Progress 08/15/23 to 08/14/24
Outputs
Target Audience:During theproject period, the third and final cohort of students completed their second year of study. The third cohort of students include the following target audience that was recruited for participation. Originally, four students were recruited into Cohort 3 for a 2-year fellowship. Additionally, with remaining funds from unused participant support costs (namely travel costs that were not utilized due to the pandemic), the program was also able to support one additional student for one year. Two female students (40%) were selected. One student identified as Black/African American (20%). One student (20%) was a transfer student from a community college. One student (20%) self-identified as a member of the LGBTQ+ community. One student identified as Asian (20%). All four students in the original cohort attended SIUE, although one was a transfer from a community college partner. Each of the four students studied a different major, but all completed studies in different majors relating to the agricultural and environmental sciences. One student majored in Biology. Another majored in Biochemistry. Another majored in Computer Science with a minor in Geography and GIS. The fourth student majored in Mechatronics and Robotics Engineering. The student that participated in ELIAS due to remaining funds was from UIUC and majored in Computer Science, with an interest in weather modeling and crop science. Although the percentage of female students was slightly below the originally proposed target of 50% for this cohort, it should be noted that overall, the ELIAS program served 7 women (53.8%), 6 racial minorities (46.2%), and 4 transfer students (30.8%) out of its 13 total students, all of which fall above the proposed targets. All five students from Cohort 3 have been immensely successful. Three students were juniors/rising seniors at the completion of their ELIAS research. They are currently applying to graduate school programs. One student is applying to graduate school programs in the area of environmental toxicology. The other two students are applying to graduate school programs in the area of data science, with applications to environmental science and geospatial analysis. Of the students that graduated, one is currently pursuing a PhD in the plant and environmental sciences, and she received a fellowship to support her studies. The second student who graduated was hired into a competitive industry rotation program and is working in the field of land management. Additionally, in following up from previous cohorts, one student from Cohort 2 that had taken a gap year between her undergraduate and graduate studies communicated that she had been accepted to her graduate program of choice. This brings both the total retention and placement rates in the ELIAS program to 100%, and this is the figure that we are most proud of. All students in the third cohort completed an independent research project, worked with their mentors to perform statistical analysis and data summarization tasks, and presented their findings at the ELIAS Spring Event as well as the undergraduate research symposia at their respective institutions. Several students also presented at the professional conferences that they attended as part of the fellowship program. The students crafted an impact statement answer to the prompt, "What is the impact of my research, and why does it matter?" for inclusion on the ELIAS website. A summary of the students' projects can be found here: https://www.siue.edu/cpan/research-partnerships/ELIAS_Students.shtml. All students also completed coursework in applied statistics, including a certificate program in either Intro to R or Intro to Python programming. Continuing with an idea that we had identified in a previous reporting period so that we could foster more interactions between the students, we hosted the Fall Orientation and the ELIAS Spring Event. The orientation event served as an onboarding opportunity where students could meet their colleagues, and where they and their research mentors could become acquainted with the program. The Spring Event remained a place where student could celebrate their achievements in a culminating experience. Students presented their research findings to the host site (the Center for Predictive Analytics at SIUE) and to one another in the Center's large meeting space. Additionally, the third cohort worked together closely, as 80% of the students were on the SIUE campus, by chance. Although this was highly abnormal, it did allow for weekly meetings and cohort building among the students that, from the perspective of the PIs, has led to long-term lasting friendships. In addition to the activities with current students in the program, efforts have also been maintained to sustain relationships with the former ELIAS Fellows. In addition to relationships with former mentors, which continue to be of utmost importance in maintaining a long-term relationship with these students, we continue to disseminate follow-up surveys to former cohorts to evaluate whether their opinion of the ELIAS Fellowship Program and their preparation for their respective future endeavors has changed since exiting the program. Additionally, as time goes on, we are noticing that students tend to become more silent. Although this is a sad happening for us as mentors, we understand this is also the natural progression of training. To maintain an understanding of each student's current placement and career trajectory, we have been scraping LinkedIn information to see if the former participant has posted any recent updates. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?The primary focus of this award is to provide experiential learning opportunities in applied statistics and crop science or a closely related field (e.g., environmental science). All students successfully completed immersive research experiences under the guidance of their primary mentor in their chosen area of interest. Students' research projects spanned areas such as toxicology and environmental contamination in water sources, automation of GIS analytical platforms for creating field maps, designing robotic systems for high-throughput phenotyping, and studying how satellite imagery can be used to study changes in phenology and human behavior over time. Through these experiences, students have gained skills in environmental toxicology, GIS, analytical chemistry, remote sensing, and agricultural robotics. In addition to these laboratory, field, and greenhouse-based research skills, students used methods in applied statistics and data science (programming, experimental design, database organization, automation and machine learning, and data analysis) to analyze their data in a real-world setting. While coursework is important in introducing statistical and data science concepts, the PIs repeatedly hear from industry advisory members that working with real-world, "messy" data was essential to truly mastering data analysis. As such, one of the components of the program is to have students generate their own datasets, organize and assemble that "messy" data into a standard data frame style master dataset, and then analyze that data. Another skill that we heard from our advisory members that was important was that students must be able to draw upon multiple skills simultaneously to analyze data, interpret output, and then report their findings. As such, all statistical mentors employed a mentoring approach in which all students are introduced to multiple data analysis techniques simultaneously, the advantages and limitations of each approach is discussed, and then possible workflows drawing upon multiple skillsets are presented. How have the results been disseminated to communities of interest?During the reporting period, multiple student presentations were provided in addition to a presentation that was given by the PIs at the ASA-CSSA-SSSA International Annual Meeting in 2023. Student presentations took place at either conferences such as the ASA-CSSA-SSSA International Annual Meeting, or smaller settings such as the ELIAS Spring Event and the SIUE Undergraduate Scholars Showcase. The overall presentation that was given at the ASA-CSSA-SSSA International Annual Meeting in Fall 2023 discussed the ELIAS program in detail and showcased the strategies employed in terms of dual training and mentorship. Additionally, all student projects are on the ELIAS webpage, as are all ELIAS resources. https://www.siue.edu/cpan/research-partnerships/ELIAS.shtml. Finally, as the project closes, we are in the final stages of analyzing participant data and outcomes collected during the exit survey. Once this data is collected and compiled with data that has been collected throughout the project, our intent is to publish the results of this project, thereby providing public access to the strategies and methods utilized in this REEU project. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
1. Conduct an experimental research project involving both traditional crop science and statistical components. During the reporting period, a total of 5 students were successfully retained in the program and trained in hands-on research in crop and environmental sciences, as well as aspects of applied statistics and data science. All students in Cohort 3 completed their independent research project, performed data analyses, and presented the results. Students' topics included toxicology and environmental contamination, automation of GIS analytical platforms, designing robotic systems for high-throughput phenotyping, and studying how satellite imagery can be used to study changes in phenology and human behavior over time. All students completed statistical coursework, including introductory statistics (all had already completed this course), experimental design, and statistical programming, and they worked with their statistical mentors to analyze, summarize, and present their own research data independently. 2. Foster mentorships with research faculty that lead to the successful placement of students in their desired graduate career tracks. The 100% retention and now also 100% placement rate of students in the program is a testament to the mentorship and experiential learning components of the ELIAS Fellowship Program. Of special note for this reporting period, one student from Cohort 2 had originally elected to take some time off between her undergraduate and graduate studies. Because of the relationships she developed with her ELIAS mentors, when she started applying to graduate school, she reached back out to her mentors to provide letters of recommendation. Through these letters, we could speak to her academic merit and research aptitude, which greatly helped her application. For all students, we also continued to work with students who had be impacted by the COVID-19 pandemic. Although not nearly as pronounced as in Cohort 2, the students in Cohort 3 were initially somewhat more reserved and timid than students who had entered the program prior to the pandemic. To address this, we continued to work to establish a sense of rapport among the students and their peers. Through these strategies, it was our ultimate goal that by the time the students completed the ELIAS Fellowship Program, they would be comfortable working in a scientific environment, would be confident, and would be able to interact easily with their peers. We continued to meet weekly with students and to provide them additional opportunities to interact with one another, and to ask questions in a very supporting and curiosity-driven research environment. We also worked to give each of these students a great sense of autonomy over their projects, and allowed them the space to make (minor) mistakes and realize that this was a natural part of science. We also continued to establish a sense of rapport among the students and their peers. While this was not always possible for students working at different universities, all research mentors agreed to adopt practices within their research setting that would allow students within their respective groups to interact with each other collegially. This included matching student schedules so that groups of students would be able to work together at the same time, mentors making a point to informally drop into laboratory groups and establish a positive, supportive, and friendly atmosphere when they visited, mentors organizing research group social events, etc. By chance, three of the students were also working together in neighboring laboratories, and so we mentors facilitated informal gatherings in the conference area adjoining the laboratory spaces. Through ongoing conversations with students, regular interactions with students, and creating an environment where students feel/felt safe to ask questions about any aspect of their career and educational progression, not just their research, the ELIAS program promotes not just the development of undergraduate research students, but also mentor-mentee relationships that students feel they can rely upon for student support and guidance. These relationships were incredibly important for the placement of students upon graduation, because not only did they earn valuable research skills, but they also had a place where they felt comfortable turning to for advice in navigating the next steps of their educational or working careers. Additionally, the evolution of students in terms of their soft-skills must be mentioned, as it has allowed them to easily integrate into their future research teams seamlessly. Of additional note, all former participants of this program are currently pursuing a PhD, are still employed by the same employer, or are still employed by the same employer and have received a promotion. This speaks to the educational preparation these students received, as well as to the quality of the students that this program attracts. 3. Develop students' technical understanding of applied statistics and their ability to communicate results effectively to diverse audiences. All students in Cohort 3 completed training in Introductory Statistics prior to this project period. During this project period, they completed training and coursework in experimental design and statistical programming (e.g., R or Python). All students completed tasks in data organization, cleaning, analysis, and visualization. All students in the 2-year experience presented at their home institution's undergraduate research symposium. All students presented at the ELIAS Spring Event. All students have helped craft impact statements and descriptions of their research for inclusion on the ELIAS website. One student presented at a professional conference and won second place in her poster division. One student used her ELIAS independent study as her senior capstone project, and a junior (now senior) student used her experiences within the ELIAS program to successfully write a seed grant application that she is carrying out this year.
