Conceptualizing Learning and Employability “Learning and Employability Framework”
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
Extensive studies have been done on employability and the factors that lead to employability. Previous studies have focused on career development programs, internships, work experience programs, soft-skill development programs, and even university admission criteria which can be considered external factors to university student learning experience. Focus on these external factors and their influence on employability appears to have taken attention away from the core function of university education, “learning”. Learning done in universities has been the focus of many studies but it’s difficult to find consensus due to different learning models and approaches considered. Learning and employability are clearly supportive constructs but this relationship appears to be under represented and lacks clarity. Present study overcomes this issue by introducing a framework that clearly represents learning and employability in a manner that is both easy to understand while providing necessary theoretical support. The “Learning and employability framework” is at attempt to overcome the limitations of popular employability models which either lacks operational clarity or simplicity. The model has identified new dimensions of employability which were not considered in previous studies and links learning process, learning environment and learning outcomes to employability. Extensive review of literature on employability and learning revealed two new factors, namely; university reputation and learning outcomes and their influence on graduate employability. While learning outcomes appear to mediate the relationship between lower-tier employability skills and employability, university reputation appear to moderate learning outcome and employability. The “learning and employability framework” can be considered as a timely and relevant study since its simple enough to be understood by students, parents, employers and faculty while providing the required operational clarity and theoretical support for research community. The framework provides direction to those looking to design curricula and pedagogic approach to maximize employability.
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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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