In-class Data Analysis Replications: Teaching Students while Testing Science
Kristina Gligoric, Tiziano Piccardi, Jake Hofman, Robert West

TL;DR
This study shows that integrating data analysis replications into a university course enables students to reproduce scientific papers, fosters critical thinking, and provides benefits for scientific reproducibility and education.
Contribution
It demonstrates the feasibility and benefits of incorporating data analysis replications into classroom settings, highlighting student capabilities and educational impacts.
Findings
Students can replicate published scientific papers, mostly qualitatively.
Attitude shifts towards reproducibility observed among students.
Provides insights for educators on implementing replications effectively.
Abstract
Science is facing a reproducibility crisis. Previous work has proposed incorporating data analysis replications into classrooms as a potential solution. However, despite the potential benefits, it is unclear whether this approach is feasible, and if so, what the involved stakeholders-students, educators, and scientists-should expect from it. Can students perform a data analysis replication over the course of a class? What are the costs and benefits for educators? And how can this solution help benchmark and improve the state of science? In the present study, we incorporated data analysis replications in the project component of the Applied Data Analysis course (CS-401) taught at EPFL (N=354 students). Here we report pre-registered findings based on surveys administered throughout the course. First, we demonstrate that students can replicate previously published scientific papers, most…
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Taxonomy
TopicsScientific Computing and Data Management · Genetics, Bioinformatics, and Biomedical Research