Publications
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2024
Citation:
Lipps S, et al. The Maize Kernel and Its Unexploited Potential Mechanisms of Resistance to Fusarium Graminearum. ASA-CSSA-SSSA International Annual Meeting. San Antonio, TX. Nov. 2024.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2023
Citation:
Butts-Wilmsmeyer C, et al. Navigating the Data Sea: The Educational Needs of the Agricultural Workforce across Varying Age and Other Educational Demographics. ASA-CSSA-SSSA International Annual Meeting. St. Louis, MO. Oct. 2023.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2023
Citation:
Hasty CA, et al. The Microscopic Shield: Can Phenylpropanoid Concentrations Provide Natural Resistance to Ear Rots and Mycotoxin Contamination, and Can We Predict Enhanced Resistance Using Genomic Techniques? ASA-CSSA-SSSA International Annual Meeting. St. Louis, MO. Oct. 2023.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2024
Citation:
Benware M-M, et al. Using Satellite Imagery to Detect Changes in Phenology Over Time: Can Changes in Vegetative Indices Predict Periods of Civil Unrest? SIUE Undergraduate Scholars Showcase. April 2024.
|
Progress 08/15/20 to 08/14/24
Outputs
Target Audience:During this project, a total of 13 students were trained as part of the ELIAS program. Our target number of students to train across the duration of the project was 12 students. In a fortuitous circumstance, we were able to leverage funds creatively and allow one additional student to participate in the research elements of the ELIAS program, bringing our total number of students trained to 13 across the lifetime of the project. Excitingly, we met or surpassed all target metrics. Of the students trained, 7 students (53.8%) were female. A total of 6 students, or 46.2%, identified as a racial minority, with 2 students (15.4%) identifying as Black/African American, 1 student identifying as Hispanic/LatinX (7.7%), and 3 students (23.1%) identifying as Asian. A total of 4 students (30.8%) were transfer college students. One student (7.7%) self-identified as a member of the LGBTQ+ community. Additionally, 7 students (53.8%) were from outside the home institution. The students came from a diversity of majors, but all with an interest in crop and environmental sciences and how data science can be applied within those disciplines. Briefly, 4 students majored in Crop Sciences; 1 student majored in Environmental Science; 1 student majored in Computer Science + Crop Science; 2 students majored in Computer Science with a demonstrated interest in GIS, weather modeling, and crop science; 3 students majored in Biology with an interest in plant genetics; 1 student majored in Biochemistry with an interest in environmental toxicology; and 1 student majored in Mechatronics and Robotics Engineering with an interest in agricultural robotics. All students from each of the cohorts have been immensely successful. Three students were juniors/rising seniors at the completion of the ELIAS program in 2024. They are currently applying to graduate school programs. One student is applying to graduate school programs in the area of environmental toxicology. The other two students are applying to graduate school programs in the area of data science, with applications to environmental science and geospatial analysis. Of the students that graduated over the course of the program, 4 are currently pursuing PhD programs. These PhD programs are in the areas of Natural Resources and Environmental Management, Genetic Engineering (2 students), and Plant Phenology and Environmental Geospatial Analysis. Two of the students who are completing their PhDs received competitive research fellowships to support their studies, and all students received either a fellowship or an assistantship. Of the three students who are currently pursuing MS degrees, one is working in the area of environmental impacts on human health. The second is working in the area of plant pathology, and she received a competitive assistantship to pursue her MS degree. The third student elected to pursue an MA in Education, with the hope of being able to take her research experiences back to the classroom to make science more tangible for high school students. All students who entered industry are still currently employed in their respective fields, and some have even seen promotions since being hired. This brings the total retention and placement rates in the ELIAS program to 100%, and this is the figure that we are most proud of. All students completed an independent research project, worked with their mentors to perform statistical analysis and data summarization tasks, and presented their findings at the ELIAS Spring Event as well as the undergraduate research symposia at their respective institutions. Several students also presented at the professional conferences that they attended as part of the fellowship program. The students in Cohorts 2 and 3 crafted an impact statement answer to the prompt, "What is the impact of my research, and why does it matter?" for inclusion on the ELIAS website. A summary of the students' projects can be found here: https://www.siue.edu/cpan/research-partnerships/ELIAS_Students.shtml. All students also completed coursework in applied statistics, including a certificate program in either Intro to R or Intro to Python programming. During the second half of the project, we identified a strategy that could be used to foster more interactions between the students. This strategy was to host the Fall Orientation and the ELIAS Spring Event as separate events, thereby providing students multiple points of contact with the larger group of their colleagues. The orientation event served as an onboarding opportunity where students could meet their colleagues, and where they and their research mentors could become acquainted with the program. The Spring Event remained a place where students could celebrate their achievements in a culminating experience. Students presented their research findings to the host site (this rotated between the partnering institutions) and to one another. In addition to the activities that were focused on supporting current students in the program, a significant effort was made to sustain relationships with the former ELIAS Fellows. In addition to relationships with former mentors, which continue to be of utmost importance in maintaining a long-term relationship with these students, we continue to disseminate follow-up surveys to former cohorts to evaluate whether their opinion of the ELIAS Fellowship Program and their preparation for their respective future endeavors has changed since exiting the program. Additionally, as time goes on, we are noticing that students tend to become more silent. Although this is a sad happening for us as mentors, we understand this is also the natural progression of training. To maintain an understanding of each student's current placement and career trajectory, we have been scraping LinkedIn information to see if former participants have posted any recent updates. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?The primary focus of this award was to provide experiential learning opportunities in applied statistics and crop science or a closely related field (e.g., environmental science). All students successfully completed immersive research experiences under the guidance of their primary mentor in their chosen area of interest. Students' research projects spanned areas such as genetic engineering, agricultural robotics, remote sensing and GIS, plant breeding, environmental toxicology, and regenerative agriculture. Through these experiences, students have gained skills that have made them highly marketable within the workforce. In addition to these laboratory, field, and greenhouse-based research skills, students used methods in applied statistics and data science (programming, experimental design, database organization, automation and machine learning, and data analysis) to analyze their data in a real-world setting. While coursework is important in introducing statistical and data science concepts, the PIs repeatedly heard from industry advisory members that working with real-world, "messy" data was essential to truly mastering data analysis. As such, one of the components of the program was to have students generate their own datasets, organize and assemble that "messy" data into a standard data frame style master dataset, and then analyze that data. Another skill that we heard from our advisory members that was important was that students must be able to draw upon multiple skills simultaneously to analyze data, interpret output, and then report their findings. As such, all statistical mentors employed a mentoring approach in which all students are introduced to multiple data analysis techniques simultaneously, the advantages and limitations of each approach were discussed, and then possible workflows that draw upon multiple skillsets simultaneously were presented. How have the results been disseminated to communities of interest?Across the lifetime of the project, multiple student presentations were provided in addition to two presentations that were given by the PIs at the ASA-CSSA-SSSA International Annual Meeting. Student presentations took place at either conference such as the ASA-CSSA-SSSA International Annual Meeting, or smaller settings such as the ELIAS Spring Event and the undergraduate research symposia at students' respective home institutions. The presentation that was given at the ASA-CSSA-SSSA International Annual Meeting in Fall 2023 discussed the ELIAS program in detailed and showcased the strategies employed in terms of dual training and mentorship, as well as the student-communicated positive impacts the project was having on their educations. Additionally, all student projects are on the ELIAS webpage, as are all ELIAS resources. https://www.siue.edu/cpan/research-partnerships/ELIAS.shtml. Finally, now that the final participant outcome data has been collected and analyzed from the final exit survey, we are preparing a publication that will be disseminated in 2025. Our intent in publishing these results, as well as the instruments and strategies used throughout the project, is to provide public access to the strategies and methods utilized in this REEU project. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
