Towards searching as a learning process: A review of current perspectives and future directions

Journal of Information Science

Volumn 42, Issue 1, 2016, Pages 19-34

  Rieh, Soo Young ^a   Collins Thompson, Kevyn ^a   Hansen, Preben ^b   Lee, Hye Jung ^c  

^a UNIVERSITY OF MICHIGAN   (United States)

^b STOCKHOLM UNIVERSITY   (Sweden)

^c Institute for Statistics and Education Consulting StatEdu   (South Korea)

Author keywords

Assessment of learning in searching; expertise modelling; searching as learning; web searching behaviour

Indexed keywords

INFORMATION SCIENCE; INFORMATION SYSTEMS;

ASSESSMENT OF LEARNING IN SEARCHING; CREATIVE-LEARNING; IMPLICIT AND EXPLICIT FEATURES; LEARNING OUTCOME; LEARNING PROCESS; SEARCHING AS LEARNING; USER INTERACTION; WEB-SEARCHING;

SAFETY DEVICES;

EID: 84954137720     PISSN: 01655515     EISSN: 17416485     Source Type: Journal    
DOI: 10.1177/0165551515615841     Document Type: Article

References (82)

1. Beheshti J, Bilal D, Druin A, et al. Testing children's information retrieval systems: Challenges in a new era. Proceedings of American Society for Information Science and Technology 2010; 47 (1): 1-4.
2. Dhillon MK., Online information seeking and higher education students. In: Chelton M, Cool C, (eds), Youth information-seeking behavior II: Context, theories, models, and issues. Lanham, MD: Scarecrow Press, 2007, pp. 165-205.
3. Druin A, Foss E, Hatley L, et al. How children search the internet with keyword interfaces. In: Proceedings of the 8th international conference on interaction design and children. New York: ACM, 2009, pp. 89-96.
4. Large A, Nesset V, Beheshti J., Children as information seekers: what researchers tell us. New Review of Children's Literature and Librarianship 2008; 14 (2): 121-140.
5. Pan B, Hembrooke H, Joachims T, et al. In Google we trust: Users' decisions on rank, position, and relevance. Journal of Computer-Mediated Communication 2007; 12 (3): 801-823.
6. Gross M, Latham D., What's skill got to do with it?: Information literacy skills and self-views of ability among first-year college students. Journal of the American Society for Information Science and Technology 2012; 63 (3): 574-583.
7. Rieh S, Kim Y, Markey K., Amount of invested mental effort (AIME) in online searching. Information Processing and Management 2012; 48 (6): 1136-1150.
8. Marchionini G., Exploratory search: From finding to understanding. Communications of the ACM 2006; 49 (4): 41-46.
9. Anderson L, Krathwohl D., A taxonomy for learning, teaching, and assessing. New York: Longman; 2001.
10. Allan J, Croft B, Moffat A., et al. Frontiers, challenges, and opportunities for information retrieval: Report from SWRIL 2012 The Second Strategic Workshop on Information Retrieval in Lorne. ACM SIGIR Forum 2012; 46 (1): 2-32.
11. Agosti M, Fuhr N, Toms E, Vakkari P, (eds). Evaluation of methodologies in information retrieval. Dagstuhl Reports 2013; 3 (10).
12. Limberg L, Alexandersson M,. Learning and information seeking. Encyclopedia of Library and Information Sciences 2010: 3252-3262.
13. Jansen BJ, Booth D, Smith B., Using the taxonomy of cognitive learning to model online searching. Information Processing and Management 2009; 45: 643-663.
14. Wilson MJ, Wilson ML., A comparison of techniques for measuring sensemaking and learning within participant-generated summaries. Journal of the American Society for Information Science and Technology 2013; 64 (2): 291-306.
15. Kuhlthau C., Seeking meaning. Westport, CT: Libraries Unlimited, 2004.
16. Vakkari P, Pennanen M, Serola S., Changes of search terms and tactics while writing a research proposal. Information Processing and Management 2003; 39 (3): 445-463.
17. Gross M, Latham D., Attaining information literacy: An investigation of the relationship between skill level, self-estimates of skill, and library anxiety. Library and Information Science Research 2007; 29 (3): 332-353.
