Relationship between levels of problematic Internet usage and motivation to study in university students

Abstract

This study explored the relationship between problematic levels of Internet use and motivation to study in a university sample. One hundred and sixty-two participants were recruited online and completed four questionnaires: Internet Addiction Test, Hospital Anxiety and Depression Scale, Emotional–Social Loneliness Scale, and the Motivated Strategies for Learning Questionnaire. Participants’ scores were analysed to determine the presence of problematic levels of Internet use and any relationship between this factor and motivation to study. The results demonstrated that levels of problematic Internet use were negatively associated with several aspects of motivation to study (intrinsic goal orientation, control over learning, and learning self-efficacy). These relationships were over and above any impact that depression, anxiety, and social isolation had on motivation to study. The results suggest that increasing employment of digital learning technologies in higher education may be generating problems for some students, which may negatively impact their academic experience and outcomes in higher education.

This is a preview of subscription content, access via your institution.

References

  1. Andrews, B., & Wilding, J. M. (2004). The relation of depression and anxiety to life–stress and achievement in students. British Journal of Psychology, 95(4), 509–521.

    Article  Google Scholar 

  2. Boekaerts, M. (2001). Context sensitivity: Activated motivational beliefs, current concerns and emotional arousal. In S. Volet & S. Jarvela (Eds.), Motivation in learning context: Theoretical advances and methodological implications (pp. 17–31). Pergamon: Amsterdam.

    Google Scholar 

  3. Bozoglan, B., Demirer, V., & Sahin, I. (2013). Loneliness, self-esteem, and life satisfaction as predictors of Internet addiction: A cross-sectional study among Turkish university students. Scandinavian Journal of Psychology, 54, 313–319.

    Article  Google Scholar 

  4. Brandtzæg, P. B., Heim, J., & Karahasanović, A. (2011). Understanding the new digital divide—A typology of Internet users in Europe. International Journal of Human Computer Studies, 69(3), 123–138.

    Article  Google Scholar 

  5. Chang, M. K., & Man Law, S. P. (2008). Factor structure for Young’s Internet Addiction Test: A confirmatory study. Computers in Human Behavior, 24(6), 2597–2619.

    Article  Google Scholar 

  6. Chen, L. Y., Hsiao, B., Chern, C. C., & Chen, H. G. (2014). Affective mechanisms linking Internet use to learning performance in high school students: A moderated mediation study. Computers in Human Behavior, 35, 431–443.

    Article  Google Scholar 

  7. Chinn, M. D., & Fairlie, R. W. (2006). The determinants of the global digital divide: A cross country analysis of computer and internet penetration. Oxford Economic Papers, 18, 153–167.

  8. Christakis, D. (2010). Internet addiction: A 21st century epidemic? BMC Medicine, 8, 61.

    Article  Google Scholar 

  9. Crawford, J. R., Henry, J. D., Crombie, C., & Taylor, E. P. (2001). Normative data for the HADS from a large non-clinical sample. British Journal of Clinical Psychology, 40(4), 429–434.

    Article  Google Scholar 

  10. De Jong Gierveld, J., & Kamphuis, F. H. (1985). The development of a Rasch-type loneliness-scale. Applied Psychological Measurement, 9, 289–299.

    Article  Google Scholar 

  11. De Jong Gierveld, J., & Van Tilburg, T. (1999). Manual of the Loneliness Scale 1999. Department of Social Research Methodology, Vrije Universiteit Amsterdam, Amsterdam (updated version 18.01. 02).

  12. Dong, G., DeVito, E. E., Du, X., & Cui, Z. (2012). Impaired inhibitory control in ‘internet addiction disorder’: A functional magnetic resonance imaging study. Psychiatry Research: Neuroimaging, 203, 153–158.

    Article  Google Scholar 

  13. Du, Y. S., Jiang, W., & Vance, A. (2010). Longer term effect of randomized, controlled group cognitive behavioural therapy for Internet addiction in adolescent students in Shanghai. Australian and New Zealand Journal of Psychiatry, 44, 129–134.

    Article  Google Scholar 

  14. Fortson, B. L., Scotti, J. R., Chen, Y.-C., Malone, J., & Del Ben, K. S. (2007). Internet use, abuse, and dependence among students at a southeastern regional university. Journal of American College Health, 56, 137–144.

    Article  Google Scholar 

  15. Galacz, A., & Smahel, D. (2007). Information society from a comparative perspective: Digital Divide and social effects of the Internet. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 1(1).