1. Conduct an experimental research project involving both traditional crop science and statistical components. Across the duration of the project, a total of 13 students were successfully retained in the program and trained in hands-on research in crop and environmental sciences, as well as aspects of applied statistics and data science. All students completed their independent research project, performed data analyses, and presented the results. Student topics spanned genetic engineering, robotics, remote sensing and GIS, plant breeding, environmental toxicology, and regenerative agriculture. All students completed statistical coursework, including introductory statistics, experimental design, and statistical programming, and they worked with their statistical mentors to analyze, summarize, and present their own research data independently. 2. Foster mentorships with research faculty that lead to the successful placement of students in their desired graduate career tracks. The 100% retention and 100% placement rates of students in the program are a testament to the mentorship and experiential learning components of the ELIAS Fellowship Program. We were successful in establishing rapport among the students, a task that was of the utmost importance but that was also highly challenging during and directly after the COVID-19 pandemic. Through these strategies, it is our ultimate goal that by the time students completed the ELIAS Fellowship Program, they would be able to interact easily with their peers. We met weekly with students and provided them additional opportunities to interact with one another, and to ask questions in a very supportive and curiosity-driven research environment. We strove to give each student a sense of autonomy over their projects, and allowed them the space to make (minor) mistakes and realize that this was a natural part of science. We also worked to establish a sense of rapport among the students and their peers. While this was not always possible for students working at different universities, all research mentors agreed to adopt practices within their research setting that would allow students within their respective groups to interact with each other collegially. This included matching student schedules so that groups of students would be able to work together at the same time, and mentors made a point to informally drop into laboratory groups and establish a positive, supportive, and friendly atmosphere when they visited. Mentors also organized research group social events, and other team building activities. Through ongoing conversations with students, regular interactions with students, and by creating an environment where students felt safe to ask questions about any aspect of their career or educational progression, not just their research, the ELIAS program promoted not just the development of undergraduate research students, but also mentor-mentee relationships that students felt they could rely upon for support and guidance. These relationships were incredibly important for the placement of students upon graduation, because not only did students earn valuable research skills, but they also had a place where they felt comfortable turning to for advice in navigating the next steps of their educational or working careers. Additionally, the evolution of students as they gained soft-skills through these guided experiences must be mentioned, as it allowed them to easily integrate into their future research teams seamlessly. Of additional note, all former participants of this program are currently pursuing a Master's or PhD, are still employed by the same employer, or are still employed by the same employer and have received a promotion. This speaks to the educational preparation these students received, as well as to the quality of the students that this program attracts. 3. Develop students' technical understanding of applied statistics and their ability to communicate results effectively to diverse audiences. All students completed training in introductory statistics, experimental design, and statistical programming (e.g., R or Python) coursework. All students completed tasks in data organization, cleaning, analysis, and visualization. All students presented at their home institution's undergraduate research symposium. All students presented at the ELIAS Spring Event. All students in Cohorts 2 and 3 helped craft impact statements and descriptions of their research for inclusion on the ELIAS website. Cohort 1 performed a similar task, but less focus on real-world impact. Students also presented at professional conferences, and one student even won second place in her poster division. Multiple students also used their ELIAS independent study projects as their senior capstone projects, and one student used her experiences within the ELIAS program to successfully write a seed grant application that she is carrying out at the time of this report.
Publications
- Type:
Peer Reviewed Journal Articles
Status:
Other
Year Published:
2025
Citation:
Butts-Wilmsmeyer CJ, MO Bohn, AE Lipka, NJ Heller, and MB Villamil. (Tentative Title) The Long Game: Training the Next Generation of Data-Savvy Agricultural and Environmental Scientists through Long-Term Mentorship and Real-World Experiences. (Proposed Journal) The Journal of Environmental Education. Please note that the DOI provided above is a placeholder and that all pertinent information will be placed into the NAL PubAg repository and that aggregated data will be placed into the NAL's Ag Data Commons upon publication.
|
Progress 08/15/22 to 08/14/23
Outputs
Target Audience:During the reporting period, the second cohort of students completed their second year of study, and the third cohort of students completed their first year of study. The second cohort of students include the following target audience that was recruited for participation. Three female students (75%) were selected. One student (25%) identified as Black/African American, and one student (75%) identified as Asian. One student (25%) was a transfer student from a community college. In addition to the student recruited from Lincoln Land Community College, who ultimately transferred to Southern Illinois University Edwardsville (SIUE), one additional student attended SIUE, and two students attended the University of Illinois at Urbana-Champaign (UIUC). The two students from SIUE pursued degrees in Biological Sciences. One of these students graduated with a competitive PhD fellowship offer in May 2023. The other is slated to graduate in December 2023 and is in the process of negotiating her graduate assistantship offer. Both of the students from UIUC majored in Crop Sciences, with one also earning a minor in Computer Science. Both graduated in May 2023, and one accepted a competitive graduate fellowship offer to pursue her Master's degree. All students in the second cohort completed an independent research project, worked with their mentors to perform statistical analysis and data summarization tasks, and presented their findings at the ELIAS Spring Event as well as the undergraduate research symposia at their respective institutions. Several students also presented at the professional conferences that they attended as part of the fellowship program.The students also crafted an impact statement answering the prompt, "What is the impact of my research, and why does it matter?" for inclusion on the ELIAS website. A summary of the students' projects can be found here: https://www.siue.edu/cpan/research-partnerships/ELIAS_Students.shtml. All students also completed coursework in applied statistics, including a certificate program in either Intro to R or Intro to Python programming. The third cohort of students include the following target audience that was recruited for participation. Two female students (50%) were selected. One student identified as Black/African American (25%). One student (25%) was a transfer student from a community college. One student (25%) self-identified as a member of the LGBTQ+ community. All four students are now attending SIUE, but all in different majors related to the agricultural and environmental sciences. One student is majoring in Biology. Another is majoring in Biochemistry. One is majoring in Computer Science, with a minor in Geography and GIS. The other is majoring in Mechatronics and Robotics Engineering. During their first year of the ELIAS program, this cohort of students completed introductory program elements, such as safety training, orientation and onboarding, introductory quizzes in fundamental scientific principles and statistical methods, and a personality assessment. All introductory program elements are designed to ensure that students admitted to the program have every opportunity to be successful. Students also completed an introductory course in statistics. Something that we did different this year to promote a sense of community among the students was to break up the orientation event, which we hosted in the fall, and the ELIAS Spring Event. The orientation event served as an onboarding opportunity where students could meet their colleagues, and where they and their research mentors could become acquainted with the program. By breaking what had once been a singular event into two separate events, this gave students more opportunities to interact with one another. It also changed the atmosphere of the ELIAS Spring Event into more of a celebratory and culminating experience. Students presented their research findings to the host site (the Department of Crop Sciences at UIUC) and to one another in the atrium during the hosting department's coffee hour. This was a fun experience for the students, and they mentioned that they appreciated the experience. The College of ACES at UIUC also allowed the students to attend the midpoint seminars given by faculty across the college so that students could learn about the research taking place at the host site and opportunities for potential graduate school programs (primarily for the third cohort, in the latter case). The students also toured the Roy J. Carver Biotechnology Center at UIUC and John Deere's Technology Innovation Center in the University Research Park. These experiences were important for students because they are able to interact with a diverse array of scientists in the digital crop sciences, to see the application of state-of-the-art technology to address research questions in this discipline, and to begin to form their professional networks. By the end of the reporting period, Cohort 2 had completed all programmatic elements, as previously described, and Cohort 3 was well on track to complete programmatic elements as proposed. For the third cohort, all students completed their guided research experience and identified their independent research project. At the time of writing this, all students are now working on their independent research projects in coordination with their research mentors. All students are expected to complete their data collection by the end of January 2024. All students are meeting with their statistical mentors routinely during the Fall 2023 semester, and this will continue into Spring 2024 as they begin the analysis of their data. All students from Cohort 3 have also met with their academic advisors and are on track to complete coursework/technical training required as part of the ELIAS fellowship program. All students have either completed their experimental design coursework, in addition to their introductory statistical coursework, or are registered to complete this coursework in the spring. All students are either in the process of completing one of Intro to R or Intro to Python, or they are registered to begin the certificate program in January. In addition to the activities with current students in the program, efforts have also been instituted to maintain relationships with the former members (Cohorts 1 and 2) of the ELIAS fellowship program. In addition to relationships with former mentors, which we have found to be of utmost importance in maintaining a long-term relationship with these students, we continue to disseminate follow-up surveys to former cohorts to evaluate whether their opinion of the ELIAS fellowship program and their preparation for their respective future endeavors has changed since exiting the program. This information, in combination with the exit surveys that all fellows must complete at the end of the program, has been crucial in determining what we can do to modify the program and how we can best serve our students. