical skills so that they can become critical thinkers, consumers, creators, and citizens. Therefore, with the rapid diffusion of new media into every aspect of society and its usage becoming a routine part of everyday life, NML acquisition becomes important for not only children but also all generations. In fact, adults need to be new media literate in order to be able to sustain themselves as well as help their kids fully function in the 21st digitalized society.

Considering both technical and socio-cultural aspects of new media, Chen et al. (2011) proposed a theoretical framework for unpacking NML. They conceptualized NML by means of two continuums: from consuming to prosuming media literacy, and from functional to critical media literacy. The former highlights the unique characteristics of new media, expanding users’ consumptive abilities to productive ones. The latter emphasizes the ability of questioning and evaluating media tools and messages in addition to accessing and operating them. Chen et al. (2011) view functionality as essential to utilize new media technologies but inadequate to get a good grasp of their social, economic, and political contexts. Hence, they call for criticality for understanding and constructing various ideologies and power positions in new media spaces. Intersecting these continuums, Chen et al. (2011) identified four dimensions of NML: functional consuming (FC), critical consuming (CC), functional prosuming (FP), and critical prosuming (CP). FC refers to the ability to access and understand media content at the textual level. CC involves the ability to analyze and criticize media content and its embedded meanings and affects at the contextual level (e.g. social, economic, and political). FP refers to the capability to operate media technologies in order to create media messages and participate in new media platforms. CP involves the competence to convey personal beliefs and values in a productive way, negotiate with others’ ideas, and consider expected impacts during media construction and participation. As can be seen from these definitions, NML is a contemporary and comprehensive set of media skills. It is a convergence of all other media-related competencies such as audiovisual literacy, information literacy, digital literacy, and so on (Chen et al., 2011). It includes both information literacy which mainly focuses on media consumption skills (FC and CC) and digital literacy which primarily centers on functional media skills (FC and FP). By expanding both information and digital literacy, NML emphasizes criticality in media prosumption (CP) due to the aforementioned unique features of new media technologies.

Building on the NML framework of Chen et al. (2011), Lin et al. (2013) proposed a refined version by identifying 10 fine-grained indicators to further elaborate NML components. In their refinement, FC is further represented by two indicators: consuming skill and understanding. The consuming skill refers to the technical skills required for accessing and operating basic hardware and software, while the understanding involves the proficiency of capturing the meaning of media content at a literal level. CC is elaborated by three indicators: analysis, synthesis, and evaluation. These focus on abilities such as deconstructing media messages with the recognition of media construction as a subjective and social process, sampling and remixing media content in a meaningful way, and criticizing media contents and making decisions about the reliability and credibility of media sources, respectively. FP is unpacked by three indicators: prosuming skill, distribution, and production. Like consuming skill, the prosuming skill involves technical capabilities to produce media contents. The distribution refers to sharing and networking activities to disseminate media messages. The production focuses on the competencies to duplicate, rearrange, and mix different formats of media content. CC is characterized by two indicators: participation and creation. Participation indicates the ability to interactively and critically participate in new media spaces, which requires social skills to achieve digital communication and collaboration. The last indicator, creation, involves the competency of creating media contents embedded with socio-cultural values and ideologies with a critical understanding of their consequences. Further explanation of these indicators can be found at Lin et al. (2013) because it is not the main focus of this study.

Research model and hypotheses

The growing popularity of new media has recently attracted educators and researchers to explore where youngsters are germane to their abilities to take part in this new media ecology, what roles it plays in their everyday lives, and how it affects their developments. Since NML is an emerging concept, the available research is limited and has particularly focused on theoretical conceptualization of NML (Lin et al., 2013), development of research instruments to measure NML (Koc and Barut, 2016; Lee et al., 2015), and exploration of youngsters’ NML levels (Chen et al., 2018; Kara et al., 2018). There are unexplored issues in this growing literature that warrant for further inquiry. For instance, research exploring the influences of NML on attitudes and behaviors in social and political life is scarce. Thus, in this study, we sought to propose and test a structural model that examines multiple relationships among NML, CS, and DT. The research questions are given below and the hypothesized structural relationships among these constructs are shown in Figure 1. The following subsections explain the underlying justification for research hypotheses:

RQ1. How do NML competencies associate with each other?

RQ2. What roles do NML competencies play in influencing CS and DT?

RQ3. How does CS mediate the relationships between NML components and DT?

