Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content
Springer Nature Link
Log in

Automated approaches to characterizing educational digital library usage: linking computational methods with qualitative analyses

  • Published:
International Journal on Digital Libraries Aims and scope Submit manuscript

Abstract

The need for automatic methods capable of characterizing adoption and use has grown in operational digital libraries. This paper describes a computational method for producing two, inter-related, user typologies based on use diffusion. Furthermore, a case study is described that demonstrates the utility and applicability of the method: it is used to understand how middle and high school science teachers participating in an academic year-long field trial adopted and integrated digital library resources into their instructional planning and teaching. Use diffusion theory views technology adoption as a process that can lead to widely different patterns of use across a given population of potential users; these models use measures of frequency and variety to characterize and describe such usage patterns. By using computational techniques such as clickstream entropy and clustering, the method produces both coarse- and fine-grained user typologies. As a part of improving the initial coarse-grain typology, clickstream entropy improvements are described that aim at better separation of users. In addition, a fine-grained user typology is described that identifies five different types of teacher-users, including “interactive resource specialists” and “community seeker specialists.” This typology was validated through comparison with qualitative and quantitative data collected using traditional educational field research methods. Results indicate that qualitative analyses correlate with the computational results, suggesting automatic methods may prove an important tool in discovering valid usage characteristics and user types.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Ayers, E., Nugent, R., Dean, N.: Skill Set Profile Clustering Based on Student Capability Vectors Computed From Online Tutoring Data. In: Proceedings of the 1st International Conference on Educational Data Mining, Montreal, Canada, pp. 210–217 (2008)

  2. Benevenuto, F., Rodrigues, T., Cha, M., Almeida, V.: Characterizing user behavior in online social networks. In: Proceedings of the 9th ACM SIGCOMM Conference on Internet Measurement Conference, ACM, Chicago, Illinois, USA, pp. 49–62 (2009). doi:10.1145/1644893.1644900

  3. Brandtzæg, P.B.: Towards a unified Media-User typology (MUT): a meta-analysis and review of the research literature on media-user typologies. Comput. Hum. Behav. 26(5), 940–956 (2010). doi:10.1016/j.chb.2010.02.008. http://www.sciencedirect.com/science/article/B6VDC-4YJSW8D-1/%2/011453cc70c0a6bdc29d3fde3b8a9304

  4. Creswell J.: Educational Research: Planning, Conducting, and Evaluating Quantitative and Qualitative Research. Pearson Education, Upper Saddle Creek, NJ (2008)

    Google Scholar 

  5. Danielson, C., McGreal, T.L.: Teacher Evaluation To Enhance Professional Practice. Association for Supervision and Curriculum Development, Alexandria, VA, USA (2000)

  6. Davis F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quart 13(3), 319–340 (1989)

    Article  Google Scholar 

  7. Deffuant G., Huet S., Amblard F.: An individual-based model of innovation diffusion mixing social value and individual benefit 1. Am. J. Sociol. 110(4), 1041–1069 (2005)

    Article  Google Scholar 

  8. Dempster A.P., Laird N.M., Rubin D.B: Maximum likelihood from incomplete data via the EM algorithm. J. R. Stat. Soc. Ser. B (Methodological) 39(1), 1–38 (1977)

    MathSciNet  MATH  Google Scholar 

  9. Dominguez, A.K., Yacef, K., Curran, J.R.: Data mining for generating hints in a python tutor. In: Proceedings of the 3rd International Conference on Educational Data Mining, Pittsburgh, PA, pp. 91–100 (2010)

  10. Dzurec L., Abraham I.: The nature of inquiry: linking quantitative and qualitative research. Adv. Nurs. Sci. 16, 73–79 (1993)

    Google Scholar 

  11. Eynon, R., Malmberg, L.: A typology of young people’s internet use: implications for education. Comput. Educ. 56(3), 585–595 (2011). doi:10.1016/j.compedu.2010.09.020. http://www.sciencedirect.com/science/article/B6VCJ-517J24P-1/%2/5c5d02fb284c227d3a9ef1cc4f3e1bf6

  12. Fuller F.F.: Concerns of teachers: a developmental conceptualization. Am. Educ. Res. J. 6(2), 207–226 (1969)

    Google Scholar 

  13. Hall G.E.: The concerns-based approach to facilitating change. Educ. Horizons 57(4), 202–208 (1979)

    Google Scholar 

  14. Hanson K., Carlson B.: Effective Access: Teachers’ Use of Digital Resources in STEM Teaching. Gender, Diversity, and Technology Institute. Education Development Center, Inc., Newton (2005)

    Google Scholar 

  15. Hew K.F., Hara N.: Empirical study of motivators and barriers of teacher online knowledge sharing. Educ. Technol. Res. Dev. 55(6), 573–595 (2007)

    Article  Google Scholar 

  16. Horrigan, J.: A typology of information and communication technology users. Research report, Pew Internet & American Life Project (2007)

  17. Kelly M.G., McAnear A.: National Educational Technology Standards for Teachers: Preparing Teachers to Use Technology. International Society for Technology in Education (ISTE), Eugene (2002)

    Google Scholar 

  18. Lage K., Maness J., Losoff B.: Receptivity to library involvement in scientific data curation: a case study at the University of Colorado Boulder. Portal Libr. Acad. 11(4), 915–937 (2011)

