Teaching in academia is often seen as a distraction from research. Teaching takes time, energy, resources and, most importantly, does not produce any papers. In many universities, if you are successful in acquiring third-party funding, you can even buy yourself out of teaching. However, the university educational system is fundamentally based on the interactions between teaching and research.
We argue that it is possible, and profitable, to create a mutualism between teaching and research. Our own experiences in the field of plant physiology has shown that bringing our latest research into the classroom can benefit both our students and ourselves as scientists.
Here’s our story.
The example of plant physiology classes.
Plant physiology courses often follow the same organization: the theory is explained in the classroom and students are then asked to perform experiments in practical sessions. Understanding a new concept in the classroom is not always easy since the main teaching medium is a slideshow, and most of the graphs presented are merely two-dimensional (one variable changes in one way or another depending on another). In reality though, concepts in plant physiology are frequently multi-dimensional and require several experiments to illustrate fully.
While the aim of practicals is to illustrate the different theoretical concepts seen in the classroom, performing experiments with plants requires time, space, equipment and money. Students regularly do not succeed in keeping plants alive (which is a lesson in itself)! As a result, they can only explore a small portion of the theory during the experiments.
For many years, in our lab and with our colleagues we have been developing computational plant models. These tools span over different scales (organ to full plant) and are based on sound mechanistic and physiological theories. We have also recently made our models readily available through web interfaces. These models can now be used by anyone, without any prerequisite computational skills, simply within a web browser. The fact that the models are based on the same theoretical principles taught in our theory classes and they can be used by many students simultaneously, makes them perfect teaching tools. Bringing our models into the classroom also allows us to engage students directly with active research in our labs.
The benefits for students.
Plant biology theory can often seem far-removed from students’ everyday experiences, and even from the limited set of experiments performed in practicals. When students can manipulate plant growth using our model, they can build a visual, interactive relationship with the theory studied in class. As the models we use are based on real plants and real pedoclimatic conditions, the questions asked of students correspond to situations that people actually encounter around the world. For example, we ask students to provide quantitative evidence (based on the model) to assess which architectural characteristics of maize roots are best promoted in drought-prone areas. We can also ask them to explain how changes in photosynthesis can be linked to changes in soil water uptake, something they can observe and test in these models.
The use of research in the classroom is an opportunity to teach students that science is always a work in progress.
Practical tasks based on computational tools allow students to go further in their understanding than with just experiments on real plants. First, the large amount of “logistical” time saved by not having to cultivate the plants can be devoted to further reflection on the causes of the observed phenomena. Secondly, the models provide access to data that are not available on real plants, either because their obtention requires the dissection of the plant, or because the corresponding measuring devices are not accessible to students.
Teachers usually update their theoretical courses as scientific knowledge evolves. This is something that students are not always aware of: what they see in class today may no longer be considered true tomorrow. The use of our on-going research in the classroom is an opportunity to teach students that science is always a work in progress.
The benefits for researchers.
Explicitly including our research into the classroom has benefited our own science in several ways.
Researchers of our lab mostly teach students from the Faculty of Bioengineering in our university. In recent years, like in many other universities, the number of students enrolled in our faculty has risen considerably. This makes it very difficult to organize practical work in the greenhouses: the facilities are still the same size as before, although they are now used by an ever-increasing number of students. This means working with larger groups and growing more plants so that everyone can work with the lab equipment. However, what can be seen as a curse by practical work supervisors can become a blessing for researchers working on computer models. Imagine: your models allow the creation of practical work adapted to learning in large groups and at the same time you win hundreds of beta-testers for free every year!
Students make thorough technical reviewers, probably better than classical journal reviewers too!
Having hundreds of students using our tools at the same time, in a directed fashion, is a great way to identify bugs. These bugs can be either just in the interface but more importantly even in the underlying model. For instance, in one of our water flow models, our students found that some specific parameter values were creating instabilities, pointing to bugs in our numerical implementations. We just hadn’t been able to test all the parameter combinations ourselves! Discrepancies between the theory explained in the classroom and the model can also be spotted by the students. When trying to understand and interpret the results of the models, students make thorough technical reviewers, probably better than classical journal reviewers too!
More than just finding bugs in your tools, students challenge your underlying assumptions. As learners, they are actively trying to understand the studied topic. They are trying to put the different pieces that make up a subject together, not only in your class, but also across different classes. We are often questioned by students about contradictions with other courses they might be studying, “[…] BUT we have seen last year with Prof. X that […]”.
For instance, a classical assumption that is taught in introductory classes is that longer roots are needed by plants in drought conditions. However, using the computer models, students can see that this is not always the case and that the reality can be more complicated. Compared to practicing scientists who might take basic assumptions for granted, students tend to ask more incisive questions. Questions that might lead you to revise your assumptions and even formulate new theories.
Bringing on-going research into the classroom also helps us refine how we explain our theories. If we can successfully explain our latest research to a classroom, there is a good chance we’ll be able to explain it clearly to fellow scientists in publications and at conferences. The classroom is the perfect place to practice how you present your science.
Teaching and research should be more integrated.
Teaching and research do not have to be mutually exclusive. Yes teaching takes time , but it can be incredibly rewarding. By explicitly integrating your latest research in the classroom , your research can directly benefit from your teaching.
In our classes we have exemplified this idea with computational tools, but it can be extended to other disciplines too. You want to teach students how to measure physiological parameters? Give them your latest mutant library to screen! Do you need a new system to monitor the soil water content in your growth setup? Put your students into groups and ask them to design a solution! From a pedagogical point of view, putting students to a useful task is always more motivating.
If students know their work will be valued, they will be more careful and dedicated, and they will learn better.
About the Authors:
Guillaume Lobet is an Assistant Professor at the Forschungszentrum Jülich in Germany and the Université catholique de Louvain in Belgium. Follow him on Twitter @guillaumelobet.
Lola Leveau is a Teaching Assistant at the Université catholique de Louvain in Belgium. Follow her on Twitter @LeveauLola
Footnote: We are not researchers in higher education quantification and a large body of literature exists on the subject (see here, here and here for instance).
Photo by Edwin Andrade on Unsplash