Figure 1.

Graphical representation of the research model.

NML components

We developed our model based on the theoretical framework of Lin et al. (2013) because it inclusively elaborates unique features of NML through its well-defined four components: FC, CC, FP, and CP. Although NML involves all these components, it particularly emphasizes prosuming skills (FP and CP) as different from traditional media literacy due to user-generated content and active participation offered by new media technologies. Referring to Toffler’s (1981) concept of “prosumer,” Chen et al. (2011) assert that a media prosumer is both a producer and a consumer since he or she often produces customized media products based on pre-existing media artifacts. New media users can make further contributions or revisions to others’ content. For example, they can read and interpret one another’s comments when making their own comments to a YouTube video or responding to a tweet. Therefore, media consumption is integrated into the process of media prosumption including production and participation.

On the other hand, functional media literacy can be considered as a prerequisite for critical media literacy. Users first need to know how to operate media tools in order to analyze, criticize, and judge the messages at hand. Van Deursen and Van Dijk (2011) classify Internet skills into two groups: medium-related and content-related skills. The former includes instrumental skills required to use the Internet, while the latter involves information processing and strategic skills required for filtering, understanding, and evaluating online content. They further stress that these skills have a sequential and conditional nature. Content-related skills are somehow dependent on medium-related skills because one can come to perform the former as long as he or she owns the latter. Indeed, a subsequent study corroborates this by showing that medium-related skills have a positive influence on content-related skills (Van Deursen et al., 2011). Therefore, it is expected that users can also learn to critique media content as they experience the given media. They can gain diverse viewpoints and critical perspectives while interacting with a variety of media participants and messages. In this way, they can develop the ability to produce media content according to their opinions and ideologies.

Based on the above explanations, it is reasonable to consider that functional and consuming media literacy involve primary skills and thus provide an essential basis to critical and prosuming media literacy that involve advanced and complex skills. Recent empirical studies corroborated this thought as well. For instance, Chen et al. (2018) reported that students aged 10–15 had higher mean scores on FC and CC than on FP and CP, with CP being the lowest one. Kara et al. (2018) found that pre-service teachers performed highest in FC and the lowest in CP. Similarly, Koc and Barut (2016) explored that college students had good levels of FC, CC, and FP, whereas they had an average level of CP skills. They also indicated that NML components were positively correlated with each other. From the discussion above, we generated the following hypotheses among the NML components:

H1. Functional consuming (FC) positively influences critical consuming (CC).

H2. Functional consuming (FC) positively influences critical prosuming (CP).

H3. Functional prosuming (FP) positively influences critical consuming (CC).

H4. Functional prosuming (FP) positively influences critical prosuming (CP).

CS

Communication is essentially known as a process of constructing common meanings through information exchange. It occurs through the transmission of a thought or feeling via various means from one person to another (Oguzkan, 2003). It plays a shaping role in sustaining many important activities of our lives. Effective communication as a social skill is associated with improved health, larger social networks, better academic and job performance, enhanced psychosocial well-being, more satisfying marriages, effective teaching, and so on (Greene and Burleson, 2003). Communication is not a spontaneous process but a socially skilled performance. Individuals should have cognitive and social abilities to start and manage this process. CS include fundamental interaction skills including verbal and non-verbal communication, message production and reception, and impression management as well as function-focused CS such as informing and explaining, arguing, persuasion, conflict management, and emotional support (Greene and Burleson, 2003).

The interest of investigating CS has recently extended to new media, especially Web 2.0 technologies such as Blogs, Wikis, Social Networking Sites, which function as both an information source and communication space for sharing and discussion. They feature various components related to communication, including interpersonal relationships, group communication, formal or informal language, rhetoric, images, sounds, videos, and so on (Oh and Owlett, 2017). Research suggests that the general use of social media is positively related to CS (Turgut et al., 2018). Facebook was shown to improve written communication of learners through easing their burden of grammar, spelling, and vocabulary as well as supporting the exchange of feedback and opinions (Khan et al., 2016). Social media use was also found to be helpful in improving students’ verbal communication because students could learn new words and idioms from their friends (Belal, 2014; Mustafa, 2018). Such evidence suggests that information sharing and social interaction provided by new media can promote an increase in CS. Therefore, it is plausible to form the hypotheses below:

H5. Functional consuming (FC) positively influences CS.

