Page 2
Using tablet
computers
for data
collectionAngie Ficek, MPH
Professional Data Analysts, Inc.
MNEA | January 2016
Page 3
❶ Why we used tablet computers
❷ How we used tablet computers
❸ What we learned
❹ What you should consider
Page 4
Different programs in different settings
with differing levels of access to technology
Page 5
We used paper forms in past evaluations.
Page 6
We first created our own secure website
for data entry.
Page 7
We chose
a secure
website
over an
app.
Page 8
We determined a tablet was the best fit
for our project.
Page 9
We used
the
refurbished
iPad 2.
Page 10
iPad Setup:Restrictions
Page 11
iPad Setup:Data plan
Page 12
iPad Setup:Contract
Page 13
iPad Setup:Training & technical assistance
Page 14
Much
quicker
process,
for us and
for
grantees.
Page 15
The data is cleaner and more secure.
Page 16
One size
does not
fit all.or
Page 17
Next time, we would better determine
who would actually use the tablet.
Page 18
There are very few ongoing costs.
Page 19
Most costs are one-time costs.
Page 20
Is a tablet a good fit?
User
Mobility
Project length
Tech expert
Ongoing TA
Cost
Page 21
Is a tablet
right for
your
project?
[email protected]
Page 24
Do I count this?
• Theme (40)
– Subtheme (15)
• Subtheme of the subtheme (5)
• Subtheme of the subtheme (10)
–Micro subtheme of the subtheme (4)
–Micro subtheme of the subtheme (6)
– Subtheme (5)
– Subtheme (20)
• Subtheme of the subtheme (10)
• Subtheme of the subtheme (10)
Page 26
To what extent can evaluators use humor
to break the ice with evaluation
participants? Does this lead to better data
collection?
I’ve got a question
Page 27
Study Design (5 case studies, cross case analysis)
• Review 12 interview transcripts with joke
• Review 12 interview transcripts without joke
• Observe each evaluator in field visit 3 times
Page 30
It is even compatible with Zotero
Page 40
Qualitative analysis software doesn’t
Page 41
Buy Nvivo + Scrivener + a cup of coffee & a pastry
$1,140 for a 12 month
license
$45 for a license$10 for a Dogwood
Coffee and Rustica
Bakery Chocolate
Pistachio Danish
Page 42
Why not use a writing a platform instead?
Page 44
How to make maps for free with CartoDB
MNEA Tech Tools Event
January 21st, 2016Kirsten L. Anderson, M.A.
Kirsten L. Anderson, L.L.C.
Page 46
Community Outreach
Page 47
Defined geographicalborders
Page 48
The data visualization
challenge
Page 51
The data visualization
solution
Page 55
Step 1. Database Export.csv
Step 2. Data Cleaning
Page 57
Step 3. Geocoding
Page 58
= CONCATENATE(A2,B2)
Page 59
excel-geocoding-tool.xlsx
Page 60
Step 4. Upload into CartoDB
Step 5. Play with fun data viz options
Page 61
https://5klynna5.cartodb.com
Page 62
Spay/Neuter Status of Pets having interaction with AHS Community Outreach in Frogtown*
*June 1 2014 – July 7, 2015Not Spay/Neutered Spay/Neutered Spay/Neutered through Kindest Cut
Original Status Current Status
Page 63
Kirsten L. Anderson, M.A.www.kirstenlanderson.com | [email protected]
Page 65
Data Visualization Using
Tableau
Page 66
What is MNHS?
● Founded in 1849
● 26 historic sites and
museums
● 700 employees
● 2 full-time evaluation
staff
Page 67
LOTS... ~150 evaluations annually
Two-thirds are public programs surveys
What does MNHS evaluate?
Page 68
What are the
audiences?
K-12
Audience
Adult
Audience
Family
Audience
Young
Adult
Audience
Page 69
Who is my client? What are their needs?
Program managers
● Individual program
● Filter by attributes
VS.
Division Directors
Senior Leadership
● BIG data
● Compare by year and
program
Page 70
Who is my client? What are their needs?
Program managers
● Individual program
● Filter by attributes
VS.
Division Directors
Senior Leadership
● BIG data
● Compare by year and
program
Page 71
Reporting methods
Technical reports...nobody read
Paper Reports
Page 72
Google Dashboards
Reporting methods
Page 74
Tableau
Audience
Reports
Print
Digital
Page 75
Ability to show individual program survey data
Page 76
Ability to show aggregate audience data
Page 77
Ability to compare programs
Page 78
Ability to compare multiple years of data
Page 79
Ability to filter and sort data
It’s interactive!!
Page 81
Pros● Transparency
● Accessible
● Easy to understand data
● A lot of visualization options
● Combining many reports into one
Page 82
Pros● Transparency
● Accessible
● Easy to understand data
● A lot of visualization options
● Combining many reports into one
Page 83
Cons● Expensive (up to $2000 per desktop license)
● Steep learning curve for creating dashboards
● Not designed for survey data
Page 84
Erica Orton
[email protected]
Page 86
Please Feed the PANDA
Please Feed the PANDA
Page 88
Joinable Shareable Queryable
Page 89
What about making connections *between* datasets?
Page 90
My project
(Not really *my* project at all, but calling it that helps get this photo in the door.)
Page 91
P Panda
A a
N news
D data
A appliance *
* Recursive acronym
Page 99
What PANDA is not.
Page 103
demo.pandaproject.net
Page 105
Please Feed the PANDA