ENHANCING LIFELONG LEARNING AWARENESS IN THE FACULTY OF ENGINEERING AT MCGILL UNIVERSITY
Bibliographic record
Abstract
Abstract – The theoretical approach to Lifelong Learning used in this paper introduces findings in the field of Self-Regulated Learning (SRL). We are using Nilson’s [4] definition of SRL, which states that self-regulation "encompasses the monitoring and managing of one’s cognitive processes, as well as the awareness of and control over one’s emotions, motivations, behavior, and environment as related to learning." The principles that guide SRL, as proposed by Schunk and Zimmerman [6-8] are: 1) Forethought; 2) Performance/volitional control and; 3) Self-reflection. Following the definition and principles suggested in the SRL literature, activities were designed to develop and strengthen engineering students’ self-regulated learning skills and awareness of such competencies. At McGill University, the Faculty of Engineering is pursuing a systematic assessment method of lifelong learning awareness by the way of activities that target the first- and final-year students.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".