ONLINE LEARNING ELEMENT DESIGN – DEVELOPMENT AND APPLICATION EXPERIENCES
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
The Capstone Design Course instructional team was selected to participate in the digital learning initiative at the University of Alberta. The goals of this initiative are to increase student engagement and promote flexible, independent learning. The objectives of the instructional team were to enhance the interactions between instructors and student design teams in the face of increasing enrolment and to align the course strategically with attributes expected for graduating engineers set out by the University of Alberta and elaborated in the Canadian Engineering AccreditationBoard (CEAB) Guidelines. Existing course lecture materials were redeveloped into an asynchronous online format for individual student engagement. Related inclass team-learning activities were prepared andimplemented. This report focuses on the design of online learning elements connected to in class active learning and project applications and our experiences with them over the course of a two-year pilot project. This paper is a follow up to “The University of Alberta Chemical Engineering Capstone Design Course Goes Flipped!”
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 | 0.000 | 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