Students Taking Numerous Honours Courses in High School Have Higher Information Literacy Levels
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.460 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it