Scientific Inquiry was one of the pillars of the original Common Curriculum, both in terms of its curricular content and its goals. Yale-NUS faculty believed that learning how scientists ask and answer questions was an essential part of a broad, liberal arts education. This was reflected in the choice of reading material in the 2015 iteration of the course, which had three textbooks – two of which covered scientific topics (“Evolution: A Very Short Introduction”, and, “Cosmology: A Very Short Introduction”), while the third on the philosophy of science ("What is this thing called Science?”) anchored learning about the process of scientific discovery.
Along with Scientific Inquiry, the original Common Curriculum included the courses Integrated Science and Foundations of Science, which were separate tracks for subsets of the student body. As part of the first review of the Common Curriculum, Integrated Science and Foundations of Science were eliminated. Scientific Inquiry itself remained as a key part of the Common Curriculum. In fact, it was expanded to two courses, Scientific Inquiry 1 and Scientific Inquiry 2 (SI1 and SI2). At the same time, Quantitative Reasoning (QR), which had originally been taught in the second semester, was moved to the first, despite some resistance to the idea of having QR be ungraded, as all first semester Common Curriculum courses were. (Curiously enough, moving QR to the ungraded semester made the same content much more popular among the students body). The reasoning was that students, having been introduced to statistics, data analysis and visualization in their first semester, could then apply those skills to scientific problems in subsequent science classes. The resulting sequence of courses was thus QR→SI1→SI2. As with other Common Curriculum modules, SI1 students attended a large, group lecture once each week, during which faculty laid out the topics and themes for the week, and then students met for two 80-minute sessions, for a combination of activities and discussions.
As a consequence of the first review of the Common Curriculum, a Science Common Curriculum Task Force convened to make recommendations on the structure and content of the new science curriculum. The task force proposed that SI1 be built around the topic of biological evolution and SI2 around climate change. The argument for evolution as the theme for SI1 is that the topic is interesting from a history of science perspective, provides a scientific answer to the origin question asked by every culture (“where do we come from?”), and – unlike most other scientific subjects – can be easily understood regardless of the strength of a student’s scientific background. Subsequently, a group of faculty met to flesh out the scope of SI1, expanding it to include human genetic variation and evolutionary history, in addition to the story of how natural selection works and was discovered. The inclusion of human variation and evolution greatly broadened the appeal of SI1 because of the social, political, and policy implications of the science.
With the genomic revolution in biology, there were almost weekly headlines about discoveries related to human evolution. (In fact, the 2022 Nobel Prize in Physiology and Medicine went to Svante Pääbo for his work on ancient DNA and human evolution.) Many of these discoveries were jaw-dropping: introgression between ancient human lineages, natural selection on snippets of ancient genomes, differentiation among human populations. Some of these discoveries were challenging and easy to misinterpret. On top of genomic discoveries, commercial services that allowed regular folks to have their own ancestry assessed from their personal genome were becoming affordable, and were providing interesting revelations about who we are as individuals. That is, not only did modern genomics allow us to trace the ancestry of humans as a species, but we could trace our individual ancestry if we were willing to pay a few bucks. Therefore faculty thought a key goal of SI1 should be to give students enough background in genetics and genomics that they could appreciate some of these discoveries. The SI team took the view that this is not just a topic of scientific interest. Having a basic understanding of these genomic interpretations are necessary for responsible citizenship in the 21st century.
These goals naturally divided SI1 into four parts: (i) classical 19th Century evidence for biological evolution, (ii) a whirlwind introduction to molecular genetics, (iii) genomic and fossil evidence of human ancestry, and (iv) genomic evidence for natural selection on humans. The latter was in some ways the most interesting and most challenging because we talked explicitly about how natural selection changed humans – sometimes through cultural changes (e.g., the spread of a genetic tolerance to lactose that accompanied the development of dairy herding). Discussions in class included the consequences at the genomic level of populations separated by 100s of generations, resulting in ethnic differentiation due to ancestry. We also talked about the evolution of human behaviour, including human social behaviour, and the limitations of what we could know or interpret from the data.
