Cognitive and non-cognitive outcomes associated with student engagement in a novel brain mapping and connectomics course-based undergraduate research experience
D'Arcy, C. E.; Martinez, A.; Khan, A. M.; Olimpo, J. T.
Show abstract
Course-based undergraduate research experiences (CUREs) engage emerging scholars in the authentic process of scientific discovery, and foster their development of content knowledge, motivation, and persistence in the science, technology, engineering, and mathematics (STEM) disciplines. Importantly, authentic research courses simultaneously offer investigators unique access to an extended population of students who receive education and mentoring in conducting scientifically relevant investigations and who are thus able to contribute effort toward big-data projects. While this paradigm benefits fields in neuroscience, such as atlas-based brain mapping of nerve cells at the tissue level, there are few documented cases of such laboratory courses offered in the domain.\n\nHere, we describe a curriculum designed to address this deficit, evaluate the scientific merit of novel student-produced brainatlasmapsofimmunohistochemically-identifiednervecellpopulations for the rat brain, and assess shifts in science identity, attitudes, and science communication skills of students engaged in the introductory-level Brain Mapping and Connectomics (BM&C) CURE. BM&C students reported gains in research and science process skills following participation in the course. Furthermore, BM&C students experienced a greater sense of science identity, including a greater likelihood to discuss course activities with non-class members compared to their non-CURE counterparts. Importantly, evaluation of student-generated brain atlas maps indicated that the course enabled students to produce scientifically valid products and make new discoveries to advance the field of neuroanatomy. Together, these findings support the efficacy of the BM&C course in addressing the relatively esoteric demands of chemoarchitectural brain mapping.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Science Education for the Youth (SEFTY): A Neuroscience Outreach Program for High School Students in Southern Nevada During the COVID-19 Pandemic 95%
- Internet-connected cortical organoids for project-based stem cell and neuroscience education 94%
- Factors that Influence Career Choice Among Different Populations of Neuroscience Trainees 93%
Similar papers in this journal
- Flying in the Face of Adversity: A Drosophila-based Virtual CURE Provides Semester-long Authentic Research Opportunity to the Flipped Classroom. 96%
- Preprint peer review enhances undergraduate biology students' disciplinary literacy and sense of belonging in STEM 95%
- Remote Learning Barriers and Opportunities for Graduate Student and Postdoctoral Learners in Career and Professional Skill Development: A Case Study 94%
Similar papers in this journal
- An innovative approach to using an intensive field course to build scientific and professional skills 94%
- A Systems Change Framework for Evaluating Academic Equity and Inclusion in an Ecology & Evolution Graduate Program 93%
- yEvo: a modular eukaryotic genetics and evolution research experience for high school students 93%
Similar papers in this journal
- Nationally endorsed learning objectives to improve course design in introductory biology 95%
- "When I talk about it, my eyes light up!" Impacts of a national laboratory internship on community college student success 95%
- Biology exams rarely use visual models to engage higher-order cognitive skills 94%
Similar papers in this journal
- Dissociating Language and Thought in Human Reasoning 87%
- Continued topographical learning- and relearning-dependent activity in the resting state after post-training sleep and wake 86%
- Prefrontal Transcranial Direct Current Stimulation globally improves learning, but does not selectively potentiate the benefits of Targeted Memory Reactivation on awake memory consolidation 86%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.