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Record W2479287046

When Conducting Research Using TL, Who Decides If Experiences Have Been Transformative - The Researcher or the Research Participant?

2016· article· en· W2479287046 on OpenAlexaffabout
C. L. Cook

Bibliographic record

VenueJournal of Transformative Learning · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicAdult and Continuing Education Topics
Canadian institutionsMount Royal University
Fundersnot available
KeywordsTransformative learningPsychologyLeadership developmentSociologyQualitative researchPedagogyPublic relationsSocial sciencePolitical science
DOInot available

Abstract

fetched live from OpenAlex

Many Canadian organizations have adopted job rotation as a leadership development intervention to ameliorate current and anticipated talent shortages in their leadership ranks (Cook in press).   Corporately structured rotational leadership development programs (RLDPs) provide high potential employees with opportunities for development through a series of planned rotational job assignments, often across diverse business units.  My recent phenomenological investigation attempted to address a gap identified by the absence of in-depth qualitative research concerning the perspectives and experiences of RLDP participants in Canada. Understanding the participants’ perspectives and experiences as they are hired to, move through, and complete an RLDP has provided a more holistic perspective of organizational programming for the purposes of developing leadership capacity through job rotation.  Applying a socio-constructivist worldview and employing the transcendental phenomenological research tradition, I sought to understand the lived experiences of nine RLDP participants at one diversified Canadian firm (Cook in press ).  Mezirow’s Transformative Learning Theory, one of the most frequently referenced, researched, and critiqued theories of adult learning, underpinned the theoretical framework for the study.  What emerged as an unanticipated research challenge was the distance between my own perspective and the research participants’ perspectives of when transformative learning may have occurred.  In my challenge to honor both the research participants’ perspectives, and also the phenomenological research tradition, an additional research question arose for me – when conducting research using transformative learning, who decides if experiences have been transformative – the researcher or the research participants?  Since arriving to the conversation of adult learning almost 40 years ago (Mezirow, 1978), transformative learning has exploded as a theory to understand adult development, and it was felt for this research that it could consequently have utility to understand leadership development.  Particularly for emerging leaders, finding their ways in their own professional and leader identities is fundamentally a learning process, and may be a transformative one for many.  Brown and Posner state the best future leaders will be those who are the best learners and are able to learn from the workplace and also from their own experiences in it (2001).  Deep learning comes from a learner’s ability to reflect and intentionally accept or reject new knowledge, to think critically about the validity of new information, and to make conscious choices and create competence for one’s own role, decisions, and relationships (Mezirow, 1991, pp. 6–7).  During the interviews with each research participant, there seemed varying degrees of willingness to decree their experiences as transformative and the challenge persisted through the data analysis phase of the study.  There seem sufficient critics and critiques of Mezirow’s work to make allowance for this research challenge, including that transformative learning theory focuses too much on the individual and thus fails to address social dynamics (Tennant, 1993, p. 35) or that what may manifest as perspective transformation may just be standard, even expected, development or maturation (Tennant, 1993).  Ultimately, I concluded (with some obviousness), that the research participant ultimately makes this decision – though the inquiry served as a powerful reminder for me to honor the method and methodology established for the research, as well as well as the conceptual and theoretical frameworks, regardless of some of the challenges they may have imposed.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.033
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0330.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.003
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.587
GPT teacher head0.543
Teacher spread0.044 · 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; both teacher heads agree on what is shown here.

Study designQualitative
Domainnot available
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

Citations0
Published2016
Admission routes2
Has abstractyes

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