Exploring the potential of blended learning to promote retention and achievement in higher education professional study programs
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
In this paper, we present a blended learning model designed for a university professional study program attended by full-time professional workers, i.e. in-service teachers studying in the field of School Administration. The model integrates four main instructional strategies at the program level: mentoring; participation in an online community of professional learning and practice; collaborative concept-mapping with an object-typed knowledge modeling software, and face-to-face seminars in a work setting. Based on interview and observation data collected during two successive small-scale experimentations of the model, we explored potential factors that could have had an impact on students' academic retention and achievement. Four types of factors were identified: personal, professional, institutional and pedagogical. We found that pedagogical and professional factors, which are insufficiently considered in theoretical models of student retention, are of primary concern for students who work full-time as professionals. A blended learning model designed at the program level and strongly “situated” in the professional practice of the students is a promising avenue to adjust to their career constraints and aspirations and, thus, promoting their academic retention and achievement.
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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 | 0.000 |
| 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 | 0.000 | 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 it