usage statistics & information behaviors: understanding user behavior with quantitative...

23
Usage Statistics & Information Behaviors: Understanding User Behavior with Quantitative Indicators John McDonald Assistant Director for User Services & Technology Innovation The Libraries of the Claremont Colleges November 2, 2007 NISO Usage Data Forum

Upload: john-mcdonald

Post on 13-Dec-2014

1.182 views

Category:

Education


1 download

DESCRIPTION

Presentation at the NISO usage data forum 2007

TRANSCRIPT

Page 1: Usage Statistics & Information Behaviors: understanding User Behavior with Quantitative Indicators

Usage Statistics &

Information Behaviors: Understanding User Behavior with

Quantitative Indicators

John McDonaldAssistant Director for User Services & Technology

InnovationThe Libraries of the Claremont Colleges

November 2, 2007NISO Usage Data Forum

Page 2: Usage Statistics & Information Behaviors: understanding User Behavior with Quantitative Indicators

Correlation: Boba Fett and Ladybugs

Page 3: Usage Statistics & Information Behaviors: understanding User Behavior with Quantitative Indicators

We have the data, now what do we do?What we have done:

Cancel journals Inform purchase decisions

What we should do: Understand usage behaviors Guide our decision making processes Understand our impact on our patrons

Page 4: Usage Statistics & Information Behaviors: understanding User Behavior with Quantitative Indicators

Information Usage Behaviors

StartingBrowsingAccessingChainingDifferentiatingExtracting

Ellis (1993), Ellis & Haugan (1997) & Meho & Tibbo (2003), McDonald (2007)

VerifyingNetworkingMonitoringManagingManipulatingTeachingEnding

Page 5: Usage Statistics & Information Behaviors: understanding User Behavior with Quantitative Indicators

Accessing

Managing & Ending

Chaining & Differentiating

Accessing & Browsing

Page 6: Usage Statistics & Information Behaviors: understanding User Behavior with Quantitative Indicators

How do we observe & measure?

Pose a QuestionHow will a new service affect our users?

Develop a Theory Explain what you think happened.

Test the TheoryDevelop metrics, collect data, analyze.

Page 7: Usage Statistics & Information Behaviors: understanding User Behavior with Quantitative Indicators

Example 1: Starting & Accessing

Question: How will a new service affect our users?

Theory: If we improve the user’s ability to identify relevant material (starting) and retrieve it (accessing), we either save them time or effort and allow them to access more material.

Test: There will be a significant increase in the usage of material.

Page 8: Usage Statistics & Information Behaviors: understanding User Behavior with Quantitative Indicators

Starting & Accessing: Use Before & After OpenURL

*significant at .05 level **significant at .01 level

Publisher Use 2000

Publisher Use 2001

Publisher Use 2002

Wilcoxon Signed-rank Test

Subjects Journals Mean SD Mean SD Mean SD z P>z

Astronomy 1 347 0 813 0 1408 0 -1.00 0.32

Biology 104 638 1625 847 2079 957 2351 -5.88 0.00**

Chemistry 42 1388 3248 1553 3889 2542 7294 -4.85 0.00**

Comp. Sci. 14 197 429 224 490 175 239 -1.63 0.10

Engineering 20 92 200 164 310 174 312 -2.41 0.02*

Gen. Sci. 3 16243 15571 20938 20345 26553 26506 -1.39 0.17

Geology 22 46 183 44 143 144 374 -3.10 0.00**

Mathematics 29 59 155 80 153 121 182 -3.68 0.00**

Physics 28 198 313 1081 2107 1526 2933 -4.00 0.00**

Total 263 701 2730 975 3527 1301 4953 -10.39 0.00**

Page 9: Usage Statistics & Information Behaviors: understanding User Behavior with Quantitative Indicators

Example 2: Differentiating

Question: Do our choices affect our users ability to differentiate between resources?

Theory: If we group resources together, we allow users to identify relevant resources and provide efficient methods to differentiate between resources.

Test: There will be a significant increase in searches across common resource groupings.

Page 10: Usage Statistics & Information Behaviors: understanding User Behavior with Quantitative Indicators

Differentiating: Federated Search Statistics

Database Searches

Web of Science 3823OPAC 3314WorldCat 3267PubMed 238INSPEC 233MathSciNet 183Faculty of 1000 Biology 176Compendex 132

Page 11: Usage Statistics & Information Behaviors: understanding User Behavior with Quantitative Indicators

Differentiating: OPAC Searches (2005 v. 2006)

Page 12: Usage Statistics & Information Behaviors: understanding User Behavior with Quantitative Indicators

Differentiating: WorldCat Searches

Page 13: Usage Statistics & Information Behaviors: understanding User Behavior with Quantitative Indicators

Example 3: Chaining

Question: Do our users move from one information resource to another?

Theory: If users are moving from resource to resource, usage of resources in the same environment (one provider) and results of that usage (citations) will increase.

Test: There will be a significant increase in the usage and/or results of usage of a resource’s material.

Page 14: Usage Statistics & Information Behaviors: understanding User Behavior with Quantitative Indicators

Chaining: JSTOR Citations (2000 v. 2004)

Page 15: Usage Statistics & Information Behaviors: understanding User Behavior with Quantitative Indicators

Example 4: Managing, Teaching

Question: Are our users managing or utilizing content differently?

Theory: A stable online archive allows users to re-access or re-use content more efficiently (utility usage or virtual vertical file), or utilize it for instructional purposes in different ways (virtual syllabus).

Test: There will be a significant increase in the systematic re-use of current, locally produced content.

Page 16: Usage Statistics & Information Behaviors: understanding User Behavior with Quantitative Indicators

Managing, Teaching: Use of local content

Page 17: Usage Statistics & Information Behaviors: understanding User Behavior with Quantitative Indicators

Example 5: Service Effects

Question: How do our choices in libraries affect user behavior?Theory: When we change the display options (e.g. cataloging) for journals, did that affect either publisher usage or SFX usage?

Test: Changing cataloging results in decreased local journal usage as measured by the publisher and SFX.

Page 18: Usage Statistics & Information Behaviors: understanding User Behavior with Quantitative Indicators

Service Effects: Usage of Journals (2005 v. 2006)

Page 19: Usage Statistics & Information Behaviors: understanding User Behavior with Quantitative Indicators

Service Effects: SFX Clickthrough Rate (Local v. Shared)

Page 20: Usage Statistics & Information Behaviors: understanding User Behavior with Quantitative Indicators

Example 5: Services Related BehaviorsWhat else do users want or need?

Are there services related behaviors that we can observe? Providing content is one option, but how are researchers using associated information services?

If we provide them the article they want in fulltext, we see that sometimes they ask for other types of things.

Can we match these things to those user behaviors?

Page 21: Usage Statistics & Information Behaviors: understanding User Behavior with Quantitative Indicators

Services Related Behaviors

Information Service Requests

Order Article via Document Delivery 951

See References for this Article 790

Search Library Catalog 580

Read Abstract 283

Search Article Title on the Web 170

Send Feedback to Library 15

See Articles citing this Article 11

Page 22: Usage Statistics & Information Behaviors: understanding User Behavior with Quantitative Indicators

What else could we be studying?

Monitoring Many information providers have e-alerts, repeat saved searches, etc.

Networking Users may want to email a citation to a colleague or another student.

Extracting Passing the bibliographic information to another database to search.

Analyzing Including user behavior information in the statistical measurement tools.

Page 23: Usage Statistics & Information Behaviors: understanding User Behavior with Quantitative Indicators

Questions?

John McDonaldNovember 2, 2007