Advertisement

Higher Education

, Volume 77, Issue 4, pp 657–678 | Cite as

Information-seeking behaviour and academic success in higher education: Which search strategies matter for grade differences among university students and how does this relevance differ by field of study?

  • Hannes WeberEmail author
  • Dominik Becker
  • Steffen Hillmert
Article

Abstract

Today, most college students use the Internet when preparing for exams or homework. Yet, research has shown that undergraduates’ information literacy skills are often insufficient. In this paper, we empirically test the relation between information-seeking strategies and grades in university. We synthesise arguments from the literature on information-seeking behaviour and approaches to learning in tertiary education. Building on the distinction between deep- and surface-level learning, we develop a classification of online search strategies and contrast it with traditional information behaviour. Multivariate analyses using a two-wave online survey among undergraduate students at a German university indicate that using advanced online information-seeking strategies is a significant and robust predictor of better grades. However, there are notable differences between subject groups: Traditional information behaviour is still crucial in the humanities. Advanced search strategies are beneficial in all settings, but only one in four students uses these early on, while this share increases to around 50% over the course of studies.

Keywords

Information-seeking behaviour Approaches to learning Information literacy skills Learning environments Achievement Higher education 

Notes

Funding

The authors gratefully acknowledge funding from the Leibniz ScienceCampus Tuebingen “Informational Environments”.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. Attewell, P. (2001). Comment: the first and second digital divides. Sociology of Education, 74(3), 252–259.CrossRefGoogle Scholar
  2. Autor, D. H., Levy, F., & Murnane, R. J. (2003). The skill content of recent technological change: an empirical exploration. The Quarterly Journal of Economics, 118(4), 1279–1333.CrossRefGoogle Scholar
  3. Baeten, M., Kyndt, E., Struyven, K., & Dochy, F. (2010). Using student-centred learning environments to stimulate deep approaches to learning: factors encouraging or discouraging their effectiveness. Educational Research Review, 5(3), 243–260.CrossRefGoogle Scholar
  4. Bernstein, B. B. (2000). Pedagogy, symbolic control, and identity: Theory, research, critique. Lanham: Rowman & Littlefield.Google Scholar
  5. Biggs, J. (1979). Individual differences in study processes and the quality of learning outcomes. Higher Education, 8(4), 381–394.CrossRefGoogle Scholar
  6. Biggs, J. B. (1985). The role of metalearning in study processes. British Journal of Educational Psychology, 55(3), 185–212.CrossRefGoogle Scholar
  7. Biggs, J. B. (1987). Student approaches to learning and studying. Melbourne: Australian Council for Educational Research.Google Scholar
  8. Bilal, D., & Kirby, J. (2002). Differences and similarities in information seeking: children and adults as Web users. Information Processing & Management, 38(5), 649–670.CrossRefGoogle Scholar
  9. Borghans, L., & Ter Weel, B. (2007). The diffusion of computers and the distribution of wages. European Economic Review, 51(3), 715–748.CrossRefGoogle Scholar
  10. Brennan, J., Jary, D., Richardson, J. T. E., & Osborne, M. (2010). The social and organisational mediation of university learning. In J. Brennan, R. Edmunds, M. Houston, D. Jary, Y. Lebeau, M. Osborne, & J. T. E. Richardson (Eds.), Improving what is learned at university (pp. 29–42). Abingdon: Routledge.Google Scholar
  11. Burger, R. (2015). CampusPanel user handbook: Documentation for the student panel of the ScienceCampus Tuebingen (wave ‘b’). Tübingen: Univ. of Tübingen.Google Scholar
  12. Busato, V. V., Prins, F. J., Elshout, J. J., & Hamaker, C. (2000). Intellectual ability, learning style, personality, achievement motivation and academic success of psychology students in higher education. Personality and Individual Differences, 29(6), 1057–1068.CrossRefGoogle Scholar
