The March 2019 OOI Data Labs workshop featured 20 participants and staff from around the country.

The March 2019 OOI Data Labs workshop featured 20 participants and staff from around the country.

OOI Ocean Data Labs Development Workshop

March 8-13, 2019

Chauncey Conference Center, Princeton, NJ

At this workshop, professors from around the country will come together to learn about and engage in efforts to bring Ocean Observatory Initiative (OOI) data into their undergraduate teaching.

You can learn more about our full series of Data Lab Workshops

Key Objectives of the Data Lab Workshop

Participants will:

  1. Learn about the OOI program and key science questions it addresses.
  2. 2. Access existing tools and resources designed to integrate OOI data into teaching.
  3. 3. Be introduced to Python as a tool for working with and engaging students in OOI data.
  4. 4. Learn how to effectively incorporate OOI data labs into undergraduate teaching.
  5. 5. Create a customized new resource to bring OOI data into your classes.
  6. 6. Have an opportunity to network with other professors interested in using oceanographic data. in undergraduate teaching.

Workshop Overview

  • Day 1: Laying the groundwork for understanding and using OOI data in teaching; explore existing OOI data labs
  • Day 2: Exploring Python and building data skills; Generating ideas for how you will bring OOI data into your undergraduate course
  • Day 3: Creating a plan:  what OOI customized resource will I create?
  • Day 4: Develop and refine your OOI customized resource
  • Day 5: Reflection and presentations: looking forward; planning for future applications of OOI in my teaching.

Agenda and Resources

Friday

Orientation – Friday March 8, 2019

Time Topic, Objectives & Activities
6:00 pm Dinner
7:30 pm Welcome and Introductions
Meet each other and review the goals of the week.
8:30 pm Conclude for evening
Saturday

Day 1 – Saturday March 9, 2019

Objective: Laying the groundwork for understanding and using OOI data in teaching.

Time Topic, Objectives & Activities
8:00 am Breakfast
9:00 am The OOI Today: An introduction to its history and the science it supports
Understand the driving forces that created the OOI and how it can enable future scientific research.
9:40 am The Structure of the OOI & the OOI Website
Learn about the OOI infrastructure and discover where key resources can be found on the OOI website.

10:30 am Coffee Break
10: 45 am Where does OOI data fit in my teaching? Case Study on Primary Production
Understand how OOI can be integrated into undergraduate teaching with a case study example.

11:30 am Exploring Learning Science Pedagogy: Designing learning experiences to support learning. 
Introduce common language/pedagogy for how we introduce and apply OOI data in our teaching – using the Learning Cycle.
12:30 Lunch
1:15 pm Exploring Learning Science Pedagogy: Designing learning experiences to support learning. Wrap up & Reflection

1:45 pm Explore Existing OOI Data Labs (Chemistry, Biology, or Geology)
Hands on exploration of previously developed Data Labs.

  1. Exploration – Chlorophyll across the year
  2. Application – Chlorophyll in and off shore
  3. Exploration – Processes that Change Salinity
  4. Application – Changes in Salinity with Depth
  5. Exploration – Plate Boundary Features
  6. Application – Geological Features of a Seamount – 2
3:00 pm Coffee Break
3:15 pm OOI Science: A Case Study with the Irminger Sea
Explore an example published dataset from the Irminger Sea that explores the disciplinary core idea (science) and the data visualization process.

4:15 pm Reflection and Feedback
Review and reflect on what was learned today.
Road Check #1
5:00 pm Free Time
6:00 pm Dinner
Sunday

Day 2 – Sunday March 10, 2019

Objective: Exploring OOI data and building data skills.

8:00 am Breakfast
9:00 am Welcome back!
OOI Science & Python Skills Building
Irminger Sea Case Study
Explore the teaching advantages of creating an instructor controlled computing environment (Google Colab). Use Python to visualize Irminger Sea data.

10:00 am Group Discussion
What have you learned so far?  How can we help get over challenges we are encountering?
10:30 am Coffee Break
10:45 am Data Lab:  Backwards Design Step 1 & 2
Work Session: What are big ideas and important understandings? What do you want your students to know/be able to do with that concept?
Step 1 – What science questions are you interested in using OOI data?
Step 2 – How would you know your students are on the right path?

12:15 pm Lunch
1:15 pm Backwards Design: Step 3
Participation in the Data Labs Project
Define the product you will develop during this workshop.

1:30 pm Introduction: Share-a-thon & Panel Discussion
Discuss student discomfort in working with data.  What challenges do our students face conducting quantitative tasks? What are the strategies we can use to overcome these challenges?
2:15 pm Teaching with Data Pedagogy
Session A:  Design Patterns to Teaching with Data
Step back and think about Pedagogy & Strategies of how to design learning experiences that help students develop quantitative data skills.

3:15 pm Coffee break
3:30 pm Data Lab: Backwards Design Revisit and Revise Step 2
Work Session – Refining your Goals/Objectives
Present you goals for student interaction with data. What data skills do you want to build with your students?
4:30 pm Reflection and Feedback
Review and reflect on what was learned today. What excited you about today – what would you share with a colleague about today’s work?
Road Check #2
5:15 pm Free time
6:30 pm Dinner
Monday

Day 3 – Monday March 11, 2019

Objective: Creating a Data Lab.

