The Relationship Among Learning Styles, Achievement, and Retention in Bible College Freshmen: A Correlational Study
Bibliographic record
Abstract
This predictive correlational study used a multiple regression to examine whether learning style and achievement, or grade point average (GPA), can predict retention for first-year, traditional Bible college freshmen. Four small Bible colleges were the sites for the research: one in Florida, two in Ohio (Northern Ohio and Southwestern Ohio), and one in Pennsylvania. The first predictor variable, learning style, was generally defined as the preferred method for a student to process and learn information. The second predictor variable, achievement, was generally defined as the end-of-semester GPA. The criterion variable, retention, was generally defined as a participant’s attendance in the semester following the data collection for learning styles and GPA. This research was designed to broaden the understanding of how students learn and, specifically, to test whether learning style and GPA can predict retention in Bible college students. Practically, the study sought this link among learning style, GPA, and retention in the participants’ second semester at Bible college to prepare possible at-risk students for early intervention. Data was collected at the sites during the last quarter of the fall semester of the 2018-2019 academic year. This research had 30 participants (N = 30). It identified a small, but significant, connection among learning styles, GPA, and retention. The results of this study focused on Bible college freshmen in the Conservative Holiness Movement (CHM). Further research is recommended to extend the results to public colleges and universities. A research study that was initiated within the first weeks of the fall semester would identify potential at-risk students, providing an opportunity for early intervention.
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.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".