  13. Callinan, J. E. (2005). Information-seeking behaviour of undergraduate biology students: a comparative analysis of first year and final year students in University College Dublin. Library Review, 54(2), 86–99.CrossRefGoogle Scholar
  14. Chin, C., & Brown, D. E. (2000). Learning in science: a comparison of deep and surface approaches. Journal of Research in Science Teaching, 37(2), 109–138.CrossRefGoogle Scholar
  15. Civilcharran, S., Hughes, M., & Maharaj, M. S. (2015). Uncovering Web search tactics in South African higher education. South African Journal of Information Management, 17(1), 1–8.Google Scholar
  16. Cox, M. J., & Marshall, G. (2007). Effects of ICT: do we know what we should know? Education and Information Technologies, 12(2), 59–70.CrossRefGoogle Scholar
  17. Dinet, J., Chevalier, A., & Tricot, A. (2012). Information search activity: an overview. Revue Européenne de Psychologie Appliquée/European Review of Applied Psychology, 62(2), 49–62.CrossRefGoogle Scholar
  18. Diseth, Å. (2007). Approaches to learning, course experience and examination grade among undergraduate psychology students: testing of mediator effects and construct validity. Studies in Higher Education, 32(3), 373–388.CrossRefGoogle Scholar
  19. Durkin, K., & Conti-Ramsden, G. (2012). Frequency of educational computer use as a longitudinal predictor of educational outcome in young people with specific language impairment. PLoS One, 7(12), e52194.  https://doi.org/10.1371/journal.pone.0052194.CrossRefGoogle Scholar
  20. Engels, T. C. E., Ossenblok, T. L. B., & Spruyt, E. H. J. (2012). Changing publication patterns in the social sciences and humanities, 2000–2009. Scientometrics, 93(2), 373–390.CrossRefGoogle Scholar
  21. Entwistle, N., & Tait, H. (1990). Approaches to learning, evaluations of teaching, and preferences for contrasting academic environments. Higher Education, 19(2), 169–194.CrossRefGoogle Scholar
  22. Gkorezis, P., Kostagiolas, P., & Niakas, D. (2017). Linking exploration to academic performance: the role of information seeking and academic self-efficacy. Library Management, 38(8/9), 404–414.CrossRefGoogle Scholar
  23. Hargens, L. L. (2000). Using the literature: reference networks, reference contexts, and the social structure of scholarship. American Sociological Review, 65(6), 846–865.CrossRefGoogle Scholar
  24. Helms-Park, R., Radia, P., & Stapleton, P. (2007). A preliminary assessment of Google Scholar as a source of EAP students’ research materials. The Internet and Higher Education, 10(1), 65–76.CrossRefGoogle Scholar
  25. Hillmert, S., Groß, M., Schmidt-Hertha, B., & Weber, H. (2017). Informational environments and college student dropout. In J. Buder & F. W. Hesse (Eds.), Informational environments: Effects of use, effective designs (pp. 27–52). New York: Springer.CrossRefGoogle Scholar
  26. Junco, R. (2012). Too much face and not enough books: the relationship between multiple indices of Facebook use and academic performance. Computers in Human Behaviour, 28(1), 187–198.CrossRefGoogle Scholar
  27. Karagiannopoulou, E., & Milienos, F. S. (2015). Testing two path models to explore relationships between students’ experiences of the teaching-learning environment, approaches to learning and academic achievement. Educational Psychology, 35(1), 26–52.CrossRefGoogle Scholar
  28. Lang, V., & Hillmert, S. (2014). CampusPanel user handbook: Documentation for the student panel of the ScienceCampus Tuebingen (wave ‘a’). Tübingen: Univ. of Tübingen.Google Scholar
  29. Lizzio, A., Wilson, K., & Simons, R. (2002). University students’ perceptions of the learning environment and academic outcomes: implications for theory and practice. Studies in Higher Education, 27(1), 27–52.CrossRefGoogle Scholar
  30. Margaryan, A., Littlejohn, A., & Vojt, G. (2011). Are digital natives a myth or reality? University students’ use of digital technologies. Computers & Education, 56(2), 429–440.CrossRefGoogle Scholar
  31. Marton, F., & Säljö, R. (1976). On qualitative differences in learning: outcome and process. British Journal of Educational Psychology, 46(1), 4–11.CrossRefGoogle Scholar