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?The primary focus of this award is to provide experiential learning opportunities in applied statistics and crop science or a closely related area (e.g., environmental science). All students successfully completed immersive research experiences under the guidance of their primary mentor in their chosen area of interest. Students' research projects spanned areas such as using genomic modeling techniques to create environmentally resilient maize varieties; using a genome-wide association study (GWAS) to identify markers associated with yield traits; designing robots that can be deployed in agricultural fields; monitoring how statins persist in the environment and act as soil contaminants that impact soil micro- and macrofauna; and creating interactive GIS tools for showcasing field and epidemiological information. Through these experiences, students have gained skills in molecular genetics, plant breeding, genomics, biochemistry, analytical chemistry, soil physics and biogeochemistry, pathology, remote sensing, agricultural robotics, and GIS. In addition to these laboratory, field, and greenhouse-based research skills, students used methods in applied statistics (programming, experimental design, and data analysis) to analyze their data in a real-world setting. While coursework is important in introducing statistical concepts, the PIs repeatedly hear from industry advisory members that working with real-world, "messy" data was essential to truly mastering data analysis. As such, one of the components of the program is to have students generate their own datasets, organize and assemble that "messy" data into a standard data frame style master dataset, and then analyze that data. Another skill that we heard from our advisory members that was important was that students be able to draw upon multiple skills simultaneously to analyze data, interpret output, and then report their findings. As such, all statistical mentors employed a mentoring approach in which all students are introduced to multiple data analysis techniques simultaneously, the advantages and limitations of each approach is discussed, and then possible workflows drawing upon multiple skillsets are presented. How have the results been disseminated to communities of interest?During the reporting period, multiple student presentations were provided in addition to a presentation that was given by the PIs at the ASA-CSSA-SSSA International Annual Meeting in 2023. Student presentations took place at either conferences such as theASA-CSSA-SSSA International Annual Meeting or the Maize Genetics Meeting, or at students' home institutions during their respective Undergraduate Research Symposia. The overall presentation that was given at theASA-CSSA-SSSA International Annual Meeting in Fall 2023 discussed the ELIAS program in detail and showcased the strategies employed in terms of dual training and mentorship. Lastly, all student projects are on the ELIAS webpage, as are all ELIAS resources.https://www.siue.edu/cpan/research-partnerships/ELIAS.shtml What do you plan to do during the next reporting period to accomplish the goals?The third and final cohort of students will be finalizing their independent research projects, data collection, statistical coursework, data analyses, and presentation commitments as part of the ELIAS program during the upcoming project period. It is anticipated that each student will present at least three presentaitons/public talks in the upcoming reporting period. It is also foreseeable that many of the students' work may be included as part of peer-reviewed publications either during the reporting period or in the near future. Upon completion of the project, we also anticipate publishing the results of the ELIAS Fellowship program in an educational journal, including survey instruments, mentorship approaches, programmatic outcomes, etc.
Impacts
What was accomplished under these goals?
1. Conduct an experiential research project involving both traditional crop science and statistical components. During the reporting period, a total of 8 students were successfully retained in the program and trained in hands-on research in crop and environmental sciences, as well as aspects of applied statistics and data science. All students in Cohort 2 completed their independent research project, performed data analyses, and presented the results. Students' topics includedtoxicology and environmental contamination, use of high performance liquid chromatography and QTOF mass spectrometry to quantify environmental contaminants, the biochemistry underlying stress response in cereal crops, genomic selection, genome-wide association study (GWAS), yield component traits and indirect selection, soil chemistry and soil physics, and land-use and soil quality under different land management systems. All students completed statistical coursework, including introductory statistics, experimental design, and statistical programming, and they worked with their statistical mentors to analyze their own research data independently. Cohort 3 was trained in guided research experiences so that they could become familiar with various tools and techniques in either a greenhouse, field, or laboratory space and could work with their mentors to design an independent research experience for their second year of the ELIAS program. Students worked in topic areas such as remote sensing and geospatial analysis, environmental toxicology, robotics and field data capture, and genotype-by-environment interactions and the impacts on grain quality. All students in Cohort 3 are currently completing their independent study projects and collecting data, with anticipated data analyses beginning by beginning of Spring 2024. All students in Cohort 3 have already completed or are in the process of completing their statistical coursework. 2. Foster mentorships with research faculty that lead to the successful placement of students in their desired graduate career tracks. The 100% retention rate of students in the program, including in Cohorts 2 and 3, is a testament to the mentorship and experiential learning components of the ELIAS fellowship program. Cohort 2 was the first cohort of students admitted following the COVID-19 pandemic. Of note, the ELIAS research experience was the first time that many students interacted with their peers and their academic community in-person. Although there were more opportunities for Cohort 3 to interact with their peers and academic community, these opportunities were often still somewhat limited in the early stages of their undergraduate careers. The ELIAS program provided students with a space where they felt a sense of belonging and felt that they had a team of mentors that cared about them as a student, as opposed to just being a face on a computer screen. This also provided some mentorship learning moments for the advisors. We noticed that the students emerging from the Pandemic, especially Cohort 2, were very reserved and timid, both within the ELIAS program and in comparison to other students we had mentored in the past. This expressed itself in many ways that required new mentorship strategies, such as (1) students being more timid about making mistakes and needing more guided direction, (2) students being more timid about asking questions and then feeling lack of direction later during their fellowship, and (3) initial hesitation to interact with their fellow peers and their lab mates. This was something we noticed in the previous reporting period as well, and the mentorship met consistently to discuss ways that we could adapt our mentorship strategies to best serve our students. Our ultimate goal was that by the time the students completed the ELIAS Fellowship program, they would be comfortable working in a scientific environment, would be confident, and would be able to interact easily with their peers. In addition to the strategies that were identified in the last reporting period and which worked very well, we also strove to establish a sense of rapport among the students and their peers. While this was not always possible for students working in different research groups, all research mentors agreed to adopt practices within their research setting that would allow students to interact with each other collegially. This included matching student schedules so that groups of students would be able to work together at the same time, mentors making a point to informally drop into laboratory groups and establish a positive, supportive, and friendly atmosphere when they visited, mentors organizing research group social events, etc. Through ongoing conversations with students, regular interactions with students, and creating an environment where they feel/felt safe to ask questions about any aspect of their career and educational progression, not just their research, the ELIAS program promotes not just the development of undergraduate research students, but also mentor-mentee relationships that students feel they can rely upon for support and guidance. These relationships were incredibly important for the placement of students upon graduation, because not only did they earn valuable research skills, but they also had a place where they felt comfortable turning to for advice in navigating the next steps of their educational or working careers. Additionally, the evolution of students in terms of their soft-skills must be mentioned, as it has allowed them to easily integrate into their future research teams seamlessly. Of additional note, follow-up correspondence from Cohort 1 indicated two additional long-term successes of the mentorship strategies employed by the ELIAS program. One student communicated that she was thoroughly enjoying her graduate studies that that she would not have known that her chosen graduate and career path existed had it not been for the ELIAS Fellowship program. That student is currently finishing her Master's degree. Another student that she plans to return to graduate school to advance her career field within the next few years, and that her experiences within the ELIAS Fellowship program helped to set her upon that trajectory. The other two students from Cohort 1 are also still successfully employed or advancing toward their PhD, which is indicative of the preparation and guidance they received as part of the ELIAS program. 3. Develop students' technical understanding of applied statistics and their ability to communicate results effectively to diverse auidences. ?All students in Cohort 2 completed training and coursework in introductory statistics, experimental design, and statical programming (e.g., R or Python). All students in Cohort 3 have completed their introductory statistical courses and have either completed or registered for courses in experimental design and statical programming. In addition, all students conducted (Cohort 2) or are beginning the process of (Cohort 3) data organization, cleaning, and analysis using data they generated/are generating as part of their independent study. All students presented at their home institutions' undergraduate research symposia. All students in Cohort 2, and two students from Cohort 3, presented at the ELIAS Spring Event. All students have helped craft impact statements and descriptions of their research for inclusion on the ELIAS website. Two students presented at professional conferences they attended, and one student earned 2nd place honors at the ASA-CSSA-SSSA International Annual Conference in both 2022 and 2023 for her presentations. Two students have also used their ELIAS research for their senior capstone presentations.
