Program
Pre-workshop
Pre-workshop tutorials
If you are new to R (or new to the ggplot2 or data.table packages), we recommend you complete the three introductory tutorials listed below. Completing these tutorials before attending the Institute will make your time with us that much more productive.
Each tutorial can be completed in under an hour if you have any experience with procedural programming languages such as MATLAB, R, or Python. Programming novices might need more than an hour each.
Tuesday, June 11
Office hours
1:00–5:00 pm Eastern Time. We are available for answering questions and resolving problems you encounter installing R or working with R in the three pre-workshop tutorials.
Wednesday, June 12
Introductions 
slides
1:00–1:50 Eastern Time
Introduce facilitators and participants, objectives, and MIDFIELD.
Break
1:50–2:00
Exploring data structure slides
2:00–3:00
Exploring data excerpts manually.
- Student 3 data example
- Student 4 data example
- CIP website NCES Classification of Instructional Programs (CIP)
Guided practice.
3:00–5:00
Self-paced case study using midfieldr and midfielddata. Real-time help.
- Case study: Goals A short reading.
- Case study: Data A midfieldr tutorial.
Wrap-up
before 5:00
Please check in with us before leaving the virtual meeting.
Homework
- Complete the guided practice “Data” tutorial.
- For our think-share activities in tomorrow’s data visualization session, consider printing a hard-copy of the worksheet. (Download link in tomorrow’s program below.)
Optional resources
- Topics from today’s guided practice are developed in greater detail in midfieldr package vignettes [link].
Thursday, June 13
Metaphors and metrics slides
1:00–1:30 Eastern Time
Pipelines, pathways, and ecosystems.
Break
1:30–1:40
Guided practice
1:40–2:30
Case study: Results Continue the case study.
Data visualization session 1 worksheets slides
2:30–3:20
A hard-copy printout of the worksheet is recommended for our think-share activities. We demonstrate the perceptual limitations of common graph types and suggest more effective alternatives. Our goals in visual rhetoric are
- Improving perception of stories in the data
- Facilitating quantitative reasoning about the data
- Enhancing credibility of evidence supporting an argument
Break
3:20–3:30
A practice research question slides
3:30–5:00
We partially define a practice research question to be examined using midfieldr and midfielddata. Working in small groups and given a specific metric, choose programs and student blocs and develop the appropriate data and chart(s) to explore possible stories in your data. Report out your progress by the end of the day.
Resources
- data dictionary: CIP codes (data set
cipincluded with midfieldr) - data dictionaries: student practice data / research data
- data dictionaries: term practice data / research data
- data dictionaries: course practice data / research data
- data dictionaries: degree practice data / research data
Wrap-up.
before 5:00
Please check in with us before leaving the virtual meeting.
Homework
- Complete the guided practice “Results” tutorial.
- Consider what research question you would like to work on during the final day of the workshop. You may continue the practice question you started today or you may develop a new research question.
- For our think-share activities in tomorrow’s data visualization session, consider printing a hard-copy of the worksheet. (Download link in tomorrow’s program below.)
Optional resources
- Topics from today’s guided practice are developed in greater detail in midfieldr package vignettes [link].
- Developing the migration yield metric. slides An optional supplement to the metaphors and metrics session that outlines the iterative process between the logic of an argument and the logic of a chart that led us to develop the migration yield metric.
Friday, June 14
Data visualization session 2 worksheets slides
1:00–2:00 Eastern Time
A hard-copy printout of the worksheet is recommended for our think-share activities. We illustrate a repertoire of chart types and how they are suited to specific data structures and answering specific types of questions.
Work on your research question
2:00–3:30
Small-group work. Consult with us on your progress, discussion
Resources
- data dictionary: CIP codes (data set
cipincluded with midfieldr) - data dictionaries: student practice data / research data
- data dictionaries: term practice data / research data
- data dictionaries: course practice data / research data
- data dictionaries: degree practice data / research data
Progress report
3:30–4:30
Share with the group.
Wrap up
4:40–4:45