Students Taking Numerous Honours Courses in High School Have Higher Information Literacy Levels
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Notice bibliographique
Résumé
A Review of:
 Fabbi, J. L. (2015). Fortifying the pipeline: A quantitative exploration of high school factors impacting the information literacy of first-year college students. College & Research Libraries, 76(1), 31-42. http://dx.doi.org/10.5860/crl.76.1.31 
 
 Abstract
 
 Objective – To assess the impact of students’ high school performances on the development of their information literacy (IL) competency.
 
 Design – Statistical analysis of test performance.
 
 Setting – A large public university in the United States of America.
 
 Subjects – 93 first-time college freshmen. Of these, 46% had been admitted on a probationary status due to GPA under the required 3.0 (“alternate admits”), and 61% had not declared a major (“exploring majors”). 39% identified as Caucasian, 25% as Hispanic, 22% as African American, and 15% as Asian. 84% declared that their best language was English only.
 
 Methods – Participants were self-selected freshmen who enrolled into programs offered by the university’s Academic Success Center. They took the iSkills test, an online evaluation of information literacy competencies developed by the Educational Testing Service, and provided background data on their high school experience. Using hierarchical multiple regression analysis, the researcher evaluated predictors of iSkills score variance among a range of high school experiences: core high school GPA, number of honours classes taken in high school, and number of research projects or assignments in high school. The analysis controlled for gender, best language, race, and admission status as either alternate admit or exploring major.
 
 Main Results – Participants’ mean iSkills scores was below the minimum passing score for the test. There was a significant positive correlation between iSkills scores and exploring major status, core high school GPA, and having taken 5 to 12 honours courses. There was a negative correlation between iSkills scores and language other than English, Asian race, alternate admission status, and having had 1 to 4 honours courses. Among the background variables, the most significant predictor of a student’s iSkills score was his or her best language, followed by race. After controlling for these variables, the most important factors were students’ high school GPAs and the number of honors courses taken.
 
 Conclusion – The researcher discovered that the number of honours courses taken in high school is a strong predictor of information literacy competency as measured by the iSkills test. This remains true when controlling for race and other background factors. This finding is consistent with the assumption that high school teachers of honours courses believe their students to be capable of learning higher-order skills and therefore adopt a constructivist pedagogy, and that such pedagogy promotes the development of information literacy skills. Yet the number of high school research projects or assignments could not be statistically correlated to information literacy competency. In subsequent focus groups, students who had taken fewer honours courses expressed test anxiety, while students who had taken numerous honours courses expressed their determination to get the correct answer. This may inform one surprising result of the study: that students who took 13 or more honours courses in high school did not score significantly better on the iSkills test than those who took 5 to 12 courses.
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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 | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,002 | 0,460 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 découle