Teacher-student relationship

Teacher-student relationships play an important role in students’ academic development and affect the school and classroom environment (Hershkovitz, 2019; Song et al., 2019). Researchers focusing on student-teacher relationships on SNSs point to both positive and negative issues. For example, Callaghan and Bower (2012) reported that the student-teacher interaction in SNSs correlated with students’ achievements and engagement levels. Hershkovitz and Forkosh-Baruch (2013) found that although communication between students and the teacher was limited, the students considered positive student-teacher relationships on SNSs as useful and supported in-class satisfaction. However, some research studies underlined the negative aspects of SNSs. Butler (2010), for instance, referred to inappropriate comments posted on SNSs. Mazer et al. (2007) explored not only the contents of the comments but also how the amount of shared information might affect the perceptions of SNS users. They found that increased number of informal photographs shared by teachers could affect student perceptions negatively.

Teachers can easily manage how much information they want to share about their private lives in their classroom communication; for example, they can create a privacy boundary for their in-class communication (McBride & Wahl, 2005). However, social media differs from traditional communication environments in that it is not an official teaching environment; therefore, teachers tend to share or express themselves freely because they assume that they are not in a formal environment. It is obvious that in-person communication differs from communication over SNSs, in which the boundaries of professional and personal life can be unclear (Carter et al., 2008). In this formal classroom environment, privacy management is easier for both teachers and students.

Maintaining the balance between academic and personal life on SNSs is difficult and can be ambiguous, sometimes causing school authorities and policy makers to ban student-teacher relationships in this type of media (Manca & Ranieri, 2017). For example, the United States of America, Israel, and Australia have implemented policies from time to time to forbid these interactions but, in fact, there is no empirical evidence to support these actions (Hershkovitz & Forkosh-Baruch, 2017). Considering the prevalence of SNSs, adopting a banning strategy is not the optimal solution; rather, in this pervasive digital era, it is better to understand the student-teacher relationship in SNSs, which could be achieved through developing Media and Information Literacy (MIL) (Buckingham, 2007). Teachers should be able to determine how much information to unveil in SNSs in order to preserve their credibility and avoid possible negative perceptions that students might construct. Regulations might have some impacts on students but scholarly studies are insufficient in this area (Veletsianos et al., 2013).

Self-disclosure and credibility

The definition of self-disclosure according to Mazer et al. (2009) is “any message about the self that a person communicates to another”. Teacher self-disclosure is viewed as a strong personal source of student-faculty communication (Fusani, 1994). Sorensen (1989) stated that there was a positive relationship between student perceptions of affective learning and teacher self-disclosure. Therefore, it can be said that teacher self-disclosure can contribute to student learning (Song et al., 2019). Self-disclosure can establish a supportive learning environment and facilitate various forms of communication between students and teachers (Cayanus & Martin, 2004).

As discussed above, student-teacher communication has extended beyond the classroom, blurring the boundaries. For this reason, Buckingham (2007) stated that utilisation of digital technologies should be approached from a pedagogical perspective. This approach should help both teachers and students manage their communication processes, and in this way, students will gain skills and competencies on how to communicate with their friends and teachers. The amount and relevance of self-disclosure are critical components of communication since there are studies claiming that an increase in teachers’ self-disclosure results in students’ uncivil behaviours (Trad et al., 2012).

Self-disclosure is a kind of friendly communication which positively affects student participation and raises teacher credibility (Cayanus & Martin, 2008). There is a moderate association between teacher credibility and teacher behaviours, such as humour, technology use, and aggressive messages (Finn et al., 2009). When students perceive their teacher as less credible, their motivation decreases, and they show less respect to their teacher. As a result of the combination of these elements, student learning is decreased. Therefore, teachers’ credibility is the key factor in attaining successful student communication.

