The Investigation of the Relationship between Cyber Loafing, Internet Addiction, Information Literacy and Cyber Bullying

Author(s):

Ömer Demir(presenting / submitting)Süleyman Sadi Seferoğlu

Conference:

ECER 2016

Network:

Emerging Researchers' Group (for presentation at Emerging Researchers' Conference)

Format:

Paper

Session Information

ERG SES D 03, ICT and Education

Paper Session

Time:

2016-08-22

13:30-15:00

Room:

OB-E2.16 (ALE 3)

Chair:

Javier Diez-Palomar

Contribution

Due to the rapid developments in ICT, some real life problems have started to be seen in the virtual environments as well. Loafing, bullying, addiction and lack of literacy can be given as examples of those problems that society face. When these problems are moved to the virtual environments, they are named as cyber loafing, cyber bullying, internet addiction and information literacy, respectively. Although these new cyber concepts are strongly related to the traditional ones, they are different in some respects.

Theoretical Framework

According to Maslow (1943), there are some hierarchical needs of humans that need to be fulfilled orderly. These hierarchical needs are physiological, safety, relationships, self-esteem and self-actualization from lower to higher needs of humans, respectively (Maslow, 1943). This hierarchy has some implications for education as well. For example, it can be applied to needs of students in the online classrooms (Milheim, 2012). When it comes to education, the main fact is that it is hard for an individual to learn effectively without feeling safe because learning is an inherently social process, which takes the third place from the bottom in Maslow’s hierarchical model. In addition, cyber bullying might also affect students’ psychology, which takes places at the bottom of Maslow’s hierarchy of needs.

Significance and Aim

Cyber bullying has myriad negative effects on the cyber victims’ psychology. It affects cyber victims’ emotions negatively (Patchin & Hinduja, 2006). Besides, it has dramatic social and physical effects on them. It might ruin cyber victims’ lives and may lead to completed suicides (Olweus & Breivik, 2014). Hence, preventing cyber bullying is of great significance in order not to disrupt cyber victims’ psychologies. And to do this, first of all, the underlying reasons of cyber bullying should be compressively understood (Eroglu & Guler, 2015).

Akca, Sayimer, Sali and Basak (2014) found out that new media literacy had a negative relationship with cyber bullying, implying the relationship between information literacy and cyber bullying. On the other hand, Leung and Lee (2011) pointed out that internet addicted people are more likely to encounter internet risks including cyber bullying than those who are not internet addicted. This finding implies the relationship between internet addiction and cyber bullying. Under the lights of above findings, it was aimed to investigate the relationship of cyber bullying with cyber loafing, internet addiction and information literacy within the scope of this study. Besides, the effects of some demographic variables on the cyber bullying were investigated as well. In reaching these goals the following research questions are tried to be answered:

1. Is there a statistically significant relationship between cyber bullying and

1a. internet addiction
1b. cyber loafing and
1c. information literacy?

2. Do the following variables have a statistically significant effect on cyber bullying?

2a. Gender
2b. Age
2c. Education status
2d. Occupation
2e. The most frequently used device to connect internet

Method

This study is a correlational study in general. Study Group A total of 181 volunteered participants, mostly undergraduate and graduate students, constituted the study group of the study. Participants are mostly women (59.7%). In addition, in terms of occupation, there are a remarkable number of students (20.4%) and academicians (19.3%) in the study group. Data Collection Tools Five data collection tools were employed within the scope of this study. First of them was demographic information scale, which was developed by the researchers and used to collect basic information about the participants. Second data collection tool was the information literacy scale, which was developed by Adiguzel (2011). The scale includes 4 factors and 29 items. These factors are “defining information needs”, “access to information”, “use of information” and “ethical and legal settings in the use of information”. Cronbach alpha reliability coefficient of the scale was calculated to be .928. Third data collection tool, internet addiction scale, was originally developed by Hahn and Jerusalem (2001). It was adapted to Turkish by Sahin and Korkmaz (2011). The scale is consisted of 19 items and 3 factors. These factors are “lost of control”, “desire to stay online more” and “negativeness in social relations”. Cronbach alpha reliability coefficient of the scale was reported as .858. Another scale used in this research was cyber loafing. It was developed by Blanchard and Henle (2008) and adapted to Turkish by Kaplan and Cetinkaya (2014). Turkish form of the mentioned scale encompasses 13 items and 2 factors. These factors are “serious cyber-loafing” and “minor cyber-loafing”. Cronbach alpha reliability coefficient of the scale was reported as .89. The fifth data collection tool was cyber bullying scale. This scale was developed by Aricak, Kinay and Tanrikulu (2012). It contains 24 items and only 1 factor. Cronbach alpha reliability coefficient of this scale was .95. Data Collection and Data Analysis Processes First of all, required permissions were obtained from developers of the aforementioned scales. Afterwards, ethical permission was obtained from the Ethic Commission of Hacettepe University. Data were collected through Google Forms., an online scale development platform. After conducting Kolmogorov-Smirnov test, it was ascertained that the data strongly violated the assumption of normality. Therefore, Spearman’s rank correlation coefficient to check correlation and Kruskal-Wallis test to check the cause and effect relation were employed in the current study.

