Multiple mini‐interview test characteristics: ‘tis better to ask candidates to recall than to imagine
Notice bibliographique
Résumé
CONTEXT: The multiple mini-interview (MMI), used to facilitate the selection of applicants in health professional programmes, has been shown to be capable of generating reliable data predictive of success. It is a process rather than a single instrument and therefore its psychometric properties can be expected to vary according to the stations generated, the alignment between the stations and the qualities an institution prioritises, and the outcomes used. The purpose of this study was to explore the MMI's test characteristics when station type is manipulated. METHODS: A 12-station MMI was established in which four stations were presented in three different ways. These included: situational judgement (SJ) stations, in which applicants were asked to imagine what they would do in specific situations; behavioural interview (BI) stations, in which applicants were asked to recall what they did in experienced situations, and free form (FF) stations, which were unstructured in that the examiner was simply given a brief explanation of the intent of the station without further guidance on how to conduct the discussion. Four circuits of the 12 stations were run with one examiner within each station. Candidates and examiners were surveyed regarding their experience. The reliability of the scores derived from the assessment was analysed separately for each station type. RESULTS: A total of 41 medical school candidates participated after completing the regular admission process. Although the score assigned did not differ across station type, BI stations more reliably differentiated between candidates (g = 0.77) than did the other station types (SJ, g = 0.69; FF, g = 0.66). The correlation between actual MMI scores and BI stations was also greatest (BI, r = 0.57; SJ, r = 0.45; FF, r = 0.42). Candidates' opinions indicated that FF stations were more anxiety-provoking, less clear, and more difficult than structured stations (SJ and BI stations). Examiner opinions indicated equivalence on these measures. CONCLUSIONS: The results suggest that structuring stations has value, although that value was gained only through the use of BI stations, in which candidates were asked to recall and discuss a specific experience of relevance to the purpose of the interview station.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,042 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».