    Article  Google Scholar 

  19. Leech N., Onwuegbuzie A.: A typology of mixed methods research designs. Qual. Quant. 43(2), 265–275 (2009)

    Article  Google Scholar 

  20. Maness J., Miaskiewicz T., Sumner T.: Using personas to understand the needs and goals of institutional repository users. D-Lib Mag. 14(9/10), 1082–9873 (2008)

    Google Scholar 

  21. Maull, K., Saldivar, M., Sumner, T.: Understanding digital library adoption: a use diffusion approach. In: Proceeding of the 11th Annual International ACM/IEEE Joint Conference on Digital libraries, ACM, pp. 259–268 (2011)

  22. Maull, K.E., Saldivar, M.G., Sumner, T.: Online curriculum planning behavior of teachers. In: Proceedings of the 3rd International Conference on Educational Data Mining, Pittsburgh, PA, pp. 121–130 (2010)

  23. Miaskiewicz, T., Sumner, T., Kozar, K.: A latent semantic analysis methodology for the identification and creation of personas. In: Proceeding of the Twenty-Sixth Annual SIGCHI Conference on Human Factors in Computing Systems, ACM, pp. 1501–1510 (2008)

  24. Moore G.A.: Crossing the Chasm: Marketing and Selling Technology Products to Mainstream Customers. HarperCollins, New York (2006)

    Google Scholar 

  25. Pennington M.C.: Cycles of innovation in the adoption of information technology: a view for language teaching. Comput. Assist. Lang. Learn. 17(1), 7–33 (2004)

    Article  Google Scholar 

  26. Ram, S., Jung, H.: The conceptualization and measurement of product usage. J. Acad. Mark. Sci. 18(1), 67–76 (1990). doi:10.1007/BF02729763. http://www.springerlink.com/content/9kjl7574145320mv/

    Google Scholar 

  27. Rogers E.M.: Diffusion of Innovations, 5th edn. The Free Press, New York (2003)

    Google Scholar 

  28. Saldivar, M.: Teacher integration of digital resources into instructional practice. CCS Report No. 4. Digital Learning Sciences, Boulder (2011)

  29. Saldivar, M.G.: Teacher adoption of a Web-based instructional planning system. Doctoral dissertation, University of Colorado. Boulder, CO (2012)

  30. Shannon C.E.: A mathematical theory of communcation. Bell Syst. Tech. J. 27, 379–423 (1948)

    MathSciNet  MATH  Google Scholar 

  31. Shih, C., Venkatesh, A.: Beyond adoption: development and application of a use-diffusion model. J. Mark. 68(1), 59–72 (2004). http://www.jstor.org/stable/30161975

    Google Scholar 

  32. Smerdon B.: Teachers’ Tools for the 21st Century: A Report on Teachers’ Use of Technology. US Dept. of Education, Office of Educational Research and Improvement, Washington, DC (2000)

    Google Scholar 

  33. Straub E.T.: Understanding technology adoption: theory and future directions for informal learning. Rev. Educ. Res. 79(2), 625–649 (2009)

    Article  Google Scholar 

  34. Sumner, T., Team, C.: Customizing science instruction with educational digital libraries. In: Proceedings of the 10th Annual Joint Conference on Digital libraries, ACM JCDL ’10, New York, NY, USA, pp. 353–356 (2010). doi:10.1145/1816123.1816178

  35. Turner M., Kitchenham B., Brereton P., Charters S., Budgen D.: Does the technology acceptance model predict actual use? A systematic literature review. Inform. Software Technol. 52(5), 463–479 (2010)

    Article  Google Scholar 

  36. Venkatraman M.P.: The impact of innovativeness and innovation type on adoption. J. Retail. 67(1), 51–67 (1991)

    Google Scholar 

  37. Weatherley, J.: A web service framework for embedding discovery services in distributed library interfaces. In: Proceedings of the 5th ACM/IEEE-CS Joint Conference on Digital libraries (JCDL ’05), ACM, New York, NY, USA, pp. 42–43 (2005). doi:10.1145/1065385.1065394

  38. Wilson B., Wood J.A.: Teacher evaluation: a national dilemma. J. Person. Eval. Educ. 10(1), 75–82 (1996)

    Article  Google Scholar 

  39. Xu, B., Recker, M., Hsi, S.: Data deluge: opportunities for research in educational digital libraries. In: Cassie M. Edwards (ed) Internet Issues: Blogging, the Digital Divide and Digital Libraries. Nova Science Pub Inc., New York (2010)

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, Institute of Cognitive Science, University of Colorado, Boulder, CO, 80309, USA

    Keith E. Maull, Manuel Gerardo Saldivar & Tamara Sumner

Authors
  1. Keith E. Maull
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Manuel Gerardo Saldivar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tamara Sumner
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Keith E. Maull.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Maull, K.E., Saldivar, M.G. & Sumner, T. Automated approaches to characterizing educational digital library usage: linking computational methods with qualitative analyses. Int J Digit Libr 13, 51–64 (2012). https://doi.org/10.1007/s00799-012-0096-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00799-012-0096-x

Keywords

Search

Navigation