H6. Functional prosuming (FP) positively influences CS.

On the other hand, the maximum benefit from new media depends on effective communication because users with good CS can easily join diverse social groups and develop new perspectives. Such exposure inherently triggers critical consciousness required by CC and CP skills. A good communicator can establish clarity and precision that are important in both decoding and encoding media messages (Kellner and Share, 2007). This is why message or media literacy is seen as the central goal of basic communication courses (Ramsey, 2017). Academicians identified some CS skills including listening, asking probing questions, interviewing, and organizing and presenting thoughts as critical to media literacy (Bordac, 2009). Prior research indicates a positive correlation between interpersonal CS and critical thinking skills (Kim and Han, 2016). Following the above findings from the literature, we generated the following hypotheses:

H7. CS positively influences critical consuming (CC).

H8. CS positively influences critical prosuming (CP).

DT

In addition to a system of government based on the sovereignty of people, democracy is a philosophy of life (Erturk, 1981). Democracy is a way of solving social and personal problems in the community (Schou, 2001). It is a means for citizens to actively participate in politics and civic life by freely expressing their own opinions, debating public issues, selecting their political representatives, and even criticizing the government. Undoubtedly, the true practice of democracy can be achieved through DT among the citizens. DT is conceptualized as the possession of attitudes and beliefs that motivate individuals to think and behave accordant with democratic values and principles (Zencirci, 2003). The more people adopt and live by the democratic principles, the more democracy develops. Scholars emphasize the importance of democratic commitment of youth in the continuity and vitality of democracy (De Groot and Veugelers, 2015). There are various factors affecting the development of DT. De Groot (2011) defines some of these as follows: an understanding of democracy and diversity for the common good, a sense of internal and external efficacy, an active connection to people whose voice is less represented politically, a willingness to become open-minded, and an ability to engage in empathy and dialogue.

Mere knowledge of democratic values is not deemed sufficient to ensure active participation in democratic processes (Subba, 2014). What is more important is providing individuals with opportunities to implement democratic beliefs and principles in every aspect of their lives. At this point, the media can make a valuable contribution. If media can critically investigate and report government actions without any favor or fear, there will be meaningful participation, responsiveness, transparency, and accountability (Diamond, 2005). Social media use positively affects participation in civic and political life (Boulianne, 2015). A recent study showed that using blogs and social networking sites positively influenced online political engagement and this relationship was mediated by exposure to cross-cutting and like-minded viewpoints (Kim and Chen, 2016). Blogging activities were found to be significantly associated with participatory and political behaviors such as online discussion, campaigning, signing petitions, and donating money (Gil de Zuniga et al., 2009). Similarly, expressive, informational, and relational uses of social media were shown to be positively related to citizen engagement, namely social capital, civic participation, and political participation (Skoric et al., 2016).

This evidence provides support for the democratic potential of new media use because democracy benefits from political discussions among citizens. Nevertheless, Gil de Zuniga et al. (2013) showed that only expressive use (e.g. writing blog posts and comments) predicted political participation, whereas mere consumptive use (e.g. passive reading blog post) did not, suggesting the importance of critical and prosuming aspects of media literacy. Correspondingly, Kim and Yang (2016) revealed that adolescents who can critically evaluate online information were more likely to display political participation and efficacy than those who lack such a skill. One another study indicated that judging the trustworthiness of online information, finding different views about political and social issues on the Internet, and producing new online content were associated with increased political engagement and exposure to diverse perspectives (Kahne et al., 2012). These findings are not surprising because the culture of democratic life essentially involves critical thinking and questioning. Arising from this literature review, we formulated the following hypotheses:

H9. Critical consuming (CC) positively influences DT.

H10. Critical prosuming (CP) positively influences DT.

Furthermore, communication is a powerful means of making democratic decisions and problem-solving. Communicative competence may itself constitute political engagement. Prior research studies conceptualize interpersonal digital communication as the antecedent of participation activities (Shah et al., 2005). They also suggest that young people’s informational and expressive uses of social media facilitate engagement in civic activities (Macafee and Simone, 2012). For instance, Kim and Yang (2016) showed that Internet usage for communication positively predicted political participation and efficacy. They concluded that interacting with others on the Internet could expose users to divergent viewpoints, promoting further reflection and deeper awareness of complex social and political issues. Another study revealed that online writing encouraged participation in public discourse (Yuit and Thai, 2010). It is plausible that CS may enable individuals to obtain adequate knowledge and skills germane to the democratization process which, in turn, improves their democratic behaviors. On this basis, we constituted the following hypothesis:

H11. CS positively influences DT.

