Hybrid teaching through Zoom and other platforms during the COVID-19 epidemic has been an illuminating as well as unsettling experience for many of us, especially for the college-going students.
According to a recent poll “Gen Z and the Toll of the Pandemic”, (https://apnorc.org/projects/gen-z-and-the-toll-of-the-pandemic/) the “Uncertainty about the pandemic and fear of infection are among the top sources of stress for this generation…. the pandemic has made it harder to have fun… has been detrimental to their relationships with their friends, physical health, dating lives, the pursuit of hobbies, and other important aspects of being a young person.” The findings confirm our own daily contact with students.
Nonetheless, most students have begun to adapt to new realities. Today’s freshman, let’s say tech-savvy Jane Digital, can do a lot of learning on her own. She believes that for every problem there must be an app and if not, it can be created. This do-it-yourself app frame-of-mind developed during these harrowing days of masked classroom teaching and remote learning from dorms and homes has been raising new questions as to how we teach. Why do we teach the way we do — simply taking Jane Digital from level X to Y, which mostly she can do herself? Even before the COVID-19 pandemic, online courses platforms such as Coursera, Khan Academy and other Web learning enterprises were increasingly offering routine teaching.
MIT president L Rafael Reif called massive online courses (MOOCs) as “the most important innovation in education since the printing press”. The advent of the printing press in the 15th century, in the course of time, liberated the European mind and enabled it to re-discover and reclaim its Graeco-Roman spirit of rational inquiry. Something similar is happening today.
MOOCs, Coursera and other learning platforms have the potential to liberate academia from routine teaching. But, then, what to do with the surplus brainpower of the highly qualified faculty when they are relieved of some of the obligations of 2-3 day weekly instructions, power points lectures, quizzes, research papers, and exams especially as we are rapidly entering the age of machine learning and artificial intelligence (AI)?
Universities need to become think tanks and take up the responsibility of confronting tough questions, such as: How would mRNA change global health? Can AI enable us to predict and prevent financial meltdowns, racial and civil conflicts, and the next school shooting? Would AI enrich or diminish humanity? Answering such seemingly absurd questions requires more than super computational power, sophisticated algorithms, and Big Data. It requires interdisciplinary collaborative research clusters of scientists, political thinkers, and philosophers.
The goal of developing faculty clusters, scholars who are unafraid to transgress disciplines and push the boundaries of conventional thinking, is to wrestle with society’s most intricate challenges. The expectation is that disruption of intellectual boundaries would result in disruptive innovations. To echo Nobel laureate Phillip Sharp’s thinking, “Convergence is a broad rethinking of how all… research can be conducted, so that we capitalise on a range of knowledge bases,” from STEM (science, technology, engineering and mathematics) to viruses, and the liberal arts.
Over the years American society has become more open and tolerant of diversity, despite the Trumpian backlash. But academicians still live in intellectual silos, most of them publishing in journals that very few people read outside their disciplines. Interdisciplinary clusters aim to bust the silo mentality.
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Bringing down the walls can be difficult but some have been trying, for example, Berkeley Startup Cluster touted itself as “a resource for innovative companies and budding entrepreneurs in Berkeley.” It’s a collaborative initiative of UC Berkeley, the local chamber of commerce, the downtown association, Berkeley National Laboratory, and the city of Berkeley.
Such across-the-discipline collaborations from diverse and even unrelated fields of interest lead to the opening up of what the evolutionary biologist Stuart A Kauffman called as “the adjacent possible”, the door that opens another door and creates possibilities of new futures. That’s the potential of cluster faculty doing collaborative research when the whole world is becoming one Big Data, which, as Forrest Gump would have said, is “like a box of chocolates. You never know what you're gonna get”. That’s the potential of faculty clusters exploring the “adjacent possible”. Serendipity could happen.
Cluster hiring initiative began at the University of Wisconsin at Madison in 1998 and today the university has 49 clusters ranging from the mundane to the esoteric, from African Diaspora to Zebrafish Biology. Dartmouth College has nine interdisciplinary academic clusters including climate change, neural code, globalisation, digital humanities, decision science, cyber-security, cystic fibrosis, healthcare delivery, and computational science, aiming “to enhancing Dartmouth's impact in the world”.
But that raises an eyebrow. With millions of research dollars being spent on these cluster initiatives, the question is: How do you assess them? Without assessment, interdisciplinary academic clusters might become part of the establishment, more interested in their own survival rather than doing innovation and solving big problems.
The way to keep multi-million dollar cluster initiatives productive is to task them specifically: The way the United States tasked the Manhattan Project to produce a nuclear weapon; the way John F Kennedy tasked NASA to land man on the Moon; and the way the Trump administration, despite its dark side, tasked Operation Warp Speed to produce COVID-19 vaccine, which was done in eight months. Universities must do more than teach. They should own global problems.
The author is the author of the forthcoming book, 'India in a New Key: Jawaharlal Nehru to Narendra Modi'. He is a professor at Norwich University, US. Views expressed are personal.
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