Publications
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2023
Citation:
Butts-Wilmsmeyer CJ, et al. Navigating the Data Sea: The Educational Needs of the Agricultural Workforce across Varying Age and Other Educational Demographics. ASA-CSSA-SSSA International Annual Meeting. 2023.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2023
Citation:
Inaoka M and AE Lipka. Identification of Genetic Markers Associated with Leaf Angle and Tassel Branch Number in Maize. Maize Genetic Meeting. 2023.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2023
Citation:
Benware M-M, et al. Genome-Wide Association Study of Resistance to Mycotoxin Production in Maize (Zea mays L.) ASA-CSSA-SSSA International Annual Meeting. 2023.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2023
Citation:
Inaoka M and AE Lipka. Identification of Genetic Markers Associated with Leaf Angle and Tassel Branch Number in Maize. UIUC Undergraduate Research Symposium. 2023.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2023
Citation:
Hendrickson J, et al. Effects of Grazing Cover Crops on Soil Stability and Aggregation. UIUC Undergraduate Research Symposium. 2023.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2023
Citation:
Benware M-M, et al. Hydroxycinnamic Acid Concentrations in Zea mays Across Four Fields with Differing Environmental Conditions. SIUE Undergraduate Scholars Showcase. 2023.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2023
Citation:
Osikoya IP, et al. Genetic Variability in Maize (Zea mays L.) Stress Resistance Traits. SIUE Undergraduate Scholars Showcase. 2023.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2023
Citation:
Lobb TA, et al. Statin Effect on Earthworms. SIUE Undergraduate Scholars Showcase. 2023.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2022
Citation:
Benware M-M, et al. Visual presentation contest: Hydroxycinnamic Acid Concentrations in Zea mays Across Four Fields with Differing Environmental Conditions. ASA-CSSA-SSSA International Annual Meeting. 2022
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2022
Citation:
Ayegbidun OA, et al. Genome-Wide Association Selection for Stress Resistance in Maize. ASA-CSSA-SSSA International Annual Meeting. 2022
|
Progress 08/15/21 to 08/14/22
Outputs
Target Audience:During the reporting period, the second cohort of students completed their first year of study within the ELIAS fellowship program, and the third cohort of students was recruited. The second cohort of students included the following target audience that was recruited for participation. Three female students (75%) were selected. One student (25%) identified as Black/African American, and one student (75%) identified as Asian. One student (25%) was a transfer student from community college. Two students were selected from the University of Illinois at Urbana-Champaign in Crop Science, with one of these students also earning a minor in Computer Science. Two students were selected from Southern Illinois University Edwardsville and are majoring in Biological Sciences. All students in the second cohort completed introductory program elements such as orientation and onboarding, safety training, introductory quizzes in fundamental scientific principles and statistical methods, and a personality assessment. All of these introductory program elements are designed to ensure that students admitted to the program have every opportunity to be successful. During the orientation event, all students were able to interact in-person and work together in an informal setting, thereby strengthening their sense of community and belonging. The benefits of this element were noticed over the summer with students and their engagement with the program and with their mentors. Additionally, students were able to meet guest scientists from multiple sectors of the agriculture industry. Each year, the orientation event is hosted by one of the participating schools in the ELIAS program, and guest speakers are invited from the surrounding area. Speakers represented organizations such as Bayer, the Geospatial Mapping, Applications, and Research Center (GeoMARC), the Missouri Botanical Garden, the National Corn-to-Ethanol Research Center (NCERC), the Missouri Botanical Garden, and the Donald Danforth Plant Science Center. Students were able to tour the Danforth Center and interact with scientists surrounded by state-of-the-art technology, a component that the students indicated was highly beneficial to them in the follow-up survey. All students completed their guided research experience and identified their independent research project during the reporting period. Three of the students in the second cohort completed their independent research projects over the Summer 2022 months. The fourth student had the opportunity to participate in an internship at the International Rice Research Institute, and we will be working with IRRI scientists to incorporate part of her research into her independent study experience in Fall 2022. All students in Cohort 2 are either in the process of cleaning and finalizing their data for statistical analysis (75%), or will be completing data collection, cleaning, and preparation for analysis during the Fall 2022 semester (25%), depending on their summer research experience. All students will be meeting with their statistical mentors routinely during the Fall 2022 semester to begin the analysis of their data, such that all students have time to prepare presentations to be given during either the latter half of the Fall 2022 semester or the Spring 2023 semester. All students from Cohort 2 have also met with their academic advisors and are on track to complete coursework/technical training required as part of the ELIAS fellowship program. All students have completed their introductory statistical coursework, and all have arranged to take an experimental design course in the upcoming academic year. Additionally, all students have met with the statistical mentors to determine which statistical programming option they would like to take. Beginning in Spring 2023, students will have the option of taking a certification course in R, a certification course in Python, or a course selected at their home institution with advisement from the statistical mentors. The third cohort of students has also been selected as of the drafting of this report. The target audience identified includes the following student body. Two female students were selected (50%). One Black/African American student was selected (25%). One Hispanic student was selected (25%). Two community college transfer students, one who is also a non-traditional college student, were selected (50%). One student was selected from Northeastern Illinois University and is majoring in Biology. The other three students were selected from Southern Illinois University Edwardsville, but from among three different majors. Those majors include Biological Sciences, Chemistry, and Mechanical Engineering. All students selected in the third cohort have an interest in environmental monitoring and sustainability. Based on the experiences of recruiting previous cohorts, we have moved to a rolling-admissions application system with a priority application due date in May, and a second review date after the start of the new school year. This has helped recruitment greatly and has especially helped in reaching the transfer student community. As an example, three of the four community college transfer students reached through the ELIAS program were recruited and admitted in the fall of their junior year due to the extended deadline. The two traditional students have accepted admission into the program, and the two transfer students who were recruited through the later admission cycle will be receiving offer letters in September. Orientation is currently being planned and will be held with the third cohort, with the second cohort having the option to attend, in October of this coming year. In addition to activities with current students in the program, efforts have also been instituted to maintain an ongoing relationship with the former members (Cohort 1) of the ELIAS fellowship program. Follow-up surveys have been disseminated to the members of Cohort 1 to determine whether their opinion of the ELIAS fellowship program and their preparation for their respective future endeavors has changed since exiting the program, and whether there is anything that we can do to modify the program and best serve our students based on Cohort 1's retrospective experiences. Changes/Problems:The COVID-19 pandemic presented numerous challenges, particularly in terms of recruitment, research experience, and cohort building. The issues surrounding cohort building were addressed during the previous reporting period through more face-to-face interactions as necessary mitigative measures were lifted. However, the COVID-19 pandemic also resulted in a significant delay in the proposed training experience. Of most significant note was that campuses across Illinois were often required to shut down, with undergraduate students being barred from research work entirely on some of our participating campuses. This lack of ability to participate in a hands-on research experience understandably deterred many students from applying during 2020, when Cohort 2 was scheduled to be recruited. Those students that we did speak with indicated a reservation of participating in a research experience when there were so many unknowns surrounding what that experience would actually look like in the coming months. Furthermore, many students