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Assessing Perceived Usability of the
Data Curation Profiles Toolkit
Using the Technology Acceptance Model
Tao Zhang, D. Scott Brandt
Purdue University
USA
Lisa Zilinski
Carnegie Mellon University
USA
Jake Carlson
University of Michigan
USA
IDCC 2015, London
The Data Curation Profiles Toolkit (DCPT)
 Created at Purdue for librarians to engage
researchers in discussion about data
 Interview protocol
 Capture information about a dataset across lifecycle
 Explore how data are used and managed
 Identify data curation needs
 Document generated from data interview
2
Using the DCPT
 Three-stage process
3
Preparation Interviews
Constructing
DCP
 DCPs as community resource
 Understand researcher needs with data
 Inform development of data services
 Data Curation Profiles Directory
http://docs.lib.purdue.edu/dcp/
Assessing the DCPT
 Various data collected on how the DCPT has been
used
 Study on effectiveness of the DCPT
 Carlson (2013): Increased users’ confidence in
discussing data sharing, but time and effort for
developing DCP as barrier to use the DCPT
 Brandt & Carlson (2013): Users recognized utility and
impact, and strongly suggested further enhancement
for data curation needs (as opposed to data
management)
4
Motivation
 Formal and structured assessment of the DCPT to
reveal factors affecting:
 User perception
 Intention to use
 Difficulties
 Areas to be improved
 Challenge for usability evaluation
 Time limit
 Task performance measures
5
Technology Acceptance Model (TAM)
 Perceived usability (PU and PEOU)
 Predict user acceptance and actual usage of technical
systems/tools
 Critical for overall user experience
6
Source: Davis (1989)
Perceived Usability
Methodology
 Survey of potential determinants of perceived usability
(28 questions measured in 5-point Likert scale)
 “I have experience in conducting one-and-one interviews.”
 “It takes __ time to learn the DCP Toolkit.”
 “I can adjust the questions in the DCP Toolkit for use in
different situations.”
 PU, PEOU, and Intention to Use the DCPT
 Questionnaire measures adopted from Davis (1989)
 Open-ended questions
 Difficulties and obstacles
 Areas that user liked and could be improved
7
Methodology
 Survey sent to 895 registered users of the DCPT
website in Dec. 2013
 28 measures of determinants
 221 responses (24.7%) in a month
 Most respondents are professional librarians with data
management related responsibilities
 Data analysis
 Likert ratings of determinants-> Exploratory Factor
Analysis -> Regression Analysis
 Qualitative analysis of open-ended responses
8
Exploratory Factor Analysis
9
Measure 1
Measure 2
Measure 3
Measure N
……
Factor 1
Measure 4
Factor 2
 Correlations between
variables result from
sharing of factors
 Uncover underlying
structure of a large set
of measured variablesFactor n
……
Factor Analysis Results
 Seven factors extracted for 84.2% of total variance
 Applicability
 Time
 Complexity
 Experience and Share
 Training and Help
 Extensibility
 Interviewee Requirements
 Factors in regression models to predict PU, PEOU,
and Intention to Use
10
Regression Results
 Multivariate, stepwise regression models
[PU PEOU Intention to Use] = Factors 1-7 + error
11
Perceived Usefulness Estimated β
Applicability 3.00
Experience and Share 2.38
Training and Help 1.17
Perceived Ease of Use Estimated β
Applicability 1.12
Time -1.11 *
Complexity -1.59
Interviewee Requirements -1.71
Intention to Use Estimated β
Applicability 0.60
Time -0.41
Complexity -0.38
Training and Help 0.29
Extensibility 0.33
*p-value = 0.064, sample size > 250 needed to
show significance
Regression Results
 Multivariate, stepwise regression models
[Intention to Use] = PU, PEOU + error
 All regression models R2 around 0.5
12
Intention to Use Estimated β
PU 0.156
PEOU 0.054 (p = 0.07 > 0.05)
Open-ended Questions
 Questions asked in the survey:
 “If you used the DCP Toolkit in the past, did you encounter any
difficulties? If yes, please explain.” (n=46)
 “If you plan to use the DCP Toolkit, what would be the obstacles
you may encounter?” (n=62)
 “What are the things you like about the DCP Toolkit?” (n=69)
 “What are the things you think should be improved in the DCP
Toolkit?” (n=54)
 Qualitative analysis method
 Two independent researchers reviewed and coded responses
 Two iterations, 66.8% agreement on initial coding and 100%
consensus on final coding results
13
Open-ended Responses
 Themes:
 Amount of time required to use the DCPT vs. depth of
information from completed DCP
 Structure and format of the toolkit
 Alignment of the DCPT with particular context
 Using the DCPT to engage faculty and library
community
14
Open-ended Responses
 Finding the right balance
 Time required for both researchers and interviewees
 Depth of information in DCP as good utility
 Applicability
 Adapting structure and format to contexts
