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Learning Research by Doing Research

I’ve written in the past about the value of research experience to students (see Preparing Undergraduates for the 21st Century). The most persuasive argument is that the students we educate today will have to retrain themselves after they complete their education at Georgetown. This will happen when totally new knowledge domains emerge to change work environments. Original scholarship and research requires critical observation, measurement, and logical skills to yield credible conclusions. This is precisely what our graduates will need to do, maybe at several times in their lives.

In talking about this idea with faculty, it’s clear that most appreciate the argument. Each of us, however, is both informed and limited by the deep specialization required in our own original research. Many fields have developed their own set of methods for research, which define the state of the art within the discipline, respected by flagship journals and prestige publishers. So, the question begged, therefore, is what kind of research experiences are desirable for our students?

The ideal would be a mix of experiences, different methods asking different questions. From the humanities, deep critical observation, inspection, and deconstruction of text, objects, and images are central to knowledge acquisition. For the digital humanities, this might involve quantitative summaries of word combinations in multiple texts of the same author or multiple authors of the same “school.” For many of the arts, it involves the comparison of alternative interpretations of the same work.

The social sciences use deep observation in many fields, sometimes carefully examining physical movements, speech utterances, social interaction, seeking understanding of behaviors and social environments. Sometimes these observations are described in words, typologies, and verbal inferences of the meaning of the observations. Other times, the observations are structured and standardized, yielding quantitative data, subjected to statistical analyses. Case studies, ethnographies, and participant observation techniques are examples of this style of research. The unique attraction of these methods is the intense observational skills they require, they need to examine both context and object.

Randomized experiments are used in both the social and natural sciences. These are used both with inanimate objects in the physical sciences and people in the social sciences. The randomized experiment is de riguer in some subfields of psychology and increasingly important in microeconomics. Experiments involve careful design of the experimental conditions, construction of an intervention/stimulus, and careful measurement of the change in status after the intervention. These too are analyzed using some sort of quantitative analyses.

Large scale studies of human populations use self-report standardized measurement on large statistical samples of the populations. These are the basis of political polling, censuses, customer satisfaction surveys, and a host of other sources of information on the society. These are gradually being blended with massive data sources from internet and other process sensors. These require quantitative analyses.

Increasingly, intensive computational methods are being applied across fields. These are sometimes based on pre-specified quantitative models that describe key aspects of a phenomenon. The models are often complex, with the implications of alternative combinations of attributes or change over time too complicated to see without examining the implications directly using the models.
These methods require deep thinking about the interactions of multiple attributes in complex systems of phenomena.

Some fields, for example, mathematics and computer science, pursue the invention of more efficient algorithms to produce designated outcomes, involving careful decomposition of the procedures, the invention of a new approach to the problem, and the demonstration of the improved procedure in a variety of situations.

All of these methods have their own unique techniques and are useful in different circumstances. Ideally, Georgetown students have a chance to experience all of these. But the diverse approaches also have commonalities. They require intense inspection and observational skills. They require critically reviewing alternative interpretations of the observations as well as self-criticism and openness to the possibility that one is missing something. These skills can’t be easily learned without the doing of them.

The more our curriculum can mount courses that provide these skills to our students, the better prepared they will be for the future they face.

2 thoughts on “Learning Research by Doing Research

  1. Thanks, Bob, for posting this because it is one of the big issues in education right now. I am also glad that you articulate so eloquently the reasons for its prominence, i.e., that we need to enable our students to reinvent themselves and their way of thinking a couple (or more) times over the course of their lives. This means that we are talking about an issue primarily of education and pedagogy. Given this framework, I am not sure that the call for undergraduate “research” really hits the spot. A few years ago, the very same challenge to teaching was to enable students to “life-long learning.” Since I believe in the power of words, I think this phrasing is still the more appropriate way of thinking about this issue. (At this point, I should apologize for a rather longish post. But I didn’t have the time to write a shorter one.)
    For my area of expertise, the humanities, what gave me some pause in your post was the quantitative space you allotted to this area of inquiry. It was one very short sentence. Then you went on to expand on other areas, the digital humanities, the social sciences, and natural sciences, where, ostensibly, numbers are more important. I think this is because it is much easier to call an engagement of undergraduates in these areas “research” as the numerical and quantitative is (seemingly) more easily – well: quantifiable. But that does not make a researcher. After all, there is a reason why it takes people six or more years to become “researchers” in most fields (even the “hard” sciences). This is called earning a PhD. That doesn’t mean that undergraduate students cannot do scholarship in the sense developed in the famous Boyer Report of the early 1990’s. They can do wonders in these ways of rethinking issues. Engagement in “scholarship of discovery” (as Boyer had it) – “research” understood in a rigorous way – is usually limited to exceptional undergraduate students. Only in Lake Woebegone do all undergraduate students participate in and contribute to research.
    The central issue for life-long learning is not necessarily learning to do disciplinary research (or even interdisciplinary research, for that matter) but understanding how an area of inquiry approaches new issues and asks appropriate questions, and how that helps you, the learner, to address new situations. That needs to be done from the very beginning of students’ education, i.e., from those courses that used to be called “core courses.” That is exactly the opposite side from where most faculty members would locate “research” in their students, precisely because they identify “research” with their respective discipline and therefore with people acquainted (somewhat) with their methods and approached. Obviously, there is much to be said for that. But that is not what most students will do, even those who major in a particular discipline. So the challenge is what departments and their respective curricula will accomplish not in their majors but in those students who will take their courses as part of their general education at the university and how those courses will contribute to the students’ ability to be life-long learners and approach the intellectual/practical/methodological challenges as they emerge in their lives.
    I think that is the appropriate framework in which the issue of life-long learning/integration of research into the curriculum should be approached and should be discussed. There is much to be done and I think it is wonderful that you have opened this conversation.

    Thanks again for the post.

  2. And, refreshingly in this day and age in higher education, not a word about “jobs,” but a steady focus on developing skills to face a changing and unpredictable future. Naturally, such experience will aid anyone in their career. But jobs are not ends, only means. Paradoxically, those who focus on the ends of understanding and analysis, may be more likely to get far more satisfaction and more from their careers.

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