  16. Garrison, D. R., & Kanuka, H. (2004). Blended learning: Uncovering its transformative potential in higher education. The Internet and Higher Education, 7(2), 95–105.

    Article  Google Scholar 

  17. Gerritsen, L. (1997). Meten met twee maten: Het meten van eenzaamheid en relatieverbrekingen blj’jong-volwassenen. Amsterdam: Dissertatie Vrije Universiteit.

    Google Scholar 

  18. Gomes, L., & Murphy, J. (2003). An exploratory study of marketing international education online. International Journal of Educational Management, 17(3), 116–125.

    Google Scholar 

  19. Griffiths, M. (2000). Internet addiction-time to be taken seriously? Addiction Research & Theory, 8, 413–418.

    Article  Google Scholar 

  20. Gundogar, A., Bakim, B., Ozer, O. A., & Karamustafalioglu, O. (2012). P-32—The association between internet addiction, depression and ADHD among high school students. European Psychiatry, 27, 1.

    Article  Google Scholar 

  21. Haines, M. E., Norris, M. P., & Kashy, D. A. (1996). The effects of depressed mood on academic performance in college students. Journal of College Student Development, 37, 519–526.

    Google Scholar 

  22. Hardie, E., & Tee, M.-Y. (2007). Excessive internet use: The role of personality, loneliness and social support networks in internet addiction. Australian Journal of Emerging Technologies and Society, 5, 34–47.

    Google Scholar 

  23. Hargittai, E. (2002). Second-level digital divide: Differences in people’s online skills. First Monday, 7(4).

  24. Hazelhurst, S., Johnson, Y., & Sanders, I. (2011). An empirical analysis of the relationship between web usage and academic performance in undergraduate students. arXiv preprint arXiv:1110.6267.

  25. Howell, D. C. (1998). Statistical methods for psychologists (4th ed.). London: Duxbury Press.

    Google Scholar 

  26. Johansson, A., & Götestam, K. G. (2004). Internet addiction: Characteristics of a questionnaire and prevalence in Norwegian youth (12–18 years). Scandinavian Journal of Psychology, 45, 223–229.

    Article  Google Scholar 

  27. Jones, S. (2008). Internet goes to college: How students are living in the future with today’s technology. Darby: DIANE.

    Google Scholar 

  28. Juriševič, M., Glažar, S. A., Pučko, C. R., & Devetak, I. (2008). Intrinsic motivation of pre service primary school teachers for learning chemistry in relation to their academic achievement. International Journal of Science Education, 30(1), 87–107.

    Article  Google Scholar 

  29. Justice, E. M., & Dornan, T. M. (2001). Metacognitive differences between traditional-age and nontraditional-age college students. Adult Education Quarterly, 51(3), 236–249.

    Article  Google Scholar 

  30. Kahari, L. (2013). The effects of Cell phone use on the study habits of University of Zimbabwe First Year Faculty of Arts students. International Journal of Education and Research, 10, 1–12.

    Google Scholar 

  31. Kandell, J. J. (1998). Internet addiction on campus: The vulnerability of college students. CyberPsychology & Behavior, 1(1), 11–17.

    Article  Google Scholar 

  32. Kim, C., & Pekrun, R. (2014). Emotions and motivation in learning and performance. In D. H. Jonassen (Ed.), Handbook of research on educational communications and technology (pp. 65–75). New York: Springer.

    Google Scholar 

  33. Konig-Zahn, C., Furer, J. W., & Tax, B. (1994). Het meten van de gezondheidstoestand (21, Lichamelijke gezondheid, sociale gezondheid: Beschrijving en evaluatie van vragenlijsten. Assen: Van Gorcum.

  34. Kross, E., Verduyn, P., Demiralp, E., Park, J., Lee, D. S., Lin, N., & Ybarra, O. (2013). Facebook use predicts declines in subjective well-being in young adults. PLoS ONE, 8(8), e69841.

    Article  Google Scholar 

  35. Kubey, R. W., Lavin, M. J., & Barrows, J. R. (2001). Internet use and collegiate academic performance decrements: Early findings. Journal of Communication, 51(2), 366–382.

    Article  Google Scholar 

  36. Leung, L., & Lee, P. S. N. (2012). Impact of Internet literacy, Internet addiction symptoms, and Internet activities on academic performance. Social Science Computer Review, 30, 403–418.

    Article  Google Scholar 

  37. Lin, S. C., Tsai, K. W., Chen, M. W., & Koo, M. (2013). Association between fatigue and Internet addiction in female hospital nurses. Journal of Advanced Nursing, 69, 374–383.