Time Topic, Objectives & Activities
8:00 am Breakfast
9:00 am Python Program Skills Building
Using an OOI Example – BOT Data and Earthquake Data
Use Python to visualize earthquake data.

10:00 am Teaching with Data Pedagogy
Session B: Developing Data Skills
Create an on-ramp for student success with data exploration and help students develop quantitative data skills.
11:00 am Coffee Break
11:15 am Backwards Design Step 3
Work Session: Zeroing in on a Dataset
Explore and expand access to OOI data platforms. Use Identify the datasets you would like to use. Group presentations on progress
12:30 pm Lunch
1:15 pm Teaching with Data Pedagogy
Session C: Getting Students to Visualize Data
Explore the big picture of skills needed to make decisions about different graph types.
1:45 pm Backwards Design Step 3
Work Session: Create a Data Lab Challenge Question
Identify how you will challenge your students to analyze the provided dataset(s). What practice(s) will they use?
3:00 pm Coffee Break
3:15 pm Exploring Learning Science Pedagogy
Foundational Ideas on Learning 
Discuss and expand your understanding of how people learn and how to bring these ideas into yourteaching.

>4:15 pm Backwards Design Step 2 & 3
Work Session: Guiding Your Students Toward an Explanation
Develop questions that will help your students address the research challenge.
4:45 pm Reflection and Feedback
Review and reflect on what was learned today.
Road Check #3
5:00 pm Free Time
6:30 pm Dinner
Tuesday

Day 4 – Tuesday March 12, 2019

Objective: Develop and refine your OOI customized resource

Time Topic, Objectives & Activities
8:00 am Breakfast
9:00 am Exploring Learning Science Pedagogy
Exploring the role of Prior Knowledge in Learning
Activity and discussion about the role of prior knowledge in learning.
10:30 am Coffee Break
10:45 am Backwards Design Step 3
Work Session:  Background and Introduction
Add an introduction to help your students access and connect to their prior knowledge and provide a motivating context for your investigation through your introduction.

11:45 pm Backwards Design Step 3
Work Session:  Group Check in
How can we help get over challenges we are encountering?
12:15 pm Lunch
1:15 pm BREAK! Virtual Tour of the COOL room:  Live link to Rutgers School of Environment and Biological Sciences (SEBS).
1:45 pm Backwards Design Step 3
Work Session:  Break into Groups and Share out
Work on refining and sharing plans for Data Lab creation.
2:45 pm Coffee Break
3:00 pm Backwards Design Step 3
Work Session:  Develop a Data Lab Assessment
Revisit assessment options.  How will you know your students have learned?  Develop Instructor Notes for your Data Lab.
4:30 pm Reflection and Feedback
Review and reflect on what was learned today.
Road Check #4
5:00 pm Free Time
6:30 pm Dinner
Wednesday

Day 5 – Wednesday March 13, 2019

Objective: Looking forward and planning for future

Time Topic, Objectives & Activities
8:00 am Breakfast
9:00 am Work Session
10:00 am Presentations (10 minutes/participant)
Share what level you will engage in moving forward; what have you accomplished? How will you move forward?
11:30 am Taking it All Home / What’s Next?
What might we take forward? What are the most valuable aspects of OOI assets for teaching? What will we take home? How can we involve more scientists in OOI? See video for inspiration.
12:00pm Final Reflection and Farewell Lunch
Summary reflection and final logistics
Final Road Check
12:30 pm Lunch
2:00 pm Depart for home

Workshop Participants

Professors

  • Tania-Maria Anders, Mt. San Antonio College
  • Kathy Browne, Rider University
  • Haley Cabaniss, University of Illinois, Urbana-Champaign
  • Walter Cho, Point Loma Nazarene
  • Rebecca Freeman, University of Kentucky
  • Karen Helgers, SUNY Ulster
  • Megan Jones, North Hennepin Community College – Geology
  • Joseph Long, University of North Carolina Wilmington
  • Cecilia McHugh, Queens College, City University of New York
  • Michael Navarro, University of Alaska Southeast
  • Jochen Nuester, CSU Chcio
  • Jessica Olney, Hillsborough Community College
  • Michael Phillips, Illinois Valley Community College
  • Lauren Sahl, Maine Maritime Academy
  • Matthew Semcheski, Florida Keys Community College
  • Gabriella Smalley, Rider University
  • Christine Tuaillon, Nassau Community College
  • Amy Weislogel, West Virginia University
  • Carol White, Southern Maine Community College
  • Alicia Williams, University of New England

Facilitators

  • Christine Bean, Rutgers University – New Brunswick
  • Catherine Halversen, Lawrence Hall of Science, UC Berkeley
  • Kristin Hunter-Thomson, Rutgers University – New Brunswick
  • Sage Lichtenwalner (@visualocean), Rutgers University – New Brunswick
  • Janice McDonnell, Rutgers University – New Brunswick
  • Anna Pfeiffer-Herbert, Stockton University
  • Dax Soule (@DaxSoule), Queens College, CUNY