Methodology

Research design

We designed our study as a correlational survey research because it aims to identify multiple relationships between NML competencies, DT, and CS. In this direction, we developed the hypothesized model given in Figure 1 and tested it on our sample using SEM. We preferred SEM because of its several advantages over other techniques such as taking a confirmatory approach to theory development, capability of incorporating both latent and observed variables, offering explicit estimates of error variance parameters, and estimating multivariate direct and indirect effects of variables under study (Teo, 2010).

Participants

Based on convenience sampling, the research sample comprised 1047 university students who volunteered to participate in the study. The participants were pursuing an undergraduate degree in a major state university located in a southwestern city of Turkey. The reason for taking this location to survey is the fact that it hosts the university where we as researchers were working as academicians. Except for this convenience, there is not any special thing different from other similar state universities. Of the sample, 31% were studying Engineering, 26% Arts and Sciences, 12% Agriculture, 11% Theology, 10% Business Administration, 5% Law, and 5% Education. Half of the students were freshmen, while the remaining were sophomore (12%), junior (20%), and senior (18%). Their ages ranged from 18 to 46 with a mean age of 21.2 (standard deviation [SD] = 2.40). The gender ratio was almost balanced as 55% were female, whereas 45% were male.

Data collection tools

We collected the necessary data through a self-administrated questionnaire which was made up of two sections. The first section included questions germane to demographic characteristics (e.g. gender, age). The second one consisted of several scales measuring model variables explained below. After obtaining permission from the faculty administrations at the university, the first author visited faculties and invited students to participate in the study. Voluntary students who filled a written informed consent were given the questionnaire. They completed it in approximately 30 minutes. The dissemination of questionnaire and data collection took place during 2015–2016 academic years.

New Media Literacy Scale

Participants’ NML competencies were measured using New Media Literacy Scale (NMLS). The NMLS was developed by Koc and Barut (2016) based on the NML framework proposed by Lin et al. (2013). The NMLS has 35 items with four factors: functional consumption (FC, 7 items), critical consumption (CC, 11 items), functional prosumption (FP, 7 items), and critical prosumption (CP, 10 items). Each item is rated on a 5-point Likert-type scale with 1 = “strongly disagree” and 5 = “strongly agree.” Item scores are summed to construct factor scores. Higher scores indicate that a person is highly competent in respective NML factors. We conducted individual confirmatory factor analysis and internal consistency analysis for each factor to assure their construct validity and reliability (Table 1). The results confirmed their unidimensionality and high reliability with acceptable goodness-of-fit statistics and Cronbach’s alpha coefficients (Nunnally and Bernstein, 1994).

Table 1.

Goodness-of-fit statistics and reliability of scales.

Variable	χ²	df	χ²/df	SRMR	RMSEA	TLI	CFI	Cronbach’s alpha
Functional consumption (FC)	39.74*	10	3.97	.02	.06	.98	.99	.85
Critical consumption (CC)	148.86*	41	3.63	.03	.05	.96	.97	.87
Functional prosumption (FP)	38.15*	8	4.77	.02	.06	.98	.99	.89
Critical prosumption (CP)	107.81*	27	3.99	.02	.06	.98	.99	.92
Communication skills (CS)	957.43*	264	3.63	.04	.05	.89	.90	.90
Democratic tendencies (DTs)	99.58*	33	3.02	.03	.05	.93	.95	.70

χ²: chi-square test; df: degrees of freedom; SRMR: standardized root mean square residuals; RMSEA: root mean square of error of approximation; TLI: Tucker–Lewis index; CFI: comparative fit index.

p < .01.

Communication Skills Evaluation Scale

Participants’ CS was measured through Communication Skills Evaluation Scale (CSES). The CSES was developed by Korkut (1996) in Turkish. It has 25 items related to communication behaviors of verbal and non-verbal expressions and interpersonal relationships. Participants rated how frequently they engage in these behaviors on a 5-point Likert-type scale ranging from 1 = “never” to 5 = “always.” A composite variable was computed by summing the scores of all items, ranging from 25 to 125. Higher scores indicate better communicative abilities. Although Korkut (1996) examined the construct validity of the CSES and concluded that it was a unidimensional scale with high internal consistency, we also conducted a confirmatory factor analysis and internal consistency analysis to assure its psychometric appropriateness for our sample. The results in Table 1 confirmed its one-factor structure and high reliability with acceptable goodness-of-fit statistics and Cronbach’s alpha coefficient (Nunnally and Bernstein, 1994).