    Article  Google Scholar 

  38. Moore, J. L., Dickson-Deane, C., & Galyen, K. (2011). e-Learning, online learning, and distance learning environments: Are they the same? The Internet and Higher Education, 14(2), 129–135.

    Article  Google Scholar 

  39. Morahan-Martin, J., & Schumacher, P. (2000). Incidence and correlates of pathological Internet use among college students. Computers in Human Behavior, 16(1), 13–29.

    Article  Google Scholar 

  40. Murayama, K., Pekrun, R., Lichtenfeld, S., & vom Hofe, R. (2013). Predicting long-term growth in students’ mathematics achievement: The unique contributions of motivation and cognitive strategies. Child Development, 84(4), 1475–1490.

    Article  Google Scholar 

  41. Norris, P. (2001). Digital divide: Civic engagement, information poverty, and the Internet worldwide. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  42. Peterson, C., & Barrett, L. C. (1987). Explanatory style and academic performance among university freshman. Journal of Personality and Social Psychology, 53(3), 603.

    Article  Google Scholar 

  43. Pintrich, P. R. (1991). A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ). Washington: Office of Educational Research and Development.

  44. Pintrich, P. R. (2004). A conceptual framework for assessing motivation and self-regulated learning in college students. Educational psychology review, 16(4), 385–407.

    Article  Google Scholar 

  45. Pintrich, P. R., & De Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82, 33–40.

  46. Pintrich, P. R., & Schrauben, B. (1992). Student’s motivational beliefs and their cognitive engagement in classroom academic tasks. In D. H. Schunk & J. L. Meece (Eds.), Student perceptions in the classroom (pp. 149–184). Lawrence Erlbaum Associates: Hillsdale.

    Google Scholar 

  47. Pintrich, P. R., Smith, D. A. F., Garcia, T., & Mckeachie, W. J. (1991). A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ). AnnArbor: University of Michigan, National Center for Research to Improve Postsecondary Teaching and Learning.

    Google Scholar 

  48. Romano, M., Osborne, L. A., Truzoli, R., & Reed, P. (2013). Differential psychological impact of internet exposure on internet addicts. PLoS ONE, 8(2), e55162.

    Article  Google Scholar 

  49. Sahin, C. (2011). An analysis of Internet addiction levels of individuals according to various variables. Turkish Online Journal of Educational Technology, 10, 60–66.

    Google Scholar 

  50. Schiefele, U., & Rheinberg, F. (1997). Motivation and knowledge acquisition: Searching for mediating processes. In M. L. Maehr & P. R. Pintrich (Eds.), Advances in motivation and achievement (Vol. 10, pp. 251–301). Greenwich: JAI Press.

    Google Scholar 

  51. Scott, P. (2000). Globalisation and higher education: Challenges for the 21st century. Journal of Studies in International Education, 4(1), 3–10.

    Article  Google Scholar 

  52. Shields, N., & Kane, J. (2011). Social and psychological correlates of Internet use among college students. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 5(1).

  53. Snaith, R. P., & Zigmond, A. S. (1994). HADS: Hospital Anxiety and Depression Scale. Windsor: NFER Nelson.

    Google Scholar 

  54. Villella, C., et al. (2010). Behavioural addictions in adolescents and young adults: Results from a prevalence study. Journal of Gambling Studies, 27, 203–214.

    Article  Google Scholar 

  55. Weigel, V. B. (2002). Deep learning for a digital age: Technology’s untapped potential to enrich higher education. Jossey-Bass, 989 Market Street, San Francisco, CA 94103-1741.

  56. Weinstein, A., & Lejoyeux, M. (2010). Internet addiction or excessive internet use. The American Journal of Drug and Alcohol Abuse, 36, 277–283.

    Article  Google Scholar 

  57. Weiss, R. S. (1973). Loneliness: The experience of emotional and social isolation.

  58. Widyanto, L., & McMurran, M. (2004). The psychometric properties of the internet addiction test. Cyberpsychology & Behavior, 7(4), 443–450.

    Article  Google Scholar 

  59. Williams, M. (2011). Internet access—Households and individuals, 2011. London: HMO, Office of National Statistics.

    Google Scholar 

  60. Young, K. (1998). Caught in the Net. New York: Wiley.

    Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Phil Reed.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Reed, P., Reay, E. Relationship between levels of problematic Internet usage and motivation to study in university students. High Educ 70, 711–723 (2015). https://doi.org/10.1007/s10734-015-9862-1

Download citation

Keywords

  • Motivation to study
  • Internet addiction
  • Depression
  • Anxiety
  • Social isolation