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Record W73724950

Selecting a Quantitative or Qualitative Research Methodology: An Experience

2002· article· en· W73724950 on OpenAlexaboutno aff
Olusegun Agboola Sogunro

Bibliographic record

VenueEducational research quarterly · 2002
Typearticle
Languageen
FieldDecision Sciences
TopicBusiness Strategies and Management Research
Canadian institutionsnot available
Fundersnot available
KeywordsDilemmaSubconsciousQualitative researchIdeologySociologyEpistemologyQuantitative researchEducational researchPoliticsPsychologyManagement scienceSocial sciencePolitical scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

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. …

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.165
metaresearch head score (Gemma)0.088
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.835
Threshold uncertainty score0.874

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1650.088
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0140.016
Scholarly communication0.0100.007
Open science0.0030.008
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.952
GPT teacher head0.749
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
DomainMethods
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations82
Published2002
Admission routes1
Has abstractyes

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