An official website of the United States government
Research experiences are important to undergraduate academic life, and many students conducted research during the COVID-19 pandemic, amid disruptions. Undergraduate researchers receive mentorship from faculty mentors and, sometimes, postgraduate mentors. Little is known about the role of multiple mentors’ competency in the science personal-identity and science social-identity of undergraduate students. Using primary data collected in 2020 (n = 841), the authors examine both faculty and postgraduate mentor competency and the impact of COVID-19 on undergraduate researchers. Having both types of mentors is beneficial for students’ science identities unless both the faculty and postgraduate mentor exhibit low competency. COVID-19 had no discernable impacts on either science identity. Findings suggest that faculty and program directors should consider mentor training to increase competency and to involve postgraduate mentors in undergraduate research experiences.
more »
« less
This content will become publicly available on June 1, 2026
The Impact of Postgraduate Mentors on Undergraduate Researcher Gains
We found that specific attributes and behaviors of postgraduate mentors are integral to students' undergraduate research experiences. This suggests that analysts and practitioners treat postgraduate mentorship as an essential part of the undergraduate research enterprise.
more »
« less
- Award ID(s):
- 2055379
- PAR ID:
- 10608620
- Editor(s):
- Barsoum, Mark J
- Publisher / Repository:
- CBE—Life Sciences Education
- Date Published:
- Journal Name:
- CBE—Life Sciences Education
- Volume:
- 24
- Issue:
- 2
- ISSN:
- 1931-7913
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
ABSTRACT Undergraduate research experiences (UREs) cultivate workforce skills, such as critical thinking, project management, and scientific communication. Many UREs in biophysical research have constraints related to limited resources, often resulting in smaller student cohorts, barriers for students entering a research environment, and fewer mentorship opportunities for graduate students. In response to those limitations, we have created a structured URE model that uses an asynchronous training style paired with direct-tiered mentoring delivered by peers, graduate students, and faculty. The adaptive undergraduate research training and experience (AURTE) framework was piloted as part of the Brown Experiential Learning program, a computational biophysics research lab. The program previously demonstrated substantial increases and improvements in the number of students served and skills developed. Here, we discuss the long-term effectiveness of the framework, impacts on graduate and undergraduate students, and efficacy in teaching research skills and computational-based biophysical methods. The longitudinal impact of our structured URE on student outcomes was analyzed by using student exit surveys, interviews, assessments, and 5 years of feedback from alumni. Results indicate high levels of student retention in research compared with university-wide metrics. Also, student feedback emphasizes how tiered mentoring enhanced research skill retention, while allowing graduate mentors to develop mentorship and workforce skills to expedite research. Responses from alumni affirm that workforce-ready skills (communicating science, data management, and scientific writing) acquired in the program persisted and were used in postgraduate careers. The framework reinforces the importance of establishing, iterating, and evaluating a structured URE framework to foster student success in biophysical research, while promoting mentorship skill training for graduate students. Future work will explore the adaptability of the framework in wet lab environments and probe the potential of AURTE in broader educational contexts.more » « less
-
Purpose This study aims to present theory, practice and original research findings to support the proposition that broad enquiry and problem-based learning (EPBL) approaches provide an appropriate pedagogical lens for sustainability educators to develop the knowledge and skills needed to work effectively within mission-oriented innovation policy (MIP) environments. Design/methodology/approach The research study comprised four elements, each of which used different research methods. The first element involved a literature review mapping the synergies between MIP and EPBL; the second element piloted the use of EPBL for undergraduate modules related to sustainability challenges; the third element involved external stakeholders in the co-creation of a postgraduate programme that brought together innovation and sustainability, with EPBL fundamental to the design and development; the fourth element curated and comparatively analysed international cases of EPBL in the context of MIP, and sustainability challenges in particular, highlighting the versatility of EPBL and the importance of creativity in EPBL design and implementation. Findings The systematic literature review reveals synergies between the key features of EPBL and defining characteristics of MIP, indicating the relevance of applying EPBL to support MIP. Two in situ pilots generated 13 recommendations on the benefits and operational challenges of applying EPBL. These recommendations informed the design and development of a postgraduate programme, involving a transdisciplinary consultation process with key industrial and societal stakeholders. Comparative analysis of four international case studies describing EPBL applied in practice in different international settings show there is no “one size fits all”. Instead, the application of EPBL to different sustainability challenges and for different learner groups demonstrates the versatility of the pedagogical approach and the creativity of the sustainability educators. Originality/value A discourse around the appropriate pedagogical methods and teaching/learning practice to equip the current and future workforce with the knowledge and skills to respond to MIP and global sustainability challenges is nascent but emerging. This paper makes a scientific and practical contribution to the discourse. The authors show how EPBL can underpin the design of programmes to provide learners with the knowledge and skills to support organisations working effectively within an MIP context, especially addressing sustainability challenges. The authors provide recommendations for educators seeking to embed EPBL within their curriculum and call for external stakeholders to proactively engage with educators to co-create programmes with context-specific outcomes.more » « less
-
High Performance Computing (HPC) is the ability to process data and perform complex calculations at extremely high speeds. Current HPC platforms can achieve calculations on the order of quadrillions of calculations per second with quintillions on the horizon. The past three decades witnessed a vast increase in the use of HPC across different scientific, engineering and business communities, for example, sequencing the genome, predicting climate changes, designing modern aerodynamics, or establishing customer preferences. Although HPC has been well incorporated into science curricula such as bioinformatics, the same cannot be said for most computing programs. This working group will explore how HPC can make inroads into computer science education, from the undergraduate to postgraduate levels. The group will address research questions designed to investigate topics such as identifying and handling barriers that inhibit the adoption of HPC in educational environments, how to incorporate HPC into various curricula, and how HPC can be leveraged to enhance applied critical thinking and problem-solving skills. Four deliverables include: (1) a catalog of core HPC educational concepts, (2) HPC curricula for contemporary computing needs, such as in artificial intelligence, cyberanalytics, data science and engineering, or internet of things, (3) possible infrastructures for implementing HPC coursework, and (4) HPC-related feedback to the CC2020 project.more » « less
-
Abstract The modeling of rates of biochemical reactions—fluxes—in metabolic networks is widely used for both basic biological research and biotechnological applications. A number of different modeling methods have been developed to estimate and predict fluxes, including kinetic and constraint‐based (Metabolic Flux Analysis and flux balance analysis) approaches. Although different resources exist for teaching these methods individually, to‐date no resources have been developed to teach these approaches in an integrative way that equips learners with an understanding of each modeling paradigm, how they relate to one another, and the information that can be gleaned from each. We have developed a series of modeling simulations in Python to teach kinetic modeling, metabolic control analysis, 13C‐metabolic flux analysis, and flux balance analysis. These simulations are presented in a series of interactive notebooks with guided lesson plans and associated lecture notes. Learners assimilate key principles using models of simple metabolic networks by running simulations, generating and using data, and making and validating predictions about the effects of modifying model parameters. We used these simulations as the hands‐on computer laboratory component of a four‐day metabolic modeling workshop and participant survey results showed improvements in learners' self‐assessed competence and confidence in understanding and applying metabolic modeling techniques after having attended the workshop. The resources provided can be incorporated in their entirety or individually into courses and workshops on bioengineering and metabolic modeling at the undergraduate, graduate, or postgraduate level.more » « less