Expected Outcomes

First, in this study it was found that there was a statistically significant negative correlation between information literacy and cyber bullying. When it comes to internet addiction and cyber loafing, it was seen that these two concepts showed statistically significant and positive correlation with cyber bullying. Amongst all above findings, it should be noted here that one of them stands out. Amongst the factors of the above constructs, “ethical and legal settings in the use of information” factor of information literacy construct yielded the highest negative correlation coefficient with cyber bullying (r=.334 ; p=.000). As for cause-effect relationship, it was found out that gender (p=.458) and the most frequently used device to connect internet (p=.170) have no statistically significant impact upon cyber bullying. Nevertheless, contrary to above findings, age (p=.028), education status (p=.000) and occupation (p=.016) have statistically significant impact upon it. That is to say, it was found out that participants above the age of 35 cyber bullied statistically less compared to the ones under the age of 25. Besides, results of the analysis showed that undergraduate students cyber bullied statistically more than graduate students did. Lastly, students reported that they cyber bullied statistically more than the office clerks and academicians do. Results Based on the findings of this study, it could be concluded that the high level of information literacy results as low level of cyber bullying in internet users’ behavior. The fact is that information literacy construct includes the factor of ethic. On the other hand, involving in cyber bullying activities can be regarded as highly unethical. In this context, it could be easier to understand the negative correlation between information literacy and cyber bullying.

References

Adiguzel, A. (2011). Bilgi okuryazarlığı ölçeğinin geliştirilmesi [The development of the scale of information literacy]. Dicle University Journal of Ziya Gökalp Faculty of Education, 17,15-28. Akca, E. B., Sayimer, I., Sali., J. B., & Basak, B. E. (2014). Okulda siber zorbalığın nedenleri, türleri ve medya okuryazarlığı eğitiminin önleyici çalışmalardaki yeri [The causes and types of cyber bullying in school and role of media literacy in preventive services]. Electronic Journal of Occupational Improvement and Research, 2, 17-30. Aricak, O. T., Kinay, H., & Tanrikulu, T. (2012). Siber zorbalık ölçeği’nin ilk psikometrik bulguları [Initial psychometric findings of the scale of cyber bullying]. Journal of the Hasan Ali Yücel Faculty of Education, 17, 101-114. Blanchard, A. L., & Henle, C. A. (2008). Correlates of different forms of cyberloafing: The role of norms and external locus of control. Computers in Human Behavior, 24, 1067−1084. Eroglu, Y., & Guler, N. (2015). Koşullu öz-değer, riskli internet davranışları ve siber zorbalık/mağduriyet arasındaki ilişkinin incelenmesi [The investigation relationships among contingencies of self-worth, risky internet behaviors and cyberbullying/cybervictimization]. Sakarya University Journal of Education, 5(3), 118-129. doi:http://dx.doi.org/10.19126/suje.04882. Hahn, A., & Jerusalem, M. (2001). Internetsucht-Reliabilität und Validität in der Online-Forschung. InOnline-Marktforschung (pp. 213-233). Gabler Verlag. Kaplan, M., & Cetinkaya, A. S. (2014). Sanal kaytarma ve demografik özellikler açısından farklılıklar: Otel işletmelerinde bir araştırma [Meaningful differences between demographic features and cyberloafing: Case in hotel businesses]. Anatolia: Turizm Araştırmaları Dergisi, 25(1), 26-34. Leung, L., & Lee, P.S.N. (2011). The influences of information literacy, internet addiction and parenting styles on internet risks. New media & society, 14(1), 117-136. Maslow, A. H. (1943). A theory of human motivation. Psychological Review, 50, 370-396. Milheim, K. L. (2012). Toward a better experience: Examining student needs in the online classroom through Maslow’s Hierarchy of Needs Model. Journal of Online Learning and Teaching, 8(2). Olweus, D., & Breivik, K. (2014). Plight of victims of school bullying: The opposite of well-being. In A. Ben-Arieh, F. Casas, I. Frønes & J. E. Korbin (Eds.), Handbook of child well-being (pp. 2593–2616). Dordrecht, The Netherlands: Springer. Patchin, J.,W., & Hinduja, S. (2006). Bullies move beyond the schoolyard: A preliminary look at cyberbullying. Youth Violence and Juvenile Justice, 4(2), 148-169. doi: 10.1177/1541204006286288. Sahin, C., & Korkmaz, O. (2011). İnternet bağımlılığı ölçeğinin Türkçeye uyarlanması [Adaptation of internet addiction scale to Turkish]. Ahmet Keleşoğlu Education Faculty (AKEF) Journal, 32, 101-115.

Author Information

Ömer Demir (presenting / submitting)

Hacettepe University

Computer Education and Instructional Technology

Ankara

Süleyman Sadi Seferoğlu

Hacettepe University, Faculty of Education, Department of Computer Education and Instructional Technology, Turkey

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