Democratic Tendency Scale

Participants’ adoption of democratic values was measured through the Democratic Tendency Scale (DTS). The DTS was developed by Zencirci (2003) in Turkish. It has 10 items loading together on a single factor. Item statements reflect general characteristics of democratic individuals such as social and political participation, awareness of human rights, freedom of expression, mutual tolerance, and behaving in line with democratic values. Participants indicated to what extent they had these characteristics on a 5-point Likert-type scale with 1 = “strongly disagree” and 5 = “strongly agree.” All item points were summed to construct a total score possibly ranging from 10 to 50, with higher scores indicating greater democratic behavior. Zencirci (2003) established construct validity and reliability of the scale by testing it on a sample of teachers and managers. Nevertheless, we conducted a confirmatory factor analysis and internal consistency analysis to assure its validity and reliability for our sample. Our findings in Table 1 revealed that it fit the data adequately and showed acceptable reliability (Nunnally and Bernstein, 1994).

Results

Preliminary analyses of the data

There were a few missing values randomly distributed within the scale items, and they were estimated using the series mean method. The skewness and kurtosis values for model variables ranged from –.40 to –.74 and –.44 to .53, respectively (Table 2). They were quite below the threshold value of |3| for skewness and |10| for kurtosis, indicating that all variables were normally distributed (Kline, 2005). We considered those cases whose Mahalanobis scores exceeded the critical chi-square value of 20.52 (degrees of freedom [df] = 5, p = .001) as multivariate outliers (Tabachnick and Fidell, 2007) and excluded them from SEM analyses. There was not any multicollinearity problem among the variables because their tolerance scores were greater than the threshold value of .20 and variance inflation factor (VIF) scores were lower than cut-off point of 10 (Tabachnick and Fidell, 2007). This was also supported by correlation coefficients ranging from .10 to .60 (Table 2). Our final sample size (n = 945) after removing the outliers was adequate for SEM analysis as it met Kline’s (2005) recommended value of 100–150 cases to obtain reliable results in SEM. We used SPSS 20 software for calculating descriptive statistics and simple correlations and AMOS 22 software with maximum likelihood as the method for parameter estimation for SEM analyses.

Table 2.

Descriptive statistics and correlations between model variables.

Variable	Correlation coefficient						Mean	SD	Skewness	Kurtosis
Variable	FC	CC	FP	CP	CS	DT	Mean	SD	Skewness	Kurtosis
Functional consumption (FC)	–	.60*	.56*	.49*	.33*	.23*	26.19	4.78	–.40	.20
Critical consumption (CC)		–	.56*	.47*	.42*	.25*	43.59	6.37	–.47	.08
Functional prosumption (FP)			–	.54*	.28*	.19*	27.21	5.62	–.74	.22
Critical prosumption (CP)				–	.22*	.10*	32.24	8.98	–.40	–.44
Communication skills (CS)					–	.36*	101.17	11.67	–.59	.29
Democratic tendencies (DTs)						–	39.24	5.17	–.45	.53

SD: standard deviation.

p < .01.

Descriptive statistics for model variables

The mean values of all variables were above the midpoint of their respective scaling range, indicating that participants had overall positive responses about the characteristics measured (Table 2). The SDs demonstrated fairly narrow dispersions of the data, suggesting that participants’ scores for each construct were closely clustered around their means. There were positive and moderate correlations (varied between .47 and .60) between NML factors (p < .01). Moreover, CS was positively and moderately correlated with FC and CC, while it was positively and weakly correlated with FP and CP factors (p < .01). DT was positively and weakly associated with all components of NML, whereas it was positively and moderately associated with CS (p < .01).