 Making decisions based on results
 Extending the DCPT
 Compact, “lite version”; online tool
 Focus on particular data types or fields
 Community building based on DCPs
15
Quantitative vs. Qualitative Results
 The balance between time and value
 Interviewee Requirements affect Perceived Ease of Use
 Complexity and Time affect Intention to Use
 Time requirement vs. thoroughness in open-ended
responses
 Training and Help
 Significant in regressions on Perceived Usefulness, Intention
to Use
 Open-ended responses requested additional help on:
 Adaptations for different purposes
 Transforming collected information into DCPs and making
decisions
18
Conclusion
 Technology-Acceptance Model useful for
assessment
 Factor analysis & regressions
 Significant factors identified for Perceived Usability &
Intention to Use
 Open-ended responses complement quantitative
results
 Usability improvement of the DCPT
 Reduce time requirement
 Increase flexibility
 Training and help
19
DCP: What We’ve Learned & Going Forward
20
Preparation
& Training
Interview/
Interact
Profiles/
Best
Practices
Utilizing
Outputs
Preparation Interviews
Constructing
DCP
DCP 1.0
DCP 2.0
DCP 2.0 Roadmap Workshop,
Purdue University, June 2015
Paper-based
Tech-based
Thank you!
Tao Zhang, D. Scott Brandt
Purdue University
USA
zhan1022@purdue.edu
techman@purdue.edu
Lisa Zilinski
Carnegie Mellon University
USA
ldz@cmu.edu
Jake Carlson
University of Michigan
USA
jakecar@umich.edu
IDCC 2015, London

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Assessing Perceived Usability of the Data Curation Profiles Toolkit Using the Technology Acceptance Model

  • 1. Assessing Perceived Usability of the Data Curation Profiles Toolkit Using the Technology Acceptance Model Tao Zhang, D. Scott Brandt Purdue University USA Lisa Zilinski Carnegie Mellon University USA Jake Carlson University of Michigan USA IDCC 2015, London
  • 2. The Data Curation Profiles Toolkit (DCPT)  Created at Purdue for librarians to engage researchers in discussion about data  Interview protocol  Capture information about a dataset across lifecycle  Explore how data are used and managed  Identify data curation needs  Document generated from data interview 2
  • 3. Using the DCPT  Three-stage process 3 Preparation Interviews Constructing DCP  DCPs as community resource  Understand researcher needs with data  Inform development of data services  Data Curation Profiles Directory http://docs.lib.purdue.edu/dcp/
  • 4. Assessing the DCPT  Various data collected on how the DCPT has been used  Study on effectiveness of the DCPT  Carlson (2013): Increased users’ confidence in discussing data sharing, but time and effort for developing DCP as barrier to use the DCPT  Brandt & Carlson (2013): Users recognized utility and impact, and strongly suggested further enhancement for data curation needs (as opposed to data management) 4
  • 5. Motivation  Formal and structured assessment of the DCPT to reveal factors affecting:  User perception  Intention to use  Difficulties  Areas to be improved  Challenge for usability evaluation  Time limit  Task performance measures 5
  • 6. Technology Acceptance Model (TAM)  Perceived usability (PU and PEOU)  Predict user acceptance and actual usage of technical systems/tools  Critical for overall user experience 6 Source: Davis (1989) Perceived Usability
  • 7. Methodology  Survey of potential determinants of perceived usability (28 questions measured in 5-point Likert scale)  “I have experience in conducting one-and-one interviews.”  “It takes __ time to learn the DCP Toolkit.”  “I can adjust the questions in the DCP Toolkit for use in different situations.”  PU, PEOU, and Intention to Use the DCPT  Questionnaire measures adopted from Davis (1989)  Open-ended questions  Difficulties and obstacles  Areas that user liked and could be improved 7
  • 8. Methodology  Survey sent to 895 registered users of the DCPT website in Dec. 2013  28 measures of determinants  221 responses (24.7%) in a month  Most respondents are professional librarians with data management related responsibilities  Data analysis  Likert ratings of determinants-> Exploratory Factor Analysis -> Regression Analysis  Qualitative analysis of open-ended responses 8
  • 9. Exploratory Factor Analysis 9 Measure 1 Measure 2 Measure 3 Measure N …… Factor 1 Measure 4 Factor 2  Correlations between variables result from sharing of factors  Uncover underlying structure of a large set of measured variablesFactor n ……
  • 10. Factor Analysis Results  Seven factors extracted for 84.2% of total variance  Applicability  Time  Complexity  Experience and Share  Training and Help  Extensibility  Interviewee Requirements  Factors in regression models to predict PU, PEOU, and Intention to Use 10