18. Neuman D., Learning in information-rich environments. New York: Springer, 2011.
19. American Association of School Librarians and Association for Educational Communications and Technology. Information power: Building partnerships for learning. Chicago, IL: American Library Association, 1998.
20. Vakkari P., Changes in search tactics and relevance judgements when preparing a research proposal: A summary of the findings of a longitudinal study. Information Retrieval 2001; 4 (3-4): 259-310.
21. Vakkari P, Huuskonen S., Search effort degrades search output but improves task outcome. Journal of the American Society for Information Science and Technology 2012; 63 (4): 657-670.
22. Xie I., Interactive information retrieval in digital environments. Hershey, PA: IGI, 2008.
23. Bloom B., Taxonomy of educational objectives. New York: McKay, 1956.
24. Arguello J, Wu W-C, Kelly D, Edwards A., Task complexity, vertical display and user interaction in aggregated search. In: Proceedings of the ACM SIGIR conference on research and development in Information Retrieval, 2012, pp. 435-444.
25. Wu W-C, Kelly D, Edwards A, Arguello J., Grannies, tanning beds, tattoos and NASCAR: Evaluation of search tasks with varying levels of cognitive complexity. In Proceedings of the 4th information interactions in context (IIiX), 2012, pp. 254-257.
26. Kelly D, Arguello J, Edwards A, Wu W-C,. Development and evaluation of search tasks for IIR experiments using a cognitive complexity framework. In: Proceedings of the international conference on the theory of information retrieval (ICTIR), 2015, pp. 101-110.
27. Head A., Beyond Google: How do students conduct academic research? First Monday 2007; 12 (8).
28. Head A, Eisenberg M., Truth be told: How college students evaluate and use information in the digital age. SSRN 2281485 2010.
29. Fast K, Campbell D., 'I still like Google': University student perceptions of searching OPACs and the web. In: Proceedings of American Society for Information Science and Technology, 2004, pp. 138-146.
30. Chung J, Neuman D., High school students' information seeking and use for class projects. Journal of the American Society for Information Science and Technology 2007; 58 (10): 1503-1517.
31. Hersh WR, Elliot DL, Hickam DH, et al. Towards new measures of information retrieval evaluation. In: Proceedings of the ACM SIGIR conference on research and development in information retrieval, 1995, pp. 164-170.
32. Kammerer Y, Nairn R, Pirolli P, Chi EH,. Signpost from the masses: Learning effects in an exploratory social tag search browser. In: Proceedings of the SIGCHI conference on human factors in computing systems, 2009, pp. 625-634.
33. White R, Roth R., Exploratory search: Beyond the query-response paradigm. Synthesis Lectures on Information Concepts, Retrieval, and Services 2009; 1 (1): 1-98.
34. White R, Drucker S., Supporting exploratory search. Communications of the ACM 2006; 49 (4): 36-39.
35. Brown C, Krumholz L., Integrating information literacy into the science curriculum. College and Research Libraries 2002; 63 (2): 111-123.
36. Oblinger D, Hawkins B., The myth about student competency. Educause Review 2006; 24 (1): 12-13.
37. Association of College and Research Libraries. Information literacy competency standards for higher education. Chicago, IL: Association of College and Research Libraries, 2000.
38. American Association of School Librarians. Standards for the 21st-century learner. Chicago, IL: American Association of School Librarians, 2007.
39. Daugherty T, Carter E., Assessment of outcome-focused library instruction in psychology. Journal of Instructional Psychology 1997; 24 (1): 29-33.
40. Wang R., The lasting impact of a library credit course. Portal: Libraries and the Academy 2006; 6 (1): 79-92.
41. Markey K, Leeder C, Rieh S., Designing online information literacy games students want to play. Lanham, MD: Rowman & Littlefield, 2014.
