Utah State University DigitalCommons@USU Instructional Technology and Learning Sciences Faculty Publications Instructional Technology & Learning Sciences 6-11-2010 Where in the World? Demographic Paerns in Access Data Mimi Recker Utah State University Beijie Xu Utah State University Sherry Hsi University of California - Berkeley Christine Garrard Utah State University Follow this and additional works at: hps://digitalcommons.usu.edu/itls_facpub Part of the Computer Sciences Commons , and the Educational Assessment, Evaluation, and Research Commons is Poster is brought to you for free and open access by the Instructional Technology & Learning Sciences at DigitalCommons@USU. It has been accepted for inclusion in Instructional Technology and Learning Sciences Faculty Publications by an authorized administrator of DigitalCommons@USU. For more information, please contact [email protected]. Recommended Citation Rcker, M., Xu, B., Hsi, S., Garrard, C. (2010). Where in the World? Demographic Paerns of Access Data. Poster presented at the 3rd International Conference on Educational Data Mining, Pisburgh, PA, June 11-13.
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Utah State UniversityDigitalCommons@USUInstructional Technology and Learning SciencesFaculty Publications Instructional Technology & Learning Sciences
6-11-2010
Where in the World? Demographic Patterns inAccess DataMimi ReckerUtah State University
Beijie XuUtah State University
Sherry HsiUniversity of California - Berkeley
Christine GarrardUtah State University
Follow this and additional works at: https://digitalcommons.usu.edu/itls_facpub
Part of the Computer Sciences Commons, and the Educational Assessment, Evaluation, andResearch Commons
This Poster is brought to you for free and open access by the InstructionalTechnology & Learning Sciences at DigitalCommons@USU. It has beenaccepted for inclusion in Instructional Technology and Learning SciencesFaculty Publications by an authorized administrator ofDigitalCommons@USU. For more information, please [email protected].
Recommended CitationRcker, M., Xu, B., Hsi, S., Garrard, C. (2010). Where in the World? Demographic Patterns of Access Data. Poster presented at the 3rdInternational Conference on Educational Data Mining, Pittsburgh, PA, June 11-13.
• A digital library of over 700 science ac5vi5es and instruc5onal resources • Based on a hands-‐on museum in California
Where in the World? Demographic Pa4erns in Access Data
• Collect geo-‐referenced data for two web-‐based educa5onal systems.
• Map geo-‐referenced data with public demographic datasets.
• Conduct sta5s5cal analyses of these rela5onships to highlight significance predictor variables.
Mimi Recker, Beijie Xu, Chris@ne Garrard, Utah State University Sherry Hsi, Lawrence Hall of Science, UC Berkeley
Instruc5onal Architect (IA)
This material is based in part upon work supported by the Na6onal Science Founda6on under Grant Number 840738 & 0840745. Any opinions, findings, and conclusions or recommenda6ons expressed in this material are those of the authors and do not necessarily reflect the views of the Na6onal Science Founda6on.
• A tool for collec5ng and reusing online learning resources • Utah-‐based • Outreach program in New York and Michigan
Exploratorium Learning Resources Collec5on (ELRC)
• Both groups were successful in local dissemina5on ac5vi5es. • The ELRC also showed more widespread U.S. visitors.
Geo-‐referenced visits info
Demographic data
1. Track web metrics using Google Analy5cs.
2. Collect geo-‐referenced visits data.
3. Join and map geo-‐referenced data with public
demographic datasets.
4. Analyze the associa5on between the two.
Geo-‐referenced data
IA’s Google Analy5cs report
ELRC’s Google Analy5cs report
Demographic data
Per capita income
Median family income
Number of schools
Number of school districts
Popula5on
• Used nega5ve binomial regression to account for skewed data. • Dependent Variable:
Number of visits • Three independent variables:
Popula5on Number of school districts Per capita income
Number of school districts
Median family income
popula@on school districts per capita income
Wald chi-‐square
p-‐value Wald chi-‐square
p-‐value Wald chi-‐square
p-‐value
IA 190.18 .000 .63 .43 27.57 .000
ELRC 71.36 .000 6.96 .008 11.70 .001
• Popula5on density significantly predicted number of online visitors. • Per capita income also significantly predicted number of online visitors. This may be a func5on of the amount of resources (e.g., computers) available in the local schools and communi5es.
