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Record W3089161958 · doi:10.5430/ijhe.v10n1p41

Mentoring Experience at University Level: EFL Mentees' Perceptions and Suggestions

2020· article· en· W3089161958 on OpenAlexvenueno aff
Tha’er Issa Tawalbeh

Bibliographic record

VenueInternational Journal of Higher Education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsnot available
Fundersnot available
KeywordsMentorshipLikert scalePsychologyMedical educationDescriptive statisticsPerceptionScale (ratio)PedagogyMedicine

Abstract

fetched live from OpenAlex

The research paper aims to investigate EFL mentees' perceptions of mentoring experience in one of the Higher Education institutes in the Kingdom of Saudi Arabia in the Academic years 2019 and 2020. The mentoring experience includes four domains: the mentorship program, mentors' roles and responsibilities, benefits of mentoring, and barriers to mentoring. The researcher attempted to answer two questions. The first explores the mentees' perceptions of the mentoring experience, and the second question attempts to find out the mentees' suggestions to make the mentoring experience more effective. A questionnaire of 4- Likert scale was used to collect data from thirty-three newly recruited instructors to answer the first question. The mentees were also asked to add their suggestions for the betterment of mentoring experiences as an answer to the second question. Descriptive statistics in the form of means, standard deviation, and percentages were used to analyze the collected data. The findings revealed that the mentees were satisfied with the mentoring experience. They have a positive attitude towards the mentorship program and the mentor's roles and responsibilities. However, a few mentees have certain concerns regarding some factors related to their mentoring experience. These were highlighted and discussed under each domain. In addition, the mentees had a number of suggestions that would contribute to having a more effective mentoring experience. Based on the findings, the researcher presented a number of conclusions and recommendations.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.740
Threshold uncertainty score1.000

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 communication0.0000.001
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 head0.064
GPT teacher head0.426
Teacher spread0.363 · 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.

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".

Quick stats

Citations3
Published2020
Admission routes1
Has abstractyes

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