Notice the goal of SI1 was not to shy away from controversy. Faculty were frank about topics like race and ancestry, and about the similarities and differences among ancestral lineages of humans. We wanted students to understand the limits of what we could conclude so students would be on the lookout for suspect claims. Disease in general, and COVID-19 in specific, played a major role in our discussions. Diseases evolve through natural selection, and they do not necessarily evolve the way a naïf might expect. We wanted students to apply what they learned about how diseases evolve to Singapore’s social distancing recommendations and lockdown during COVID-19. Would these recommendations have an effect on the virulence of COVID-19? (As it turns out, Singapore’s recommendations should have facilitated the spread of less virulent strains of COVID-19.) For one of the final assignments, students assessed how best to treat patients in Singapore with blood thinners, for which different human lineages have strongly different reactions. That is, different races respond to drugs differently. A dose that might be effective for a person of one ancestral lineage might be lethal to a person of another. We wanted students to address real risks that influence people in Singapore, using the critical and quantitative skills they had learned in QR and throughout the first semester of SI1.
Every week had a theme or topic. For each topic small groups of students tried to address how we can know something in science by working with physical or tactile models (e.g., cutting and mixing strips of construction paper to show how linkage blocks on chromosomes undergo exponential decay over generations due to recombination), then through computational models and simulations (simulating exponential decay by following simple rules of recombination with an Excel macro), and then by analysing their results in comparison to real, often genomic data (if our observed linkage blocks are a certain size, how many generations of recombination occurred since a selective sweep?). That is, we wanted students to understand – and in many cases come up with – the algorithms on which more complicated computational models and simulations relied. In about half the weeks we did some programming or statistical analysis, although not always with the R skills that students learned in QR. We felt it was more important that students get some results than copy-paste R code. We tried to stress that scientific inquiry often relied on comparisons: is treatment A different from treatment B? From the control? From what we expect? How do we generate our expectation? How much uncertainty is there around our expectations?
Among the more popular activities was one where students manually constructed a “genome” that programmed simple rules for an “animal” to forage on a field with barriers and food. The intelligent student-designed “genomes” competed against dumb genomes, but ones that were allowed to mutate, recombine, compete, and evolve through natural selection, in silico. In each iteration of SI1, the “dumbly” evolving genomes outperformed the intelligent student-designed genomes after a few generations, often by evolving patterns that looked like forethought – but weren’t. Our aim was to let students appreciate how, in not many generations, natural selection produced results more clever than theirs – at least in silico.
COVID-19 pulled the rug out from everything. In 2020 the facilitators of the Common Curriculum very rapidly went from discussing the possibility that we would have to change how we engaged with students, to hybrid in-person/online teaching, to 100% distance learning by the end of the semester. This rendered moot many of the exercises based on tactile and physical modelling. Although we could and did have intense class discussions, our ability to do group work suffered, especially group work that relied on physical models. The one-hour large lectures for SI1 became recorded events, and then the following year events that only some students could attend. The excitement and immediacy of the lecture, the spontaneity and back-and-forth between students and the instructor, the pop and sizzle of a live audience, disappeared as faculty spoke to empty seats in the Performance Hall and students watched from their laptops in their residence halls. Some might argue that COVID-19 and distance learning had larger effects than just on SI1. Because we can superficially mimic some of the one-on-one interactions of a small class through Zoom lectures, large universities saw that they could enrol hundreds – even thousands – of people in distantly taught classes. This may have influenced how people view the small liberal arts college model.
Not everything we tried worked. The instructional team was very excited about SI1 and we often packed too much into it – too much into the semester, but too much into individual classes as well. Students and faculty had strikingly varied backgrounds and that influenced both the delivery and reception of the content in SI1. For all that, what is striking now, years later, is how many students from the last cohorts to go through SI1 remember it fondly. Many students bump into their former instructors and comment, "That was a great class."
And it was.
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