Findings of structural model testing

We performed a path analysis to test the fit between our data and the research model (Figure 1). We relied on composite scales instead of multiple indicators to reduce the number of parameters and model complexity. This practice, also known as item parceling, has been claimed to offer some advantages for SEM (e.g. higher reliability increased normality, fewer and more stable parameter estimates, and better model fit) as long as indicators/items in a composite scales/parcels are unidimensional, valid, and reliable measures (Bandalos and Finney, 2001). We deemed it suitable since the unidimensionality, construct validity, and reliability of each of our scales were established in previous studies and also confirmed for our sample as described in the methodology section above. The goodness-of-fit value was significant and thus failed to indicate an acceptable fit (χ² = 20.23, df = 3, p < .01). Although the chi-square statistic is a fundamental index in model testing, it is known to be biased toward large samples and complex models. Therefore, scholars recommend a variety of fit indices such as the ratio of χ²/df, standardized root mean square residuals (SRMR), root mean square of error of approximation (RMSEA), comparative fit index (CFI), and Tucker–Lewis index (TLI) (Kline, 2005). The χ²/df value less than 3, SRMR and RMSEA values less than or equal to .05, and CFI and TLI values greater than .95 indicate a good fit (Hair et al., 2010). Turning back to our findings, some indices indicated an acceptable fit (SRMR = .02, CFI = .99, TLI = .95), whereas others did not support this (χ² = 20.23, df = 3, p < .01, χ²/df = 6.74, RMSEA = .08). Moreover, as shown in Figure 2, standardized path estimates between CS and CP (β = .03, p > .05) as well as CP and DT (β = –.03, p > .05) were quite small and insignificant, rejecting hypotheses H8 and H10.

Figure 2.

Results of path analysis for the research model.

Having found an inadequate model fit, we decided to modify our model based on the modification indexes provided by SEM output. There was a recommendation of adding a path from CC to CP. Since this was also justifiable with the theoretical framework of NML, we decided to add this recommended path. The modified model was again subjected to path analysis. This time, the findings indicated a perfect model fit (χ² = 8.38, df = 4, p > .05, χ²/df = 2.10, SRMR = .01, RMSEA = .03, CFI = .99, TLI = .99). In fact, model comparison indices for the modified model (Akaike information criterion [AIC] = 42.38, consistent Akaike information criterion [CAIC] = 141.85, and expected cross validation index [ECVI] = .04) were smaller than those for the initial hypothesized model (AIC = 56.23, CAIC = 161.55, ECVI = .06), suggesting a better fit of the modified model to the dataset.

The resulting standardized path estimates and the amount of variances explained for the modified model are presented in Figure 3. As expected, there was a positive correlation between two exogenous variables, FC and FP (p < .01). FC, FP, and CS significantly influenced CC with explaining 52% of its variance, supporting hypotheses H1, H3, and H7. Comparing their direct effects on CC, FC (β = .46, p < .01) was the most influential predictor, followed by FP (β = .24, p < .01) and CS (β = .20, p < .01). FC, FP, and CC had a significant influence on CP with accounting for 35% of its variance, supporting hypotheses H2 and H4. The direct effect of FP on CP (β = .35, p < .01) was more than those of FC (β = .20, p < .01) and CC (β = .14, p < .01). FC and FP were significant in influencing CS with explaining 12% of its variance, supporting hypotheses H5 and H6. FC (β = .25, p < .01) was a more influential determinant of CS than FP (β = .14, p < .01). CC and CS had a significant effect on DT with the latter (β = .31, p < .01) being a stronger predictor than the former (β = .13, p < .01). Both explained 14% of the variance in DT.

Figure 3.

Results of path analysis for the modified research model.

In SEM studies, in addition to direct effects, it is important to examine indirect effects in order to fully understand the impact of each determinant on an outcome. Table 3 summarizes standardized direct, indirect, and total effect sizes in our modified model. Both FC and FP indirectly influenced CC through the mediation of CS. FC (β = .05, p < .01) had a little more indirect effect on CC than did FP (β = .03, p < .01). They also indirectly affected CP through the mediation of both CC and CS. Besides, CS indirectly affected CP through the mediation of CC. Hence, FC (β = .07, p < .01) was the most influential indirect predictor of CP, followed by FP (β = .04, p < .01) and CS (β = .03, p < .01). FC and FP indirectly influenced DT through the mediation of CC and CS. Also, CS had an indirect effect on DT through CC. Comparing their indirect effects on DT, FC (β = .14, p < .01) was the most influential predictor, followed by FP (β = .08, p < .01) and CS (β = .03, p < .01).

Table 3.

Standardized direct, indirect, and total effects of the modified research model.

