Online master degree in library science

INTRODUCTION

Many schools of library and information science (LIS) are faced with an acute problem. Both quantitative and qualitative research paradigms are represented in the LIS literature, yet only a single research methods course is offered at the master's level. This being so, the problem invites a number of questions: What ought such a course include? Should instructors, opting for breadth, attempt to teach both qualitative and quantitative methods? Alternatively, might it be desirable to opt for one or the other and achieve a greater degree of depth? How should such a course be taught? These questions are certainly important. The answers hinge on the answer to yet another question--can LIS programs afford to graduate information professionals who are literate in one methodological paradigm only?

Evaluating the research output in an appropriate domain is an essential component of professionalism. That is the case for all professions. In LIS, a profession that has adopted a user-centered approach to service provision, services and systems must constantly be reviewed in light of the most current research findings. Only by doing so can LIS practitioners express confidence that their services and systems are the best they can offer. When viewed in this way, it becomes obvious that the toolkit of the competent information professional must include an understanding of the methods of both paradigms. Without this understanding, master's level graduates will be inadequately prepared to do research or to be critical consumers of the research of others.

To acquire this element of the toolkit requires not only a theoretical grounding in methods but also a practical element--LIS students must experience research. The value of experiential learning is well documented in the education literature. Schall (1996) points out that professionals often deal with complex issues and argues for the inclusion of experiential learning in graduate and professional curricula. Schall believes that, through hands-on experience in dealing with such issues during course work, today's student will be able to address these issues in future professional practice. Research too is complex, and students cannot learn to do or to evaluate research from the literature alone. Practical hands-on experience in doing research is an essential ingredient of the learning process. Consequently, an LIS research methods course must embrace a substantial practical element that takes students through the process of design, data collection, data analysis, and reporting.

THE TWO PARADIGMS

As pointed out by Orlikowsky and Baroudi (1991), a quantitative research methodology is appropriate where quantifiable measures of variables of interest are possible, where hypotheses can be formulated and tested, and inferences drawn from samples to populations. Qualitative methods, on the other hand, are appropriate when the phenomena under study are complex, are social in nature, and do not lend themselves to quantification. Typically, qualitative methods are used when understanding the cultural context from which people derive meaning is an important element of a study. Such cultural context is usually not susceptible to quantification and aggregation and is, therefore, usually ignored in quantitative studies. Yet failure to understand cultural context may deprive the researcher of a real understanding of the problem at hand (Kaplan & Maxwell, 1994).

In LIS, researchers grapple with problems of both sorts--they study information systems as well as the interactions of people with those systems. In other words, they are concerned with both functionality and usability. The cultural context is vital for determining usability and, to some extent, for functionality. Researchers are beginning to recognize that resorting to a single methodological paradigm in LIS research does not provide the understanding needed to design and maintain effective services. It follows, therefore, that courses based on a single methodological paradigm are inadequate preparation for the information professional.

QUANTITATIVE METHODS

Because quantitative methods are well defined and easy to validate, it has not been a difficult problem, historically, to fit these methods into a single semester course. In quantitative research, observations are reported in aggregate quantitative form. Formal hypotheses are posed that are tested and either accepted or rejected. To conduct quantitative research implies the need for very precise identification and definition of variables and the ability to operationalize them in such a way that numbers can be attributed to them--e.g., age, GRE, opinions on satisfaction, liking, and so on. Admittedly, this is often difficult because many variables may be relevant. Fidel and Soergel (1983) identified more than 200 variables that affect just the online bibliographic search process. However, if the variables of interest have been identified and operationalized and a data gathering scheme has been devised, the researcher can design the study and rely on well established and accepted criteria for judging its validity. In other words, much can be said about the validity, reliability, and generalizability of the study from the design alone.

While identifying and operationalizing variables in complex research problems is difficult, once it has been done, the process of data gathering and analysis is well defined and relatively straightforward. Furthermore, unless the study is longitudinal, data collection is generally also relatively fast-i.e., once the study design is determined, the gathering and analysis of data proceed rapidly. In addition, although data for quantitative studies can be gathered in the field, more often data are gathered in-house (through laboratory experiments) or through survey instruments of various types. In any case, from a pedagogical standpoint, data for a variety of quantitative studies can be gathered "from within the classroom" so to speak.

Given the nature of quantitative research, it is entirely possible to teach a quantitative methods course with dummy data only. Although students invariably question the limited relevance of dummy data in the learning process, many courses are, nevertheless, taught in exactly this way. Of course, this approach lends itself rather well to the time constraints imposed by the academic semester. Pedagogically, the quantitative approach is also well suited to simple examples that can be tackled in a short time. "Dummy" studies (using small data sets and a limited set of variables) can be "conducted" and the results analyzed in class. Thus, students can be given considerable practice over the course of a semester in testing a variety of hypotheses.

QUALITATIVE METHODS

Qualitative research, on the other hand, is highly time consuming. The very language of qualitative research suggests an exhaustive process--prolonged engagement, intensive observation, thick description (Lincoln & Guba, 1985). Good design is, of course, a requisite for any type of study. However, it is fair to say that qualitative studies lack the same clear cut and objective standards for design as quantitative studies--i.e., the qualitative design emerges as the study unfolds. Indeed, Creswell (1994) points out that there is little agreement among researchers in terms of a set of precise procedures for data collection, analysis, and reporting of qualitative studies. Consequently, the evaluation of a qualitative study cannot be realized in the absence of data collection and analysis (since analysis proceeds hand in hand with observation). The quantitative researcher can be confident that the standards of rigor for design and analysis have been met before data collection commences. The qualitative researcher cannot do the same. As Lincoln and Guba (1985) point out, the pillars of qualitative research--credibility, transferability, dependability, and confirmability--cannot be demonstrated in the absence of data. Of course, this does not mean that the design process for a qualitative study is unimportant. Before collecting and analyzing data, the qualitative researcher must, according to Berg (1998), "sketch out the entire research project in an effort to foresee any possible glitches that might arise" (p. 27). But unlike a quantitative study, an evaluation of the design without data is much more difficult.