that our project team spoke with often expressed concern about either their own health or the health of their family members that they were living with should that student eventually be allowed onto campus to participate in a research experience. Additionally, many historically underrepresented students indicated that they could not participate in research experiences due to them being needed at home to help take care of family members during the pandemic, thereby inadvertently creating a potential to inadvertently exclude students from among our target demographic populations. Rather than jeopardizing the research and training experience of these students and inadvertently excluding some students from participation, the project team elected to postpone the recruitment of Cohort 2 by one year. However, this created a perpetual lag in the recruitment of students, with Cohort 2 being recruited in 2021 and Cohort 3 being recruited in 2022. Since all campuses have been reopened and recruiting and training efforts resumed, all target metrics and training goals have been met for each cohort relative to the proposed training plan. However, it is highly unlikely that Cohort 3 will have completed all elements of the ELIAS fellowship program during only the first year of the training experience, which corresponds to the current project end date of the award. So as to provide Cohort 3 with the same two-year experience as the previous cohorts and to allow for all project components to be completed by Cohort 3 prior to the award end date, the project team would like to request a no-cost extension of time of 12 months. The two-year model has been incredibly beneficial to the students participating in the ELIAS program as it allows students (1) to focus on a guided research experience and gaining fundamental research and statistical skillsets prior to completing an independent study research project, (2) to prioritize their research experience without fear of lack of financial support to complete the experience, and (3) to participate more fully in the data analysis and presentation portions of their research experience without feeling as if they need to rush through these components as an obligation to creating a research poster, as opposed to a research experience. The two-year model also allows for greater breadth of statistical training in not just introductory statistical coursework, but also experimental design and professional development courses leading to industry-aligned certification in statistical programming. If granted, this no-cost extension of time would allow Cohort 3 to participate in the orientation, onboarding, guided research experiences, and introductory statistical training components that all other cohorts have typically undertaken during the 2022-23 academic year, and then to participate in an independent study, advanced applied statistical coursework, data analysis, and presentation/publication activities in the 2023-24 academic year. Post-pandemic, another issue that has emerged is the rising cost of student living expenses due to inflation. This issue has become so severe that potential recruits have communicated to the project team that they feel they cannot afford to take part in the ELIAS fellowship program, even with the stipend. Cohort 2 students have communicated that they feel like they will have to find another job this upcoming year to help pay for their living expenses. Additionally, the costs of conference travel have also been increasing, leaving some students feeling as if the program does not provide as many benefits as it did pre-pandemic. During both Cohorts 2 and 3, we have recruited one fewer student than our target, and there were also funds to support an additional rising senior that have not been utilized. To address these concerns, the project team would like to propose that the remaining participant support costs be redistributed such that all participants in Cohorts 2 and 3 receive increased stipend and travel support, please. What opportunities for training and professional development has the project provided?The primary focus of this award is to provide experiential learning opportunities concurrently in applied statistics and crop science or a related area (e.g. environmental science). All students successfully completed an immersive, independent research experience under the guidance of their primary research mentor in their chosen area of interest. Students' research projects spanned areas such as creating value-added maize varieties through genomic selection with enhanced nutritional profiles; using genome editing techniques to discover and manipulate genes that are involved in stress response in horticultural crops; characterizing variation in rice varieties for resistance to rice blast; and understanding the short- and medium-term impacts on soil microbial, chemical, and physical health when farmland is converted back to less intensive farming strategies. Through these experiences, students have gained skills in molecular genetics, plant breeding, genomics, biochemistry, agronomy, plant pathology, and soil biogeochemistry. In addition to these skills in life science research, which students used to generate their research data, students used methods in applied statistics (programming, experimental design, and data analysis) to analyze their data in a real-world setting. While coursework is important in introducing statistical concepts, the PIs repeatedly hear from industry advisory members that working with real-world, "messy" data was essential to truly mastering data analysis. As such, one of the components of the program is to have students generate their own datasets, organize and assemble that "messy" data into a standard data frame style master dataset, and then analyze that data. Another skill that we heard from our advisory members that was important was that students be able to draw upon multiple skills simultaneously to analyze data, interpret output, and then report their findings. As such, all statistical mentors have adapted and continue to employ a mentoring approach in which all students are introduced to multiple data analysis techniques simultaneously, the advantages and limitations of each approach is discussed, and then possible workflows drawing upon multiple skillsets are presented. Mentors have begun having these conversations with students and will continue having these conversations throughout the upcoming academic year. How have the results been disseminated to communities of interest?During the reporting period, one presentation was given at an international conference, one presentation was given at a national conference, and one presentation was given at an undergraduate research symposium. Most of the results of Cohort 2's research will be disseminated during the next reporting period. In addition, all content has been created for a webpage dedicated to the ELIAS fellowship program, the students, and their research projects. The webpage is currently under development and is expected to be deployed in Fall 2022. What do you plan to do during the next reporting period to accomplish the goals?The second cohort of students will be finalizing their statistical coursework, research analyses, and presentation commitments as part of the ELIAS program during the upcoming project period. It is anticipated that each student will present at least three presentations/public talks in the upcoming reporting period. It is also foreseeable that many of the students' work may be included as part of peer-reviewed publications in the upcoming year. The third and final cohort of students has been recruited, and it is anticipated that all students will accept admission into the ELIAS fellowship program. We are currently in the process of placing the third cohort of students with their mentors. All students will attend a combination of orientation, networking, and social events throughout the year to build camaraderie and promote a sense of community among the fellows and the mentor team. At least one of these events will be in-person to help further establish that sense of community. One challenge that was encountered as a result of the COVID-19 pandemic was a year-delay in the recruitment of Cohort 2. This is detailed more under Changes/Problems; briefly, necessary campus closures and lack of access to research facilities would have made the immersive hands-on research experience effectively impossible for all incoming students. Rather than jeopardize the studentexperience, the mentor team elected to postpone the recruitment of the second cohort. This translated to an additional delay in the recruitment of the third and final cohort, which is now expected to begin their guided research and introductory statistical experience in the 2022-23 academic year and complete their independent research, presentation, and applied statistical experience during the 2023-24 academic year. The project team would like to request a no-cost extension of time of 12 months that would allow the third cohort the full two years to complete the ELIAS fellowship and meet all program components, rather than rushing to complete program components before the current proposal end date of August 2023. If granted this no-cost extension of time, this would allow Cohort 3 to participate in the orientation, onboarding, guided research experiences, and introductory statistical training components that all other cohorts have typically undertaken during the upcoming project period.
Impacts
What was accomplished under these goals?
