A rich education ecosystem includes both remote and in-person variants. Educators must work with students to get the balance right. For a while, due to the pandemic, we all had to make do with the remote version, and now we are seeing some negative consequences in the form of chronically demotivated students.
Though the pandemic popularized comparisons of remote to in-person education, students have had the option of distance learning for decades. There is extensive scientific literature that examines the pros and cons of each teaching format.
Most of the studies are based on people who voluntarily choose between remote or in-person learning based on their life circumstances. Given the stigma that remote education has among many employers, the people who choose remote learning tend to be people who have a mature attitude to their education. Through perseverance, they will strive to overcome the stigma and the personal impediment they face, such as a physical disability or the need to be at home with a young child.
These systematic differences between those who choose remote versus in-person undermine the value of such studies for understanding the impact of a mass shift to remote learning since most people don’t work as diligently as those who end up choosing remote learning.
To get around this weakness, a minority of studies employ what is known as randomized control – whereby people are randomly assigned to either remote or in-person learning. It ensures that the two groups are similar in student characteristics, making it easier to generalize to the rest of the population based on their experience.
However, the problem with these studies is that the random assignment is transient, lasting a course or two. It limits their value in understanding what happens when there is a mass, sustained shift to remote learning. For example, it is entirely plausible that the most significant downsides of remote education begin to materialize only after six months of the format when students become disenchanted and demotivated.
For this reason, the pandemic has provided education scholars with a wealth of new evidence on the impact of remote education. It has involved everyone switching to remote learning en masse and covering all courses for a sustained period. Unlike previous studies, students were not allowed to treat remote education as a small-scale experiment for one of their courses; instead, it forcibly became a way of life.
As the data has accumulated and scholars have analyzed it, the initial results suggest that remote learning is not as good as initially advertised. A series of op-eds in major newspapers, coupled with heated exchanges on social media, has presented these findings in lay terms, with professors and students expressing deep frustration.
In particular, university professors have complained about abnormally low motivation levels among their students, leading to declining commitment and performance. Moreover, this has continued even upon the resumption of in-person classes – an outcome worse than the most pessimistic predictions that critics of remote education would have made before the pandemic.
In some sense, these results should not be too surprising to professors, given their professional proclivities. They fight tooth and nail to get jobs in the top universities precisely because they want to be down the hall from the best scholars so that they can exchange ideas over coffee and after seminars. They want to be able to interact with the best students, too, for the same reason. If you offered them the choice of chatting with their peers and disciples exclusively via video calls, most would indeed decline, preferring the more lasting connections that arise when meeting face-to-face.
It will take time to fully analyze the wealth of data generated by almost two years of the sector-level switch to remote learning. We will continue gathering new data as institutions increasingly offer options such as hybrid and asynchronous teaching.
Educators and students must collaborate on the process of analyzing the data. It may turn out that one side needs to do more work than the other to fix the problems that have arisen. In that case, a shared approach to analyzing the data is central to legitimizing the diagnosis and resulting recommendations.
For example, I am convinced that academic standards have been slipping due to students being coddled too much, breeding a destructive sense of entitlement. If my hunch is correct, then professors need to collectively raise academic standards with the support of deans and parents, and students need to accept the need to raise their game. If I am wrong, a completely different course of action might be necessary, involving professors evolving their pedagogical techniques.
Either way, at least one side needs to make a significant change, and collaboratively analyzing the data is critical to the legitimacy of the process. After all, as Leo Tolstoy once quipped: “Everyone thinks of changing the world, but no one thinks of changing himself.”