Research Lab Curriculum with Tutorials for EXperimentalisT Interactive LEarning

AUTHORS

• Hawley Helmbrecht, Chemical Engineering, UW Seattle
• Elizabeth Nance, Chemical Engineering, UW Seattle

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ABSTRACT

Tutorials for EXperimentalisT Interactive LEarning (TEXTILE) is a module-based laboratory education curriculum that we developed within the Nance Lab in the chemical engineering department. We developed TEXTILE as an approach to training lab members in data science methodologies commonly used within the lab for studying and quantifying brain disease. We developed TEXTILE during COVID-19 lockdown and laboratory shutdown when many students were about to lose their summer research opportunities. To keep students involved in research, we developed a virtual data science course that resulted in independent student research projects. Student experiences in STEM education are affected by participation in research. Undergrad student involvement in research introduces students to cutting-edge research and increases skills in critical thinking and problem solving. TEXTILE increases access to research while decreasing the time burden of lab training. We taught 15 students for 12 weeks in Summer 2020. By approaching lab education through a structured format, I learned that students want to learn beyond a specific methodology; exact lab techniques should be supplemented with research design, greater field specific scientific lessons, and data management. TEXTILE is transformative for lab training as it decreases overall training time and transitions students from structured education to freeform research-based learning. Although we developed TEXTILE specifically for methodologies from our lab, the basic educational outline and goals can be applied to any research area using data analysis. With TEXTILE, instructors from other disciplines will decrease the time-commitment of lab training therefore increasing a lab’s capacity to provide research opportunities for a more undergrads.

SUMMARY

RESEARCH QUESTION

Can we develop curriculum to effectively train students in computational/data science based lab methodologies?

RESEARCH METHODS / SCHOLARLY BASIS

Curriculum development of research lab methodologies taught to a cohort of students from high school, undergraduate, and graduate levels. To keep students involved in research, we developed a virtual data science course that resulted in independent student research projects. Student experiences in STEM education are affected by participation in research. Undergrad student involvement in research introduces students to cutting-edge research and increases skills in critical thinking and problem solving. TEXTILE increases access to research while decreasing the time burden of lab training.

RESULTS

We taught 15 students for 12 weeks in Summer 2020. By approaching lab education through a structured format, I learned that students want to learn beyond a specific methodology; exact lab techniques should be supplemented with research design, greater field specific scientific lessons, and data management. TEXTILE is transformative for lab training as it decreases overall training time and transitions students from structured education to freeform research-based learning.

APPLICATION

Although we developed TEXTILE specifically for methodologies from our lab, the basic educational outline and goals can be applied to any research area using data analysis. With TEXTILE, instructors from other disciplines will decrease the time-commitment of lab training therefore increasing a lab’s capacity to provide research opportunities for a more undergrads.