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Record W4225406374 · doi:10.5539/ies.v15n3p1

On Becoming an Effective Mentor in Adult Education—Investigating the Perceptions of Greek Adult Educators

2022· article· en· W4225406374 on OpenAlexvenueno aff
Marios Koutsoukos

Bibliographic record

VenueInternational Education Studies · 2022
Typearticle
Languageen
FieldPsychology
TopicMentoring and Academic Development
Canadian institutionsnot available
Fundersnot available
KeywordsLifelong learningPsychologyAdult educationTrainerAdult learnerContext (archaeology)PedagogyPerceptionAdult LearningConstructiveMedical educationAndragogyProcess (computing)Medicine

Abstract

fetched live from OpenAlex

Interest in mentoring, which is an innovative method in adult education (CEDEFOP, 2013), has been growing rapidly in Europe, especially since the Lisbon European Council in 2000. In Greece, this interest has found expression either through the development of educational material in the context of adult educator training programmes, or the investigation of the mentoring needs of adult learners (Koutsoukos, 2021). In spite of the obvious fact that the mentor plays a key role in ensuring that the mentoring process is constructive and successful, there has been little research to date on the attributes of an effective mentor in adult education. The present study, using multimethod research, examined the perceptions of 337 Greek adult educators as to what characteristics constitute an effective mentor, as well as the role and the selection criteria of a successful mentor. The findings indicated that the key qualities of an effective mentor were: having sufficient training in adult education and mentoring, teaching, communication and relational skills, as well as having a positive attitude to lifelong learning and a willingness to innovate. In addition, the role of an effective mentor was perceived by the study participants as being a trainer, a model teacher, as well as an equal partner.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.316
Threshold uncertainty score0.650

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.045
GPT teacher head0.425
Teacher spread0.380 · 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 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

Citations2
Published2022
Admission routes1
Has abstractyes

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