42. Madden M, Jones S., The internet goes to college. Pew Internet and American Life Project, 2002.
43. Head A, Eisenberg M., How college students use the Web to conduct everyday life research. First Monday 2011; 16 (4).
44. Julien H, Barker S., How high-school students find and evaluate scientific information: A basis for information literacy skills development. Library and Information Science Research 2009; 31 (1): 12-17.
45. Rowlands I, Nicholas D, Williams P, et al. The Google generation: The information behaviour of the researcher of the future. Aslib Proceedings 2008; 60 (4): 290-310.
46. Brown C, Murphy T, Nanny M., Turning techno-savvy into info-savvy: authentically integrating information literacy into the college curriculum. The Journal of Academic Librarianship 2003; 29 (6): 386-398.
47. Jenson J., It's the information age, so where's the information? Why our students can't find it and what we can do to help. College Teaching 2004; 53 (3): 107-112.
48. Latham D, Gross M., Broken links: Undergraduates look back on their experiences with information literacy in k-12 education. School Library Media Research, http://www.eric.ed.gov/ERICWebPortal/search/detailmini.jsp?-nfpb=true&-&ERICExtSearch-SearchValue-0=EJ823031&ERICExtSearch-SearchType-0=no&accno=EJ823031 (2008,. accessed 14 April 2015).
49. Lee H, Lee J, Makara K, et al. Does higher education foster critical and creative learners? An exploration of two universities in South Korea and the USA. Higher Education Research and Development 2014; 34 (1): 131-146.
50. Bloom B, Krathwohl D., Taxonomy of educational objectives book 1: Cognitive domain. Reading, MA: Addison Wesley, 1984.
51. BonJour L., Epistemology: Classic problems and contemporary solutions. Lanham, MD: Rowman & Littlefield, 2002.
52. Powell KC, Kalina CJ., Cognitive and social constructivism: Developing tools for an effective classroom. Education 2009; 130 (2): 241.
53. Rosenwald M., Serious reading takes a hit from online scanning and skimming, researchers say. The Washington Post, http://www.washingtonpost.com/local/serious-reading-takes-a-hit-from-online-scanning-and-skimming-researchers-say/2014/04/06/088028d2-b5d2-11e3-b899-20667de76985-story.html (2014,. accessed 14 April 2015).
54. Carr N., The shallows. New York: W.W. Norton, 2010.
55. Rowlands I, Nicholas D., Information behaviour of the researcher of the future. Centre for Information Behaviour and the Evaluation of Research, http://www.webarchive.org.uk/wayback/archive/20140614113419/http://www.jisc.ac.uk/media/documents/programmes/reppres/gg-final-keynote-11012008.pdf (2008,. accessed 14 April 2015).
56. Bailey P, Chen L, Grosenick S, et al. User task understanding: a web search engine perspective. In: NII Shonan workshop, 8-11 October 2012, Shonan, Japan, http://research.nii.ac.jp/ntcir/shonan/Bailey-NIIShonan-UserTaskUnderstanding.pdf
57. Eickhoff C, Teevan J, White R, et al. Lessons from the journey: A query log analysis of within-session learning. In: Proceedings of the seventh ACM international conference on web search and data mining (WSDM), 2014, pp. 223-232.
58. Raman K, Bennett PN, Collins-Thompson K., Understanding intrinsic diversity in web search: Improving whole-session relevance. ACM Transactions on Information Systems 2014; 32 (4): 1-45.
59. Rose DE, Levinson D., Understanding user goals in web search. In: Proceedings of the 13th international conference on the World Wide Web (WWW '04), 2004, pp. 13-19.
60. Odijk D, White RW, Awadallah AH, Dumais S., Struggling and success in web search. In: Proceedings of the 24th ACM international conference on information and knowledge management (CIKM 2015), 2015.
61. White RW, Hassan A, Singla A, Horvitz E,. From devices to people: attribution of search activity in multi-user settings. In: Proceedings of the 23rd international conference on World Wide Web (WWW '14), 2014, pp. 431-442.
