Reduce Friction, Increase Learning

Keep Your Trombone On A Stand!

David Dalpiaz

February 9, 2023

Introduction

Trombones

Figure 1: Two trombones, each disassembled and in a case.

Image Source: Wikimedia Commons

Friction

(a) A block with mass \(m\) on a slope.
(b) Free body diagram of the block on a ramp. The force of friction, \(F_f\) points uphill.
Figure 2: Friction represented by a block on a ramp.

Image Source: Wikimedia Commons

Trombones, But Less Friction

Figure 3: A trombone, assembled, resting on a stand.

Image Source: PublicDomainPictures.net

Barriers to Education

  • Admissions
  • Finances
  • Registration
  • …

These are largely outside the control of course instructors.

Friction in Education

In the presence of friction, some kinetic energy is always transformed to thermal energy, so mechanical energy is not conserved.

Courses convert students’ motivation, effort, and prior knowledge to learning. (Ambrose et al. 2010) Friction in education results in wasted motivation and effort.

The Metaphor, Overexplained

  • Barriers to education keep the block off the ramp.
  • Students’ motivation, effort, and prior knowledge are potential energy.
  • We want to convert this potential energy into kinetic energy, learning.
  • Friction is motivation and effort that is not converted from potential to kinetic energy.

Potential Sources of Friction

  • Modality of course activities
  • Course material accessibility and costs
  • Deadlines
  • Time to feedback
  • Exam proctoring
  • …

What can we do to reduce these frictions?

Current Work

Lecture Modality

Are in-person lectures a source of friction?

Figure 4: A beautiful but empty classroom.

Image Source: Campus Instructional Facility | University of Illinois

Lecture Modality, Continued

A natural experiment occurred in STAT 385, Statistical Programming Methods.

Section A

  • Online
  • Asynchronous
  • Pre-recorded videos

Section B

  • In-person
  • Synchronous.
  • Equal access to videos

Result

Less than 10% in-person attendance by Week 14.

Course Communication

What channels do we use to communicate with students? Are they the right choices? For me, currently:

  • One email per week, at the start of the week
  • Discussion forum: Ed Discussion
    • I love this! Do students?
  • Office hours
  • Email

What about Slack Discord?

Course Communication, Ed

Figure 5: A course instructor talking to himself to demonstrate the features of Ed, including executable code and threaded responses.

Time To Feedback

Autograding is wonderful! PrairieLearn (West, Herman, and Zilles 2015) in particular!

  • Scale!
  • Flexibility!
  • Instant feedback!
  • …

PrairieLearn R Autograder

Joint work with Dirk Eddelbuettel and Alton Barbehenn

  • R Autograder, Docker image and entrypoint
  • plr, R package containing helper functions for using the PrairieLearn R autograder

Recent improvements to plr:

  • Security!
  • Reduced computation required to grade student code
  • Ease of test case authoring

PrairieLearn R Autograder Example

(a) Question statement
(b) Grading results
(c) Test case details with diffs
Figure 6: An autograded Prairielearn question for R code

Deadlines

Use flexible deadlines!

  • Far fewer last-minute extension requests.
  • Preferred to using drops for some number of assignments.

How? Buffer points. Consider a homework with deadlines:

  • 105% Credit: Thursday, February 2, 11:59 PM
  • 100% Credit: Thursday, February 9, 11:59 PM
  • 75% Credit: Thursday, February 16, 11:59 PM

Importantly: Buffer points are not extra credit.

Office Hours

In-person or online? My current preference is online.

  • One click access!
    • Could use scheduled reminders
  • Screen sharing!
  • Remote control!

Computer Literacy

  • A lot of exciting work is hidden behind “drudgery.” (Bryan 2020)
  • Students are often interested in data and data applications, but “bad with computers.”
  • These students are unaware of “simple” things like window management with [alt] + [tab], let alone more “advanced” techniques.
  • How can we remove this friction?

Exam Proctoring

Figure 7: A testing facility, the Computer-Based Testing Facility (CBTF) (Zilles et al. 2015) at University of Illinois, containing numerous computers arranged in rows.

Image Source: AE3 | University of Illinois

Exam Proctoring, Continued

Does Zoom-based online proctoring reduce friction?

Tools:

Observations:

  • Familiar versus unfamiliar environments for students
  • Security, time, and flexibility trade-offs

Content Accesability

Future Work

Robust Feedback

Instant feedback is great, but what is that feedback?

In addition to feedback being quick and frequent, it should be robust.

Two small trials:

  • Video feedback for final projects
  • Reactive and tutorial style lecture content
    • Can we learn anything from eSports and streaming?

Multimedia Feedback

… designing quiz feedback to instantly (dynamically) deploy a multimedia video that covers the topic has the greatest impact on learning performance. Students who had the opportunity to learn the concept visually through the use of pictures, video and audio performed 5.3 times better than a student who did not receive multimedia feedback. This was true of all learners independent of age, gender, level of education and English-language ability. It was also true across four different types of questions reflecting the first four levels of Bloom’s taxonomy.

Fein (2017) Multimedia Learning: Principles of Learning and Instructional Improvement in Massive, Open, Online Courses (MOOCS)

Multimedia Feedback, Expert View

Figure 8: Ben “Merlini” Wu streams a game of Dota 2 on Twitch.

Authentic Autograded Experiences

PrairieLearn is the interface to learning with the least friction that I have used.

Can we go further?

The interface to learning should be as similar as possible to the interface to doing.

My Interface To Doing

Figure 9: A screenshot of the RStudioIDE during package development.

Reduce Friction, Increase Learning

(a) A block on a ramp.
(b) A trombone.
Figure 10: Trombones, blocks, and ramps as an over-complicated metaphor about friction and learning.

Image Source: Wikimedia Commons

References

Ambrose, Susan A, Michael W Bridges, Michele DiPietro, Marsha C Lovett, and Marie K Norman. 2010. How Learning Works: Seven Research-Based Principles for Smart Teaching. John Wiley & Sons.
Bryan, Jenny. 2020. “Object of Type ‘Closure’ Is Not Subsettable.” RStudio. January 31, 2020. https://github.com/jennybc/debugging/.
CAST. 2018. “Universal Design for Learning Guidelines Version 2.2.” http://udlguidelines.cast.org.
Fein, Adam Daniel. 2017. “Multimedia Learning: Principles of Learning and Instructional Improvement in Massive, Open, Online Courses (MOOCS).”
West, Matthew, Geoffrey L Herman, and Craig Zilles. 2015. “PrairieLearn: Mastery-Based Online Problem Solving with Adaptive Scoring and Recommendations Driven by Machine Learning.” In 2015 ASEE Annual Conference & Exposition, 26–1238.
Zilles, Craig, Robert Timothy Deloatch, Jacob Bailey, Bhuwan B Khattar, Wade Fagen-Ulmschneider, Cinda Heeren, David Mussulman, and Matthew West. 2015. “Computerized Testing: A Vision and Initial Experiences.” In 2015 ASEE Annual Conference & Exposition, 26–387.

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