Academic success in five programs in allied health at the British Columbia Institute of Technology
Notice bibliographique
Résumé
This study examined the nature and strength of relationship between specific related high school academic grades and the cumulative graduating average of students in five allied health programs at the British Columbia Institute of Technology. Lack of scientific studies on selection criteria for determining the cumulative graduating average of allied health professionals at the British Columbia Institute of Technology (B.C.I.T.) was evident. Educators argue that in order to enhance educational opportunities for institute students, there is a professional obligation upon the policy-makers to gather appropriate data to determine which factors contribute to the success of the allied health student. With the high cost of technical education, admission officers and admissions committees are accountable for their selection processes to the institute's administration, decision makers, provincial and federal funding sources, and society. The results of this study may assist admissions officers in selecting academic variables that indicate the cumulative graduating average so that a better match can be made between the students and their performance in allied health programs. The accessible population of 629 graduates from the allied health technologies in this study were biomedical electronics, medical laboratory, medical radiography, nuclear medicine, and prosthetics and orthotics. The dependent variable measurement of academic achievement for these students was their cumulative graduating average. Single variables consisted of the grade point average of the following: pretechnology academic requirements, high school English, high school algebra, high school biology, high school chemistry, and high school physics. Descriptive statistics, zero-order correlations, and stepwise multiple regression analysis were the statistical methods employed to determine which specific academic variable or multiple of variables exhibited a strong relationship between the cumulative graduating average and academic variables. The analysis identified certain variables that strongly related to the cumulative graduating average, both singly and in combination with others. Each of the program significant combination of variables are provided here in order of descending influence: Biomedical Electronics Technology- high school algebra; Medical Laboratory Technology- the pretechnology grade point average, high school chemistry, biology, and algebra; Medical Radiography Technology- high school biology and chemistry; Nuclear Medicine- the pretechnology grade point average, high school chemistry, and high school biology; Prosthetics and Orthotics Technology- the pretechnology grade point average and high school chemistry. Academic variables did not account for more than 34% of the total variables in any of the programs. The level of significance for individual variables was the convention, 0.05. Clearly, each program had its own character; however, the performance of students in the natural sciences were significant in four of the five programs. An attempt was made to investigate which specific high school subjects correlated highly with the cumulative graduating average of students at the B.C.I.T. through a inspection of five programs for five graduating classes. Relevant variables were identified that were indicative of academic achievement in each specific program of study. Investigating the nature and strength of relationship between preprofessional grades and the cumulative graduating average of allied health students at B.C.I.T. could benefit both students and admissions officers by supplying a piece to an educational puzzle that would demystify the selection process. The information presented may assist admissions officers and prospective allied health students make more suitable educational choices.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».