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Record W2921833778 · doi:10.5539/ies.v12n4p1

The Importance of Leadership Education in University: Self-Leadership Example

2019· article· en· W2921833778 on OpenAlexvenueno aff
Elif Bozyiğit

Bibliographic record

VenueInternational Education Studies · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicEducation Practices and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyTurkishCronbach's alphaLeadership styleEducational leadershipLeadershipSocial psychologyScale (ratio)Mathematics educationPedagogyPsychometricsDevelopmental psychology

Abstract

fetched live from OpenAlex

Self-leadership is a form of leadership that has emerged in the last quarter of a century. The purpose of this study is to determine whether there is a difference in self-leadership strategies between students who choose leadership course and do not choose. The sample of this research consisted of 144 sports management students in 2018; 35 female (24.3%) and 109 male (75.7%). The average age of students is 22.38 (sd=2.88). While 30 students (20.8%) stated that they chose leadership course, 114 students (79.2%) stated that they did not choose leadership course. In this study, the Turkish version of Abbreviated Self-Leadership Questionnaire (ASLQ) was used as a data collection tool, but original ASLQ was developed by Houghton et al. (2012). The Turkish version of the scale was adopted by Şahin (2015). As a result of the reliability analysis, the Cronbach’s alpha value was found to be .74. There was a significant difference between ASLQ total scores of students who choose the leadership course and do not choose (yes/no). There was a significant difference between students who choose the leadership course and do not choose (yes/no) and the subscale scores; behavior awareness and volition, constructive cognition, and task motivation. According to the results obtained through the analysis, hypothesis 1 and 2 were accepted.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.736
Threshold uncertainty score0.555

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.263
GPT teacher head0.358
Teacher spread0.096 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations6
Published2019
Admission routes1
Has abstractyes

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