Selecting a Quantitative or Qualitative Research Methodology: An Experience
Why this work is in the frame
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Bibliographic record
Abstract
Olusegun A. Sogunro, Central Connecticut State University The selection of appropriate research method has always been a dilemma for many researchers and evaluators. While quantitative-- qualitative research debate ravages, what is obvious is that there is no one best research method for all research and evaluations. Different research purposes require use of different research methods, separately or in concert with each other. For all practical purposes, both quantitative and qualitative methods have different, but complementary roles to play in a research process and outcome. This paper explains experience of author in using a mixture of two research approaches to evaluate a leadership training program. The fray between champions of these two distinguishable research approaches is essentially ideological and political. Basically, two approaches differ in their ways of conducting research, and each tends to claim superiority over other. Ironically, each tradition overtly discredits other as if it is infallible. The stage is always charged so that, given chance, these champions would fight at any to defend their research philosophies. Fueling this charged situation is subconscious luring of graduate students into these dichotomous camps of research methodologies and paradigms, especially from standpoint of research orientations of professors - instructing or advising. This paper presents my experience as a researcher, using both quantitative and qualitative research methods. Definitions Creswell (1994) defined a quantitative research as an inquiry into a social or human problem, based on testing a theory composed of variables, measured with numbers, and analyzed with statistical procedures, in order to determine whether predictive generalizations of theory hold true and a qualitative research as an inquiry process of understanding a social or human problem, based on building a complex, holistic picture, formed with words, reporting detailed views of informants, and conducted in a natural setting (pp. 1-2). In a very simplistic form, Punch (1998) defined quantitative research as empirical research where data are in form of and qualitative research as empirical research where data are not in form of (p. 4). Gay and Airasian (2000) defined quantitative research as the collection of numerical data in order to explain, predict and/or control phenomena of and qualitative research as the collection of extensive data on many variables over extended period of time, in a naturalistic setting, in order to gain insights not possible using other types of research (p. 627). While both research approaches are equally recognized and used in conducting research, major differences between them are in areas of data collection and analyses. According to Gall, Gall & Borg (1999), quantitative research heavily on numerical data and statistical analysis. In contrast, qualitative research make little use of numbers or statistics but instead rely heavily on verbal data and subjective analysis (p. 13). My Experience in Using a Mixture of Quantitative and Qualitative Research Approaches In course of undertaking evaluation study toward my dissertation, it became apparent that suggestions given to me by my advisors were largely based on their professional preparations, interest or orientations. For instance, one professor suggested use of questionnaire for data collection while other suggested that use of interviews alone would suffice. However, based on my curiosity to explore two research approaches, I adopted mixed methodology approach. Between January 1994 and December 1995, I conducted evaluation study of impact of a leadership training program on participants. The program was organized by Rural Education Development Association (REDA) of Alberta, Canada. …
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.069 | 0.064 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.009 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it