Student Satisfaction with Blended and Online Courses Based on Personality Type / Niveau de satisfaction des étudiants dans les cours hybrides et en ligne basé sur le type de personnalité
Bibliographic record
Abstract
The purpose of the study was to investigate differences in perceived student satisfaction in blended and online learning environments based on personality type. A total of 72 graduate students enrolled in blended and online courses at two research universities in the United States completed an abbreviated online version of the Myers-Briggs Type Indicator (MBTI®) and an online student satisfaction questionnaire. Overall, results indicate participants were satisfied with courses delivered in both environments. Analyses revealed several significant differences in perceived student satisfaction with certain elements in blended and online courses based on personality type. Cette étude a pour but d'examiner si la satisfaction des étudiants à l’égard d’environnements d'apprentissage hybride et en ligne varie en fonction du type de personnalité. 72 étudiants de cycle supérieur inscrits dans des cours hybrides et en ligne de deux universités de recherche américaines ont rempli en ligne une version abrégée de l'indicateur de types psychologiques de MyersBriggs (MBTI ®) ainsi qu’un questionnaire mesurant le niveau de satisfaction des étudiants. Dans l'ensemble, les résultats indiquent que les participants étaient satisfaits des cours enseignés dans ces deux environnements. Les analyses ont révélé que la satisfaction des étudiants à l’égard de certains éléments des cours hybrides et en ligne varie en fonction du type de personnalité.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".