TEXTILE (Tutorials for EXperimenTalist Interactive LEarning) in Data Science

This TEXTILE curriculum teaches trainees data science from the biological perspective of brain cell shape quantification.

What is TEXTILE?

In the Disease Directed Engineering Lab (nancelab.com), we develop tools to inform how we can more effectively treat the diseased brain. In our lab, we take a lot of cool immunofluorescent images of brain cells. To better analyze those cells, we developed a data science pipeline for cell segmentation and quantification. To train others within and outside of our lab to use our cell quantification pipeline, we developed TEXTILE!

This is the home repository for our first TEXTILE course from Summer 2020.

TEXTILE Curriculum

TEXTILE is a semi-linear, module-based learning system!

What does that mean?

/semi-linear/ We have three linear pathways to follow along with:

1. Research Lab Specific (purple, top row): Motivates the greater TEXTILE work within the context of the Disease Directed Engineering Lab.
2. Data Science Specific (green, middle row): The data science fundamentals needed to support the end learning goal of image processing and train students on data management for experimentalists.
3. Image Processing Specific (blue, bottom row): The cell segmentation and quantification lessons

Based on the personal preference and previous experience of the trainee, the three pathways can be followed independently or together. Additionally, based on students' previous experience, the curriculum can begin at any point on the linear pathway. For example, if the student is familiar with data science but not image processing, they can learn only the image processing specific pathway and skip the data science specific pathway.

/module-based/ Every lesson is a module with three parts:

1. pre-module: A primer to get you thinking about the main lesson
2. main module: The main educational lesson
3. post-module: A reflection exercise with opportunities to explore more independently.

TEXTILE Curriculum. Demonstrates the three educational paths - Research Lab Specific (purple), Data Science Specific (green), and Image Processing Specific (blue). Entry points are displayed as doorways (yellow). Image from Helmbrecht H., Nance E. Effective Laboratory Education with TEXTILE: Tutorials in EXperimentalisT Interactive LEarning. Journal of Chemical Engineering Education. In Press.

See the Publication

1. For more information about the Summer 2020 curriculum including student outcomes, learning objectives, and teaching methods, see our publication (Coming Soon!):

Helmbrecht H., Nance E. Effective Laboratory Education with TEXTILE: Tutorials in EXperimentalisT Interactive LEarning. Journal of Chemical Engineering Education. In Press.

2. Check out the published slides from our presentation of TEXTILE at the American Institute for Chemical Engineers (AIChE) 2021 Conference:

Helmbrecht H., Nance E., Textile: Tutorials in Experimentalist Interactive Learning. Computer Aids for Chemical Engineering. Paper # 449d (https://cache.org/sites/default/files/449d_2021TeachingDataScience_HelmbrechtNance.pdf)

How to Use as a Student:

Welcome to TEXTILE! We hope this curriculum can jump start your cell analysis work.

1. Determine starting point: (below are some examples)

   • No coding experience: Start at beginning of Data Science Pathway

   • Coding experience without image processing experience: Skip the data Science pathway and begin with the Image Processing Specific Pathway

   • Trainee with the Disease Directed Engineering Lab: Begin with the Data Science in the Nance Lab module. Then begin the data science specific pathway, followed by the image processing specific pathway before doing the Research Paper Specific Workflow module back in the Research Lab Specific Pathway.

2. Download the repository

3. Work through the modules in linear order based on the pathways you chose

How to Use as an Instructor

Welcome to TEXTILE! For instructors we have two pathways to follow: Teaching Current Modules and Developing Your Own Curriculum.

Teaching Current Modules:

1. Download the repository and plan to teach the Data Science Specific and Image Processing Specific pathways
2. At least two days before the lesson, send out the pre-module activity
3. Teach the module live either by presenting the PPT file in earlier Modules or completing a code-along with areas for students to ask questions and explore independently
4. After the lesson, send out the post-module reflection to students

Developing Your Own Curriculum:

1. Identify your end goal: We recommend a methodology that produces a data set with a large number of features and application variability
2. Break down your end goal into the basic units needed to learn it (each of these units becomes a module)
3. Organize the modules by topics (these become the linear pathways)
4. Follow the "How to Module" Module PPT to explore how to design learning objectives and create modules of your own

What's next for TEXTILE?

Thanks for asking! We are planning an expansion for Summer 2022 which will include:

1. Recorded lessons of the current curriculum
2. Machine learning lessons for multiple particle tracking
3. Demos of wet lab techniques used to acquire data in curriculum
4. Lessons on database management for nanotherapeutic experiments
5. Additional instructor material such as a syllabus and suggested classroom timelines

We look forward to sharing the next evolution of our curriculum.