BioGraphI - Biologists and Graph Interpretation: Professional development for an online curriculum to foster data literacy and value diverse identities (RCN-UBE Introduction)
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31 May 2023 | Contributor(s): Suann Yang, Rachel Pigg | doi:10.25334/RZF7-HD17
Biologists and Graph Interpretation (BioGraphI) is an RCN of faculty who work collaboratively to increase student persistence in biology through improving representation of diverse scientists in the curriculum and incorporating data interpretation skills.
BioGraphI Interview Questions - Google Docs
29 Dec 2022 | Contributor(s): Rachel Pigg, Suann Yang | doi:10.25334/VP1B-5G33
This document contains and describes the interview questions used in interviews conducted by the Biologist and Graph Interpretation (BioGraphI) Network. Curriculum developers use it to prepare for the interview component of a BioGraphI module.
BioGraphI OER Lesson Guide Template - Google Docs
29 Dec 2022 | Contributor(s): Suann Yang, Rachel Pigg | doi:10.25334/D4VP-MK95
This template of a lesson plan was developed for the Biologists and Graph Interpretation (BioGraphI) Network. Curriculum developers use it to make a BioGraphI module.
An Overview of the Biologists and Graph Interpretation Project
06 Oct 2022 | Contributor(s): Suann Yang, Rachel Pigg | doi:10.25334/ZAWN-5M02
Biologists and Graph Interpretation (BioGraphI) is an NSF Research Coordination Network of faculty who work collaboratively to increase student persistence in biology through improving representation of diverse scientists in the curriculum and incorporating data interpretation skills. This...
Why representation matters: Interpreting data to identify factors that affect Black students’ persistence in STEM
22 Aug 2022 | Contributor(s): Suann Yang, Catherine Quinlan | doi:10.25334/7B59-SJ83
In this lesson, learners interpret a table summarizing the factors influencing the persistence of Black students at an HBCU. Then, learners view and reflect on an interview with science education researcher Dr. Catherine Quinlan, who collected the data that they interpreted.
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