What Underachieving Middle School Students Believe Motivates them to Learn

Chapter 1: The Challenge to Educate Everyone Chapter 2: A Review of Literature Chapter 3: Methods Chapter 4: The Results      Transferability      Transcript Quotes      Participants      What Motivates? Chapter 5: Discussion References Appendixes Biography

A Note About Transferability and Generalizability There are two key questions that often interest users of research when they review a study: "Are the data reliable and valid?" and "Are the results generalizable?" The first questions the trustworthiness and credibility of the data. The second ascertains if the conclusions of an educational study pertain to other students. Reliability, validity, and generalizability are central assumptions of quantitative research. Reliability and validity are guaranteed by proven statistical analyses of the data collection tools and the data themselves, as well as a strict adherence to the experimental model. Generalizability is guaranteed by the use of random sampling of participants and random assignment to treatment or control groups. Qualitative studies often raise questions of transferability and generalizability of results. In this study, for example, the sample is small, numbering far fewer than the minimum of 30 desired in experimental samples or the 100 minimum for descriptive studies (Fraenkel & Wallen, 1996), and participants were not selected randomly. The sample is also narrow: it selects middle school students over those in elementary or high school, and students from rural, central New England, rather from other possible demographic regions. Further, the use of case studies, interviews, and observations are subjective data collection and analysis methods falling far from the experimental model. On what basis can the results of this study be transferred or generalized? One response is to explore relativism and the tenuous relationship between individuals and the population as a whole. How much do individual stories tell us about people in general? To what degree are the individuality of their stories a distraction from identifying generalities of the human condition? Are generalizations a distraction from finding complexities in human nature? To what degree are the individuality of their stories doorways into significant properties and principles? Are these stories descriptions of random events or are they windows to other patterns? Generalizability is a tenuous condition, but case studies are more than interesting stories in isolation. They help build a richer theory by raising nuances and illuminating ways the theory needs to be expanded. Another more powerful response is to explore the variety of sources that contribute legitimate transferability and generalizability to the conclusions of qualitative studies. One of those sources is complexity theory (formerly referred to as chaos theory). Complexity theory describes how there is order within complex (and often seemingly chaotic and random) systems (Gleick, 1987). Complexity theory searches for the underlying patterns hidden within "random" or "unpredictable" events. LeCompte (1993) argues that two fields of complexity theory are important to the social sciences. The first is "stable, aperiodic order, which describes phenomena, like cycles of weather, which are locally unpredictable but globally stable" (p. 23). That is to say that we cannot predict what will happen on any one day in any one location, and that day’s weather will be unique from any previous day. However, weather operates within some tightly bounded and well-defined parameters, and each individual day, despite it’s unpredictability, tells us something about those patterns. Learning and motivation theory may fall within this category since, although we may not be able to predict what exactly will motivate any particular student at any particular moment, clear patterns emerge when the ongoing phenomena are studied. The second area of complexity theory is fractal order. Best known for it’s snow-flake-type images and Mandelbrot art, these complex shapes are created by repetitions of simple designs. The simple mathematical rules on which they are based are hidden within the complexity of their forms. Case studies, such as this one, provide an opportunity to search for those underlying patterns by changing the researcher’s perspective from breadth to depth (LeCompte, 1993). Perhaps even more basic than exploring complexity theory is understanding the role of case studies in theory-building studies. Theories grow from the patterns we see between various cases, so at one level, the case studies of theory-building studies are presented to the reader, not as the theory, but as another case to be compared to the reader’s own wealth of personal experience. The reader is to decide whether the results from each case (as well as my conclusions in the next chapter) match their own interpretations and personal theories. In the end, it is up to the reader to judge the generalizability of this study. The author can help the reader, however, by providing a thick narrative of the data collected (Janesick, 1994; Lincoln & Guba, 1986; Glesne & Peshkin, 1992; and Bogdan & Biklen, 1998). That data was collected from multiple methods: informal conversations with students and teachers, student and teacher interviews, classroom observations, and a state-wide survey. The data from those sources were blended into the rich description of the schools, teachers, and participants presented in the next section. The data from multiple sources were categorized into seven motivational topics, and the final section in this chapter presents what was learned about each category. Within each topic, the thick narrative comes from sharing the participants’ ideas and words, and examples from the interview transcripts and observation field notes, and statistics from the Aspirations data. These multiple sources either confirmed findings or revealed differences of perspective, adding to the strength of the study.

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Mike Muir Assistant Professor of Education University of Maine at Farmington 104 Main Street Farmington, ME 04938 207.778.7179 wilder@somtel.com http://violet.umf.maine.edu/~mmuir