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Evaluation & MathDLFlora McMartin
Broad-based Knowledge
MathDL Workshop, October 2008
What We Know about Math Users
National survey of faculty (4,678 respondents, 242 Math)
MathDL Workshop, October 2008
Institution Type
MathDL Workshop, October 2008
Types of Digital Resources
Type of Resource % VF
Online Scholarly Resources
19
Digital Images 18
Teaching/learning Exercises
29
Data Sets 11
Animations/simulations 15% of respondents reporting Very Frequent (VF) use (top box score)
MathDL Workshop, October 2008
Most Popular uses of Digital Resources
Type of Resource MathOnline Scholarly Resources
• Prof. Dev. as Teacher• Grants, Scholarship
Digital Images• Student Study Aid/Review• Prof. Dev. as Teacher• Lecture
Teaching/learning Exercises
• Student Study Aid/Review• Posted on course website
Data Sets• Student Research/PBL• Prof. Dev. as Teacher• Lecture
Animations/simulations
• Student Study Aid/Review• Lecture
MathDL Workshop, October 2008
Importance of DL Features
Type of Feature %
CONTENT
Supplemented with materials to explain use in teaching 17
Supplemented with materials to use for professional development as a teacher
6
PEDAGOGY
Peer reviewed & high quality 34
Organized to find materials quickly 45
Percentage of respondents who ranked feature as most important
MathDL Workshop, October 2008
Motivations for Using Digital Resources
Motivation Mean
Improve students’ learning 3.83
Stay abreast of professional developments 3.79
Helps me keep fresh 3.78
Incorporating digital resources in class is fun 3.62
Saves me time 3.38
Helps me develop my teaching skills 3.29
Students expect me to use digital resources in their instruction
2.63
Help me better accommodate students with disabilities 2.74
Helps students learn difficult concepts 2.73
The usefulness of digital resources are overrated 2.73
Scale: 1 = strongly disagree, 5 = strongly agree
In Sum
MathDL Workshop, October 2008
No direct relationship between highly valuing educational digital resources and level of use
Faculty prefer search for finding materials
Barriers to use cannot be simply described
Overcoming Barriers to Use of DLs
Activation energy – how much? What is it?
Intrinsic motivation is a powerful force – how big a reservoir?
Students as extrinsic motivators
Tradition is another powerful driver (change is hard)
All work practices are different
Never underestimate the willingness of a motivated individual to do their own thing (or ignore you)MathDL Workshop, October 2008
Application to the MathDL
Do these findings apply to MAA members?
Study done in 2006, how have changes on Web since then (e.g., growth in popularity of Youtube, iTunes U, blogs, wikis, etc.) affected users?
MathDL and MAA sites have changed what does that mean to users?
And?
MathDL Workshop, October 2008
Evaluation, next stepsNeed to understand user needs,
preferences and behaviorsAre they aware of it?Can they find it?If they find it, will they use it?What does it allow users to do that they
could not do before?
Need to understand the environment and competition toAct strategicallyDevelop marketing plansMake strategic partnersMeasure success and affordability (know when
experiments work or fail)MathDL Workshop, October 2008
User Panels
Panels repre
MathDL Workshop, October 2008
WHY?
Users becoming more sophisticated and fickle –online survey response rates trending down
• Ability to track users’ attitudes, behaviors over time
Panels carefully selected to match demographics of audience
20 + panelists
Respond to 3 – 5 surveys over course of year
Potential Questions Usability – e.g., is the site
intuitive? How do users move
between MAA and MathDL? How does use of Google
work for/against use of MathDL?
The Plan Selection Criteria
Teaching Experience
Types of School/institution
Type of course (online, traditional)
Use of Web/DL resources (professional development, integrated into course)
Math Course Topics (Calc, remedial math, etc.)
2 panels NovicePrevious users of
MathDL
Implemented in 2009 MathDL Workshop, October 2008
More about Research on Faculty Use of the NSDLFor more details visit
http://serc.carleton.edu/facultypart
We wish to acknowledge the National Science Foundation for their support (DUE-0435398). The findings presented here do not necessarily represent the views of the NSF.
Researchers: Alan Wolf, University of Wisconsin, Madison Josh Morrill, Morrill Solutions ResearchGlenda Morgan, George Mason UniversityEllen Iverson, Carleton CollegeCathy Manduca, Carleton CollegeFlora McMartin, Broad-based Knowledge
MathDL Workshop, October 2008
