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Record W2972799976 · doi:10.28945/4254

International Curriculum and Conceptual Approaches to Doctoral Programs in Leadership Studies

2019· article· en· W2972799976 on OpenAlexaboutno aff
Petros G. Malakyan

Bibliographic record

VenueInternational journal of doctoral studies · 2019
Typearticle
Languageen
FieldHealth Professions
TopicDoctoral Education Challenges and Solutions
Canadian institutionsnot available
Fundersnot available
KeywordsCourseworkEducational leadershipContext (archaeology)Leadership studiesCurriculumExperiential learningTeacher leadershipLeadership stylePedagogyEngineering ethicsSociologyPolitical sciencePublic relationsEngineering

Abstract

fetched live from OpenAlex

Aim/Purpose: This study explores the various teaching and learning approaches, curriculum design, and program requirements for 70 doctoral programs in leadership. Background: Early research indicates that few studies have addressed learner-centred and process-based approaches to leadership studies among doctoral programs in leadership worldwide. This study is the first complete review of programs in the interdisciplinary field of leadership. Methodology: A qualitative method approach through internet-mediated research was employed to identify explicit and implicit textual data on learning approaches of doctoral programs in leadership. The sample represents a list of 70 doctoral programs in leadership studies and organisational leadership (62 programs are in the United States and eight in Europe, Canada, Philippines, and South Africa). Contribution: This study provides an overview of doctoral program characteristics, delivery methods, coursework and research requirements, discipline-relevant teaching and learning approaches, and process-based approach to leadership. It may serve as a resource and a roadmap to assess teaching and learning approaches of doctoral programs in leadership for program reviews and improvement. Findings: The significant findings of this study are: (a) 91.4% of doctoral programs are coursework-driven, leaving little room for original research. (b) 46% of programs show lack of evidence to context-based approaches to learning (learning as a social activity served outside of classroom environment where learning tools and the context intersect with human interactions). (c) Various teaching and learning approaches, including those prescribed to constructivist, interactionist, situated, and action-based learning approaches. Recommendations for Practitioners: Leadership cannot be understood or learned without social interactions in context. In order to produce experts and “stewards of the field,” a clearer learner-centred strategy to doctoral education, including context-based experiences, should be considered. This pedagogical approach needs to be explicitly articulated (on the public website) to enable students to make an informed decision about doctoral programs in leadership. Recommendation for Researchers: In order to produce theoreticians and “stewards of the discipline” (Golde & Walker, 2006), doctoral curricula design and implementation should seek a balance between coursework, independent research, and creation of collaborative learning environment between students and faculty. Further, due to the shift from the leader-centred to the process-based understanding of leadership, doctoral programs in leadership should consider the relationship process between leaders and followers as one academic inquiry or continuum. Impact on Society: Doctoral programs in leadership that utilise more learner-centred and context-based approaches for knowledge acquisition (epistemologies) as well as studying the leadership phenomenon as a relationship process are more likely to become more impactful and sustainable in society. Future Research: More research seems necessary to identify the extent to which learner-centred approaches within doctoral programs in leadership positively impact on doctoral students’ motivation for learning, program completion, retention, and personal and professional development.

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)0.013
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0030.004
Scholarly communication0.0050.003
Open science0.0010.008
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0130.002

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 head0.818
GPT teacher head0.561
Teacher spread0.257 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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".

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Citations8
Published2019
Admission routes1
Has abstractyes

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