62. Kim J, Collins-Thompson K, Bennett PN, et al. Characterizing web content, user interests, and search behavior by reading level and topic. In: Proceedings of the fifth ACM international conference on web search and data mining (WSDM), 2012, pp. 213-222.
63. Collins-Thompson K, Callan J., Predicting reading difficulty with statistical language models. Journal of the American Society for Information Science and Technology 2005; 56 (13): 1448-1462.
64. Wildemuth BM., The effects of domain knowledge on search tactic formulation. Journal of the American Society for Information Science and Technology 2004; 55 (3): 246-258.
65. White RW, Dumais ST, Teevan J,. Characterizing the influence of domain expertise on web search behavior. In: Proceedings of the second ACM international conference on web search and data mining (WSDM), 2009, pp. 132-141.
66. Zhang X, Cole M, Belkin N., Predicting users' domain knowledge from search behaviors. In: Proceedings of the 34th international ACM SIGIR conference on research and development in information retrieval, 2011, pp. 1225-1226.
67. Russell DM, Stefik MJ, Pirolli P, Card SK,. The cost structure of sensemaking. In: Proceedings of the INTERACT '93 and CHI'93 conference on human factors in computing systems, 1993.
68. Zhang P, Soergel D., Towards a comprehensive model of the cognitive process and mechanisms of individual sensemaking. Journal of American Society of Information Science and Technology 2014; 65 (9): 1733-1756.
69. Hansen P,. User interface design for IR interaction: A task-oriented approach. In: Proceedings of the third international conference on the conceptions of the library and information science, 1999, pp. 191-205.
70. O'Day V, Jeffries R., Orienteering in an information landscape: How information seekers get from here to there. In: Proceedings of the INTERCHI conference on human factors in computing systems (CHI'93), 1993, pp. 438-445.
71. Marchionini G, Geisler G, Brunk B., Agileviews: A human-centered framework for interfaces to information spaces. In: Proceedings of the American Society for Information Science, 2000, pp. 271-280.
72. Hansen P, Järvelin K., Effects of foreign language and task scenario on relevance assessment. Journal of Documentation 2005; 61 (5): 623-639.
73. Hearst M., Search user interfaces. New York: Cambridge University Press, 2009.
74. Zhang M, Quintana C., Scaffolding strategies for supporting middle school students' online inquiry processes. Computers and Education 2011; 58: 181-196.
75. Kuhlthau CC, Maniotes LK, Caspari AK., Guided inquiry: Learning in the 21st century. Westport, CT: Libraries Unlimited, 2007.
76. Kuhlthau CC, Maniotes LK, Caspari AK., Guided inquiry design: A framework for inquiry in your school. Santa Barbara, CA: Libraries Unlimited, 2012.
77. Quintana C, Reiser BJ, Davis EA, et al. A scaffolding design framework for software to support science inquiry. Journal of the Learning Sciences 2004; 13: 337-386.
78. White RW, Huang J,. Assessing the scenic route: Measuring the value of search trails in web logs. In: Proceedings of the 33rd annual international ACM SIGIR conference on research and development in information retrieval, 2010, pp. 587-594.
79. Collins-Thompson K, Bennett PN, White RW, et al. Personalizing web search results by reading level. In: Proceedings of the twentieth ACM international conference on information and knowledge management (CIKM), 2011, pp. 403-412.
80. Tan C, Gabrilovich E, Pang B,. To each his own: Personalized content selection based on text comprehensibility. In: Proceedings of the fifth ACM international conference on web search and data mining (WSDM), 2012, pp. 233-242.
81. Eickhoff C, Dungs S, Tran V,. An eye-tracking study of query reformulation. In: Proceedings of the 38th annual international ACM SIGIR conference on research and development in information retrieval, 2015, pp. 13-22.
82. Buckland M., Information and information systems. New York: Praeger, 1991.