Various studies have shown that students’ learning is positively affected when they attribute high credibility to their teachers (Frymier & Thompson, 1992; McCroskey et al., 2004); however, SNS communication as a way of establishing friendships between teachers and students may impact on the boundaries of personal and professional life negatively in terms of credibility. For example, Barber and Pearce (2008) argued that the teacher’s presence on Facebook affected teacher credibility adversely, and it was not only their presence but also what was shared that could possibly have an effect on perceptions towards teachers. For instance, if a student is exposed to unwanted photos of the teacher on Facebook, this can affect the teacher’s credibility negatively (Hutchens & Hayes, 2014; Johnson, 2015). Since excessive disclosure can decrease teacher’s credibility, contrary to what Mazer et al. (2009) reported that self-disclosure increases teacher credibility, teachers should pay attention to the type of information they share and the amount of disclosure they have with students (Johnson, 2015).

Communication practices between teachers and students and how they perceive each other’s behaviours on SNSs needs further investigation (Manca & Ranieri, 2015; 2017). Some research reveals that students prefer passive behaviours while interacting with their teachers and avoid active interactions, such as chatting, commenting, and posting (Aydin, 2014). Understanding why learners enact this behaviour would reveal how SNS-based friendships can be utilised for better communication. Thus, it is important to explore teacher-student friendship on SNSs to determine how students perceive their teachers’ use of SNSs and how teachers should use these social interaction tools.

Research aim and research questions

The existing research mostly focuses on use of SNSs for academic purposes. In general, studies report the effects of usage or non-usage of SNSs on students’ achievement and the use of SNSs as communication tools for teaching and learning processes (Froment et al., 2017). There is a well-documented doctoral dissertation (Plew, 2011) pertaining to Facebook friendships between teachers and students from the teachers’ perspective. However, there are very few comprehensive studies examining students’ perceptions towards student-teacher relationships on SNSs. Therefore, this study is important for teachers, policy makers, and school authorities in relation to creating new regulations, policies or guidelines on student-teacher relationships on SNSs. With the purpose of analysing the factors that affect student-teacher relationship on SNNs, this study addressed the following research questions:

1) What are the students’ views about the student-teacher interaction in SNSs?

2) What type of posts do students want their teachers to share and not to share?

3) What type of actions do students expect from their teachers on SNSs?

4) What are the factors that affect the student-teacher relationship on SNSs?

Research design

This study used a mixed-methods approach with an exploratory sequential design (Creswell, 2011). In this context, qualitative data collection and an analysis shaped quantitative data collection tool were utilised; therefore, the interview results emerging from the first phase of the study assisted in developing the instrument of the second phase of the study.In such exploratory research design, researchers often try to understand a situation using a qualitative research group with the aim of developing a quantitative instrument based on the obtained qualitative data. The final aim is to test and generalize the findings of the first phase of the study via a large number of participants. The priority of this study was quantitative, with a greater emphasis being placed on quantitative methods.

Participants

In the qualitative phase, there were 21 university students attending a large state university in Turkey. The participants in the quantitative phase comprised 1,324 university students from 19 different universities in Turkey. Descriptive data about the participants obtained from the qualitative and the quantitative phases are summarised in Table 1. The participants were selected via convenience sampling method. The immediate academic colleagues of the researchers were the main sources for finding the participants. The participants were undergraduates ranging from freshmen to seniors aged from 18 to 23 years, attending various departments of different faculties (education, law, engineering, sport sciences, communication, and so on).

Data collection and analysis

The primary data collection tool was the semi-structured interview developed by the researchers. To ensure the validity of the data collection tool, two experts were consulted and two other researchers from the same academic field reviewed the open-ended questions. According to their feedback, the interview questions were modified and finalised. Examples of the interview questions are: “What do you think about being friends with your teachers on social networks? Can you elaborate on your response?” and “What kind of content should or should not be shared by your teachers on social networks?”.

The qualitative data were analysed with the content analysis method (Strauss & Corbin, 1990). The qualitative data of the study were transcribed, segmented, and coded (Johnson & Christensen, 2004). The researchers organised the codes and interpreted the findings to form the items of the data collection instrument of the second phase (Yildirim & Simsek, 2005). The qualitative data were analysed by two researchers for inter-rater reliability.

