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The skill of analyzing and interpreting research data is central to the scientific process, yet it is one of the hardest skills for students to master. While instructors can coach students through the analysis of data that they have either generated themselves or obtained from published articles, the burgeoning availability of preprint articles provides a new potential pedagogical tool. We developed a new method in which students use a cognitive apprenticeship model to uncover how experts analyzed a paper and compare the professional’s cognitive approach to their own. Specifically, students first critique research data themselves and then identify changes between the preprint and final versions of the paper that were likely the results of peer review. From this activity, students reported diverse insights into the processes of data presentation, peer review, and scientific publishing. Analysis of preprint articles is therefore a valuable new tool to strengthen students’ information literacy and understanding of the process of science. 

Biomedicine today is experiencing a shift towards decentralized data collection, which promises enhanced reproducibility and collaboration across diverse laboratory environments. This inter-laboratory study evaluates the performance of biocytometry, a method utilizing engineered bioparticles for enumerating cells based on their surface antigen patterns. In centralized and aggregated inter-lab studies, biocytometry demonstrated significant statistical power in discriminating numbers of target cells at varying concentrations as low as 1 cell per 100,000 background cells. User skill levels varied from expert to beginner capturing a range of proficiencies. Measurement was performed in a decentralized environment without any instrument cross-calibration or advanced user training outside of a basic instruction manual. The results affirm biocytometry to be a viable solution for immunophenotyping applications demanding sensitivity as well as scalability and reproducibility and paves the way for decentralized analysis of rare cells in heterogeneous samples. 

Abstract Biomedicine today is experiencing a shift towards decentralized data collection, which promises enhanced reproducibility and collaboration across diverse laboratory environments. This inter-laboratory study evaluates the performance of biocytometry, a method utilizing engineered bioparticles for enumerating cells based on their surface antigen patterns. In a decentralized framework, spanning 78 assays conducted by 30 users across 12 distinct laboratories, biocytometry consistently demonstrated significant statistical power in discriminating numbers of target cells at varying concentrations as low as 1 cell per 100,000 background cells. User skill levels varied from expert to beginner capturing a range of proficiencies. Measurement was performed in a decentralized environment without any instrument cross-calibration or advanced user training outside of a basic instruction manual. The results affirm biocytometry to be a viable solution for immunophenotyping applications demanding sensitivity as well as scalability and reproducibility and paves the way for decentralized analysis of rare cells in heterogeneous samples. 

ABSTRACT The initial phase of the COVID-19 pandemic changed the nature of course delivery from largely in-person to exclusively remote, thus disrupting the well-established pedagogy of the Genomics Education Partnership (GEP; https://www.thegep.org ). However, our web-based research adapted well to the remote learning environment. As usual, students who engaged in the GEP’s Course-based Undergraduate Research Experience (CURE) received digital projects based on genetic information within assembled Drosophila genomes. Adaptations for remote implementation included moving new member faculty training and peer Teaching Assistant office hours from in-person to online. Surprisingly, our faculty membership significantly increased and, hence, the number of supported students. Furthermore, despite the mostly virtual instruction of the 2020–2021 academic year, there was no significant decline in student learning nor attitudes. Based on successfully expanding the GEP CURE within a virtual learning environment, we provide four strategic lessons we infer toward democratizing science education. First, it appears that increasing access to scientific research and professional development opportunities by supporting virtual, cost-free attendance at national conferences attracts more faculty members to educational initiatives. Second, we observed that transitioning new member training to an online platform removed geographical barriers, reducing time and travel demands, and increased access for diverse faculty to join. Third, developing a Virtual Teaching Assistant program increased the availability of peer support, thereby improving the opportunities for student success. Finally, increasing access to web-based technology is critical for providing equitable opportunities for marginalized students to fully participate in research courses. Online CUREs have great potential for democratizing science education.