Preparing Lifelong Learners for a Diversifying Economy Through Micro-Credentials and Laddering at Athabasca University
Bibliographic record
Abstract
Learners need relevant and transformative skills to adapt to a world of increasing change and complexity. It is important to provide diverse opportunities to support lifelong learning. In response to the Alberta 2030: Building Skills for Jobs report and Alberta’s Recovery Plan to the Covid-19 pandemic, PowerED™ by Athabasca University, Ethically Aligned AI, and Athabasca University’s Faculty of Science and Technology developed three online, on-demand micro-credentials. The three micro-credentials, Ethics and Artificial Intelligence, Innovative and Diversified Energy Resources, and Energy Efficiency in Architecture Engineering (AEC) and Construction Industry, were funded by the Government of Alberta to provide job-ready skills in priority areas. Athabasca University’s PowerED unit is designing and developing these three micro-credentials in partnership with Athabasca University faculty and subject matter experts. PowerED™ is Athabasca University’s award-winning continuing education unit that provides an on-demand approach to the online learning experience which includes a mix of multi-media (videos, podcasts) interactive tools, case studies, gamification, competency assessment, downloadable materials, and AI simulations for immediate assessment. The micro-credentials are being designed to be flexible and can be accessed from any device that connects to the internet. Each micro-credential is made up of a set of modules and learners can combine different micro-credentials to develop specific competencies to focus on specific skill development requirements. Modules are being designed so that in the future, individual modules can be re-packaged into unique micro-credential offerings. In completing these micro-credentials, learners will be able to obtain relevant skills in key areas of employment. These micro-credentials will ladder into the BSc programs at Athabasca University, creating additional opportunities to continue learning in a flexible and accessible way. To facilitate this, we are developing a micro-credential framework at the institutional level that will also align with future frameworks in Alberta and Canada.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
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".