Teaching applied spatial statistics: Using open educational and reproducible resources

Anastasia Soukhov (PhD Candidate, McMaster University) Antonio Paez (Associate Professor, McMaster University)

Overview

1. The course materials
2. Learners’ reflections
3. My reflections

I’m a PhD Candidate in the School of Earth, Environment and Society.

Researching equitable, just and sustainable transportation systems.

Mostly quantitative spatial work; taught Applied Spatial Statistics (ENVSOCTY 4GA3) Winter 2023 using reproducible flow.

This presentation is about my experience as a sessional using Open Educational Resources and the perspective of the learners (their reflections).

This presentation - and anything I seem to be doing - is fully reproducible.

A) Course materials

Getting started with ENVSOCTY 4GA3

The Webbook:

Part 1: Introductions

Part 2: Getting to know the techniques

Part 3: Point pattern analysis

Part 4: Areal unit data

Part 5: Field data

The availability of this textbook and its reproducibility made catching up on the material much easier! First time teaching. I also reused the course layout / breakdown

The webbook is accompanied by R package {isdas}:

Contains .Rmd templates (Chapters and Activities):

Contains data sets:

1 activity per chapter… learners can knit to .pdf, .html, and .docx; high-quality deliverable that learners take ownership of! Fully reproducible and customizable

Mark breakdown for learners

• 40% weekly assignments: delivered as a “flipped classroom”
• 30% final group project report
• 30% reflections

Example reflection question

What is in your opinion the most important thing that you learned while in this course? How did you learn it? What challenges and opportunities did you face when learning this thing? Did learning this thing impact you? If so, how?

Would you say this experience will impact how you do things in the future, and if so how?

Reflection marking rubric (Whalen, 2020)

Reflective learning framework and video

Reflection marking rubric (Whalen, 2020)

Reflective learning framework and video

What we think this course does

• Saves the learners money
• Focuses the mind away from the trivial
• Teaches valuable skills
• Incentivises ownership of the learning process
• Provides a positive challenge

B) But what did they think? Learners’ reflections

Flipped classroom (1/5)

“I enjoyed the split classroom style. It made for a demanding but not stressful experience. I also liked the lab and classroom topics, applying the concepts and then learning the details was really helpful for understanding..”

New tools for the future (2/5)

“…I’ve even done a bit of R coding in my free time using open-source data just for fun when a random topic … that I want to investigate further (i.e. covid cases and vaccinations, real estate prices…)”

Science communication (3/5)

” This reflection merely put into words a realization that I had failed to experience in earlier stats courses:… being able to analyse your data in a way that is fair, comparable, and communicable is invaluable.”

Threshold concepts: e.g., null landscapes (4/5)

“Learning about the null landscape was where my mindset started to switch…. So naturally, I started to think about how you could consider points random….[how] to explain randomness statistically. This was linked with hypothesis testing, which helped me understand set boundaries in the setting of point pattern analysis.”

Webbook (5/5)

” The textbook was very comprehensive, and the integration with R-Studio definitely enhanced my understanding of the code connected with each concept..”

“While the textbook was a superb resource, it is also quite dense, and something like a chapter summary at the end that highlights the key takeaways ….”

Clusters of topics within learners’ reflections

C) My reflections

Wrapping up: my reflections

• Transparency and openness of course material: easier for all
• The flipped classroom format: two-way knowledge transfer.
• Reflections in place of tests: gives space for connections

Room for improvement:

• How to engage the disengaged?
• Prevalence of AI: the temptation for use on take-home reflections

• Open course material made it easier for me to catch-up
  • Made me more confident
  • Transparent; who worked on it before me and what they did.
  • Thankful for the learners before me; that got the course progression correct: “… By the time the course had moved into spatially continuous data, I was in a pretty good groove. Thanks to my gradual build-up of better statistical understanding over the course of the semester, I’d say I had the easiest time with this section”
• The flipped classroom; facilitated a space for learning.
• Reflections and group project in place of tests: learners make connections between feelings, thoughts and concepts as well as apply them in a project of their choosing.

Thank you! Questions/Comments?

Anastasia Soukhov (soukhoa@mcmaster.ca)

I’d like to acknowledge funding recieved through the MacPherson Institute’s 2020/21 OER Creation Grant (PI: Antonio Paez)