Progress 09/01/24 to 08/31/25
Outputs
Target Audience:The target audience of this grant is undergraduate students who are interested in careers at the intersection of the crop/environmental sciences and data science. Students were recruited heavily from Illinois universities. Students were recruited using flyers, classroom visits, and advertisement from faculty mentors both within and outside the ELIAS-DS program. Students are admitted on a rolling basis into the Explorers program. To make application into the program easier for students, all recruitment materials contained a QR code that linked them to an online application. We will be recruiting from the Explorers participants to identify ELIAS-DS Fellows during the next reporting period. Changes/Problems:The most significant challenge that we encountered was the uncertainty surrounding the federal funding freeze in early 2025. In our best faith effort, we followed the guidance available to us and did not participate in grant activities or spend grant dollars during this timeframe. However, this occurred directly in what should have been our peak recruiting timeframe. Therefore, we had a very delayed start to the grant project. When we were confident we could continue with the project, we pivoted to our alternative, online asynchronous modality so that students could participate in the Explorers pathway during the academic year instead of during the summer. While less favorable because it poses challenges for in-person relationships, the formation of a strong cohort, and limited mentorship interactions, the online asynchronous version has also enabled us to keeping serving students, just with a slower start than we originally anticipated. We will continue to attempt to recruit from other universities across from Illinois and reach our target of 50 students in the Explorers pathway per cohort. We will also likely be selecting cohorts 1 and 2 of the ELIAS-DS Fellows simultaneously as one large group of Fellows, as opposed to two separate cohorts. We will select these Fellows from the pool of Explorers cohorts 1 and 2. As such, while it may take another 18-24 months to recover the time lost and raise our participant numbers back to target levels, we have enacted contingency plans to address the delayed start. What opportunities for training and professional development has the project provided?This project has provided undergraduate students opportunities for training in data science skillsets such as advanced excel, R, data/statistical analysis, ArcGIS, remote sensing, python, and machine learning. In addition to these quantitative skillsets, students have also received training in soft skills such as effective communication in the workplace, SMART goals, time management, conflict resolution, resume development, and how self-awareness of their personalities can help them maintain a positive research and teamwork experience. How have the results been disseminated to communities of interest?
Nothing Reported
What do you plan to do during the next reporting period to accomplish the goals?Over the next reporting period, we will continue to recruit students into the Explorers track and bring the first cohort of students to the completion of their training. We will also recruit the second cohort of Explorers students. Likewise, we will recruit the first and second cohorts of ELIAS-DS Fellows and pair them with their research mentors.
Impacts
What was accomplished under these goals?
Data Science Technical Skills: Develop students' understanding of data science through hands-on training with real-world data. Under this project goal, the project team first identified the skill sets that were most crucial for students to gain under each of the broad topic areas of general soft skills, Excel, Power BI, R, data/statistical analysis, GIS tools, remote sensing applications, Python, and machine learning applications. We then aligned this to what students could be reasonably expected to know coming into the program and created resources that would help bridge the gap between what students typically know upon entering the program and what future employers and potential graduate programswould like them to know/what makes them more competitive applicants upon graduation. In addition to resources that we created ourselves, we leveraged interactive curricular resources through DataCamp and ESRI at our institutions to bring students the most complete learning experience possible. These tools also allow us to track what types of skills students are learning by type. For our first group of students, the types of skills they were initially most attracted to were programming and data visualization. They were particularly comfortable working in R and were excited to engage with that technology. With advanced Excel, they were less excited by that technology but relatively comfortable with it. With Power BI, Python, and ArcGIS, all students were more hesitant to engage with those technologies and moved through the modules much more slowly than with the R and Excel modules. This suggests a familiarity with R and Excel, as well as with data entry and routine statistical analysis, but not necessarily with other aspects of data science. In particular, this finding highlights that students may not have been exposed to the fundamentals underlying big data analysis, particularly the operational aspects of the data handling process. It also demonstrates a certain timidity with programming that is akin to what many students encounter when they are learning a new foreign language: they often think of it as an input/output system, as opposed to conversing with the computer. This is something we will focus on and incorporate as we move into the next phases of the Explorers Pathway, as well as the Fellows Pathway. 2. Mentorship: Foster mentorships with faculty that lead to the successful retention and placement of students in their desired career tracks. Students in the Explorers track are now starting to interact with faculty members and now have additional connections on their respective campuses. Although this form of mentorship is at an early stage, it is also crucial for student success because it helps students know they do have a support network on their campuses that care about them as individuals and see them more than just a number. As we move deeper into the Explorers program and students interact with more faculty both at their campus and at other campuses, we expect these valuable mentorship connections to become stronger, and that this will continue to translate to student belonging. Students who will be continuing on into the Fellows pathway will also have increased one-on-one mentorship, and we anticipate this will also lead to successful student retention, placement, and success. 3. Application and Communication: Enhance students' ability to use data science tools to solve research questions in crop science and communicate findings to diverse audiences. Although this goal is something that we will address more fully during the latter stages of the Explorers pathway and especially during the Fellows pathway, we have introduced students to the foundations of effective communication. In our onboarding and soft skills module, we have short lessons on effective communication in the workplace, conflict resolution, and a written reflection on the data report of their personality assessment.
Publications
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