Lifelong learning - a new conceptual framework, and the role of an undergraduate engineering education
Bibliographic record
Abstract
Lifelong learning is used extensively within education and specifically within engineering education, but is not well-defined, which makes it hard for learning organizations to clarify how they are supporting the lifelong learner. This paper proposes a new conceptual framework of lifelong learning which breaks it into three layers: a long-term career- and life-focussed learning layer, a medium-term “programme of learning” layer, and a real-time layer for monitoring and adjusting learning as it happens. The paper then considers the role of undergraduate engineering education in developing these facets and looks at how well the proposed conceptual framework maps to existing programmes in the authors’ home institution. Although the proposed framework was developed for engineering, and engineering education specifically, the framework is intended to be taken up more widely. The proposed conceptual framework will support the individual learner achieve greater intentionality as they develop their learning skills throughout their life and will support learning institutions to articulate the intended learning skills around lifelong learning more precisely.
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 | 0.001 | 0.002 |
| 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 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".