The approach used by CIDR staff in assisting faculty and TAs can be considered a research perspective because the stages of the process are similar to traditional research approaches (Figure 1).

When faculty and TAs request CIDR services, those services -- whether they are about a course, TA supervision, departmental workshops, or assessment -- begin with a consultation in which the CIDR consultant works closely with the faculty member or TA to determine needs and then gather appropriate data to assist in decision-making and design of a plan of action. Thus, the services provided are data-driven rather than prescriptive, and the consultant's role, regardless of the kind of service requested, is to gather the appropriate data to understand the context and relevant issues, make sense of that information, and help the faculty member or TA decide how to use that information to enhance instruction. The following information explains the evolution of the stages of the consultation as a research process at CIDR and identifies some of the advantages of such an approach.

In our earliest consulting attempts with faculty at the University of Washington, we realized through trial and error experimentation that our most successful consultations emerged when we:

• collected baseline data for instructors to be used for diagnosis and problem identification (a data collection step); assisted instructors in analyzing the data (a data analysis step);
• provided suggestions or recommendations based on the analysis of data from a specific course within a particular discipline (a data interpretation step); and
• outlined with the instructor specific implementation strategies for modifying instructor behavior, classroom procedures, or course documentation (a data translation step).

Over and over, we were struck with the similarity between the phases involved in faculty consultations in which the client seemed most pleased and the steps required by the various research studies with which we were concurrently involved. Those steps, 1) identification of the research question, 2) collection of data, 3) analysis of data, 4) interpretation of data, and 5) development of implications based on findings or recommendations for further studies (Kerlinger, 1986), provide the underlying structure. Our modification, for consultation purposes, re-labels the steps as: 1) identification of problem, issue or question; 2) collection of data; 3) analysis of data; 4) interpretation of data; and 5) translation of data. The model as displayed requires movement through the five basic phases with possible return to any step as the process proceeds and reveals significant findings and/or insights into what is occurring.

Identification of Question/Problem/Issue

As with any research process, our first step is to identify the appropriate question. Typically, the questions emerge in the initial interview between the consultant and the instructor. Questions, problems, or issues may range from concerns about a set of student ratings to concerns about how to restructure an entire course, or how to introduce writing or small group activities to how to adopt a new way of evaluating student performance. By the end of the initial interview, however, the consultant and the faculty member will have clearly in mind what kinds of questions the faculty member is trying to address.

Collection of Data

We then begin collecting data about a particular course and the instructor's interaction with students about that course material. We sometimes use quantitative research methods-class surveys, student ratings data, and experimental designs--any method that will enable us to see what is going on with a particular group of students inside and outside the specific classroom setting. In many cases, we use qualitative research methods including field observations, videotaping, student and faculty interviews, content analysis of class documents, and collection of critical incidents, always attempting to triangulate our data by using multiple types of data, sources, times of the term, methods, or researchers. At a minimum we collect student perception data, professor perception data, course documentation data, and, when available, student achievement data. In addition, we may add peer evaluation data, video critique data, classroom observation data, student achievement on standardized tests data, etc. The challenge is to collect sufficient information to provide insights into what is occurring in a particular instructional context.

Analysis of Data

The next step, as in all research, is to analyze the information that has been collected. We use a repertoire of standard analyses from computing simple correlations to developing qualitative matrices of the data. We conduct statistical analyses or, more often, juxtapose descriptive information, looking for themes, patterns, consistencies, inconsistencies, and discrepancies in the data. We attempt to confirm the accuracy, completeness, and significance of the data. The data are analyzed until we are confident that we have as clear a picture as possible of what is happening in a particular course.

Interpretation of Data

Next, we attempt to help the classroom instructor make sense of the analysis of the data. Using instructional theory, research on teaching, and our own experience working with students on this campus, we try to assist in the systematic, accurate attachment of meaning to the findings. Instructors who are often not involved in looking at educational research are typically quite responsive to and appreciative of our attempts to assist them in interpreting the data to determine what is going on in their classrooms. Always, we point out that the data belong to the instructors. What instructors decide to do as a result of studying the data is their decision to make. The question we are interested in pursuing after discussing possible meaning remains, "After viewing/seeing the data collected in your classroom, what are your concerns?" The identification of the primary concerns provides the initial direction for possible changes.

Translation of Data

The last phase of our framework is designed to assist instructors in translating their concerns into goals and strategies for change. Possible targeted changes may occur in terms of changes in curriculum, course structure, or instructional methods. Analysis of student perception data, for example, might highlight how students believe that they learn best in a particular course and could suggest changes to enhance learning possibilities. Analyses of peer observation information or document reviews give us insights into what other experts feel should be taught in a given course. We work as a confederate with the instructor to translate the analysis of data into targeted changes which show promise for enabling students to achieve the instructor's goals for the course. Following the implementation of change, we might go back into a classroom, for instance, to collect new data and begin the cycle once more.

The familiar traditional research steps, then, form the basis of our consulting model. Using this model, we can accommodate complexities of particular course content, level of students, expectations for student achievement, instructor presentation style, classroom methods, or instructional materials.

Advantages of a Research Approach to Consulting

So why assume a research perspective when assisting faculty and TAs with their teaching? In retrospect, the need and desirability for this kind of approach seem fairly obvious. Using an application of the traditional research process enables the instructional consultant to use a process familiar to professors to assist them to make significant instructional modifications in their classes without requiring new ways of thinking. Thus, the approach is both systematic and complete and also familiar and appealing to the client--the individual professor or graduate teaching assistant.

In addition, this perspective defines the role of the instructional developer or consultant in relation to the classroom instructor--the client. We see ourselves as classroom researchers gathering information that will be useful for the instructor to inform his or her decision-making. The classroom becomes a place where we gather data, where we research what goes on between students and instructors. This research perspective limits and describes our involvement. We are, then, data collectors and analyzers, not classroom evaluators and not counselors. We are responsible to our client, the individual classroom instructor. Thus, this research perspective guides our relationships with instructors.

This research perspective also precludes our feeling that we must have answers. We become, instead, investigators in a partnership relationship with a particular instructor, attempting to find the answers to an individual's instructional questions. The approach eliminates the possibility of applying standardized, generic, predetermined suggestions or recommendations for unique, often idiosyncratic, contextual and discipline-specific teaching difficulties. This perspective also keeps us from moving directly from problems to solutions without a careful analysis of the complexities of the particular instructional situation.

Finally, the research perspective enables us to have great confidence in the data we use as the basis for collaborating with the instructor to develop strategies for change. Using established quantitative and qualitative research approaches, we check the accuracy and validity of the findings. These data, rather than personal, or even expert, opinion, dictate what is done to assist the instructor.

References

Kerlinger, F. N. (1986). Foundations of behavioral research (3rd ed.). New York: Holt, Rinehart and Winston.

Note: This explanation of CIDR's research approach to consultation is an adaptation from Nyquist, J. D., & Wulff, D. H. (2001), Consultation using a research perspective. In K. G. Lewis & J. Povlacs Lunde (Eds.), Face to face: A sourcebook of individual consultation techniques for faculty/instructional developers (2nd ed., pp. 45-62). Stillwater, OK: New Forums Press.