Outcome	Determinant	Direct effect	Indirect effect	Total effect
Critical consumption (CC)	Functional consumption (FC)	.46	.05	.51
	Functional prosumption (FP)	.24	.03	.27
	Communication skills (CS)	.20	–	.20
Critical prosumption (CP)	Functional consumption (FC)	.20	.07	.27
	Functional prosumption (FP)	.35	.04	.39
	Critical consumption (CC)	.14	–	.14
	Communication skills (CS)	–	.03	.03
Communication skills (CS)	Functional consumption (FC)	.25	–	.25
Communication skills (CS)	Functional prosumption (FP)	.14	–	.14
Democratic tendencies (DTs)	Functional consumption (FC)	–	.14	.14
	Functional prosumption (FP)	–	.08	.08
	Critical consumption (CC)	.13	–	.13
	Communication skills (CS)	.31	.03	.34

Discussion and conclusion

Our results suggest that FC and FP positively influence CC, CP, and CS. While individuals learn and operate new media tools, they can get help and feedback from others and get exposed to new forms of messages and language usage. Such interactions might enhance their communicative competence. Harrison and Wessels (2005) argue that communication and cooperation can be established between the public, local, and private sectors through new media. As Gerhards and Schafer (2010) state, it is possible to avoid the oppressiveness and miscommunication through the easier communication and information access provided by new media. Individuals can experience a high level of social interaction due to the unique characteristics of Web 2.0 tools. Corroborating our findings, earlier studies show that new media platforms increase communication abilities (Khan et al., 2016; Mustafa, 2018; Turgut et al., 2018). Furthermore, individuals may encounter misinformation while surfing online. This requires them to be able to criticize and judge media messages. Hence, accessing and interpreting diverse messages may facilitate the development of critical thinking skills (Lin et al., 2013). The ease of embedding ideological messages even into the entertainment content in contemporary media requires individuals to be conscious and critical even when they are having fun. For these reasons, it is reasonable to find that functional media use is positively associated with critical media usage.

The findings reveal that CC positively influences CP and DT. Critical competence in consuming media can be reflected in prosuming media through the new technologies that turn the popular consumption culture to active production (Lee et al., 2015). Although democracy has a long history, it has become more developable and diffusible by means of new media (Nilsson and Carlsson, 2014). Social media use has been shown to support political and civic engagement by increasing socialization and information sharing among individuals (Gil de Zuniga et al., 2009; Kim and Chen, 2016; Skoric et al., 2016). New media has greatly expanded traditional political actions and organizations by offering innovative forms of engagement such as conversing about social issues in discussion forums, participating in campaigns in social media, and signing online petitions (Kim and Yang, 2016). New media makes political participation easy by overcoming the barriers between different social groups. Today’s youth show higher interest and spend more time interacting with civic and political issues on new media than ever before (Kahne et al., 2012). For instance, Twitter has become a functional environment even for minorities to be able to make their voices heard. It is also an ideal tool for politicians who want to reach big masses.

As anticipated, CS positively predicted CC and DT. One plausible reason for this is that individuals who are prone to communication tend to involve in various social settings. By this way, they have the opportunity to face with diverse thoughts and discussions. Such interactions prompt individuals to engage in critical thinking skills including analysis, synthesis, and evaluation. CS has also been reported to be associated with critical thinking in previous studies (Kim and Han, 2016). Furthermore, it is not surprising to expect those individuals with effective CS to easily participate in discussions on social and political issues, which, in turn, can lead to enhancements in DT. It has been evidenced that the practice of CS in digital media stimulates interest in expressive and participatory activities (Shah et al., 2005). Such engagements can promote awareness and reflection on social and political issues and thus support political and civic behaviors (Kim and Yang, 2016; Macafee and Simone, 2012). On the other hand, the missing direct effect of CS on CP can be explained by the indirect effect of CS on CP through CC. Individuals with better communicative abilities need to be highly competent in critical media consumption before they become literate in critical media prosumption. In other words, individuals’ ability to communicate effectively is not enough on its own to drive their media production; they have to be skilled in media consumption as well. This finding is also consonant with the theoretical framework of NML (Chen et al., 2011; Lin et al., 2013) in which consuming media skills are integrated and implied in the prosuming media skills.

