Below is a reflection by Michael Meaney, who is currently studying at The University of Cambridge as a Gates Cambridge Scholar. Here, Michael shares a few of his thoughts on conducting research and searching for truth during his time at Cambridge.
Academic research is fundamentally about the pursuit of truth. And though it may silly or obvious to affirm this, the truth matters. In an age of fake news, scientific illiteracy, and our self-designed reality cocoons of social media, a firm commitment to the truth and the process by which to discover is of the utmost importance.
It was my time as a John Carroll Fellow at Georgetown University that planted the seeds of my own commitment to pursuing the truth. Participating in undergraduate research with Fr. Matt Carnes and as a Raines Fellow exposed me to the contested nature of truth in academic disciplines. “Established truth,” at least in the social sciences, is never really established. Assumptions,
access to data, and methods design are the essential components of deriving conclusions. These components change over time and are inherently political, meaning we need to interrogate and probe any truth dujour.
The extraordinary opportunity to pursue research at the University of Cambridge as a Gates Cambridge Scholar has brought the contingency of truth into sharper relief. In my own field of education, where the paradigm wars still rage, the seeming incompatibility of quantitative and qualitative methods belies a more problematic reality: what “works” on average for the group may not be sufficient for an individual, or perhaps many individual students. Educators are thus faced with a choice: should I focus my concerns on accomplishing the greatest amount of good for the average student? Or, should I concern myself with exploring with great care and detail the individual experience of a single learner, who, in and of themselves – because each student’s life is equally worthy and valuable – deserves tremendous attention and focus on their needs?
Educators concerned with what works on average might focus on the total achievement increase for a certain class observed after a certain pedagogical intervention; for example, a science experiment where students are assigned to work in groups. If the post-intervention class assessment score increased, on average, by ten percent, an educator might conclude that the intervention was successful. This kind of analysis might neglect, however, the minimal improvement demonstrated by a single student, whom we’ll call Jenny. Jenny might have increased her score by only one percent, or perhaps not at all.
The intervention for her was not successful. Group work typically requires some degree of extroversion. Jenny, a bit shy, might have found the activity anxiety-inducing and distracting, and was thus unable to gain much from the exercise. If the ten percent improvement research results were published, schools across a particular country might be inclined to try this new intervention that “works,” while at the same time, students like Jenny across that country would be disadvantaged because of it.
On the other hand, educators concerned with the individual student experience might focus on Jenny at the expense of the average student, for whom the intervention was successful. With a more critical perspective, an educator might assess the intervention as being biased toward extroverts, a character trait suited to those fluent in a culture’s native language and who identify with a racially dominant group. In this light, the intervention, rather than marking an improvement in overall pedagogy for students, might instead represent a tool for social and cultural reproduction of privilege, at the expense of Jenny and other students.
What is perhaps most difficult about this thought experiment is that both circumstances could accurately reflect reality: a singular, empirically valid reality that holds within it contradictory and incompatible truths, reflective of differing individual experiences. The choice of whose experiences to focus on is central to my own research. I am interested in Massive Open Online Courses, or MOOCs, and their implications for educational equity. When MOOCs began making international headlines in 2012, the group intended to benefit the most were traditionally underrepresented learners on university campuses, in the United States and around the world. I seek determine whether and how MOOCs have achieved their stated goal of “democratizing” higher education for traditionally underrepresented learners. Where my research departs from existing literature is that the population of learners I am interested in are those specifically not well-represented in existing research.
To date, learning analytics of massive data sets from MOOCs have focused on behavior patterns of average MOOC users and/or completers. The group is composed disproportionately of white, well-educated, employed men. I am interested in applying learning analytics to massive data sets of user behavior for traditionally underrepresented learners. While these datasets will not be as large as those used in studies that focus on broader segments of MOOC users, the sample sizes and data will be large enough to draw meaningful and significant conclusions. As I delve into these complicated matters, I know I am not alone. My colleagues in the education faculty similarly grapple with near-impossible to solve questions. My fellow Gates Cambridge peers do the same across fields ranging from political theory in film to infectious disease modeling to particle physics. Some fields are more exact than others, but all are contested, unsettled, and evolving.
There are no absolutely right answers, just difficult dimensions and terrain to navigate. It is both maddening and humbling. Each hard-earned citation is a literal footnote, a mere fragment of insight toward some far-off conclusion. But this also underscores the beautiful realization of one’s own limited impact as an individual; that we are part of a larger story of people working to do good in the world, seekers of truth spanning back generations, trying to make incremental progress. As individuals, we are only capable of so much, but as community we can – and must – make meaningful progress toward the further uncovering truth.