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ANALYSIS OF TECHNOLOGY ADDICTION OF HIGH SCHOOL AND UNIVERSITY STUDENTS USING DATA MINING TECHNIQUES

Year 2016, Volume: 4 , 284 - 291, 01.09.2016

Abstract

The
rapid evolution of technological devices also makes it increasingly challenging
to determine which is the most needed. These devices have become addictive,
especially for the young generation. In this study, we have made a survey was
composed of 31 questions over total of 240 high school and university students
to find out which criterions are related with each other in this survey. We
have analyzed survey results using Apriori Algorithm that is one of the data
mining techniques to ensure extracting some association rules. In the future,
to increase social communication between individuals, based on these rules, a
lesson about preventing technology addiction may be prepared than given to the
students in high schools and universities to raise awareness.

References

  • Agrawal, R., Imielinski, T., & Swami, A. (1993). Mining association rules between sets of items in large databases. In Proc. of the ACM SIGMOD Conference on Management of Data, 201-216. Agrawal, R., & Srikant, R. (1994). Fast Algorithms for Mining Association Rules. Proceedings of the 20th VLDB Conference, 487-499. Alaçam, H. (2012). Denizli Bölgesi Üniversite Öğrencilerinde İnternet Bağımlılığının Görülme Sıklığı ve Yetişkin Dikkat Eksikliği Hiperaktivite Bozukluğu İle İlişkisi, Pamukkale Üniversitesi Tıp Fakültesi, Uzmanlık Tezi, Denizli. Block, JJ. (2007). Prevalence Underestimated in Problematic Internet Use Study, CNS Spectr., 12-14. Ceyhan, A.A., & Ceyhan, E., (2009). Ergenlerde Problemli İnternet Kullanım Ölçeği (PİKÖ-E) Geliştirme Çalışmaları, X. Ulusal Psikolojik Danışma ve Rehberlik Kongresi, Çukurova Üniversitesi, 42. Chang, K. J., & An, E. J. (2011). Effects of internet game addiction on healthrelated lifestyle of Korea elementary school students. The FASEB Journal, 25, 770-22. Goldberg, I. (1996). Goldberg's Message. Retrieved March 7, 2016 from http://users.rider.edu/~suler/psycyber/supportgp.html. Gökçearslan, Ş., & Durakoğlu, A. (2014). Ortaokul Öğrencilerinin Bilgisayar Oyunu Bağimlilik Düzeylerinin Çeşitli Değişkenlere Göre İncelenmesi, Dicle Üniversitesi Ziya Gökalp Eğitim Fakültesi Dergisi, 23, 419-435. Greenfıeld, D.N. (1999). Psychological Characteristics Of Compulsive Internet Use: A Preliminary Analysis, Cyberpsychol Behav., 2, 403-412. Hahn, A., Jeruselam, M. (2001).Internetsucht: Reliabilität und validität in der online-Forschung. Online: http://psilab.educat.huberlin.de/ssi/publikationen/internetsucht_onlineforschung_2001b.pdf. Huang, M.