The second data collection tool was the questionnaire used to obtain the quantitative data of the study. The questionnaire was developed based on the scale development stages recommended by DeVellis (2003). The first step was to create an item pool based on the interview results and the researchers’ experiences. The questionnaire was determined to be a five-point Likert scale. Then, the questionnaire items were evaluated by field experts in terms of validity and clarity. An exploratory factor analysis (EFA) was applied to group-related items, and five items were removed. Thus, the questionnaire was finalised with 17 items. In order to determine the factor pattern coefficients, the quantitative data were analysed via the principal components analysis (PCA), which “simplifies the complexity in high-dimensional data while retaining trends and patterns” (Lever et al., 2017: 641). The suggestion of Thompson (2004) that noteworthy factors should have eigenvalues greater than 1.0, which is also known as the K1 rule, was applied.

Qualitative results

As summarized in the dataset (http://bit.ly/33kFVcB), the interviews with the students revealed their views and assisted in the development of the items in the questionnaire. The most prominent finding is that according to the students, political and religious views should not be shared by teachers. This finding is also included in the quantitative phase as two separate items, as explained in the next sub-chapter.

Additionally, some students did not want to be friends with their teachers on SNSs because they believed that being friend with a teacher on social media would probably affect the level of respect between them negatively. On the other hand, more than half of the students saw being a friend with their teachers on SNSs as a positive contribution to their daily interaction. In addition, the students thought that SNSs increased communication between students and teachers.

Quantitative results

EFA was conducted to ensure the construct validity of the instrument using IBM SPSS v. 20. The result shows that the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy was 0.87, suggesting the absence of multi-collinearity. A KMO greater than .50 is considered acceptable, a value above .80 is commendable (Kaiser, 1974), and values closer to 1 indicate a better correlation between variables (Norusis, 1998). Bartlett’s test for sphericity was performed, and the approximate chi-square was 11058.274, p<.000. These two tests showed that factorial analysis was appropriate for this set of data. PCA with Varimax rotation was used to reveal the factor loadings. Four factors emerged from the data: The first factor, consisting of four items, was labelled as “perceived utility”, the second factor (seven items) as “perceived barriers”, the third factor (two items) as “perceived unfavourable teacher behaviours”, and the last factor (four items) as “perceived favourable teacher behaviours”. The factorial loadings, mean and standard deviation of the items are presented in dataset (http://bit.ly/2XIBIOy).

Table 2 presents the four noteworthy factors with an Eigenvalue greater than 1, as suggested by Guttman (1954, cited in Thompson, 2004). The satisfactory reliability values of the factors of the scale ranged from 0.72 to 0.91, and that of the whole scale was 0.83. The highest variance (34.69%) belonged to the perceived barriers factor and the lowest variance (7.83%) to the perceived unfavourable teacher behaviours. The percentages of variance explained by the remaining two factors were 15.35% for perceived utility and 9.43% for perceived favourable teacher behaviours. The four factors accounted for 67.30% of the total variance.

Recommendations for further research

Since this study focused on the students’ perspective, further investigations should be undertaken concerning teachers’ views about student-teacher friendship. Teachers might not favour communication via SNSs because it will surely interrupt and distract their daily routines, such as lecturing, researching, and organising official meetings. Therefore, it is important to elucidate teachers’ perspective about communication over SNSs. Since the social and cultural environment affects communication, to determine how different cultures react to SNSs communication, the same questionnaire can be applied to participants from various cultures.

Limitations

Although this research had over 1,000 participants, the participants were reached through convenience sampling; the data obtained from 1,324 respondents cannot give a representative result for Turkey. In addition, culture is one of the most important determinants of human relations, and the data in this study was affected by the subculture of university students in Turkey. Lastly, although it was not intended, the majority of the students that volunteered were female, and it is possible that female students’ online attitude differs from that of male students. 1