Impact of Media on Major Choice: Survey of Communication Undergraduates

Media and communication technologies engulf modern lives, influence one's perceived view of the world, and mediate personal interactions with individuals and society. Despite the undeniable reach and pervasiveness of information and entertainment industries, vocational scholars have not fully explored the way media and communication technologies influence students' choices of college majors or careers. Other predictors of choice, such as demographics, beliefs about academic disciplines, individual motivations, personality traits, and the roles of family, friends, and mentors (i.e., salient referents) have been studied in higher education advising and counseling research. We explored the extent to which media exposure, information technology use, and prominent public personalities have an impact major choice. We reasoned that because of the possible sway of media and communications technology on their choice of study, college students in communications majors, such journalism, advertising, public relations, telecommunications, and speech communication, would offer initial insight needed for our study. We relied on a multimethod approach for measurement development and model-testing purposes, which included focus groups, expert feedback, and a large-scale survey of communication majors at three large U.S. communication programs (N = 2,401).

Literature Review

A major in communication continues to be a popular choice with undergraduates despite job market uncertainty. In 2012–2013, the most recent year of National Center of Education Statistics (NCES) (2016) data, 84,817 bachelor's degrees in communication fields were conferred in the United States, a slight increase (1.2%) over the previous year, and a 24.9% increase over the previous 10 years. In fact, since NCES started collecting data in 1970, communication major enrollments have always shown growth. Craig and Carlone (1998) warned that these NCES data need careful interpretation because of various specialized majors within the field. For example, for the first time in history, journalism programs have experienced fewer student enrollments than in the past. Becker, Vlad, and Simpson (2014) found 3.1% fewer students enrolled in journalism undergraduate programs in 2013 than had declared it as a major in 2010, the historical enrollment high point for the field. The diffusion of Internet and communication technologies over the past two decades has dramatically disrupted media industries, and hence, their traditional career paths. However, the number of students choosing communication majors continues to grow despite ambiguous career opportunities. With regard to these majors, the prevailing concerns for academic advisors and career counselors are summed in the question: How or why do students choose communications majors?

Method

On the basis of the research questions, we chose a large sample-survey method to advance our study. The survey provided data measuring for the four independent variables (media exposure, technology use, and two types of salient referents) and the single dependent variable (choice of journalism as a major). Because the independent variables were continuous and the dependent variable was dichotomous and nominal, a discriminant analysis was a suitable statistical method.

A Qualtrics survey was administered during a 6-week period in 2013 at three large, U.S. public universities in the Southeast, Midwest, and Mid-Atlantic regions, respectively. We employed several procedures to develop and refine the survey instrument:

• 1.

  We conducted 4 focus groups of undergraduate communication students at two different large U.S. universities to determine student motivations for communication degrees.

• 2.

  A committee of experts (i.e., 6 international and national researchers and 3 doctoral students) reviewed the motivations and the questionnaire.

• 3.

  A pilot of the survey was conducted with students (N = 104) at a southeastern U.S. university in the fall semester of 2012. The pilot was used to test the validity and reliability of survey items.

As a result of these efforts, we dropped a salient referent item after conducting exploratory factor analysis on the pilot survey; that is, the item did not load onto any clearly defined factor such as unmediated referents (parents, teachers) or mediated referents (e.g., media figures from newspapers, broadcasts, or Internet channels). The final questionnaire required approximately 12 minutes to complete. See the Appendix for a summary of the survey instrument.

The survey garnered a 33.2% response rate for the individuals invited from three U.S. mass communication programs (N = 2,401) to take part in the survey. Respondents were recruited from five communication majors offered at the three universities: advertising, journalism, public relations, telecommunications, and speech, rhetoric or organizational communication. After deleting cases for missing data (with no systematic bias detected), the sample (N = 2,107) was comprised of 75% female, and 78% White, 9% Black or African American, 6% Asian, 4% Hispanic or Latino, 2% multiracial or other, and fewer than 1% Native American, Pacific Islander, or Alaskan Native students.

Operational Definitions and Descriptive Statistics

Media exposure

Four single-item variables measured media exposure. Students were asked to recall, using a 7-point Likert-type scale (1 = never to 7 = several times a day), the frequency with which they watched, listened to, or read the news before the age of 18 years and the time they presently spend accessing news. They also responded to items on the number of hours on an average day they consume video programming and participate in online pursuits. On average, respondents reported watching 2.3 hours of video daily and spent slightly more than 5 hours online per day (Table 1). They also reported a mean of 4.4 hours on news consumption before age 18 years and 5.0 hours today, which translates to a range between once a week (4) and several times (5) a week.