-J., Chen, M.-Y., & Cheng, C.-C. 2014. Using Data Mining Technology to Explore Internet Addiction Behavioral Patterns. Independent Computing (ISIC), 2014 IEEE International Symposium on. 1-5. Information and Communication Technology (ICT) Usage Survey on Households and Individuals. (2015). Retrieved March 10, 2016 from http://www.turkstat.gov.tr/PreHaberBultenleri.do?id=18660. Khamphakdee, N., Benjamas, N., & Saiyod, S. (2014). Network Traffic Data to ARFF Convertor for Association Rules Technique of Data Mining. 2014 IEEE Conference on Open Systems (ICOS), 89-93. Lin, X. (2002). A Brief Introduction to Internet Addiction Disorder. Chinese Journal of Clinical Psychology, 10(1), 74-77. Scherer, K. (1997). College Life On-Line: Healthy And Unhealthy Internet Use, JCSD, 38, 655-665. Morahan-Martin, J. & Schumacher, P. (2000). Incidence And Correlates Of Pathological Internet Use Among College Students, Comp. Human Behav., 16, 13-29. Şahin, C., & Korkmaz, Ö. (2011). İnternet Bağımlılığı Ölçeğinin Türkçeye Uyarlanması. Selçuk Üniversitesi Ahmet Keleşoğlu Eğitim Fakültesi Dergisi. 32, 101-115. Şahin, C., & Tuğrul, V. M. (2012). İlköğretim Öğrencilerinin Bilgisayar Oyunu Bağımlılık Düzeylerinin İncelenmesi. Journal of World of Turks, 4(3), 115-130. Turkish Statistical Institute. (2015). Science, Technology and Information Society: Information Society Statistics. Retrieved March 10, 2016 from http://www.turkstat.gov.tr/UstMenu.do?metod=temelist. Weinstein, A. M. (2010). Computer and video game addiction-a comparison between game users and non-game users. The American Journal Of Drug And Alcohol Abuse, 36(5), 268-276. WEKA. (2016), . Retrieved March 22, 2016 from http://www.cs.waikato.ac.nz/ml/weka/downloading.html. Xiaoqian, Q. (2012). The Research on the Application of Fuzzy Neural Network in Internet Addiction Decision. International Conference on Computer Science and Service System, 2205-2208. Wu, X., Kumar, V., Quinlan, J. R., Ghosh, J., Yang, Q., Motoda, H., J. McLachlan, G., Ng, A., Liu, B., S. Yu, P., Zhou, Z., Steinbach, M., J. Hand, D., & Steinberg, D. (2008). Top 10 algorithms in data mining. Knowl Inf Syst, 14(1), 1-37. Xiaoqian, Q. (2012). The Research on the Application of Fuzzy Neural Network in Internet Addiction Decision. Computer Science & Service System (CSSS), 2012 International Conference on, 2205-2208. Xu, Z., Turel, O., & Yuan, Y. (2012). Online game addiction among adolescents: motivation and prevention factors. European Journal of Information Systems, 21(3), 321-340. Young, K.S. (1997). Internet addiction: symptoms, evaluation and treatment. In Clinical Practice: A Source Book, 17, 19-31.
Year 2016, Volume: 4 , 284 - 291, 01.09.2016