1. Conduct an experiential research project involving both traditional crop science and statistical components. Four students (Cohort 2) were successfully retained in the program and trained in hands-on research in crop and environmental sciences. All students have been provided with preliminary exposure to statistical methods, have met with their statistical mentors, and have planned an independent research project with consideration of proper experimental design and future analysis. Three of the four students in Cohort 2 have completed their independent research projects, with the fourth student planning to complete her independent research project in Fall 2022 so that she could take part in an internship experience with the International Rice Research Institute (IRRI) during the summer months. Student research areas spanned topics including genomic selection and genome-wide association study (GWAS), genome editing, land-use and soil quality under different land management strategies, and plant breeding for disease resistance. All students have generated or are in the process of generating noel datasets in laboratory, field, or greenhouse settings under the guidance of their research mentor. Students will be working to analyze these datasets during the next reporting period. Students from Cohort 2 have also met with their mentors and academic advisors to plan their statistical coursework for the 2022-23 academic year. All students have completed an introductory statistics course and are planning to take an experimental design course as well as one certification course in statistical programming. 2. Foster mentorships with research faculty that lead to the successful placement of students in their desired graduate career tracks. The 100% retention of students in Cohort 2, in addition to the 100% retention and placement of Cohort 1, is a testament to the mentorship and experiential learning components of the ELIAS fellowship program. Cohort 2 is the first cohort of students admitted following the COVID-19 pandemic. Of note, the ELIAS research experience was the first time that many students interacted with their peers and their academic community in-person. There were both some extreme benefits to this, such as naturally providing students a space where they felt a sense of belonging and felt that they had a team of mentors that cared about them as a student, as opposed to just being a face on a computer screen, as well as some mentorship learning moments for the advisors. The mentors noticed that many of the students emerging from the pandemic were very reserved and timid, both within the ELIAS program and in our other student cohorts. We noticed that this expressed itself in many ways that were quite different from our mentorship experiences prior to the pandemic, such as (1) students being more timid about making mistakes and needing much more guided direction, as well as reassurance, during the initial phases of their fellowship, (2) students being more timid about asking questions and then feeling lack of direction later during their fellowship, and (3) initial hesitation to interact with their fellow peers and their lab mates. In retrospect, these changes in student interactions are very understandable, and the mentor team meets consistently to address such issues as they arise in a very timely fashion. Immediately upon identification of these issues, the mentorship team created the following strategies to help better assist all students in the ELIAS program. These additional strategies include: (1) breaking the orientation meeting into two components, a fall component where all students and mentors attend to receive information pertaining to the program and program requirements, and a second event that highlights various career pathways, provides an overview of the graduate school application process, and invites guest speakers to share their research and more about potential experiences for students; (2) ensuring that all students are placed in a laboratory setting where either the primary mentor, a graduate student, or a postdoctoral research associate will be present at all times to provide guidance; and (3) formalized mid-semester feedback meetings with students, their research mentor, and their statistical mentor to ensure any student questions and mentor expectations are addressed before potential conflicts arise. Through ongoing conversations with students, regular interactions with students, and creating an environment where they feel safe to ask questions about any aspect of their career and educational progression, not just their research, the ELIAS program continues to promote not just the development of undergraduate research students, but also mentor-mentee relationships that students feel they can rely upon for support and guidance. Of additional note, follow-up correspondence from Cohort 1 has indicated two additional long-term successes. One student communicated that she was thoroughly enjoying her graduate studies and that she would not have known that her chosen graduate and career path existed had it not been for the ELIAS fellowship program. A second student has also communicated that she plans on returning to graduate school to advance in her career field within the next few years, and that her experiences within the ELIAS fellowship program helped to set her upon that trajectory. 3. Develop students' technical understanding of applied statistics and their ability to communicate results effectively to diverse audiences. All students in Cohort 2 have completed their introductory statistical courses and have identified courses in experimental design and statistical programming that can be used to satisfy the course requirements of the ELIAS fellowship program. In addition, all students have begun working with data generation, organization, and cleaning in preparation for the data analyses they will undertake during the upcoming academic year. One student presented her guided research project as part of the undergraduate research symposium at her home institution. All students will be presenting their independent research projects, including data analyses and data visualizations that they will be responsible for generating under the guidance of their statistical mentors, during the next academic year.
Publications
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2022
Citation:
Ayegbidun, O.A., et al. Genome-Wide Association Study of Selected Commercial Maize Germplasm Under Environmental Stress. Maize Genetics Conference. 2022.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2022
Citation:
Inaoka, M. and S. Hind. Susceptibility of Pumpkin and Squash Plants to Bacterial Spot and Bacterial Wilt Diseases. UIUC Undergraduate Research Showcase. 2022.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2021
Citation:
Butts-Wilmsmeyer, C.J., et al. Making Lemonade out of Lemons: Unexpected Positive Lessons in Undergraduate Student Mentorship, Diversity, Equity, and Inclusion during the COVID-19 Era. ASA, CSSA, SSSA International Annual Meeting. 2021.
|
Progress 08/15/20 to 08/14/21
Outputs
Target Audience:During the reporting period, the first cohort of students completed their second year of study with the program. These students included the following target audience that was recruited for participation. Two female participants (50%) were selected. One Hispanic student (25%) was selected. One student was a transfer student from Parkland Community College (25%). Two student were selected from the University of Illinois at Urbana-Champaign, one in Crop Science, and one in Computer Science + Crop Science. One student was selected from Northeastern Illinois University. These students continued independent study research work, both in terms of data generation in a traditional research setting and the statistical analysis of that data, under the guidance of their two mentors, one in research methods and one in statistical analysis. In addition to completing and disseminating their research through oral and written communications, all students completed advanced coursework in statistical programming, experimental design, and data analysis. All students were successfully placed in either a graduate school position or a workforce position in their chosen area of expertise. When recruiting for the second cohort, the COVID-19 pandemic created multiple issues, which are detailed further in the Changes/Problems section.Briefly, we were faced with the decision of recruiting from a very limited pool of applicants and missing the target population of undergraduate students, or delaying applications a year. We chose to dealy applications for a year, so as to best serve the intended students and provide them with the in-person, hands-on experiences in research that the first cohort of students repeatedly told us was the most valuable part of the program. Recruitment for the second cohort of students began in March 2021 andis now being finalized at the time of this report, with a minor recruitment event to be held at each institution at the start of the new semester and applications being due in mid-September to ensure the broadest, most diverse population of students is reached. Now that all campuses are being opened to the public, both in-person and online recruitment events will be held for the third cohort of students starting this fall, with applications being released earlier in the spring semester, which more closely resembles the original recruitment and application timeline prior to the limitations posed by the COVID-19 pandemic. Changes/Problems:The COVID-19 pandemic has presented many challenges, especially in terms of recruitment and cohort building. All PIs commented that the most successful way we recruited applicants for Cohort 1 was through face-to-face interactions with the students and encouraging them to apply. The COVID-19 pandemic limited these interactions, to the point where multiple PIs and Key Personnel commented that it feels as if there is an entire year, maybe two years, of students that we do not know and have not interacted with. Additionally, the few students we were able to communicate with often expressed concern, either about their own health or that of the family members they were living with, should they come work on campus. In some instances, undergraduate students were banned from research work entirely on some of our participating campuses, not being allowed into buildings, further deterring students from participating in the program. Due to the slim applicant pool and the often non-existent ability for incoming students to participate in research, the PIs opted not to recruit Cohort 2 until the summer and fall of 2021, when we could start to interact with students and could guarantee that they would be allowed to be allowed on campus, at least with relative certainty. As such, we will almost certainly need to request a no-cost extension, please. In regards to cohort building and sense of community, we do not expect this to remain an issue once in-person events resume. The COVID-19 pandemic was not all bad, perhaps, in terms of what we learned about our students and how we could better support them. Many of the disparities between underserved populations was highlighted during the pandemic. Because we could see these disparities, and we as mentors had our administration's approval to work creatively to address them, the mentor team was able to devise multiple solutions to accommodate the barriers that often limit participation of underserved student populations in research. As examples, mentors devised projects that could be completed by the research students in their homes or in an accessible outdoor setting, loaned laboratory equipment, and created computational projects using preexisting or simulated databases. Speaking with our students, especially those from disadvantaged backgrounds, they often were concerned about participating in research because of what can be relatively rigid research schedules, schedules that do not take into account financial hardships or familial expectations and needs. These are examples of positive changes that the mentor team, and others, may be able to incorporate to increase accessibility to research experiences for undergraduates from underprivileged backgrounds. Another aspect of the program that we will be changing, in response to another aspect we learned from our disadvantaged students, is the timing of the research project. Initially, we had planned for the research component of the program to take place in the summer, so as not to distract from the students' coursework during the academic year. While this option worked for some of our students, others, particularly those from economically disadvantaged backgrounds, communicated that they had really hoped to also take advantage of an industry internship, both for the experience and also because of financial reasons. They further communicated that the fellowship stipend was sufficient that they did not have to take on another job during the academic year and could, therefore, both conduct research and complete their coursework. But, the inability to complete an internship with industry over the summer put them at a significant financial and professional networking disadvantage relative to their classmates. To ensure this was not a deterrent to participation in the ELIAS program, we created a second timing option for students