  • 11. Regression Results  Multivariate, stepwise regression models [PU PEOU Intention to Use] = Factors 1-7 + error 11 Perceived Usefulness Estimated β Applicability 3.00 Experience and Share 2.38 Training and Help 1.17 Perceived Ease of Use Estimated β Applicability 1.12 Time -1.11 * Complexity -1.59 Interviewee Requirements -1.71 Intention to Use Estimated β Applicability 0.60 Time -0.41 Complexity -0.38 Training and Help 0.29 Extensibility 0.33 *p-value = 0.064, sample size > 250 needed to show significance
  • 12. Regression Results  Multivariate, stepwise regression models [Intention to Use] = PU, PEOU + error  All regression models R2 around 0.5 12 Intention to Use Estimated β PU 0.156 PEOU 0.054 (p = 0.07 > 0.05)
  • 13. Open-ended Questions  Questions asked in the survey:  “If you used the DCP Toolkit in the past, did you encounter any difficulties? If yes, please explain.” (n=46)  “If you plan to use the DCP Toolkit, what would be the obstacles you may encounter?” (n=62)  “What are the things you like about the DCP Toolkit?” (n=69)  “What are the things you think should be improved in the DCP Toolkit?” (n=54)  Qualitative analysis method  Two independent researchers reviewed and coded responses  Two iterations, 66.8% agreement on initial coding and 100% consensus on final coding results 13
  • 14. Open-ended Responses  Themes:  Amount of time required to use the DCPT vs. depth of information from completed DCP  Structure and format of the toolkit  Alignment of the DCPT with particular context  Using the DCPT to engage faculty and library community 14
  • 15. Open-ended Responses  Finding the right balance  Time required for both researchers and interviewees  Depth of information in DCP as good utility  Applicability  Adapting structure and format to contexts  Making decisions based on results  Extending the DCPT  Compact, “lite version”; online tool  Focus on particular data types or fields  Community building based on DCPs 15
  • 16. Quantitative vs. Qualitative Results  The balance between time and value  Interviewee Requirements affect Perceived Ease of Use  Complexity and Time affect Intention to Use  Time requirement vs. thoroughness in open-ended responses  Training and Help  Significant in regressions on Perceived Usefulness, Intention to Use  Open-ended responses requested additional help on:  Adaptations for different purposes  Transforming collected information into DCPs and making decisions 18
  • 17. Conclusion  Technology-Acceptance Model useful for assessment  Factor analysis & regressions  Significant factors identified for Perceived Usability & Intention to Use  Open-ended responses complement quantitative results  Usability improvement of the DCPT  Reduce time requirement  Increase flexibility  Training and help 19
  • 18. DCP: What We’ve Learned & Going Forward 20 Preparation & Training Interview/ Interact Profiles/ Best Practices Utilizing Outputs Preparation Interviews Constructing DCP DCP 1.0 DCP 2.0 DCP 2.0 Roadmap Workshop, Purdue University, June 2015 Paper-based Tech-based
  • 19. Thank you! Tao Zhang, D. Scott Brandt Purdue University USA zhan1022@purdue.edu techman@purdue.edu Lisa Zilinski Carnegie Mellon University USA ldz@cmu.edu Jake Carlson University of Michigan USA jakecar@umich.edu IDCC 2015, London

Editor's Notes

  1. Why still need usability evaluation? Cannot sit down and observe the creation of DCP. Have to come up with a new approach to usability and user evaluation.
  2. Perceived Usefulness: The degree to which a person believes that using a particular system would enhance his or her job performance. Perceived Ease of Use: The degree to which a person believes that using a particular system would be free of effort. TAM is probably new to the audience, previously used in information systems and software tools First time TAM is used in data curation tools
  3. Example measure: The DCP Toolkit is relevant to my current job responsibilities.
  4. No prior code book, start with own categories
  5. Applicability is the only factor that significantly affects all three dependent variables (Perceived Usefulness, Perceived Ease of Use, and Intention to Use).
  6. So this study has helped us begin to prioritize requirements for the next Data Curation Profiles Toolkit, DCP 2.0. The concerns of balancing time and value are very important to us and the success of DCP. We know we need to address preparation, and that this will be through more and better training (guides, videos, tutorials, etc.). We want to keep the librarian as a focus for using the product, and increase the community that does so, but realize that others (humans and infrastructure) will be “actors” as well. And will help us create new outputs, the Profiles of course, but also recommendations for best practices and content that can interface with other tools. We will be holding a workshop in June in which will invite some experts in the field to work on producing the roadmap, so stay tuned for more information on that in the next month.