Abstract

References

  • Agrawal, R., Imielinski, T., & Swami, A. (1993). Mining association rules between sets of items in large databases. In Proc. of the ACM SIGMOD Conference on Management of Data, 201-216. Agrawal, R., & Srikant, R. (1994). Fast Algorithms for Mining Association Rules. Proceedings of the 20th VLDB Conference, 487-499. Alaçam, H. (2012). Denizli Bölgesi Üniversite Öğrencilerinde İnternet Bağımlılığının Görülme Sıklığı ve Yetişkin Dikkat Eksikliği Hiperaktivite Bozukluğu İle İlişkisi, Pamukkale Üniversitesi Tıp Fakültesi, Uzmanlık Tezi, Denizli. Block, JJ. (2007). Prevalence Underestimated in Problematic Internet Use Study, CNS Spectr., 12-14. Ceyhan, A.A., & Ceyhan, E., (2009). Ergenlerde Problemli İnternet Kullanım Ölçeği (PİKÖ-E) Geliştirme Çalışmaları, X. Ulusal Psikolojik Danışma ve Rehberlik Kongresi, Çukurova Üniversitesi, 42. Chang, K. J., & An, E. J. (2011). Effects of internet game addiction on healthrelated lifestyle of Korea elementary school students. The FASEB Journal, 25, 770-22. Goldberg, I. (1996). Goldberg's Message. Retrieved March 7, 2016 from http://users.rider.edu/~suler/psycyber/supportgp.html. Gökçearslan, Ş., & Durakoğlu, A. (2014). Ortaokul Öğrencilerinin Bilgisayar Oyunu Bağimlilik Düzeylerinin Çeşitli Değişkenlere Göre İncelenmesi, Dicle Üniversitesi Ziya Gökalp Eğitim Fakültesi Dergisi, 23, 419-435. Greenfıeld, D.N. (1999). Psychological Characteristics Of Compulsive Internet Use: A Preliminary Analysis, Cyberpsychol Behav., 2, 403-412. Hahn, A., Jeruselam, M. (2001).Internetsucht: Reliabilität und validität in der online-Forschung. Online: http://psilab.educat.huberlin.de/ssi/publikationen/internetsucht_onlineforschung_2001b.pdf. Huang, M.-J., Chen, M.-Y., & Cheng, C.-C. 2014. Using Data Mining Technology to Explore Internet Addiction Behavioral Patterns. Independent Computing (ISIC), 2014 IEEE International Symposium on. 1-5. Information and Communication Technology (ICT) Usage Survey on Households and Individuals. (2015). Retrieved March 10, 2016 from http://www.turkstat.gov.tr/PreHaberBultenleri.do?id=18660. Khamphakdee, N., Benjamas, N., & Saiyod, S. (2014). Network Traffic Data to ARFF Convertor for Association Rules Technique of Data Mining. 2014 IEEE Conference on Open Systems (ICOS), 89-93. Lin, X. (2002). A Brief Introduction to Internet Addiction Disorder. Chinese Journal of Clinical Psychology, 10(1), 74-77. Scherer, K. (1997). College Life On-Line: Healthy And Unhealthy Internet Use, JCSD, 38, 655-665. Morahan-Martin, J. & Schumacher, P. (2000). Incidence And Correlates Of Pathological Internet Use Among College Students, Comp. Human Behav., 16, 13-29. Şahin, C., & Korkmaz, Ö. (2011). İnternet Bağımlılığı Ölçeğinin Türkçeye Uyarlanması. Selçuk Üniversitesi Ahmet Keleşoğlu Eğitim Fakültesi Dergisi. 32, 101-115. Şahin, C., & Tuğrul, V. M. (2012). İlköğretim Öğrencilerinin Bilgisayar Oyunu Bağımlılık Düzeylerinin İncelenmesi. Journal of World of Turks, 4(3), 115-130. Turkish Statistical Institute. (2015). Science, Technology and Information Society: Information Society Statistics. Retrieved March 10, 2016 from http://www.turkstat.gov.tr/UstMenu.do?metod=temelist. Weinstein, A. M. (2010). Computer and video game addiction-a comparison between game users and non-game users. The American Journal Of Drug And Alcohol Abuse, 36(5), 268-276. WEKA. (2016), . Retrieved March 22, 2016 from http://www.cs.waikato.ac.nz/ml/weka/downloading.html. Xiaoqian, Q. (2012). The Research on the Application of Fuzzy Neural Network in Internet Addiction Decision. International Conference on Computer Science and Service System, 2205-2208. Wu, X., Kumar, V., Quinlan, J. R., Ghosh, J., Yang, Q., Motoda, H., J. McLachlan, G., Ng, A., Liu, B., S. Yu, P., Zhou, Z., Steinbach, M., J. Hand, D., & Steinberg, D. (2008). Top 10 algorithms in data mining. Knowl Inf Syst, 14(1), 1-37. Xiaoqian, Q. (2012). The Research on the Application of Fuzzy Neural Network in Internet Addiction Decision. Computer Science & Service System (CSSS), 2012 International Conference on, 2205-2208. Xu, Z., Turel, O., & Yuan, Y. (2012). Online game addiction among adolescents: motivation and prevention factors. European Journal of Information Systems, 21(3), 321-340. Young, K.S. (1997). Internet addiction: symptoms, evaluation and treatment. In Clinical Practice: A Source Book, 17, 19-31.
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Details

Journal Section Articles
Authors

Meltem Kurt Pehlivanoğlu This is me

Nevcihan Duru This is me

Publication Date September 1, 2016
Published in Issue Year 2016 Volume: 4

Cite

APA Kurt Pehlivanoğlu, M., & Duru, N. (2016). ANALYSIS OF TECHNOLOGY ADDICTION OF HIGH SCHOOL AND UNIVERSITY STUDENTS USING DATA MINING TECHNIQUES. The Eurasia Proceedings of Educational and Social Sciences, 4, 284-291.