Search bioRxiv⌕ Search

bioRxiv · 10.1101/2021.11.29.469764

The Importance of Mentors and How to Handle More Than One Mentor

Abstract

IntroductionWorking with multiple mentors is a critical way for students to expand their network, gain opportunities, and better prepare for future scholastic or professional ventures. However, students from underrepresented groups (UR) are less likely to be mentored or have access to mentors, particularly in science, technology, engineering, and mathematics (STEM) fields. We developed and implemented a workshop, to provide the necessary foundation for students to be better prepared for establishing future mentorships throughout graduate and professional school. MethodsFaculty well-versed in the area of effective mentorship from multiple universities developed and delivered a 1.5-hour workshop to address the roles of a mentor, especially when it comes to UR students, and how students may effectively work with multiple mentors. This workshop was delivered to a group of students from the HBCU Winston Salem State University, and a pre/post-Likert scale-based survey was administered. ResultsWe analyzed the raw data with nonparametric tests for comparison within paired samples. Wilcoxon matched-pairs and signed-rank tests showed statistically significant growth in student self-ratings related to the workshop learning objectives. ConclusionsThe "How to Handle More than One Mentor to Achieve Excellence" workshop was well received as a component of pre-graduate and pre-professional training. Incorporating workshops like this may increase student preparedness around developing and cultivating healthy mentorship relationships throughout STEM training. EDUCATIONAL OBJECTIVESBy the end of this workshop, learners will be able to: O_LIDescribe the role of mentors in developing the next generation of trainees. C_LIO_LIDescribe current research on mentorship among underrepresented populations. C_LIO_LIApply skills on effective communication needed in the development of successful mentorship relationships. C_LIO_LIWork with multiple mentors at one time while maintaining solid professional and personal relationships. C_LI

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Marshall, A. G., Brady, L., Palavicino-Maggio, C., Neikirk, K., Vue, Z., Beasley, H., Garza Lopez, E., Murray, S., Martinez, D., Shuler, H., Spencer, E., Morton, D., Hinton, A.. 2021-12-01. The Importance of Mentors and How to Handle More Than One Mentor. https://doi.org/10.1101/2021.11.29.469764

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Evaluating Large Language Models as Tools to Navigate Researchers in Rapidly Evolving Research Landscapes: A Case Study in Cancer Drug Response Prediction

Large Language Models (LLMs) have emerged as promising tools for assisting researchers in automating and accelerating the synthesis of literature reviews. However, their reliability is a significant concern due to issues like factual inaccuracies and hallucinations. The key question is whether LLMs can reliably provide comprehensive, up-to-date overviews and analyses. This study evaluates the performance of three leading LLMs (OpenAI's ChatGPT, Google's Gemini, and DeepSeek) on the complex task of generating a comprehensive survey paper on deep learning for cancer Drug Response Prediction (DRP). By testing both standard and Deep Research (DR) / Deep Think (DT) modes of LLMs with prompts of varying detail, this paper assesses key academic dimensions, including reference management, content quality, and analytical depth. Key findings reveal that while DR modes of LLMs significantly improve reliability by eliminating hallucinations, performance variations exist across models and prompts. A trade-off between reference quantity and integration quality was observed, and even the best-performing models lacked the analytical depth of human experts, often requiring extensive human supervision. The study concludes that LLMs currently serve as powerful assistive tools but still cannot replace the critical validation and synthesis provided by human researchers. Choosing the best LLM to use depends on the task in hand, while several strategies can be implemented to improve the produced output.

scientific communication and education↗

Welfare concerns for mounted load carrying by working donkeys in Pakistan

Working donkeys (Equus asinus) are vital to peoples livelihoods. They are essential for carrying goods, however globally, overloading is one of the primary welfare concerns of working donkeys. We studied mounted load carrying by donkeys and associated factors in Pakistan. A cross-sectional study of donkey owners (n = 332) was conducted, and interviews were undertaken based on a questionnaire. Owners estimated that the median weight of their donkeys was 110kg (interquartile range (IQR) 100-120kg), and that they carried a median mounted load of 81.5kg (IQR 63-99kg). We found that 87.4% of donkeys carried a load above 50% of their bodyweight ratio (BWR), the median BWR carried was 77.1% (IQR 54.5-90.7%), and 25.3% of donkeys carried above 90% BWR. Donkeys that were loaded at more than 50% BWR were more likely to sit, compared to donkeys loaded with less weight (p=0.01). Donkeys working in peri-urban and urban areas were more likely to carry a greater BWR than donkeys working in rural areas (P<0.001), as were those carrying construction materials or bricks, compared to agricultural materials (p=0.004). Age (p=0.03) and breed (p=0.01) were also associated with carrying a higher weight. Overloading based on current recommendations (50% BWR) was common, with the majority (87.4%) of donkeys reported to carry more than the recommended 50% limit. This survey provides evidence of on-the-ground working practices and factors associated with mounted load carrying, which is critical for developing evidence-based recommendations for loading, in order to improve the welfare of working donkeys.

scientific communication and education↗