Bibliographic record
Abstract
As part of a new third year project course for the Electrical Engineering program, a reflection journal was introduced as part of the work to be undertaken by students. The aim of the one term course is to provide a project experience that will provide design experience in teams, will draw together material from the previous years of academic study as well as further prepare students for their capstone project. The reflection journal has been introduced to provide a regular opportunity for the student to consciously reflect on their progress, challenges encountered, as well as a way to develop their writing skills. This is an attempt to encourage students to look at the process of learning in a project environment and to develop some degree of metacognition1. By undertaking this type of reflection Cowan [1] suggests that this assists students from looking at solving a particular challenge to generalizing the problem solving process, fitting with the objectives of aproject course. The entries for the journal are weekly and are assessed each week by an instructor and contributed to 15% of the final mark. Because this form of assessment would be new to most of the students instructions were provided including a rubric. These instructions as well asthe instructor’s experiences and opinion of the success of the journal will be presented.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.007 |
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 source (direct Gemma or distilled Codex), 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".