Interdisciplinarity is used to integrate and synthesize new research directions between scientific domains, but it is not the only means by which to generate novelty by bringing diverse perspectives together. Internationality draws upon cultural and linguistic diversity that can potentially impact interdisciplinarity as well. We created an interdisciplinary class originally intended to bridge computational and plant science that eventually became international in scope, including students from the United States and Mexico. We administered a survey over 4 years designed to evaluate student expertise. The first year of the survey included only US students and demonstrated that biology and computational student groups have distinct expertise but can learn the skills of the other group over the course of a semester. Modeling of survey responses shows that biological and computational science expertise is equally distributed between US and Mexico student groups, but that nonetheless, these groups can be predicted based on survey responses due to subspecialization within each domain. Unlike interdisciplinarity, differences arising from internationality are mostly static and do not change with educational intervention and include unique skills such as working across languages. We end by discussing a distinct form of interdisciplinarity that arises through internationality and the implications of globalizing research and education efforts.
more » « less- PAR ID:
- 10552434
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Plant Direct
- Volume:
- 8
- Issue:
- 10
- ISSN:
- 2475-4455
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
Universities serve as a hub for the advancement of water science and engineering knowledge and innovations. Communities outside of academia hold equally valid expertise on water and environmental topics. However, there is a lack of avenues for knowledge exchange between academia and non-academic communities including homeowners, industry professionals, policy makers, and K-12 students and teachers. Many universities and research centers attempt to enhance knowledge sharing by organizing broader impact outreach events such as lab tours, demonstrations, hands-on activities, and public presentations. This work studies water-focused students who we define to be students from all disciplines (engineering, biology, sociology, geography, planning, etc.) that study water resources, quality, treatment, and management. Anecdotally, we have seen that of a pool of approximately 100 water-focused students, only the same small subset participates in every event while over 70% of those invited never volunteer. Therefore, there is a need to assess why we see this occurrence. This study aims to survey undergraduate and graduate student water scholars’ motivations and barriers for participating in volunteer broader impact outreach events outside of their degree requirements. This study collected quantitative and qualitative data. Quantitative data were collected through Likert-scale type responses to motivating and hindering factors. Qualitative data were collected through written responses to questions on specific positive or negative student experiences and attitudes. Four main outreach trends emerged: 1) Students enjoy attending outreach events and find it helpful to themselves and to society; 2) Attending events leads students to want to participate in more; 3) Lack of time is by far the top hinderance; 4) Students are motivated by mentor support. Study findings suggest three possible steps to implementing a targeted strategy for broader impact student outreach that aligns with student desires at university research centers: 1) Choice of outreach events should emphasize the contribution to society; 2) Outreach recruitment should emphasize skills students will gain; 3) Faculty mentors should genuinely support their students’ outreach endeavors including finding relevant outreach opportunities.more » « less
-
Despite the interest in equity, little research has considered students with disabilities in PreK-12 computer science education. The 2022 Computer Science Teachers Association and Kapor Center facilitated Landscape Survey of PreK-12 CS Teachers, which had over 2200 responses, gives us new insight. There were few significant differences between the experiences and perceptions of teachers with disabilities and those without. Accessibility was the least taught computing concept. Furthermore, teachers reported on a variety of barriers that students with disabilities encounter related to structural barriers, students choosing note to take CS, and teachers' perceptions of student ability. The findings point to the need for interventions related to resources, outreach, and policy.more » « less
-
Course-based undergraduate research experiences (CUREs) are an effective way to integrate research into an undergraduate science curriculum and extend research experiences to a large, diverse group of early-career students. We developed a biology CURE at the University of Miami (UM) called the UM Authentic Research Laboratories (UMARL), in which groups of first-year students investigated novel questions and conducted projects of their own design related to the research themes of the faculty instructors. Herein, we describe the implementation and student outcomes of this long-running CURE. Using a national survey of student learning through research experiences in courses, we found that UMARL led to high student self-reported learning gains in research skills such as data analysis and science communication, as well as personal development skills such as self-confidence and self-efficacy. Our analysis of academic outcomes revealed that the odds of students who took UMARL engaging in individual research, graduating with a degree in science, technology, engineering, or mathematics (STEM) within 4 years, and graduating with honors were 1.5–1.7 times greater than the odds for a matched group of students from UM’s traditional biology labs. The authenticity of UMARL may have fostered students’ confidence that they can do real research, reinforcing their persistence in STEM.more » « less
-
This Research paper discusses the opportunities that utilizing a computer program can present in analyzing large amounts of qualitative data collected through a survey tool. When working with longitudinal qualitative data, there are many challenges that researchers face. The coding scheme may evolve over time requiring re-coding of early data. There may be long periods of time between data analysis. Typically, multiple researchers will participate in the coding, but this may introduce bias or inconsistencies. Ideally the same researchers would be analyzing the data, but often there is some turnover in the team, particularly when students assist with the coding. Computer programs can enable automated or semi-automated coding helping to reduce errors and inconsistencies in the coded data. In this study, a modeling survey was developed to assess student awareness of model types and administered in four first-year engineering courses across the three universities over the span of three years. The data collected from this survey consists of over 4,000 students’ open-ended responses to three questions about types of models in science, technology, engineering, and mathematics (STEM) fields. A coding scheme was developed to identify and categorize model types in student responses. Over two years, two undergraduate researchers analyzed a total of 1,829 students’ survey responses after ensuring intercoder reliability was greater than 80% for each model category. However, with much data remaining to be coded, the research team developed a MATLAB program to automatically implement the coding scheme and identify the types of models students discussed in their responses. MATLAB coded results were compared to human-coded results (n = 1,829) to assess reliability; results matched between 81%-99% for the different model categories. Furthermore, the reliability of the MATLAB coded results are within the range of the interrater reliability measured between the 2 undergraduate researchers (86-100% for the five model categories). With good reliability of the program, all 4,358 survey responses were coded; results showing the number and types of models identified by students are presented in the paper.more » « less
-
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.