Student survey Evaluations

Pretraining assessment

The pilot cohort consisted of 6 students, 2 from Texas A&M college station, 2 from TAMU Kingsville, and 2 from TAMU Corpus Christi. To start with, 2 students indicated that they had a background in animal science, 2 students indicated a background in plant science, one student with computer science, and one student with spatial data experience. At the beginning of the training program, the students indicated that they had a mean of 4.3 (on a scale of 0-10 (Range 0 - 8)) understanding of data management in Agriculture. One-third of the students (2/6) indicated that they never had experience with data handling, and a half (3/6) of the students had some data analysis experience whereas one student (1/6) indicated partial experience of working with data. Half of the students (3/6) had previously taken a course in data analysis whereas the rest were unaware of the methods and tools applied in the analysis of data. Students indicated that they learn more through hands-on exercises, one on one interactions, seeing and watching someone do analysis, and understanding the practical application of what is being discussed. All students were excited about the cross-disciplinary engagement and thought that students would complement each other, feel excited about different disciplines coming together, and indicated that this approach helps to understand the big picture and understand beyond the details of the concept. On the perception of teamwork, students indicated that they would grow knowledge, learn from other members, consider that the whole group feels challenged, and indicated this to be an efficient way to meet and work with people.

Post training assessment

In general, students indicated that they were very satisfied with the internship experience. On a scale of 0-10, the mean satisfaction score was 8.75 (range 7.5 - 10). On a scale of 0-0, students indicated that they were more confident to work with and talk about data from animal systems than at the beginning of the project (mean 8.5; range 7-10). On a scale of 0-10 students indicated that they were more confident to work with and talk about data related to plant systems (mean= 8.41; range= 7-10). All students agreed that they learned at least one new concept related to animal data ecosystem and all students (6/6) agreed that they learned at least one new concept related to data ecosystem in plant science.

Students indicated that the program was a good start for understanding the overall data architecture (n=2), indicating good progress on data application (n=2), and thought it helpful to understand in detail possibilities and progress(n=2). All students (n=6) agreed that their understanding of big data in agriculture changed significantly because of the course. Consequently, 4 students indicated that they were interested in exploring career opportunities related to big data in agriculture whereas (n=2) indicated their interest in the application of the developed tools for on-farm use.

When evaluating the effect of cross-disciplinary training in learning concepts outside of their own discipline, the mean score was 9.4 (range 8-10) on a scale of 0-10, agreeing to that cross-disciplinary training was helpful in learning concepts outside of their own field. When asked about the most significant concept they learned, other than plant science data, and animal science data, students indicated that they were excited to learn spatial data management and MySQL which were new concepts to them. All students indicated that they learned team management skills and skills working with people that are different from their own.

Students suggested improvement in communications, message delivery, in-person meetings, weekly reporting of briefs, and reviews, and making students write the training book for students to benefit more from the program. Students indicated that further support on interaction with data and team, access to data earlier in the program, opportunities for one-on-one communication, and prerecorded videos will be helpful for the success of future iterations of the program. Students indicated easy access to coordinators, the overall organization of the program, meeting students outside of their disciplines and organization, interactive subject content, and group interaction components as the major strength of the program.

Overall, on a scale of 0-10, students provided a score of 5.5 (range 3-8) for their post-course competency in MySQL and Agriculture database management.