Findings of indirect effects highlight the importance of CC and CS in explaining DT because of both their direct effects on DT and mediating roles in the indirect effects of FC and FP on DT. These results suggest that criticality and effective communication are required for the contribution of new media use to the formation of democratic attitudes and behaviors. Digital technologies have transformed monolog-dominated communication patterns into more dialogical, multidimensional, and interactive ones. However, such a structural change itself may not warrant for democratic development because some important concepts and approaches beyond the pure use of new media are missing. Our study suggests that critical thinking and effective communication are some of these significant factors. If individuals have such abilities adequately and integrate them effectively into their media usage, they can freely express their thoughts, participate in social and political discussions, and criticize various media messages, which are at the base of democracy. Prior research also corroborates that expressive and critical media use contributes to political and democratic engagement (Gil de Zuniga et al., 2013; Kim and Yang, 2016; Macafee and Simone, 2012).

Based on the results, we propose several implications for future research and practice. Media education curriculums should be renovated to include the unique aspects of new media so that students can be prepared for ongoing changes in the digitalizing society. Since misinformation can be easily disseminated in new media and this has a high potential to affect human life, all individuals should be trained to become new media literate citizens. Educators can encourage students to engage in critical media consumption and production in order to support their communication and exhibition of democratic behaviors. Future research should focus on not only media consumption but also media production of individuals as new technologies allow for creating and sharing their own content. Furthermore, functional competencies of NML can be fostered since they affect critical ones and CS, which in turn, affect DTs. One way to do this might be to facilitate or increase the access and use of new media as recent research studies suggest that NML is positively related to ownership of new media technologies (Chen et al., 2018) and experience with them (Zhang and Zhu, 2016). As a state policy, all public and private organizations can adopt and develop some initiatives to cultivate a culture of digitalization that encourages individuals to utilize new media technologies. For instance, educational institutions can expand new media integration into their administrative and instructional processes so that students can operate new media tools for both consumption and production of related content. Proactive interventions can be conceived to increase the exposure to new media both in and out of school context. Finally, our model can be improved by integrating different variables as well as testing it on different populations. Such investigations will reveal other factors affecting the development of NML and thus allow educators to consider them in planning and conducting relevant educational interventions.

As with all empirical research, this study is subject to several limitations. First, our model explained limited variance in the endogenous variables except for critical media consumption skills. This implies the possibility of other constructs that could be added to the model to obtain a better understanding and greater prediction. Second, the utilization of self-reported data raises the possibility of inflation of association among the constructs as well as concern for generalizability. Future research can corroborate the findings with actual performances of participants with regard to model variables. Third, the application of cross-sectional methodology prevented us from exploring participants’ growth or mutation with regard to model variables in time. Since NML skills are altering based on individuals’ interactions with new media developments, the results only reflect the given situation and relationships at the time of the study. Fourth, volunteer participants may be different from others in terms of declaring the talents regarding research variables (e.g. CS) or tendency to show off themselves (e.g. mentality). Finally, communicational experiences are directly affected by situational factors such as language, culture, social roles, and physical environment as well as personal characteristics such as gender and age (Hargie, 2006). Our findings are restricted to the CS of typical Turkish university students. The model can be tested and hopefully improved on culturally, professionally, and personally different populations in future studies.

Footnotes

Acknowledgements

All authors have agreed to the submission and that the article is not currently being considered for publication by any other print or electronic journal.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was produced from an academician training project funded by the Turkish Council of Higher Education and Suleyman Demirel University (SDU) under the grant number of OYP05740-YL-14. The authors thank these institutions for their financial support.

ORCID iDs

Esra Barut Tugtekin

Mustafa Koc

Author biographies

Esra Barut Tugtekin received her BA and MA degree in Computer Education and Instructional Technology from Inonu University, Turkey, and Suleyman Demirel University, Turkey, respectively. She is currently working as a research assistant and pursuing a PhD degree in Computer Education and Instructional Technology in Anadulu University, Turkey. Her current academic interests include new media literacy, technology integration into schools, instructional design, and educational multimedia.

Mustafa Koc received his BA degree in Mathematics Education from Selçuk University, Turkey. He received his MEd and PhD degrees in Educational Technology from the University of Missouri-Columbia, USA, and University of Illinois at Urbana-Champaign, USA, respectively. He is working as a professor at the College of Education, Suleyman Demirel University, Isparta, Turkey. His current research interest includes new media literacy, learning analytics, technology use in teacher education, and social and psychological aspects of technology use.

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