1) The document presents a path analysis of educator perceptions of open educational resources (OER) using the Technology Acceptance Model. It examines how factors like perceived usefulness, ease of use, and self-efficacy impact behavioral intention and actual use of OER.
2) The analysis found moderate effects of self-efficacy on ease of use and strong effects of ease of use on both perceived usefulness and behavioral intention to use. Behavioral intention had a strong effect on actual use.
3) There were also differences found between educator groups (K-12, higher ed, etc.), with K-12 educators showing particular interest. Future research should examine indirect effects on use and how to better meet the
6. Research Rationale
• Purpose – Improving integration of OER
• Interest – Open access to educational resources
• Justification – Empowerment though knowledge
• AAAE National Research Agenda – “Develop
and validate systems-based models that will advance our
understanding of information and technology diffusion and its
practice.”
• Land Grant Mission – obligation to share resources for
the public good
7. Research Problem
Open Educational Resources are freely
available materials that may not fall under
the radar of many educators who would
benefit from their use.
We need to know more about people’s
attitudes who adopt these resources so that
we can improve access and use.
8. Objectives
• Understand factors that impact OER
adoption
• Understand differences in users in terms
of educational setting
• Guide instructional messaging for future
educators
9. Theory Base
• Social Cognitive Learning Theory
Bandura 1977
PERSON
Efficacy
Expectations
BEHAVIOR Outcome
Expectations
OUTCOME
11. Research Questions
• In a Web landscape cluttered with resources
how do user attitudes towards OER impact their
acceptance?
• Does general computer self-efficacy impact the
acceptance of OER?
• Do group differences exist among the educators
represented in the sample?
15. Instrument
• 5 application self-efficacy items
• 5 ease of use items
• 5 usefulness items
• 3 intention to use items
• 2 actual use items
• Gender, age, education, workplace, years
experience
16. Data Analysis
• Normalization
• Descriptives
• Outliers & way outliers included
• Path Analysis
– Model fitness
– Correlation coefficients
• Discriminant Analysis
– MANOVA
– Descriptive discriminant analysis
18. Does application self-efficacy have an effect
on perceived ease of use?
• Moderate direct effect
• Higher computer self-efficacy = perception
that OER are easy to use
• Maybe a disconnect between perceptions
of typically used applications and OER
19. Does ease of use have a positive
effect on perceived usefulness?
• Strong direct effect
• The easier to use an OER seems to be =
the OER seems more useful
• Design of OER must be clear and easy
20. Does ease of use have a positive effect on
behavioral intention to use?
Does perceived usefulness have a positive
effect on behavioral intention to use?
• Small direct effects to intention to use
• Indirect effects should be considered
• Direct effects to actual use should be
considered
21. Does behavioral intention to use have a
positive effect on actual use?
• Strong direct effect
• If you think you will use OER = you are
more likely to use them more & often
• Confirms an important aspect of the TAM
22. Do group differences exist among the
educators represented in the sample?
Function
1
Function
2
Function
3
Function
4
Self-efficacy -.181 .959 .511 -.275
Ease of use .519 -.784 1.190 .765
Usefulness 1.272 .481 -1.057 -.374
Intention -.997 -.510 .269 -.706
Actual use -.582 .407 -.365 1.000
23. Who will be interested?
• Digital collections
managers/administrators
• Educators
• Educational technologists
• Instructional designers
25. What’s next?
• Future models should test indirect and
direct effects from Perceived Ease of Use
& Perceived Usefulness to Actual System
Use
• Explore the perceived needs of K-12
educators in relation to OER
• Examine how OER are integrated in
teacher education programs