Table 1 Descriptive statistics of variables

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Internet and technology use

A 10-item index was developed to capture variance in Internet and technology use. Different from measuring consumption of media, the index serves as a proxy for participating in and producing media. Students selected all platforms in which they had engaged in the prior month. Some items represented very common technologies, while others were less common. Examples include participated in a social network, such as Facebook; posted information on a microblog, such as Twitter, Pinterest, or Tumblr; uploaded a video to a video-sharing site, such as YouTube; edited images in an editing program, such as Photoshop; created an audio podcast or produced an audio recording using a program, such as Audacity, Pro-tools, or Garageband; and created a web site using HTML/CSS (hypertext markup language/cascading style sheets). The index ranged from 0 to 10 technologies. On average, respondents used almost 5 of the 10 listed technologies within the past month (Table 1). Of the 10 Internet and technology behaviors examined, the percentage of students who had engaged in each activity ranged from 12% (created a web site using HTML/CSS) and 96% (Facebook use).

Salient referents

On the basis of prior research and focus group findings, a series of survey items were included to examine the possible influence of personally known individuals (unmediated salient referents) and of media figures students may see, read, or hear (mediated salient referents). Participants were asked to choose on a 5-point scale the degree to which each affected choice of major (1 = no influence; 5 = major influence). An exploratory factor analysis with principal axis extraction and a promax rotation resulted in 2 factors along the mediated and unmediated lines: a 6-item subscale of unmediated salient referents (α = .76) and a 5-item subscale of mediated salient referents (α = .86). Unmediated influences included family, friends, other students, a high school advisor or teacher, a college advisor, a college social organization, a college professor or instructor, and a job or internship supervisor or coworker. Mediated influences included media or communication professionals seen on TV news (e.g., CNN, Fox, CBS, local news), read in newspapers or magazines, or heard on the radio as well as authors of blogs or social media accounts and performers on niche programs or networks (e.g., National Geographic, Discovery Channel, Food Network, Travel Channel, ESPN).

Major choice

The dependent variable was dichotomous: journalism or other communication major. The category other communications major contained all respondents who identified their majors as advertising; communication (speech, rhetoric, organizational communications, group communications, etc.); public relations; or telecommunications. Thirty-four percent of respondents identified as journalism majors; the others had declared other communication majors.

Results

To determine the influence of the predictor variables on choice of major, we conducted two discriminant analyses. The first demonstrated that the predictors were significantly related to an individual majoring in journalism or in another area of communications (i.e., advertising, public relations, telecommunication, or communication). Predictor variables included all four measures of media exposure (current exposure to news, exposure to news before the age of 18 years, hours of video watched per day, time spent online per day), technology use, and both types of salient referents (mediated and unmediated). A student's year in school was included as a control.

These variables combined to create a significant discriminant function: eigenvalue of .186; Wilks' lambda of 843, chi-square of 3,338.38 (df = 8, p = .000). Table 2 reports the standardized canonical discriminant function coefficients, and Table 3 shows the structure matrix. The canonical function coefficient for the single function was −.321 for nonjournalism majors and .578 for journalism majors. The classification analysis indicated that this model correctly predicted group membership 70.6% of the time.

Table 2 Standardized canonical discriminant function coefficients

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Table 3 Structure matrix

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Relating the canonical function coefficients for the journalism majors and nonmajors to the predictor variables indicated that journalism majors consume more news, consumed more news in the past, produce more media content, and were influenced to a greater degree by mediated referents. Nonjournalism majors were distinguished only by the strength of the unmediated referents.

In another analysis, we sought to determine whether the same predictors for journalism majors could differentiate among the nonjournalism majors as well. Five dependent variable categories of major were included in the analysis: journalism, advertising, public relations, telecommunication, and other communication. The predictor variables combined to create 3 of 4 significant discriminant functions (Table 4). The classification analysis indicated that this model correctly predicted group membership 42.8% of the time.

Table 4 Eigenvalues and Wilks' lambda for second analysis

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Table 5 presents the standardized canonical discriminant function coefficients and the canonical coefficient for each major by each function. We compared these coefficients with the coefficients for the predictor variables to determine the variables that best discriminate among major. As in the first analysis, we found that majoring in journalism was related to amount of news consumed, amount of news consumed before age 18 years, and mediated referents. Not surprisingly, these journalism-related predictors were negatively related to the four nonjournalism majors. The second function, which had the strongest weighting from the number of video hours watched per day, was positively related to majoring in telecommunications and negatively related to majoring in public relations. The third function was strongly related to only one predictor, with a negative relationship to the Internet and technology use index, and it was not strongly related to any major; however, it had the strongest relationship with majoring in advertising. The negative coefficient indicates a positive relationship between technology use (e.g., producing media content) and majoring in advertising. Similar to advertising, it had a relationship to telecommunication. The positive coefficient indicates a negative relationship between one of the technology-use measures, producing media content (not shown), and majoring in telecommunication.

Table 5 Canonical correlations for second analysis

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The design of the quantitative analysis technique restricts the ability to make causal claims. For example, the direction of causality between news consumption and choosing journalism remains unclear. Although journalism majors consume more news at present, the data neither discern the degree to which this behavior is associated with the decision to major in journalism nor indicate whether the intake of news resulted from class assignments. The measure of news consumption before age 18 years was included to tap interest in journalism before starting college, but reliance on behavioral self-reports is associated with other types of limits on interpretation. Despite the limitations, this study supports the proposition that media consumption relates to the choice of journalism as a college major.

