Mentors' approach to practicum mentoring in the Spanish and Thai contexts: a two-cohort comparison using the Mentoring Profile Inventory
Bibliographic record
Abstract
Purpose The purpose of this study was to better understand the work of mentors or cooperating teachers (CTs) in Spain and Thailand, by comparing how mentors in both contexts conceive of their work in teacher education. Design/methodology/approach A comparative study based on a crossnational research (CNR) approach was used. An internationally validated instrument, the Mentoring Profile Inventory (MPI), was given to 171 Spanish and 170 Thai CTs, and an analysis usingttests and constant comparative methods was conducted. Findings The main results indicate that the Spanish cohort reported being significantly more challenged than their Thai counterparts in working with preservice teachers (PSTs). Both groups indicated a similar degree of motivation. The comparative analysis revealed that the Thai CTs emphasized the importance of ethics in teaching and being a role model for PSTs, whereas the Spanish CTs emphasized the need for strong interpersonal relationships as being central to successful mentoring. Research limitations/implications Understanding mentors' challenges and motivations can form the basis for reflecting upon the essential components of teacher preparation in both contexts. Furthermore, comparative cross-context analyses, as demonstrated in this paper, are vital for the identification of important differences that might otherwise remain invisible or unrecognized from a single-context perspective. Originality/value The study is original in its focus in that it offers insights that help better understand attitudes and performance within and across contexts – in this case, a European and an Asian country – using a common metric, the MPI. This study serves as an exemplar for other comparison studies for countries of mentors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".