  32. Muthén, L. K., & Muthén, B. O. (2012). Mplus user’s guide (7th ed.). Los Angeles: Muthén & Muthén.Google Scholar
  33. Olsen, M. W., & Diekema, A. R. (2012). “I just Wikipedia it”: information behaviour of first-year writing students. Proceedings of the American Society for Information Science and Technology, 49(1), 1–11.CrossRefGoogle Scholar
  34. R Core Team. (2017). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing https://www.r-project.org/.Google Scholar
  35. Ramsden, P. (1991). A performance indicator of teaching quality in higher education: the course experience questionnaire. Studies in Higher Education, 16(2), 129–150.CrossRefGoogle Scholar
  36. Ramsden, P., & Entwistle, N. J. (1981). Effects of academic departments on students’ approaches to studying. British Journal of Educational Psychology, 51, 368–383.CrossRefGoogle Scholar
  37. Richardson, M., Abraham, C., & Bond, R. (2012). Psychological correlates of university students’ academic performance: a systematic review and meta-analysis. Psychological Bulletin, 138(2), 353–387.CrossRefGoogle Scholar
  38. Scouller, K. (1998). The influence of assessment method on students’ learning approaches: multiple choice question examination versus assignment essay. Higher Education, 35(4), 453–472.CrossRefGoogle Scholar
  39. Thatcher, A. (2008). Web search strategies: the influence of web experience and task type. Information Processing & Management, 44(3), 1308–1329.CrossRefGoogle Scholar
  40. Timmers, C. F., & Glas, C. A. W. (2010). Developing scales for information-seeking behaviour. Journal of Documentation, 66(1), 46–69.CrossRefGoogle Scholar
  41. Tinto, V. (1975). Dropout from higher education: a theoretical synthesis of recent research. Review of Educational Research, 45(1), 89–125.CrossRefGoogle Scholar
  42. Trigwell, K., Ashwin, P., & Millan, E. S. (2013). Evoked prior learning experience and approach to learning as predictors of academic achievement. British Journal of Educational Psychology, 83(3), 363–378.CrossRefGoogle Scholar
  43. Tsai, M.-J. (2009). Online information searching strategy inventory (OISSI): a quick version and a complete version. Computers & Education, 53(2), 473–483.CrossRefGoogle Scholar
  44. Tsai, M.-J., & Tsai, C.-C. (2003). Information searching strategies in web-based science learning: the role of Internet self-efficacy. Innovations in Education and Teaching International, 40(1), 43–50.CrossRefGoogle Scholar
  45. Van Lohuizen, M. T., Kuks, J. B. M., Van Hell, E. A., Raat, A. N., & Cohen-Schotanus, J. (2009). Learning strategies during clerkships and their effects on clinical performance. Medical Teacher, 31(11), e494–e499.CrossRefGoogle Scholar
  46. Weber, H., Hillmert, S., & Rott, K. (2018). Can digital information literacy among undergraduates be improved? Evidence from an experimental study. Teaching in Higher Education.  https://doi.org/10.1080/13562517.2018.1449740.
  47. Whitmire, E. (2002). Disciplinary differences and undergraduates’ information-seeking behaviour. Journal of the American Society for Information Science and Technology, 53(8), 631–638.CrossRefGoogle Scholar
  48. Wittwer, J., & Senkbeil, M. (2008). Is students’ computer use at home related to their mathematical performance at school? Computers & Education, 50(4), 1558–1571.CrossRefGoogle Scholar
  49. Zeegers, P. (2004). Student learning in higher education: a path analysis of academic achievement in science. Higher Education Research & Development, 23(1), 35–56.CrossRefGoogle Scholar
  50. Zhang, L.-F. (2000). University students’ learning approaches in three cultures: an investigation of Biggs’s 3P model. The Journal of Psychology, 134(1), 37–55.CrossRefGoogle Scholar
  51. Zhu, Y. Q., Chen, L. Y., Chen, H. G., & Chern, C. C. (2011). How does internet information seeking help academic performance?–the moderating and mediating roles of academic self-efficacy. Computers & Education, 57(4), 2476–2484.CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Department of SociologyUniversity of TuebingenTuebingenGermany

Personalised recommendations