As the social psychologist Kurt Lewin once said, "there is nothing so practical as a good theory."

The connections, or in some cases the "disconnects," between theory, research, and practice have been written about for many years, and will be a topic of exploration in this course. But before we get too far along, it is important to recognize some of what makes the study of research at the doctoral level so uniquely challenging.

Doctoral students in every field often find the research courses in their program to be the most difficult for two reasons. First, much of what you will be learning represents new knowledge and learning. Whereas most students are fairly familiar with the theories, models, and literature in their chosen field, for instance organizational theory, encountered in their undergraduate or master's courses, the terminology and language of research as it must be explored at the doctoral level is much less familiar.

The other reason has less to do with familiarity, and more to do with the fact that some of the concepts you will be expected to learn are fairly complex, or at the least build upon more foundational understanding of relatively basic-but still new-concepts. In addition, the world of social and behavioral science research is not always looked at in terms of simple black and white distinctions or definitions. In fact, it is the shades of color and meaning to which the PhD scholar-practitioner is often most attuned, as this is where the frontier of new knowledge often lies. Note, however, that there will be times when it is helpful to portray things as having clear boundaries, while at other times we will present alternative ways of looking at the same general concepts.

This is a bit like the various ways of viewing light. In some experiments, the only way to explain the behavior of light is to characterize it as a "wave-like" entity. At other times, it is more helpful to consider light as particles. From yet another perspective, light is viewed as nothing more than energy bundled in to different packets, or quanta, which vibrate at different frequencies.

Here's an example about how research can be viewed in different ways, and here we offer some of the first terms you should capture, read up on, and provide some definitions for in your study notes for this course.

One way that some have classified research is to distinguish between basic and applied research. In this classification scheme, basic research refers to studies aimed primarily at developing or testing theory. In contrast, applied research, in this classification scheme, refers to studies whose purpose is aimed primarily at informing practice and that have an applied focus. Recently, many scholars have tended to avoid these terms in some cases because they believe it tends to perpetuate the notion of a theory-practice gap, while others would prefer to side-step what in some fields has been a bias towards basic theoretically-oriented research.

Consider the basic-applied perspective as the wave-theory of light. Now, consider another perspective, call it the "particle researcher's" viewpoint. From this perspective research is seen as exploratory or explanatory. Exploratory research is that which attempts to explore or describe some phenomenon, and often attempts to answer questions about what, where, or when. Explanatory research, which often follows initial exploratory studies on newly discovered phenomena, seeks to explain or even predict certain phenomena, and is driven by questions about how, why, and so what.

Now, neither the basic-applied nor exploratory-explanatory are necessarily better ways to view research, as each offers some unique and valuable ways of thinking about and discussing research, while also having some limitations. For instance, some research is intended to inform both theory and practice, and thus the basic-applied distinction is not helpful as a way to label or identify such studies.

How does this all come together in the context of research in organization and management? Much like Lewin, we believe that good theory can be helpful to practicing managers and leaders, as it can serve to inform the kinds of data and metrics to be used in making decisions. The call for evidence-based management by a recent president of the Academy of Management (Rousseau, 2006) builds on the call for "data-based decision making" made by Deming and others in the 1980s, and those with advanced training in research and data analysis-the PhD scholar-practitioner-have the potential to provide leadership in building connections between theory and practice.