Discussion

Do media exposure, technology use, and both types of salient referents influence choice of college major? With respect to RQ1, the extent to which media exposure influences choice of major, the findings suggest that greater exposure to news before and after age 18 years was related to majoring in journalism and not related to other communication majors. However, on the cultivation-like effects of video exposure and time spent online, the results were mixed. In regard to RQ2, the use of technology for content participation and creation appeared as a factor for students choosing journalism. Finally, RQ3, which addressed the role of salient unmediated or mediated referents showed that mediated referents such as news anchors and journalists seen on television, were related to choice of journalism, but there was a negative relationship with choices of other communication majors. Conversely, unmediated referents such as parents, teachers, and job supervisors, influenced all communication majors except those who chose journalism.

Of all the findings, the most meaningful result demonstrates that majoring in journalism can be predicted by news consumption habits and mediated referents. The analysis was less successful at predicting communication major selection other than journalism, most likely because the predictor variables we utilized in this study focused primarily on factors that were expected to sway journalism students in their major selection.

In a surprising result, the relationship between mediated referents and choice of journalism was strong compared to that of other communication majors. Perhaps students who follow media personalities—writers, anchors, television and radio news reporters, bloggers, and especially niche media professionals—are more influenced to major in journalism than by any other factor, including parents. Perhaps journalism majors are predisposed to receive less support from sources of authority, such as teachers and parents. An interesting follow-up study might expose the extent that journalism students perceive support from authority figures on the basis that journalism majors rely on mediated sources for career and life guidance. Perhaps students who pursue other communication majors received more feedback from parents, friends, and teachers informing them of the challenges of placement in newspaper and television careers. In addition, the findings suggest that journalism majors use technology to produce media content to a greater extent than other communication majors. Thus, journalism majors may envision their selected career as a venue for creative expression.

Conclusions and Implications

Through this study, we sought to determine the effects of media, information technology, and salient referents (people who influence students) on choice of major. In addition to answers to the research questions, the work offers two contributions to the literature base. First, until this study, salient referents meant only individuals known personally to a student (i.e., unmediated). This study brings another dimension to the salient referent construct: mediated referents. Unlike past publications, this study suggests that students may be swayed by persons who they do not personally know in their choice of major. Perhaps some students are equally or more influenced by parasocial relationships with media figures, which we labeled as mediated salient referents in this study. In fact, our research suggests that unmediated salient referents had little impact on journalism as a career choice, which counters the research demonstrating salient referents as reliable predictors. In a second contribution, this is the first research study to bridge the previously unexplored intersection of choice of major and media exposure or information technology use. We are unaware of any other study making the connection between these behaviors to majors.

The implications for journalism and other communication majors include opportunities for interesting follow-up studies. Future researchers might investigate whether negative relationships with unmediated salient referents predict major choice. Prospective students who do not get support from within their social circle may look to mediated channels for guidance and inspiration. However, active participation with and consumption of media channels do not translate to job security because consumption does not necessarily translate to literacy. Therefore, future research on the relationships of literacy levels to major choice might yield interesting results valuable to advisors.

The findings suggest that the curriculum should be updated to gain relevance with students living digital lives. Data from our survey indicated that most journalism students participate in online programming and with others through social media; they reported using more than one half the technologies listed. However, other communication majors may need instruction and encouragement in developing digital media skills.

For advisors, the results suggest some simple strategies. First, advisors might encourage students to explain the elements of news and entertainment media that sparked their career interests. They may recommend the ubiquitous number of sources in video, print, and social media to explore.

Second, with an understanding that unmediated sources may influence journalism majors, advisors might query the extent that persons of authority or in the media drive the decisions. By gauging the way students developed perceptions of their ideal career path, advisors learn more about the advisee and gain insight that may lead to greater understanding of students pursuing the field. For example, advisors may ascertain the extent that creative expression inspired a career selection and hence identify appropriate careers, in addition to journalism, that the student might want to explore.

Advising administrators, especially those in a college of communication or media studies, may want to use a variant of our survey to learn more about the students seeking a communication degree. Administrators in other departments can modify our survey instrument to better fit specifics of the disciplines in their units.

Finally, we encourage internship supervisors, prospective employers, and public policy makers that the media influences students in a way not recognized before: choice of major. If communication majors are being influenced by media exposure and information technology use, are students in other disciplines also pursuing degrees on the basis of unmediated sources in the media? We are aware of an institution that added a forensic science major in response to demand from fans of the many crime-scene investigation television programs; anecdotes suggest that many students abandon the major once they learn that real forensic science is not nearly as glamorous or fast paced as it on television shows. This situation contributes to the argument that future research should be directed on the way media affects choice of different majors, including journalism.