such that they could also participate in a summer internship with an industry partner, if they chose. What opportunities for training and professional development has the project provided?The primary focus of this award is to provide experiential learning opportunities concurrently in applied statistics and crop science or a related area (e.g. environmental science). All students successfully completed an immersive, independent research experience under the guidance of their primary research mentor in their chosen area of interest. Students' research spanned areas such as understanding the genetic variability underlying secondary metabolites that are responsible for enhanced environmental stress tolerance in maize and improving glucosinolate concentration of broccoli sprouts and microgreens at different maturity stages, with the end goal of providing a more desirable product for consumers; evaluating the responsiveness of different maize and soybean varieties under different agronomic conditions and making recommendations to growers; the improvement horticultural crop resiliency using gene editing techniques, including CRISPR/Cas; developing new genomic technologies in agricultural production systems and simulating their utility; and monitoring ecological health in sensitive ecosystems. Through these experiences, students have learned skills in agronomy, molecular genetics, plant breeding, analytical chemistry, genomics, plant pathology, and measuring environmental resiliency from a spatiotemporal perspective. In addition to these skills in life science research, which students used to generate their research data, students used methods in applied statistics (programming, experimental design, and data analysis) to analyze their data in a real-world setting. While coursework is important in introducing statistical concepts, the PIs repeatedly heard from industry advisory members working with real-world, "messy" data was essential to truly mastering data analysis. As such, one of the components of the program was to have students generate their own datasets, organize and assemble that "messy" data into a standard data frame style master dataset, and then analyze that data. Another skill that we heard from our advisory members that was important was that students be able to draw upon multiple skills simultaneously to analyze data, interpret output, and then report their findings. As such, all statistical mentors used a mentoring approach in which all students were introduced to multiple data analysis techniques simultaneously, the advantages and limitations of each approach was discussed, and then possible workflows drawing upon multiple skillsets were presented. Students then analyzed their data independently and were responsible for describing their workflow, evaluating the different possible methods they had available to them, and then presenting their data to their mentors for initial feedback before compiling a report and/or presentation. One of the aspects of the program that has been difficult to support was the sense of community and networking among peers. Necessary campus closures and state mitigative measures in response to the COVID-19 pandemic made it nearly impossible to foster any connections between the students and to build a cohort community. This was also reflected in students' exit surveys. But, one in-person and one virtual social event was held this past reporting period, following state and national guidance. Future professional development events, including a visit with USDA-NASS, is planned for the coming reporting period. How have the results been disseminated to communities of interest?At this time, multiple presentations have been made at campus and regional conferences, one abstract has been submitted to an international conference, one peer-reviewed journal article has been published, and one peer-reviewed journal article is in the final stages of preparation. Students have also blogged about their research experiences. To reach a greater number of audiences, a webpage dedicated to the ELIAS students and their research is in the process of being built and is expected to be completed in the next reporting period. As many of the students' projects are also part of larger overall research projects, these data and their research will be disseminated in peer-reviewed journals and conference presentations as part of the larger research projects. What do you plan to do during the next reporting period to accomplish the goals?We will be finalizing the recruitment of the second cohort of students and reviewing their applications to the program in September 2021. Following recruitment, we will be placing selected students with mentors in their desired areas of interest, and immersing these students in applied research settings withing their area of interest. Students will also take introductory courses in statistics and may opt to take their statistical programming course (e.g. R Programming). Aggregated results from the first cohort's exit survey will be disseminated to all Co-PIs and mentors so as to guide and either continue or improve future mentorship and experiential learning efforts. It is planned that all research work related to Cohort 1's research efforts will be finalized and then submitted for review in both peer-reviewed journals and international conference presentations. To further highlight students' work, both former and current, a webpage highlight the fellows and their work is currently under construction and should be completed early in the next project period. As campuses start to open back up and to allow visitors, recruitment events will be held at each of the campuses in the fall to recruit for Cohort 3 (August 2022 start date).
Impacts
What was accomplished under these goals?
Conduct an experiential research project involving both traditional crop science and statistical components. Four students were successfully retained in the program and trained in both crop sciences and statistical methods. All students completed an independent research project in their area of expertise under the guidance of two mentors, a primary research mentor and a statistics mentor. Their research spanned areas such as genome editing, plant breeding and biofortification, plant pathology and genomics, natural resources and environmental sciences, aquatic ecology, and agronomic management. Through this experience, one student also gained exposure to another field of crop sciences that she did not know existed, took an interest to that research, and ultimately entered the workforce in this area of data-driven crop science research. All students generated novel datasets in laboratory, field, or greenhouse settings under the guidance of their research mentor, and then analyzed those datasets under the guidance of their statistics mentor. All students in Cohort 1 also finished their coursework in applied statistics, taking courses in introductory statistics, R programming/statistical programming, and experimental design and analysis. One problem that we encountered, but which turned into a positive opportunity, was that one of the institutions was not able to continue offering an R programming course due to instructor shortages. To address this issue, the PIs partnered with SIUEs Office of Online Services and Educational Outreach to develop a new professional development course in R Programming, administer the program online, and offer the course to students at any university. The other benefit to this new strategy was that students who complete this course earn a professional development certificate in R Programming. During the exit survey, students were asked to rate the various components of the ELIAS fellowship program (research, mentorship, coursework, presentation of research results, preparation for graduate school, and networking/community) using a five-point Likert scale, with the options of Very Poor, Poor, Okay, Great, and Excellent. All students not only rated the research experience as excellent, they all independently spoke highly of the research experience and research mentorship as the components of the program they found most beneficial. All students, when asked what accomplishment(s) they were most proud of as part of the ELIAS program, also cited their research experiences and the dissemination of the results that came from their research. 2. Foster mentorships with research faculty that lead to the successful placement of students in their desired graduate career tracks. The 100% placement of students in their chosen graduate or career tracks, with both students who are moving on to industry planning to take advantage of employer incentives for graduate education, is a testament to the mentorship and experiential learning components of the ELIAS fellowship program. All students spoke favorably of their mentors and rated the mentorship component as either Excellent or Great. Interestingly, the female students consistently rated the mentorship component more highly than their male counterparts. Upon further communication with these students, a few trends emerged, including (1) making professional connections, (2) being introduced to and immersed in a research setting, (3) and having someone who "looked" like them (one student was Latina from a metropolitan area, and one student was an economically disadvantaged female from a rural area; both were paired with mentors from similar backgrounds) who could help them navigate expectations and opportunities in the realm of scientific research. Also interestingly, the female students communicated that the ELIAS program was integral to them receiving instruction in research and statistical methods, whereas the male students indicated that, while the program helped, it was not as integral to their overall training in research and statistical methods. Given the small sample size, the trend that mentorship is especially vital to helping female students enter data-driven agricultural research may not be representative of the overall population. But, the data thus far presents an interesting hypothesis that will be examined in future cohorts. 3. Develop students' technical understanding of applied statistics and their ability to communicate results effectively to diverse audiences. All fellows also rated their coursework, preparation for graduate school, and introduction to the application of statistical methods and analyses in a research setting as either Excellent or Great. The three students who were able to present their research at conferences or symposia rated the Oral Presentation component as Excellent, while one student rated this component as only Okay. However, this student had been slated to present at a conference that was cancelled due to the COVID-19 pandemic; this student also stated that their most proud accomplishment was conducting an independent study project as part of a larger project that led to a publication. All students presented their results in written format. Formats included project updates, online blog posts, and, in two cases, peer-reviewed publications. One of these journal articles has been published, and the other is in the final drafting stages.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
Fernandes, Samuel B., et al. "How Well Can Multivariate and Univariate GWAS Distinguish Between True and Spurious Pleiotropy?." Frontiers in genetics 11 (2021): 1747.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2021
Citation:
D'Agostino, L and S. Hind. Engineering Pumpkin Plants to Control Western Corn Rootworm, a
Significant Insect Pest of Corn. UIUC Undergraduate Research Symposium. 2021.
- Type:
Conference Papers and Presentations
Status:
Other
Year Published:
2020
Citation:
Stenger, L. AgReliant Summer Internship Presentations. 2020.
- Type:
Conference Papers and Presentations
Status:
Submitted
Year Published:
2021
Citation:
Butts-Wilmsmeyer, CJ et al. Making Lemonade out of Lemons: Unexpected Positive Lessons in Undergraduate Student Mentorship, Diversity, Equity, and Inclusion during the COVID-19 Era. ASA, CSSA, SSSA International Annual Meeting. 2021.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2021
Citation:
Garc�a, S., and P. Geddes. 2021. Do artificial floating wetlands improve habitat quality for aquatic macroinvertebrates in urbanized rivers? Society of Wetland Scientists Annual National Conference (Poster presentation virtual).
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2021
Citation:
Garc�a, S., and P. Geddes. 2021. Do artificial floating wetlands improve habitat quality for aquatic macroinvertebrates in urbanized rivers? NEIU Student Research and Creative Activities Symposium. Chicago, IL. (Oral presentation - virtual). Award-winning oral presentation.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2020
Citation:
Garc�a, S., and P. Geddes. 2020. Macroinvertebrates as biological indicators of habitat quality: The role of artificial floating wetlands in aquatic ecosystems. NEIU Student Center for Science Engagement Annual Symposium, Chicago, IL. (Oral presentation - virtual).
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2020
Citation:
Garc�a, S., and P. Geddes. 2020. Macroinvertebrates as biological indicators: The role of artificial floating wetlands in aquatic ecosystems. NEIU Biology Department Virtual Research Symposium. Chicago, IL. (Oral presentation - virtual).
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